SlideShare a Scribd company logo
1 of 12
Download to read offline
www.ijmer.com

International Journal of Modern Engineering Research (IJMER)
Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3255-3266
ISSN: 2249-6645

Tannin gel derived from Leaves of Ricinus Communis as an adsorbent
for the Removal of Cu (II) and Ni (II) ions from aqueous solution
M. Makeswari1, T. Santhi2
Department of chemistry, Karpagam University, Coimbatore 641021, Tamil Nadu, India.

ABSTRACT: The biosorption of Cu (II) and Ni (II) ions from aqueous solutions by Tannin gel derived from Leaves of
Ricinus Communis was investigated as a function of pH ZPC, Initial pH, adsorbent dose, contact time and metal ion
concentration. The aim of this study was to prepare the adsorbent and to find a suitable equilibrium isotherm and kinetic
model for the removal of Cu (II) and Ni (II) ions in a batch reactor. The maximum percentage of adsorption for the removal
of Cu (II) ion was found to be 76.92% at 7.04 pH and for the removal of Ni (II) ion was 71.74% at 7.12 pH. The adsorption
of Cu (II) and Ni (II) ions followed the Pseudo-second-order and Intra particle diffusion rate equations and fits the
Langmuir, Freundlich and Frenkel-Halsey-Hill isotherm equations well. The effects of the presence of one metal ion on the
adsorption of the other metal ion were investigated in binary and ternary mixture and then the results were compared with
single system. We investigate the recovery of the used adsorbent for its reusing is of great importance for environmental and
economical reasons. i.e., TGLRC will be recovered by desorption method by using proper desorption agent like H 2O by
batch mode study. Activated carbon developed from Ricinus Communis leaves can be an attractive option for heavy metal
removal from water and waste water since test reactions made on stimulated waste water sowed better removal percentage
of Cu (II) and Ni (II) ions.

Keywords: Adsorption; Tannin gel; Ricinus communis leaves; Binary and Tertiary; Desorption.
I.

INTRODUCTION

The pollution of water resources due to the indiscriminate disposal of heavy metals has been causing worldwide
concern for the last few decades. It is well known that some metals can have toxic or harmful effects on many forms of life.
Among the most toxic metals are chromium (Cr), copper (Cu), lead (Pb), zinc (Zn) and mercury (Hg), which is one of the 11
hazardous priority substances in the list of pollutants contained in the Water Framework Directive (Directive 2000/60/EC)
[1]. Many industries discharge heavy metals such as lead, cadmium, copper, nickel and zinc in their wastewaters [2]. Metals
such as copper and nickel are known to be essential to plants, humans and animals, but they can also have adverse effects if
their availability in water exceeds certain threshold values.
Therefore, it is urgent to remove heavy metals such as copper and nickel from wastewater. Although heavy metal
removal from aqueous solutions can be achieved by conventional methods, including chemical precipitation,
oxidation/reduction, electrochemical treatment, evaporative recovery, filtration, ion exchange and membrane technologies,
they may be ineffective or cost-expensive, especially when the metal ion concentrations in solution are in the range of 1–100
mg/L [3, 4]. Recently, adsorption technology has become one of the alternative treatments in either laboratory or industrial
scale [5, 6]. There are many adsorbents in use. Activated carbons (AC) are known as very effective adsorbents due to their
highly developed porosity, large surface area, variable characteristics of surface chemistry, and high degree of surface
reactivity [7]. However, due to their high production costs, these materials tend to be more expensive than other adsorbents.
This has led a growing research interest in the production of activated carbons from renewable and cheaper precursors. The
choice of precursor largely depends on its availability, cost, and purity, but the manufacturing process and intended
applications of the product are also important considerations [8]. Several suitable agricultural by-products (lignocellulosics)
including fruit stones, olive waste cake, pine bark, rice husks, pistachio-nut shells and wheat bran have been investigated in
the last years as activated carbon precursors and are still receiving renewed attention.
In recent years, considerable attention has been focused on the removal of heavy metals from aqueous solution
using natural raw materials are an interesting potential source of low-cost adsorbents [9-11]. Tannins, natural biomass
containing multiple adjacent hydroxyl groups and exhibiting specific affinity to metal ions, can probably be used as
alternative, effective and efficient adsorbents for the recovery of metal ions. During the last years, the interest on
biomaterials and specifically in tannins was growing.
The term tannins cover many families of chemical compounds. Traditionally they have been used for tanning
animal skins, hence their name, but one also finds several of them used as water treatment agents. Their natural origin is as
secondary metabolites of plants [12], occurring in the bark, fruit, leaves, etc. While Acacia and Schinopsis bark constitute the
principal source of tannins for the leather industry, the bark of other non-tropical trees such as Quercus ilex, suber, and
robur, Castanea, and Pinus can also be tannin-rich.
Tannin gelification is a chemical procedure that inmobilizes tannins in an insoluble matrix [13, 14] so their
properties involving, e.g. metal chelation, are available then in an efficient adsorbing agent. In addition, the resulting
material from gelification (sometimes called tannin rigid gel) presents interesting properties from the point of view of
resistance, nonflammability or mechanical undeformability [15, 16]. Gelifications of tannins have been widely reported
either in scientific literature or in patents. Experimental conditions of gelification may imply the use of formaldehyde or
other aldehyde in a basic or acidic environment. Examples of basic gelification are shown in scientific literature previously
[17-19] and in patents such as US patent 5,158,711 [20]. Acid gelification is also presented by other researchers [21, 22].
www.ijmer.com

3255 | Page
International Journal of Modern Engineering Research (IJMER)
www.ijmer.com
Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3255-3266
ISSN: 2249-6645
The chemical basis of the tannin gelification is widely reported [23]. Formaldehyde and other aldehydes react with tannins to
induce polymerization through methylene bridge linkages at reactive positions on the tannin flavonoid molecules.
Agricultural by-products are high volume, low value and underutilized lignocellulosic biomaterials, and contain
high levels of cellulose, hemicellulose and lignin. Ricinus communis is a species of flowering plant in the spurge family,
Euphorbiaceae. It belongs to a monotypic genus, Ricinus, and subtribe, Ricininae.
Ricinus communis grows throughout the drier parts and near drainages of India. Annual production of Ricinus
communis is estimated to be more than 1.0 tons globally, of which India accounts for 60% of the production. The adsorption
ability of Ricinus communis leaves was previously investigated for the adsorption of Cu 2+ ion and Ni2+ ion from aqueous
solution [24, 25].
In this study, Tannin gel has been prepared from the cheap and abundantly available agricultural waste product
leaves of Ricinus communis (TGLRC) and applied them to remove heavy metals such as Cu (II) and Ni (II) ions from waste
water.
The objective of this study is to systematically examine adsorption mechanisms, adsorption isotherms, adsorption
kinetics and properties of a tannin gel adsorbent synthesized from leaves of Ricinus communis (TGLRC) for removal of Cu
(II) and Ni (II) ions from aqueous solutions.

II.

MATERIALS AND METHODS

Preparation of Adsorbent
Tannin extracts
The Ricinus communis leaves were obtained from the agricultural form in Tirupur district (Tamil Nadu). It was airdried and powdered in a grinder. Dried Ricinus communis with the mass of 100 g were mixed with 600 mL of water. Then 5
g of NaOH were added and the mixture was stirred in magnetic stirrer at 90C for 1 h. Solids was separated by filtration and
liquid fraction was dried in oven (65C) overnight. The resultant was considered the tannin extract.
Tannin gel preparation (TGLRC)
Tannin gels were prepared according to the basis of Nakano et al. [17]. Five grams of tannin extract were dissolved
in 32mL of NaOH (PANREAC) 0.125 mol L−1 and 30mL of distilled water at 80 ◦C. When mixture was homogeneous,
certain amount of aldehyde (Formaldehyde) was added and reaction was kept at the same temperature for 8 h until
polymerization was considered completed. Then, the apparent gummy product was lead to complete evaporation of water
remain and dried in oven (65º C) overnight. After drying, tannin rigid gels were crushed to small particles. They were
washed successively with distilled water and 0.01 molar HNO3 was used to remove unreacted sodium hydroxide. Finally, the
adsorbent was dried again in oven. Differences are found between this preparation way and the description made by
Yurtsever and Sengil [26], mainly concerning the amount of formaldehyde.
Preparation of stock solution
Samples of potassium chromate (K2CrO4), copper sulphate penta hydrate (CuSO4.5H2O) and Nickel sulphate hexa
hydrate (NiSO.6H2O) was obtained from Aluva, Edayar (specrum reagents and chemicals pvt. Ltd). All other chemicals used
in this study were analytical grade and Purchased from Aluva, Edayar (specrum reagents and chemicals pvt. Ltd)
A Stock solution of 1000 mg/L was prepared by dissolving accurately weighed amounts of potassium chromate
(K2CrO4) in doses of 1000 mL double-distilled water. Working copper and Nickel solutions were prepared just before used
by appropriate dilutions of stock solution.
Characterization of the adsorbent
The point of zero surface charge characteristic of TGLRC was (pH ZPC) determined by using the solid addition
method. A Fourier transform infrared spectroscopy (SHIMADZU, IR Affinity-1) with KBr pellet was used to study the
functional groups available on the surface of TGLRC, with a scanning range of 4000-400cm-1. The crystalline structure of
TGLRC was evaluated by X-ray diffractometer, by using Cu K α radiation (1.54060 Å) at 45 kV and 30 mA with a scan
analysis. The concentration of Cu (II) and Ni (II) ions was determined using UV-vis spectrophotometer (SHIMADZU UV2450).
Batch adsorption studies
The adsorption experiments were carried out in a batch process to evaluate the effect of pH, contact time, adsorbent
dose, adsorption kinetics, adsorption isotherm, influence of other metal ions in single and binary system and regeneration of
Cu (II) and Ni (II) ions onto TGLRC.
Batch equilibrium studies
To study the effect of parameters such as adsorbent dose, metal ion concentration and solution pH for the removal
of adsorbate on TGLRC, batch experiments were performed. Stock solutions of CuSO4.5H2O and NiSO4.6H2O was prepared
and further diluted to the 25 – 200 mg/ L concentrations for the experiments. pH adjustment was fulfilled by adding 0.1 M
HCl or 0.1 M NaOH into the solutions with known initial metal concentrations. Batch adsorption experiments were
conducted in asset of 250 mL stoppered flasks containing 200 mg adsorbent and 50 mL of metal solutions with different
concentrations (25-200 mg / L) at the optimum solution pH. The flasks were agitated using a mechanical orbital shaker, and
maintained at room temperature for 2 h at a fixed shaking speed of 120 rpm until the equilibrium was reached. The
www.ijmer.com

3256 | Page
International Journal of Modern Engineering Research (IJMER)
www.ijmer.com
Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3255-3266
ISSN: 2249-6645
suspensions were filtered and metal concentrations in the supernatant solutions were measured using a Digital photo
colorimeter (model number-313). From the initial and final concentrations, percentage removal can be calculated by use of
the formula:
𝑪𝟎 − 𝑪𝒇
% 𝒐𝒇 𝑹𝒆𝒎𝒐𝒗𝒂𝒍 =
× 𝟏𝟎𝟎
(𝟏)
𝑪𝟎
where Co is the initial concentration of Cu (II) and Ni (II) ions in mg/L and Cf is the final concentration of Cu (II) and Ni (II)
ions in mg/L. The results obtained in batch mode were used to calculate the equilibrium metal uptake capacity. The amounts
of uptake of Cu (II) and Ni (II) ions by TGLRC in the equilibrium (qe) were calculated by the following mass-balance
relationship:
𝑪𝟎 − 𝑪𝒆
𝒒𝒆 =
× 𝑽
(𝟐)
𝑾
where qe is the equilibrium uptake capacity in mg/g, V is the sample volume in liters, Co is the initial metal ion
concentration in mg/L, Ce the equilibrium metal ion concentration in mg/L, and W is the dry weight of adsorbent in grams.

III.

RESULTS AND DISCUSSION

Characterization of TGLRC adsorbent
Zero point charges (pHZPC)
The zero surface charge characteristics of TGLRC were determined by using the solid addition method [27]. The
experiment was conducted in a series of 250 mL glass stoppered flasks. Each flask was filled with 50 mL of different initial
pH NaN02 solutions and 200 mg of TGLRC. The pH values of the NaN02 solutions were adjusted between 2 to 10 by adding
either 0.1 M HNO3 or 0.1 M NaOH. The suspensions were then sealed and shaken for 2 h at 120 rpm. The final pH values of
the supernatant liquid were noted. The difference between the initial pH (pH i) and final pH (pHf) values (pH = pHi - pHf) was
plotted against the values of pHi. The point of intersection of the resulting curve with abscissa, at which pH of 0, gave the
pHzpc.
0.6

pHZPC - TGLRC

pHi - pHf

0.4
0.2
0
-0.2

0

5

-0.4

10

Initial pH
Figure. 1. Zero point charge of TGLRC.

The pHZPC of an adsorbent is a very important characteristic that determines the pH at which the adsorbent surface
has net electrical neutrality. Fig.1. shows that the plot between ΔpH, i.e. (pHi – pHf) and pHi for pHZPC measurement. The
point of zero charge for TGLRC is found to be 5.12. This result indicated that the pHZPC of TGLRC was depended on the
raw material and the activated agency. The zero point charge (pH ZPC = 5.12 for TGLRC) is below the solution pH (pH =
7.04 for Cu (II) and 7.12 for Ni (II) ion adsorption) and hence the negative charge density on the surface of TGLRC
increased which favours the adsorption of Cu (II) and Ni (II) ions [28].
FTIR analysis of TGLRC
64
62

TGLRC-Ni

60
58

TGLRC-Cu

56
54

%T

52

TGLRC-B

50
48
46
44
42
40
38
36
4500

4000

3500

3000

2500

2000

1500

1000

500

1/cm

Figure. 2. FTIR spectra for TGLRC before and after adsorption of Cu (II) and Ni (II) ions.
www.ijmer.com

3257 | Page
International Journal of Modern Engineering Research (IJMER)
www.ijmer.com
Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3255-3266
ISSN: 2249-6645
Surface functional groups were detected by Fourier-transform infrared spectroscopy. The Fig. 2 shows the FTIR
spectra of TGLRC before and after adsorption of Cu (II) and Ni (II) ions from aqueous solution. The functional groups of the
adsorbents and the corresponding infrared absorption frequency are shown in Table 1. These spectra contain peaks at 34213462 cm-1. This indicates the presence of hydrogen-bonded OH groups. The peak 3421 cm-1 which is originated from
TGLRC before adsorption of Cu (II) and Ni (II) ions is shifted to 3462 cm-1 in TGLRC-Cu (after adsorption of Copper) and
shifted to 3446 cm-1 in TGLRC-Ni (after adsorption of Nickel). The intense bent at about region 2852-2854 cm-1 for the
precursor was attributed to the asymmetric and symmetric vibration modes of methyl and methylene group (C-H group)[29].
The peak around 1647-1653 cm-1 can be assigned to aromatic ring vibrations. The peak at 1018-1047 cm-1 is related to
lignin. Therefore it is possible that cellulose, hemicelluloses as well as lignin, having many OH groups in their structure,
make up most of the absorbing layer.
Table 1. The FTIR spectral characteristics of TGLRC before and after adsorption of Cu (II) and Ni (II) ions.
IR Peak
Frequencies (cm-1)
Assignment
______________________________________________________________________________
1
3447
Bonded –OH groups
2
2852
Aliphatic C-H groups
3
1647
Aromatic ring vibrations
4
1022
-C-C group
______________________________________________________________________________
X-ray diffraction analysis

Intensity

500
400
300
200
100

Intensity

0

40

60

80

100

80

100

80

100

Angle Two Theta

0

Intensity

20

700
600
500
400
300
200
100
20

700
600
500
400
300
200
100
0

40

60

Angle Two Theta

0

20

40

60

Angle Two Theta

Figure. 3. XRD pattern of TGLRC before and after adsorption of Cu (II) and Ni (II) ions.
Adsorption reaction may lead to changes in molecular and crystalline structure of the adsorbent and hence an
understanding of the molecular and crystalline structures of the adsorbent and the resulting changes thereof would provide
valuable information regarding adsorption reaction. Hence, XRD patterns of the adsorbent before and after adsorption of Cu
(II) and Ni (II) ions have been studied.
As a representative case the XRD patterns of TGLRC before and after treatment with Cu (II) and Ni (II) ions are
shown in Fig. 3. The results indicated that the diffraction profiles of TGLRC before and after adsorption of Cu (II) and Ni
(II) ions exhibited broad peaks and the absence of a sharp peak revealed a predominantly amorphous structure, the broad
peak seems to be appear at around 2θ = 21, 22, 26 and 28° which was similar to the peak of crystalline carbonaceous
structure such as graphite. It is evident from the figure that the XRD pattern of TGLRC loaded with Cu (II) and Ni (II) ions
exhibits no variation in the crystal structure and this suggests that the Cu (II) and Ni (II) ions might diffuse into micropores
and sorbs mostly by physisorption without altering the structure of the adsorbent. From the XRD analysis for the adsorbent
(TGLRC), we concluded that the tannin gel preparation was completed. The above observation corroborated well with batch
sorption experiments.
Batch adsorption studies
Effect of solution pH
The zeta-potentials of the TGLRC particles in water were measured at different pH. It was found that TGLRC
particles are positively charged at low pH and negatively charged at high pH, having a point of zero charge (pH zpc) at pH
5.12 for TGLRC. Therefore, it can be expected that positively charged metal ions are likely to be adsorbed by the negatively
charged TGLRC particles at a pH > ZPC.

www.ijmer.com

3258 | Page
International Journal of Modern Engineering Research (IJMER)
Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3255-3266
ISSN: 2249-6645

Effect of Solution pH

80
70
60
50

TGLRC-Ni

TGLRCCu

40
30
20
10
2.52
3.18
4.28
5.14
6.05
7.12
8.04
9.05

0
2.68
3.29
4.38
5.13
6.38
7.04
8.01
9.19

% Adsorption Cu & Ni (II) ions

www.ijmer.com

Initial pH
Figure. 4. Effect of solution pH on the adsorption of Cu (II) and Ni (II) ions on TGLRC.
The pH of the aqueous solution has been identified as the most important variable governing metal adsorption onto
adsorbents. This is partly due to the fact that hydrogen ions themselves are a strongly competing adsorbate and because the
solution pH influences the ionization of surface functional groups. In order to establish the effect of pH on the adsorption of
Cu (II) and Ni (II), the batch equilibrium studies at different pH values were carried out in the range of 2–9 (Fig. 4). We note
that as the pH of the solution increased from 2.0 to 9.0, the adsorption capacity of TGLRC increased up to pH 7.0 for the
adsorption of Cu (II) and Ni (II) ions by TGLRC and then decreased at pH > 6.0. The amount adsorbed increased as pH
increased from 2.0 to 7.0 may be due to the presence of negative charge on the surface of the adsorbent that may be
responsible for metal binding. However, as the pH is lowered, the hydrogen ions compete with the metal ions for the sorption
sites in the sorbent; the overall surface charge on the adsorbent becomes positive and hinds the binding of positively charged
metal ions [30]. At pH higher than 7.0, the precipitation of insoluble metal hydroxides takes place restricting the true
adsorption studies [31].
However, when the pH of the solution was increased, the uptake of metal ions was increased. It appears that a
change in pH of the solution results in the formation of different ionic species, and different carbon surface charge. At pH
values lower than 5, the metal ions can enter into the pore structure may be due to its small size. So, an optimized pH of 7.04
for the removal of Cu (II) ions and 7.12 for the removal of Ni (II) ions by TGLRC adsorbent is taken for all the adsorption
experiments.

% Removal of Cu & Ni (II) ion

Effect of contact Time
90
80
70
60
50
40
30
20
10
0

Effect of contact Time

TGLRC-Cu
TGLRC-Ni

5

10

15

20

25

30

35

40

45

Time (min)
Figure. 5. Effect of Contact time on the adsorption of Cu (II) and Ni (II) ions onto TGLRC.
The uptake of Cu (II) and Ni (II) ions onto TGLRC as a function of contact time is shown in Fig. 5. The effect of
contact time between the adsorbents and Cu (II) and Ni (II) ions showed that the Cu (II) was removed within 45 min by
TGLRC and Ni (II) ions was removed within 40 min by TGLRC and remains almost constant even up to an hour.
This may be due to the attainment of equilibrium condition at 45 min of contact time for Cu (II) removal with
TGLRC and 40 min for the removal of Ni (II) with TGLRC, which are fixed as the optimum contact time. At the initial
stage, the rate of removal of Cu (II) and Ni (II) ions was higher, due to the availability of more than required number of
active sites on the surface of carbons and became slower at the later stages of contact time, due to the decreased or lesser
number of active sites.
www.ijmer.com

3259 | Page
International Journal of Modern Engineering Research (IJMER)
www.ijmer.com
Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3255-3266
ISSN: 2249-6645
Effect of adsorbent dose
The effect of adsorbent dose on the percentage removal of Cu (II) and Ni (II) ion was studied at initial Cu (II) and
Ni (II) ion concentration of 100 mg/L by allowing a contact time of 60 min and at the solution pH of 7.04 for Cu (II) and
7.12 for Ni (II) ions. The results are presented in Fig. 6. It is showed that the percentage removal of Cu (II) and Ni (II) ion
increased with increase in adsorbent dose from 200 mg/50mL to1000 mg/50mL. This increase in Cu (II) and Ni (II) ion
removal is due to the availability of higher number of Cu (II) and Ni (II) ions per unit mass of adsorbent (TGLRC), i.e.,
higher metal ions/ adsorbent ratio. Thus, further experiments were carried out using 200 mg of adsorbent per 50 ml of Cu (II)
and Ni (II) ion solution, as it exhibits appreciable removal capacity, for the optimization of adsorption parameters.

% Removal of Cu & Ni (II) ion

Effect of adsorbent dose
100
80
60
TGLRC-Cu

40

TGLRC-Ni

20
0
200

400

600

800

1000

Adsorbent dose (mg /50mL)
Figure. 6. Effect of adsorbent dose on the adsorption of Cu and Ni (II) ions by TGLRC.
Effect of metal ion concentration
Effect of metal ion concentration
% Removal of Cu & Ni (II)
ion

100

TGLRCCu

80
60
40
20
0
25

50

75

100

125

150

175

200

Concentration of Cu & Ni(II) ion (ppm)
Figure. 7. Effect of metal ion concentration on the adsorption of Cu (II) and Ni (II) ions by TGLRC.
The effect of initial metal ion concentration on adsorption capacity of TGLRC was carried out at a carbon dosage of
200 mg/ 50 mL, pH 7.04 for Cu (II) ion removal and 7. 12 for Ni (II) ion removal by TGLRC, contact time 1 h, temperature
303K for different initial metal ion concentration from 25 to 200 mg/50mL and is shown in Fig. 7. As shown, the amount of
metal uptake per unit weight of the adsorbent increases with increasing initial metal ion concentration showing the maximum
adsorption capacity of 5.48 mg /50mL to 31.32 for Cu (II) ion removal and the maximum adsorption capacity of 5.53
mg/50mL to 26.57 mg/50mL for Ni (II) ion removal by TGLRC. This is because at higher initial concentrations, the ratio of
initial number of moles of metal ions to the available adsorption surface area is high. This may be attributed to an increase in
the driving force of the concentration gradient with increase in the initial metal ion concentration [32] .
Adsorption isotherms
Adsorption isotherm is the most important information which indicates how the adsorbate molecules distribute
between the liquid phase and the solid phase when adsorption process reaches on Equilibrium state. When the system is at
Equilibrium is of importance in determining the maximum sorption capacity of TGLRC towards metal solution. Equilibrium
data are a basic requirement for the design of adsorption systems and adsorption models, which are used for the
mathematical description of the adsorption equilibrium of the metal ion by the adsorbent. The results obtained for adsorption
of Cu (II) and Ni (II) ions were analyzed by use of well-known models given by the Langmuir, Freundlich, Temkin,
Dubinin–Radushkevich, Harkin-Jura and Frenkel-Halsey-Hill adsorption isotherm models [34 - 38]. For the sorption
isotherms, initial metal ion concentration was varied whereas solution pH and amount of adsorbent were held constant. The
sorption isotherms for Cu (II) and Ni (II) ions were obtained for TGLRC at solution pH 7.04 and pH 7.12, respectively.
www.ijmer.com

3260 | Page
www.ijmer.com
𝑪𝒆
𝟏
𝑪𝒆
=
+
𝒒𝒆
𝒒 𝒎𝒂𝒙 𝒃
𝒒 𝒎𝒂𝒙

International Journal of Modern Engineering Research (IJMER)
Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3255-3266
ISSN: 2249-6645
𝑳𝒂𝒏𝒈𝒎𝒖𝒊𝒓 𝒎𝒐𝒅𝒆𝒍

𝟒

𝟏
𝒍𝒐𝒈 𝑪 𝒆 + 𝒍𝒐𝒈 𝑲
𝑭𝒓𝒆𝒖𝒏𝒅𝒍𝒊𝒄𝒉𝒎𝒐𝒅𝒆𝒍
𝒏
𝒒 𝒆 = 𝜷 𝐥𝐧 𝜶 + 𝜷 𝐥𝐧 𝑪 𝒆
𝑻𝒆𝒎𝒌𝒊𝒏 𝒎𝒐𝒅𝒆𝒍
𝐥𝐧 𝒒 𝒆 = 𝐥𝐧 𝑸 𝒎 – 𝑲𝜺 𝟐
𝑫𝒖𝒃𝒊𝒏𝒊𝒏 − 𝑹𝒂𝒅𝒖𝒔𝒉𝒌𝒆𝒗𝒊𝒄𝒉 𝒎𝒐𝒅𝒆𝒍
The mean adsorption energy, E (kJ/mol) is calculated with the help of following equation:
𝟏
𝐄 =
−𝟐′
𝐘
𝟏
𝑩𝟐
𝟏
=
–
𝐥𝐨𝐠 𝑪 𝒆
𝑯𝒂𝒓𝒌𝒊𝒏 − 𝑱𝒖𝒓𝒂 𝒎𝒐𝒅𝒆𝒍
𝒒 𝒆𝟐
𝑨
𝑨
𝒍𝒐𝒈 𝒒 𝒆 =

𝐥𝐧 𝒒 𝒆 =

𝟏
𝟏
𝐥𝐧 𝑲 – 𝐥𝐧 𝑪 𝒆
𝒏
𝒏

𝑭𝒓𝒆𝒏𝒌𝒆𝒍 − 𝑯𝒂𝒍𝒔𝒆𝒚 − 𝑯𝒊𝒍𝒍 𝒎𝒐𝒅𝒆𝒍

𝟓
(𝟔)
𝟕
(𝟖)
(𝟗)

(𝟏𝟎)

where Ce is the Cu (II) and Ni (II) ion concentration in the solution (mg/L), qe is the Cu (II) and Ni (II)
concentrations in the solid adsorbent (mg/g), q m is the maximum adsorption capacity (mg/g), K f is a constant related to the
adsorption capacity (mg1-1/n L1/n/g), b is a constant related to the energy of adsorption (L/g), n is a constant related to the
energy of adsorption, α (L/g) is Temkin constant representing adsorbent–adsorbate interactions and β (mgL-1) is another
constant related with adsorption heat, ε is the Polanyi potential (kJ 2 mol2) and E (kJ/mol) is the mean adsorption energy. B2
is the isotherm constant, represented by Harkin-Jura isotherm model. The adsorption isotherm parameters for all the six
isotherm models are calculated and the values are summarized in Table 2.
Table 2. Adsorption isotherm parameters for the adsorption of Cu (II) and Ni (II) ions.
Isotherm model

Parameters

Cu (II) ion

Ni (II) ion

Langmuir

Qm (mgg-1)
b (Lmg-1)
R2

43.47
0.0160
0.9390

30.303
0.0201
0.9790

Freundlich

n
Kf (mgg-1)
R2

1.8382
3.0690
0.9950

2.3364
3.8994
0.9960

α (Lg-1)
β (mgL-1)
b
R2

0.1093
8.0810
311.73
0.9230

0.3424
5.8130
433.36
0.9690

21.019
0.2
0.625
0.685

19.005
0.2
0.625
0.728

Temkin

Dubinin-Radushkevich

Harkin-Jura

Frenkel–Halsey–Hill

Qm (mgg-1)
K (x10-5mol2kJ-2)
E(kJmol-1)
R2
A
B
R2
1/n
K
R2

47.619
1.7142
0.840
0.544
0.7231
0.943

58.823
1.8823
0.812
0.428
1.1577
0.996

In the present investigation, the equilibrium data were analyzed using the Langmuir, Freundlich, Temkin, DubininRadushkevich, Harkin-Jura and Frenkel-Halsey-Hill isotherm models. To optimize the design of an adsorption system, it is
important to establish the most appropriate isotherm model. The mono-component equilibrium characteristics of adsorption
of Cu (II) and Ni (II) ions by TGLRC were described by these six different isotherm models. The experimental equilibrium
adsorption data were obtained by varying the concentration of Cu (II) and Ni (II) ions with 200mg/50 mL of TGLRC.
The adsorption data obtained by fitting the different isotherm models with the experimental data are listed in Table
2, with the linear regression coefficients, R 2. As seen from Table 2, the Langmuir, Freundlich and Frenkel-Halsey-Hill
www.ijmer.com

3261 | Page
International Journal of Modern Engineering Research (IJMER)
www.ijmer.com
Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3255-3266
ISSN: 2249-6645
isotherms were generate a satisfactory fit to the experimental data as indicated by correlation coefficients. This shows the
heterogeneity of the surface of TGLRC and the multilayer adsorption nature of the Cu (II) and Ni (II) ions on TGLRC.
TGLRC have a homogeneous surface for adsorption of metal ions. The Langmuir isotherm equation is therefore
expected to best represent the equilibrium adsorption data. The R 2 values for the Langmuir model are closer to unity than
those for the other isotherm models for TGLRC for both Cu (II) ion removal (R2 = 0.939) and for the removal of Ni (II) (R2 =
0.979). Therefore, the equilibrium adsorption of Cu (II) and Ni (II) ions on TGLRC can be represented appropriately by the
Langmuir, Freundlich and Frenkel-Halsey-Hill isotherm models in the concentration range studied.
Adsorption kinetics
The kinetics of adsorbate uptake is important for choosing optimum operating conditions for design purposes. In
order to investigate the mechanism of adsorption and potential rate controlling steps such as chemical reaction, diffusion
control and mass transport process, kinetic models have been used to test experimental data from the adsorption of Cu (II)
and Ni (II) ions onto TGLRC. These kinetic models were analyzed using pseudo-first-order, pseudo-second-order and
intraparticle diffusion models, which were respectively presented as follows in Eqs. (11) – (14) [39 – 41]:
𝐥𝐧 𝒒 𝒆 − 𝒒 𝒕 = 𝐥𝐧 𝒒 𝒆 − 𝒌 𝟏 𝒕

𝑷𝒔𝒆𝒖𝒅𝒐 𝒇𝒊𝒓𝒔𝒕 𝒐𝒓𝒅𝒆𝒓 𝒎𝒐𝒅𝒆𝒍

𝒕
𝟏
𝟏
=
+
𝒕
𝟐
𝒒𝒕
𝒌𝟐 𝒒𝒆
𝒒𝒆

𝑷𝒔𝒆𝒖𝒅𝒐 𝒔𝒆𝒄𝒐𝒏𝒅 𝒐𝒓𝒅𝒆𝒓 𝒎𝒐𝒅𝒆𝒍

𝒒 𝒕 = 𝒌 𝒊𝒅 𝒕 𝟏/𝟐 + 𝑪
𝒒𝒕 =

𝟏
𝛃𝐥𝐧 𝜶𝜷

+

(𝟏𝟏)
(𝟏𝟐)

𝑰𝒏𝒕𝒓𝒂 𝒑𝒂𝒓𝒕𝒊𝒄𝒍𝒆 𝒅𝒊𝒇𝒇𝒖𝒔𝒊𝒐𝒏 𝒎𝒐𝒅𝒆𝒍
𝟏
𝜷 𝐥𝐧 𝒕

(𝟏𝟑)

𝑬𝒍𝒐𝒗𝒊𝒄𝒉 𝒎𝒐𝒅𝒆𝒍

(𝟏𝟒)

where t is the contact time of adsorption experiment (min); q e (mg/g) and qt (mg/g) are respectively the adsorption
capacity at equilibrium and at any time t; k1 (1/min), k2 (g/mg min), α (mg/g min), β (g/mg), kid (mg/g min1/2) are the rate
constants for these models, respectively. The correlation coefficients for all the four kinetic models were calculated and the
results are shown in Table 3.
Table 3. Comparison of the correlation coefficients of kinetic parameters for the adsorption of
Cu (II) and Ni (II) ions onto TGLRC.

Models

Parameters

Pseudo first-order model

k1 (min-1)
qe (mg/g)
R2

Pseudo second-order model

k2 (g/mg/min)
qe (mg/g)
h
R2

Intra particle diffusion model

Elovich model

Cu (II) ion

0.1658
173.78
0.677

Ni (II) ion

0.1496
64.71
0.644

0.0004
41.66
0.7005
0.9920

0.0005
38.46
0.8613
0.973

kdif (mg/(g.min1/2))
C
R2

3.411
5.044
0.983

3.510
4.063
0.989

A E (mg(g/ min))
b (g/ mg)
R2

0.1452
0.3928
0.9110

0.1453
0.6071
0.9530

The adsorption process of Cu (II) and Ni (II) ions can be well fitted by use of the pseudo-second order rate constant
for TGLRC. The linear regression coefficient value R2 = 0.992 for Cu (II) and R2 = 0.973 for Ni (II) obtained for pseudosecond-order kinetics was closer to unity than the R2 value (0.677 = Cu (II) ions and 0.644 = Ni (II) ions) for first-order
kinetics. This indicates that adsorption of Cu (II) and Ni (II) ions by TGLRC follows pseudo-second-order kinetics.
In the intra particle diffusion model, the values of q t were found to be linearly correlated with the values of t 1/2. The
linear regression coefficient value R2 = 0.983 for Cu (II) and R2 = 0.989 for Ni (II) obtained for Intra particle diffusion model
was closer to unity. The kdif values were calculated by use of correlation analysis. kdif = 3.411 for the removal of Cu (II) ions
www.ijmer.com

3262 | Page
International Journal of Modern Engineering Research (IJMER)
www.ijmer.com
Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3255-3266
ISSN: 2249-6645
and kdif = 3.510 for the removal of Ni (II) ions. The data indicates that the adsorption kinetics follows the pseudo-secondorder rate with intraparticle diffusion as one of the rate determining steps.
Influence of other metal ions on the adsorption of Cu (II) and Ni (II) ions.
Effect of Ni (II) ions and Cr(III) ions on adsorption of Cu (II) and Ni (II) ions (binary system)

Binary system
90

% ads of Cu in presence of Ni.
% ads of Cu in presence of Cr.

% removal of Cu & Ni (II) ions

80

% ads of Ni in presence of Cu.
 % ads of Ni in presence of Cr.

70
60
50
40
30
20
10
0
0

10

20
30
40
0
10
20
30
40
Concentration of other metal ions (ppm)
Figure. 8. Effect of other metal ions in binary system on the adsorption of Cu (II) and Ni (II) ions onto TGLRC.
The concentration of the Cu (II) ion solution was kept as 100 ppm. The concentration of Ni (II) ion was varied as
10, 20, 30, and 40 ppm. Each solution was placed in a bottle with TGLRC and the pH was adjusted to 7.04. After shaking for
60 min percentage adsorption was calculated. Percentage adsorption decreased from 76.92 to 55.56 % as the concentration of
Ni (II) solution was increased. This showed competitive adsorption was, to some extent, taking place between the Cu (II)
ions and the Ni (II) ions. The same procedure was repeated for Cu (II) ions in presence of Cr(III) ions. The percentage
adsorption of Cu (II) ions decreased to 76.92–58.33% in the presence of Cr(III) ions. This is clearly shown in Fig. 8 for
TGLRC. When the same procedure was repeated for the adsorption of Ni (II) ions onto TGLRC at pH 7.12, adsorption
decreased to 71.73–53.13 % in the presence of Cu (II) ions and to 71.73–55.81% in presence of Cr(III) ions. This is clearly
shown in Fig. 8.
Effect of Cu (II), Ni (II) and Cr(III) ions on the adsorption of Cu (II) and Ni (II) ions (tertiary system)

Ternary system

90
% removal of Cu & Ni

80

% ads of Cu in presence of Ni & Cr

% ads of Ni in presence of Cu &Cr.

70
60
50
40
30
20
10
0
0

10

20

30

40

0

10

20

30

40

Concentration of other metal ions (ppm)
Figure. 9. Effect of other metal ions in tertiary system on the adsorption of Cu (II) and Ni (II) ions onto TGLRC.

www.ijmer.com

3263 | Page
International Journal of Modern Engineering Research (IJMER)
www.ijmer.com
Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3255-3266
ISSN: 2249-6645
The concentration of Cu (II) ion solution was kept as 100 ppm. The concentrations of Ni (II) and Cr(III) ion
solutions were varied as 10, 20, 30, and 40 ppm. Solutions of both Ni (II) ions and Cr(II) ions were added to Cu (II) solution
in a bottle with TGLRC and the pH was adjusted to 7.12. After shaking 1 h percentage adsorption was calculated. Percentage
adsorption decreased from 76.92 to 62.5 % as the concentrations of Ni (II) ions and Cr(III) ions were increased. This showed
competitive adsorption was, to some extent, taking place between the Ni (II) ions, the Cu (II) ions, and the Cr(III) ions.
Percentage adsorption of Cu (II) was reduced in the presence of the other metals, as is clearly shown in Fig. 9. The same
procedure was repeated for the adsorption Ni (II) ions onto TGLRC at pH 7.12 and percentage adsorption decreased from
71.71-52.17%, as the concentration of Cu (II) and Cr(III) was increased from 10-40 ppm, as illustrated in Fig. 9.
A fixed quantity of Cu (II) ions and Ni (II) ions onto TGLRC could only offer a finite number of surface binding
sites, some of which would be expected to be saturated by the competiting metal solutions. The decrease in sorption capacity
of same activated carbon in target metal solution than that of single metal may be ascribed to the less availability of binding
sites. In case of binary and ternary metal solution, the binding site is competitively divided among the various metal ions.
It is generally complicated to find a common rule to identify how metal properties affect the competitive sorption.
Among various factors that affect the sorption preferences of a sorbent, binding of metal ions on material largely depends on
physicochemical properties of metals.
The HSAB (hard and soft acids and bases) theory developed by Pearson [42] and extended to activated carbons
adsorption by Alfarra et al, [43]. Once acids and bases have been classified as hard or soft, a simple rule of the HSAB
principle can be given: hard acids prefer to bond to hard bases, and soft acids prefer to bond to soft bases. Generally, the C–
O or C=O bonds are more polar and less polarizable, hence harder than the C–C or C=C bonds. In this concept, the oxygen
surface groups of TGLRC are the hard sites that fix hard metal ions. According to this theory, Ni (II), Cu (II) and Cr(III)
cations are borderline acids [42]. Changing the experimental conditions, metal ions with a borderline hardness can be
biosorbed by the hard sites of TGLRC. The cationic exchange between the oxygenated surface groups (hard base) of TGLRC
and borderline acids gives ionic bonds which are more easily dissociated. But the competitive process cannot be explained
exactly by the hardness of cations because other effective factors and hardness values of Ni (II), Cu (II) and Cr (III)
borderline acids are close each other.

% Removal of Cu & Ni (II) ions onto TGLRC

Desorption and Reusability
70
60

% Desorption of Cu & Ni (II) ions
% of Recycling adsorption of Cu & Ni (II) ions

TGLRC-Ni

50
40

TGLRC-Cu

30
20
10
0
2.2 3.22 4.03 5.19 6.2 7.03 8.11 9.1

2.26 3.12 4.08 5.09 6.05 7.12 8.05 9.08

Initial pH
Figure. 10. Effect of pH on the desorption and recycling adsorption of Cu (II) and Ni (II) ions.
To investigate the possibility of repeated use of the adsorbent, desorption experiments were conducted under batch
experimental conditions and desorption efficiencies were showed in Fig. 10. If the adsorbed Cu (II) ion and Ni (II) ion can
be desorbed using neutral pH water, then the attachment of the copper and nickel ion of the adsorbent is by weak bonds. To
study the effect of solution pH on Cu (II) and Ni (II) ion desorption, 50 mL of distilled water at different pH values (2 - 9)
was agitated with 200 mg of TGLRC in a mechanical orbital shaker at room temperature. The pH was adjusted with 0.1 M
NaOH and 0.1 M HCl solutions. We could get maximum removal of 59.77% of adsorbed Cu (II) ion for 3.22 pH water and
53.77% of adsorbed Ni (II) ion for 3.12 pH water onto TGLRC, after 2 h of contact time between the loaded matrix and the
desorbing agents.
After desorption, the adsorbents were further used for adsorption of Cu (II) and Ni (II) ions. The percentage
removal of Cu (II) ions was found to be 53.85% for TGLRC at pH 7.04 and the removal of Ni (II) ion was found to
be 51.85 % for TGLRC at pH 7.12 (Fig.10). The increase in removal of Cu (II) and Ni (II) ions at pH 8 may be
because of precipitation of metal ions in alkaline medium rather than adsorption.

www.ijmer.com

3264 | Page
www.ijmer.com

International Journal of Modern Engineering Research (IJMER)
Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3255-3266
ISSN: 2249-6645

IV.

CONCLUSION

In this work, Tannin gel derived from Ricinus Communis leaves as a sorbent has been proposed to be an
efficient and economical alternative in Cu (II) and Ni (II) ion removal from water. The findings herein made us
conclude that:
(1) Batch sorption studies of Cu (II) and Ni (II) ions showed that the TGLRC can be successfully used to remove Cu and Ni
(II) ions from aqueous solution.
(2) The adsorption data were well fitted by the Langmuir isotherm model; this is indicative of monolayer adsorption by
TGLRC.
(3) By applying the kinetic models to the experimental data, it was found that the kinetics of Cu and Ni (II) ion adsorption
onto TGLRC followed by the pseudo-second order rate equation and intra particle diffusion is one of the rate limiting
step. Results of kinetic studies demonstrated that the Cu and Ni (II) ion adsorption was rapid and efficient.
(4) Percentage adsorption of Cu (II) and Ni (II) ions on TGLRC was higher in the single-ion systems than in binary and
ternary systems, which is indicative of competitive adsorption among the metal ions.
(5) Adsorbed Cu (II) and Ni (II)ions can be desorbed from both the adsorbents by use of double distilled water — 59.7 % of
adsorbed Cu (II) ions were recovered from TGLRC and 53.7 % of adsorbed Ni (II) ions were recovered from TGLRC at
pH 3.22 and pH 3.12, respectively.
(6) The experimental studies showed that Tannin gel prepared from leaves of Ricinus Communis could be used as an
alternative, inexpensive and effective material to remove high amount of Cu (II) and Ni (II) ions from aqueous solutions.

REFERENCES
[1]
[2]
[3]
[4]
[5]
[6]
[7]
[8]
[9]

[10]
[11]
[12]
[13]
[14]
[15]
[16]
[17]
[18]
[19]
[20]
[21]
[22]

[23]

F. Rozada, M. Otero, A. Moran, and A.I. Garcia, Adsorption of heavy metals onto sewage sludge-derived
materials,
Bioresource Technology, 99, 2008, 6332–6338.
K.K. Krishnani, X. Meng, C. Christodoulatos, and V.M. Boddu, Biosorption mechanism of nine different heavy metals onto
biomatrix from rice husk,” Journal of Hazardous Materials, 153, 2008, 222–1234.
S. Liang, XY. Guo, N.C. Feng, and QH. Tian, Application of orange peel xanthate for the adsorption of Pb 2+ from aqueous
solutions, Journal of Hazardous Materials, 170, 2009, 425.
R.P. Dhakal, K.N. Ghimiere, K. Inoue, Adsorptive separation of heavy metals from an aquatic environment using orange waste,
Hydrometallurgy. 79, 2005, 182.
U. Kumar, M. Bandyopadhyay, Sorption of cadmium from aqueous solution using pretreated rice husk, Bioresource Technology,
97, 2006, 104.
K.K. Singh, M. Talat, S.H. Hasan, Removal of lead from aqueous solutions by agriculture waste maize bran, Bioresource
Technology, 97, 2006, 2124.
W. Zhang, QG. Chang, WD. Liu, BJ. Li, WX. Jiang, LJ. Fu, Selecting activated carbon for water and wastewater treatability
studies, Environ Prog. 26, 2007, 289.
D. Prahas, Y. Kartika, N. Indraswati, and S. Ismadji, Activated carbon from jackfruit peel waste by H3PO4
chemical activation:
pore structure and surface charac-terization, Chemical Engineering Journal, 140, 2007, 32.
S. Altenor, B. Carene, E. Emmanuel, J. Lambert, J.J. Ehrhardt, and S. Gaspard, Adsorption studies of methylene blue and phenol
onto Vetiver roots activated carbon prepared by chemicalactivation, Journal of Hazardous Materials, 165(1–3), 2009, 1029–
1039.
A. Demirbas, A. Heavy metal adsorption onto agro-based waste materials: a review, Journal of Hazardous Materials, 157(2–3),
2008, 220–229.
F.A. Pavan, A.C. Mazzocato, Y. Gushikem, Removal of methylene blue dye from aqueous solutions by adsorption using yellow
passion fruit peel as adsorbent,” Bioresou. Technol. 99(8), 2008, 3162–3165.
P. Schofield, D.M. Mbugua, and A.N. Pell, Analysis of condensed tannins: a review, Animal Feed Science and Technology. 91(1),
2001, 21–40.
A. Pizzi, Advanced Wood Adhesives Technology, Marcel Dekker, New York. 1994.
N.E. Meikleham, A. Pizzi, Acid- and alkali-catalyzed tannin-based rigid foams,” J. of App. Poly. Sci. 53(11), 1994, 1547–1556.
G. Tondi, W. Zhao, A. Pizzi, G, Du, V. Fierro, and A. Celzard, Tannin-based rigid foams: a survey of chemical and physical
properties, Bioresource Technology, 100(21), 2009a, 5162–5169.
W. Zhao, V. Fierro, A. Pizzi, G. Du, A. Celzard, Effect of composition and processing parameters on the characteristics of tanninbased rigid foams, Part II: Physical properties, Materials Chemistry and Physics. 123(1), 2010, 210–217.
Y. Nakano, K. Takeshita, T. Tsutsumi, Adsorption mechanism of hexavalent chromium by redox within condensed-tannin gel,
Water Research.35(2), 2001, 496–500.
Y.H. Kim, Y. Nakano, Adsorption mechanism of palladium by redox within condensed-tannin gel, Water Research. 39(7), 2005,
1324–1330.
G. Tondi, C.W. Oo, A. Pizzi, M.F. Thevenon, Metal absorption of tannin-based rigid foams, Ind. Crops. Prod, 29(2–3), 2009b,
336–340.
W. Shirato, Y. Kamei, Insoluble tannin preparation process, waste treatment process and adsorption process using tannin, US
patent. 5, 158, 1992, 711.
G. Vázquez, G. Antorrena, J. González, M.D. Doval, Adsorption of heavy metal ions by chemically modified Pinus pinaster bark,
Bioresource Technology, 48(3), 1994, 251–255.
G. Vázquez, J. González-Álvarez, S. Freire, M. López-Lorenzo, and G. Antorrena, Removal of cadmium and
mercury ions
from aqueous solution by sorption on treated Pinus pinaster bark: kinetics and isotherms, Bioresource Technology, 82(3), 2002,
247–251.
A. Pizzi, Tannins: major sources, properties, applications, in Monomers, Polymers and Composites from Renewable Resources(eds
M.N. Belgacem and Gandini), Elsevier, Amsterdam, Ch 8. 2008.

www.ijmer.com

3265 | Page
www.ijmer.com
[24]

[25]
[26]
[27]
[28]
[29]
[30]
[31]
[32]
[33]
[34]
[35]
[36]
[37]
[38]
[39]
[40]
[41]
[42]
[43]

International Journal of Modern Engineering Research (IJMER)
Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3255-3266
ISSN: 2249-6645

M. Makeswari, T. Santhi, Optimization of Preparation of Activated Carbon from Ricinus communis Leaves by MicrowaveAssisted Zinc Chloride Chemical Activation: Competitive Adsorption of Ni 2+ Ions from Aqueous Solution, Journal of Chemistry,
Article ID 314790, 12 pages, doi:10.1155/2013/314790. 2013a.
M. Makeswari, and T. Santhi, Use of Ricinus communis leaves as a low cost adsorbent for removal of Cu (II) ions from aqueous
solution, Research on chemical intermediates, 39(2), 2013b.
M. Yurtsever, I.A. Sengil, Biosorption of Pb(II) ions by modified quebracho tannin resin, Journal of Hazardous
Materials,
163(1), 2009, 58–64.
A. Kumar, B. Prasad, and I.M. Mishra, Adsorptive removal of acryloinitrile by commercial grade activated carbon: kinetics,
equilibrium and thermodynamics, Journal of Hazardous Materials, 152, 2008, 589-600.
P. Janos, H. Buchtova, and M. Ryznarova, Sorption of dye from aqueous solution onto fly ash, Water Research. 37, 2003, 49384944.
K. Nakanishi, Infrared Absorption Spectroscopy-Practical, Holden-Day, San Francisco, CA,17-57, 1962.
J. Chang, R. Law, and C. Chang, Biosorption of lead copper and cadmium by biomass of Pseudomonas aeruginosa, Water
Research, 31, 1997, 1651.
Z. Elouear, R. Ben Amor, J. Bouzid, N. Boujelben, Use of phosphate rock for the removal of Ni 2+ from aqueous solutions: kinetic
and thermodynamics studies, Journal of Environmental Engineering, 135, 2009, 259.
I.D. Mall, V.C. Srivastava, N.K. Agarwal, and I.M. Mishra, Removal of congo red from aqueous solution by bagasse fly ash and
activated carbon: Kinetic study and equilibrium isotherm analyses, Chemosphere, 61, 2005, 492–501.
I. Langmuir, The adsorption of gases on plane surface of glass, mica and platinum, Journal of American chemical society, 40,
1918, 1361 – 1403.
H. Freundlich, Uber die adsorption in losungen (Adsorption in solution). Z. Phys. Chem, 57, 1906, 384 - 470.
I.A.W. Tan, B.H. Hameed, A.L. Ahmad, Equilibrium and kinetic studies on basic dye adsorption by oil palm fibre activated
carbon, Chemical Engineering Journal, 127, 2007, 111–119.
M.M. Dubinin, E.D. Zaverina, L.V. Radushkevich, Sorption and structure of activated carbons, I. Adsorption of organic vapours,
Zh. Fiz. Khim. 21, 1947, 1351–1362.
C.A. Basker, Applicability of the various adsorption models of three dyes adsorption onto activated carbon prepared from waste
apricot, Journal of Hazardous Materials, 135B: 2006, 232-241.
J. Halsey, Physical adsorption on Non-uniform surfaces, Chem. Phys. 16: 1948, 931.
Y.S. Ho, G. Mckay, G. Sorption of dye from aqueous solution by peat, Chemical Engineering Journal, 70, 1998a, 115–124.
Y.S. Ho, G. Mckay, Kinetic models for the sorption of dye from aqueous solution by wood, Journal of Environmental Science
Health Part B: Process Saf. Environ. Prot, 76(B), 1998b, 184–185.
W.J. Weber Jr, J.C. Morris, Kinetics of adsorption on carbon from solution, Journal of Sanitary Engineering Division, 89(2), 1963,
31–60.
R.G. Pearson, Hard and soft acids and bases, American journal of Chemical Society,85, 1963, 3533-3539.
A. Alfarra, E. Frackowiak, and F. Beguin, The HSAB concept as a means to interpret the adsorption of metal ions onto activated
carbons, Applied Surface Science,228, 2004, 84-92.

www.ijmer.com

3266 | Page

More Related Content

What's hot

Biological wastewater treatment processes
Biological wastewater treatment processesBiological wastewater treatment processes
Biological wastewater treatment processesArvind Kumar
 
International Refereed Journal of Engineering and Science (IRJES)
International Refereed Journal of Engineering and Science (IRJES)International Refereed Journal of Engineering and Science (IRJES)
International Refereed Journal of Engineering and Science (IRJES)irjes
 
Advanced oxidation processes
Advanced oxidation processesAdvanced oxidation processes
Advanced oxidation processesMdRomzanAli1
 
Characterization of Clay/Chitosan Nanocomposites and their Use for Adsorption...
Characterization of Clay/Chitosan Nanocomposites and their Use for Adsorption...Characterization of Clay/Chitosan Nanocomposites and their Use for Adsorption...
Characterization of Clay/Chitosan Nanocomposites and their Use for Adsorption...Editor IJCATR
 
advanced oxidation process
advanced oxidation processadvanced oxidation process
advanced oxidation processMahendheran Mech
 
Oxidative treatment of high explosives contaminated wastewater
Oxidative treatment of high explosives contaminated wastewaterOxidative treatment of high explosives contaminated wastewater
Oxidative treatment of high explosives contaminated wastewaterRaafat Alnaizy, PhD
 
Lecture 1 unit i environmental pollutant
Lecture 1 unit i environmental pollutantLecture 1 unit i environmental pollutant
Lecture 1 unit i environmental pollutantVikesh Lade
 
Wastewater
WastewaterWastewater
Wastewatertcha163
 
Wwtp presentation asim
Wwtp presentation asimWwtp presentation asim
Wwtp presentation asimAsimDin2
 
Chemical treatment methods
Chemical treatment methodsChemical treatment methods
Chemical treatment methodsMahaswari Jogia
 
Removal of Pb II from Aqueous Solutions using Activated Carbon Prepared from ...
Removal of Pb II from Aqueous Solutions using Activated Carbon Prepared from ...Removal of Pb II from Aqueous Solutions using Activated Carbon Prepared from ...
Removal of Pb II from Aqueous Solutions using Activated Carbon Prepared from ...ijtsrd
 
Dr.Parameswari- PhD agri NANOZYME for ETP sludge,COD,BOD reduction
Dr.Parameswari- PhD agri NANOZYME for ETP sludge,COD,BOD reductionDr.Parameswari- PhD agri NANOZYME for ETP sludge,COD,BOD reduction
Dr.Parameswari- PhD agri NANOZYME for ETP sludge,COD,BOD reductionkaliappan Sashi Kumar
 
Chemical characteristics of sewage and their testing
Chemical characteristics of sewage and their testing Chemical characteristics of sewage and their testing
Chemical characteristics of sewage and their testing Naina Gupta
 
Industrial wastewater treatment via photocatalysis
Industrial wastewater treatment via photocatalysisIndustrial wastewater treatment via photocatalysis
Industrial wastewater treatment via photocatalysisJay Lakhani
 
Ecomix Presentation 2014 (EN)
Ecomix Presentation 2014 (EN)Ecomix Presentation 2014 (EN)
Ecomix Presentation 2014 (EN)Ecosoft
 
COD reduction of aromatic polluted waste water by Advanced Oxidation Process ...
COD reduction of aromatic polluted waste water by Advanced Oxidation Process ...COD reduction of aromatic polluted waste water by Advanced Oxidation Process ...
COD reduction of aromatic polluted waste water by Advanced Oxidation Process ...Wade Bitaraf
 

What's hot (20)

Biological wastewater treatment processes
Biological wastewater treatment processesBiological wastewater treatment processes
Biological wastewater treatment processes
 
International Refereed Journal of Engineering and Science (IRJES)
International Refereed Journal of Engineering and Science (IRJES)International Refereed Journal of Engineering and Science (IRJES)
International Refereed Journal of Engineering and Science (IRJES)
 
Advanced oxidation processes
Advanced oxidation processesAdvanced oxidation processes
Advanced oxidation processes
 
Characterization of Clay/Chitosan Nanocomposites and their Use for Adsorption...
Characterization of Clay/Chitosan Nanocomposites and their Use for Adsorption...Characterization of Clay/Chitosan Nanocomposites and their Use for Adsorption...
Characterization of Clay/Chitosan Nanocomposites and their Use for Adsorption...
 
advanced oxidation process
advanced oxidation processadvanced oxidation process
advanced oxidation process
 
Oxidative treatment of high explosives contaminated wastewater
Oxidative treatment of high explosives contaminated wastewaterOxidative treatment of high explosives contaminated wastewater
Oxidative treatment of high explosives contaminated wastewater
 
Lecture 1 unit i environmental pollutant
Lecture 1 unit i environmental pollutantLecture 1 unit i environmental pollutant
Lecture 1 unit i environmental pollutant
 
Wastewater
WastewaterWastewater
Wastewater
 
Recycling of Jarosite For Recovery of Valuable Metals and its Utilisation
Recycling of Jarosite For Recovery of Valuable Metals and its UtilisationRecycling of Jarosite For Recovery of Valuable Metals and its Utilisation
Recycling of Jarosite For Recovery of Valuable Metals and its Utilisation
 
Wwtp presentation asim
Wwtp presentation asimWwtp presentation asim
Wwtp presentation asim
 
Chemical treatment methods
Chemical treatment methodsChemical treatment methods
Chemical treatment methods
 
Removal of Pb II from Aqueous Solutions using Activated Carbon Prepared from ...
Removal of Pb II from Aqueous Solutions using Activated Carbon Prepared from ...Removal of Pb II from Aqueous Solutions using Activated Carbon Prepared from ...
Removal of Pb II from Aqueous Solutions using Activated Carbon Prepared from ...
 
Article 3
Article 3Article 3
Article 3
 
Ln2419351940
Ln2419351940Ln2419351940
Ln2419351940
 
Dr.Parameswari- PhD agri NANOZYME for ETP sludge,COD,BOD reduction
Dr.Parameswari- PhD agri NANOZYME for ETP sludge,COD,BOD reductionDr.Parameswari- PhD agri NANOZYME for ETP sludge,COD,BOD reduction
Dr.Parameswari- PhD agri NANOZYME for ETP sludge,COD,BOD reduction
 
Effluent treatment
Effluent treatmentEffluent treatment
Effluent treatment
 
Chemical characteristics of sewage and their testing
Chemical characteristics of sewage and their testing Chemical characteristics of sewage and their testing
Chemical characteristics of sewage and their testing
 
Industrial wastewater treatment via photocatalysis
Industrial wastewater treatment via photocatalysisIndustrial wastewater treatment via photocatalysis
Industrial wastewater treatment via photocatalysis
 
Ecomix Presentation 2014 (EN)
Ecomix Presentation 2014 (EN)Ecomix Presentation 2014 (EN)
Ecomix Presentation 2014 (EN)
 
COD reduction of aromatic polluted waste water by Advanced Oxidation Process ...
COD reduction of aromatic polluted waste water by Advanced Oxidation Process ...COD reduction of aromatic polluted waste water by Advanced Oxidation Process ...
COD reduction of aromatic polluted waste water by Advanced Oxidation Process ...
 

Viewers also liked

Cz3210711074
Cz3210711074Cz3210711074
Cz3210711074IJMER
 
Mechanical Characterization of Biodegradable Linen Fiber Composites
Mechanical Characterization of Biodegradable Linen Fiber CompositesMechanical Characterization of Biodegradable Linen Fiber Composites
Mechanical Characterization of Biodegradable Linen Fiber CompositesIJMER
 
Strong Image Alignment for Meddling Recognision Purpose
Strong Image Alignment for Meddling Recognision PurposeStrong Image Alignment for Meddling Recognision Purpose
Strong Image Alignment for Meddling Recognision PurposeIJMER
 
Behavioural Modelling Outcomes prediction using Casual Factors
Behavioural Modelling Outcomes prediction using Casual  FactorsBehavioural Modelling Outcomes prediction using Casual  Factors
Behavioural Modelling Outcomes prediction using Casual FactorsIJMER
 
Analytic Model of Wind Disturbance Torque on Servo Tracking Antenna
Analytic Model of Wind Disturbance Torque on Servo Tracking AntennaAnalytic Model of Wind Disturbance Torque on Servo Tracking Antenna
Analytic Model of Wind Disturbance Torque on Servo Tracking AntennaIJMER
 
Heavy Mineral Studies of Beach Sands of Vagathor, North Goa, India
Heavy Mineral Studies of Beach Sands of Vagathor, North Goa,  IndiaHeavy Mineral Studies of Beach Sands of Vagathor, North Goa,  India
Heavy Mineral Studies of Beach Sands of Vagathor, North Goa, IndiaIJMER
 
Application of Neural Network for Cell Formation in Group Technology
Application of Neural Network for Cell Formation in Group  TechnologyApplication of Neural Network for Cell Formation in Group  Technology
Application of Neural Network for Cell Formation in Group TechnologyIJMER
 
Optimization of Tool Wear: A Review
Optimization of Tool Wear: A ReviewOptimization of Tool Wear: A Review
Optimization of Tool Wear: A ReviewIJMER
 
Worker Scheduling for Maintenance Modeling Software
Worker Scheduling for Maintenance Modeling SoftwareWorker Scheduling for Maintenance Modeling Software
Worker Scheduling for Maintenance Modeling SoftwareIJMER
 
Design of Shaft Is an Important Tool in Mercerization Machine
Design of Shaft Is an Important Tool in Mercerization Machine Design of Shaft Is an Important Tool in Mercerization Machine
Design of Shaft Is an Important Tool in Mercerization Machine IJMER
 
Security in Wireless Sensor Networks Using Broadcasting
Security in Wireless Sensor Networks Using BroadcastingSecurity in Wireless Sensor Networks Using Broadcasting
Security in Wireless Sensor Networks Using BroadcastingIJMER
 
Safety Margin of Slope Stability Using Common Deterministic Methods
Safety Margin of Slope Stability Using Common Deterministic  MethodsSafety Margin of Slope Stability Using Common Deterministic  Methods
Safety Margin of Slope Stability Using Common Deterministic MethodsIJMER
 
Investigations of Surface Dissolution on Fatigue Crack Nucleation in Ni-22Cr-...
Investigations of Surface Dissolution on Fatigue Crack Nucleation in Ni-22Cr-...Investigations of Surface Dissolution on Fatigue Crack Nucleation in Ni-22Cr-...
Investigations of Surface Dissolution on Fatigue Crack Nucleation in Ni-22Cr-...IJMER
 
Efficient Energy Management System with Solar Energy
Efficient Energy Management System with Solar EnergyEfficient Energy Management System with Solar Energy
Efficient Energy Management System with Solar EnergyIJMER
 
Three Party Authenticated Key Distribution using Quantum Cryptography
Three Party Authenticated Key Distribution using Quantum CryptographyThree Party Authenticated Key Distribution using Quantum Cryptography
Three Party Authenticated Key Distribution using Quantum CryptographyIJMER
 
Evaluation of Total Productive Maintenance Implementation in a Selected Semi-...
Evaluation of Total Productive Maintenance Implementation in a Selected Semi-...Evaluation of Total Productive Maintenance Implementation in a Selected Semi-...
Evaluation of Total Productive Maintenance Implementation in a Selected Semi-...IJMER
 
Network Performance Analysis of Dynamic Routing Protocols for Real Time Appl...
Network Performance Analysis of Dynamic Routing Protocols for  Real Time Appl...Network Performance Analysis of Dynamic Routing Protocols for  Real Time Appl...
Network Performance Analysis of Dynamic Routing Protocols for Real Time Appl...IJMER
 
Ac32618621
Ac32618621Ac32618621
Ac32618621IJMER
 
Ijmer 46063339
Ijmer 46063339Ijmer 46063339
Ijmer 46063339IJMER
 
Orientation Effects of Stress Concentrators on the Material Deformation Beha...
Orientation Effects of Stress Concentrators on the Material  Deformation Beha...Orientation Effects of Stress Concentrators on the Material  Deformation Beha...
Orientation Effects of Stress Concentrators on the Material Deformation Beha...IJMER
 

Viewers also liked (20)

Cz3210711074
Cz3210711074Cz3210711074
Cz3210711074
 
Mechanical Characterization of Biodegradable Linen Fiber Composites
Mechanical Characterization of Biodegradable Linen Fiber CompositesMechanical Characterization of Biodegradable Linen Fiber Composites
Mechanical Characterization of Biodegradable Linen Fiber Composites
 
Strong Image Alignment for Meddling Recognision Purpose
Strong Image Alignment for Meddling Recognision PurposeStrong Image Alignment for Meddling Recognision Purpose
Strong Image Alignment for Meddling Recognision Purpose
 
Behavioural Modelling Outcomes prediction using Casual Factors
Behavioural Modelling Outcomes prediction using Casual  FactorsBehavioural Modelling Outcomes prediction using Casual  Factors
Behavioural Modelling Outcomes prediction using Casual Factors
 
Analytic Model of Wind Disturbance Torque on Servo Tracking Antenna
Analytic Model of Wind Disturbance Torque on Servo Tracking AntennaAnalytic Model of Wind Disturbance Torque on Servo Tracking Antenna
Analytic Model of Wind Disturbance Torque on Servo Tracking Antenna
 
Heavy Mineral Studies of Beach Sands of Vagathor, North Goa, India
Heavy Mineral Studies of Beach Sands of Vagathor, North Goa,  IndiaHeavy Mineral Studies of Beach Sands of Vagathor, North Goa,  India
Heavy Mineral Studies of Beach Sands of Vagathor, North Goa, India
 
Application of Neural Network for Cell Formation in Group Technology
Application of Neural Network for Cell Formation in Group  TechnologyApplication of Neural Network for Cell Formation in Group  Technology
Application of Neural Network for Cell Formation in Group Technology
 
Optimization of Tool Wear: A Review
Optimization of Tool Wear: A ReviewOptimization of Tool Wear: A Review
Optimization of Tool Wear: A Review
 
Worker Scheduling for Maintenance Modeling Software
Worker Scheduling for Maintenance Modeling SoftwareWorker Scheduling for Maintenance Modeling Software
Worker Scheduling for Maintenance Modeling Software
 
Design of Shaft Is an Important Tool in Mercerization Machine
Design of Shaft Is an Important Tool in Mercerization Machine Design of Shaft Is an Important Tool in Mercerization Machine
Design of Shaft Is an Important Tool in Mercerization Machine
 
Security in Wireless Sensor Networks Using Broadcasting
Security in Wireless Sensor Networks Using BroadcastingSecurity in Wireless Sensor Networks Using Broadcasting
Security in Wireless Sensor Networks Using Broadcasting
 
Safety Margin of Slope Stability Using Common Deterministic Methods
Safety Margin of Slope Stability Using Common Deterministic  MethodsSafety Margin of Slope Stability Using Common Deterministic  Methods
Safety Margin of Slope Stability Using Common Deterministic Methods
 
Investigations of Surface Dissolution on Fatigue Crack Nucleation in Ni-22Cr-...
Investigations of Surface Dissolution on Fatigue Crack Nucleation in Ni-22Cr-...Investigations of Surface Dissolution on Fatigue Crack Nucleation in Ni-22Cr-...
Investigations of Surface Dissolution on Fatigue Crack Nucleation in Ni-22Cr-...
 
Efficient Energy Management System with Solar Energy
Efficient Energy Management System with Solar EnergyEfficient Energy Management System with Solar Energy
Efficient Energy Management System with Solar Energy
 
Three Party Authenticated Key Distribution using Quantum Cryptography
Three Party Authenticated Key Distribution using Quantum CryptographyThree Party Authenticated Key Distribution using Quantum Cryptography
Three Party Authenticated Key Distribution using Quantum Cryptography
 
Evaluation of Total Productive Maintenance Implementation in a Selected Semi-...
Evaluation of Total Productive Maintenance Implementation in a Selected Semi-...Evaluation of Total Productive Maintenance Implementation in a Selected Semi-...
Evaluation of Total Productive Maintenance Implementation in a Selected Semi-...
 
Network Performance Analysis of Dynamic Routing Protocols for Real Time Appl...
Network Performance Analysis of Dynamic Routing Protocols for  Real Time Appl...Network Performance Analysis of Dynamic Routing Protocols for  Real Time Appl...
Network Performance Analysis of Dynamic Routing Protocols for Real Time Appl...
 
Ac32618621
Ac32618621Ac32618621
Ac32618621
 
Ijmer 46063339
Ijmer 46063339Ijmer 46063339
Ijmer 46063339
 
Orientation Effects of Stress Concentrators on the Material Deformation Beha...
Orientation Effects of Stress Concentrators on the Material  Deformation Beha...Orientation Effects of Stress Concentrators on the Material  Deformation Beha...
Orientation Effects of Stress Concentrators on the Material Deformation Beha...
 

Similar to Tannin gel from Ricinus leaves removes Cu and Ni

A comparative study and kinetics for the removal of hexavalent
A comparative study and kinetics for the removal of hexavalentA comparative study and kinetics for the removal of hexavalent
A comparative study and kinetics for the removal of hexavalentAlexander Decker
 
A comparative study and kinetics for the removal of hexavalent
A comparative study and kinetics for the removal of hexavalentA comparative study and kinetics for the removal of hexavalent
A comparative study and kinetics for the removal of hexavalentAlexander Decker
 
Sorption kinetics and equilibrium studies on the removal of toxic cr(vi) ions...
Sorption kinetics and equilibrium studies on the removal of toxic cr(vi) ions...Sorption kinetics and equilibrium studies on the removal of toxic cr(vi) ions...
Sorption kinetics and equilibrium studies on the removal of toxic cr(vi) ions...Alexander Decker
 
Sorption kinetics and equilibrium studies on the removal of toxic cr(vi) ions...
Sorption kinetics and equilibrium studies on the removal of toxic cr(vi) ions...Sorption kinetics and equilibrium studies on the removal of toxic cr(vi) ions...
Sorption kinetics and equilibrium studies on the removal of toxic cr(vi) ions...Alexander Decker
 
Vol. 1 (1), 2014, 12–22
Vol. 1 (1), 2014, 12–22Vol. 1 (1), 2014, 12–22
Vol. 1 (1), 2014, 12–22Said Benramache
 
Use of Pine and Cinchona Barks for Mercury Removal.ppt
Use of Pine and Cinchona Barks for Mercury Removal.pptUse of Pine and Cinchona Barks for Mercury Removal.ppt
Use of Pine and Cinchona Barks for Mercury Removal.pptKAMAL_PANDEY123
 
Biosorption of Copper (II) Ions by Eclipta Alba Leaf Powder from Aqueous Solu...
Biosorption of Copper (II) Ions by Eclipta Alba Leaf Powder from Aqueous Solu...Biosorption of Copper (II) Ions by Eclipta Alba Leaf Powder from Aqueous Solu...
Biosorption of Copper (II) Ions by Eclipta Alba Leaf Powder from Aqueous Solu...ijtsrd
 
Removal of heavy metals from tannery effluent using Acacia nilotica and Solan...
Removal of heavy metals from tannery effluent using Acacia nilotica and Solan...Removal of heavy metals from tannery effluent using Acacia nilotica and Solan...
Removal of heavy metals from tannery effluent using Acacia nilotica and Solan...Akshay Prabha
 
Payal phd slides final1 [autosaved]
Payal  phd slides final1 [autosaved]Payal  phd slides final1 [autosaved]
Payal phd slides final1 [autosaved]payaljain273589
 
Biosorption of cu(ii) ions from aqueous solution using
Biosorption of cu(ii) ions from aqueous solution usingBiosorption of cu(ii) ions from aqueous solution using
Biosorption of cu(ii) ions from aqueous solution usingAlexander Decker
 
Biosorption of cu(ii) ions from aqueous solution using
Biosorption of cu(ii) ions from aqueous solution usingBiosorption of cu(ii) ions from aqueous solution using
Biosorption of cu(ii) ions from aqueous solution usingAlexander Decker
 
E041013242
E041013242E041013242
E041013242IOSR-JEN
 
Equilibrium and Kinetics Adsorption of Cadmium and Lead Ions from Aqueous Sol...
Equilibrium and Kinetics Adsorption of Cadmium and Lead Ions from Aqueous Sol...Equilibrium and Kinetics Adsorption of Cadmium and Lead Ions from Aqueous Sol...
Equilibrium and Kinetics Adsorption of Cadmium and Lead Ions from Aqueous Sol...theijes
 
Bio-Adsorbent.pdf
Bio-Adsorbent.pdfBio-Adsorbent.pdf
Bio-Adsorbent.pdfDrBabarAli2
 
Corchorusolitoriuswaste(mulukiya) as a potential sorbent for the removal of c...
Corchorusolitoriuswaste(mulukiya) as a potential sorbent for the removal of c...Corchorusolitoriuswaste(mulukiya) as a potential sorbent for the removal of c...
Corchorusolitoriuswaste(mulukiya) as a potential sorbent for the removal of c...IOSR Journals
 
IRJET- Review on Removel of Heavy Metal using Low - Cost Absorbents
IRJET- Review on Removel of Heavy Metal using Low - Cost AbsorbentsIRJET- Review on Removel of Heavy Metal using Low - Cost Absorbents
IRJET- Review on Removel of Heavy Metal using Low - Cost AbsorbentsIRJET Journal
 
IRJET- Study of Sugarcane Bagasse and Orange Peel as Adsorbent for Treatment ...
IRJET- Study of Sugarcane Bagasse and Orange Peel as Adsorbent for Treatment ...IRJET- Study of Sugarcane Bagasse and Orange Peel as Adsorbent for Treatment ...
IRJET- Study of Sugarcane Bagasse and Orange Peel as Adsorbent for Treatment ...IRJET Journal
 

Similar to Tannin gel from Ricinus leaves removes Cu and Ni (20)

A comparative study and kinetics for the removal of hexavalent
A comparative study and kinetics for the removal of hexavalentA comparative study and kinetics for the removal of hexavalent
A comparative study and kinetics for the removal of hexavalent
 
A comparative study and kinetics for the removal of hexavalent
A comparative study and kinetics for the removal of hexavalentA comparative study and kinetics for the removal of hexavalent
A comparative study and kinetics for the removal of hexavalent
 
Sorption kinetics and equilibrium studies on the removal of toxic cr(vi) ions...
Sorption kinetics and equilibrium studies on the removal of toxic cr(vi) ions...Sorption kinetics and equilibrium studies on the removal of toxic cr(vi) ions...
Sorption kinetics and equilibrium studies on the removal of toxic cr(vi) ions...
 
Sorption kinetics and equilibrium studies on the removal of toxic cr(vi) ions...
Sorption kinetics and equilibrium studies on the removal of toxic cr(vi) ions...Sorption kinetics and equilibrium studies on the removal of toxic cr(vi) ions...
Sorption kinetics and equilibrium studies on the removal of toxic cr(vi) ions...
 
Vol. 1 (1), 2014, 12–22
Vol. 1 (1), 2014, 12–22Vol. 1 (1), 2014, 12–22
Vol. 1 (1), 2014, 12–22
 
1
11
1
 
Use of Pine and Cinchona Barks for Mercury Removal.ppt
Use of Pine and Cinchona Barks for Mercury Removal.pptUse of Pine and Cinchona Barks for Mercury Removal.ppt
Use of Pine and Cinchona Barks for Mercury Removal.ppt
 
Biosorption of Copper (II) Ions by Eclipta Alba Leaf Powder from Aqueous Solu...
Biosorption of Copper (II) Ions by Eclipta Alba Leaf Powder from Aqueous Solu...Biosorption of Copper (II) Ions by Eclipta Alba Leaf Powder from Aqueous Solu...
Biosorption of Copper (II) Ions by Eclipta Alba Leaf Powder from Aqueous Solu...
 
Removal of heavy metals from tannery effluent using Acacia nilotica and Solan...
Removal of heavy metals from tannery effluent using Acacia nilotica and Solan...Removal of heavy metals from tannery effluent using Acacia nilotica and Solan...
Removal of heavy metals from tannery effluent using Acacia nilotica and Solan...
 
Payal phd slides final1 [autosaved]
Payal  phd slides final1 [autosaved]Payal  phd slides final1 [autosaved]
Payal phd slides final1 [autosaved]
 
Biosorption of cu(ii) ions from aqueous solution using
Biosorption of cu(ii) ions from aqueous solution usingBiosorption of cu(ii) ions from aqueous solution using
Biosorption of cu(ii) ions from aqueous solution using
 
Biosorption of cu(ii) ions from aqueous solution using
Biosorption of cu(ii) ions from aqueous solution usingBiosorption of cu(ii) ions from aqueous solution using
Biosorption of cu(ii) ions from aqueous solution using
 
Lm3519611971
Lm3519611971Lm3519611971
Lm3519611971
 
E041013242
E041013242E041013242
E041013242
 
Equilibrium and Kinetics Adsorption of Cadmium and Lead Ions from Aqueous Sol...
Equilibrium and Kinetics Adsorption of Cadmium and Lead Ions from Aqueous Sol...Equilibrium and Kinetics Adsorption of Cadmium and Lead Ions from Aqueous Sol...
Equilibrium and Kinetics Adsorption of Cadmium and Lead Ions from Aqueous Sol...
 
Bio-Adsorbent.pdf
Bio-Adsorbent.pdfBio-Adsorbent.pdf
Bio-Adsorbent.pdf
 
Corchorusolitoriuswaste(mulukiya) as a potential sorbent for the removal of c...
Corchorusolitoriuswaste(mulukiya) as a potential sorbent for the removal of c...Corchorusolitoriuswaste(mulukiya) as a potential sorbent for the removal of c...
Corchorusolitoriuswaste(mulukiya) as a potential sorbent for the removal of c...
 
IRJET- Review on Removel of Heavy Metal using Low - Cost Absorbents
IRJET- Review on Removel of Heavy Metal using Low - Cost AbsorbentsIRJET- Review on Removel of Heavy Metal using Low - Cost Absorbents
IRJET- Review on Removel of Heavy Metal using Low - Cost Absorbents
 
10.1.1.1062.5005.pdf
10.1.1.1062.5005.pdf10.1.1.1062.5005.pdf
10.1.1.1062.5005.pdf
 
IRJET- Study of Sugarcane Bagasse and Orange Peel as Adsorbent for Treatment ...
IRJET- Study of Sugarcane Bagasse and Orange Peel as Adsorbent for Treatment ...IRJET- Study of Sugarcane Bagasse and Orange Peel as Adsorbent for Treatment ...
IRJET- Study of Sugarcane Bagasse and Orange Peel as Adsorbent for Treatment ...
 

More from IJMER

A Study on Translucent Concrete Product and Its Properties by Using Optical F...
A Study on Translucent Concrete Product and Its Properties by Using Optical F...A Study on Translucent Concrete Product and Its Properties by Using Optical F...
A Study on Translucent Concrete Product and Its Properties by Using Optical F...IJMER
 
Developing Cost Effective Automation for Cotton Seed Delinting
Developing Cost Effective Automation for Cotton Seed DelintingDeveloping Cost Effective Automation for Cotton Seed Delinting
Developing Cost Effective Automation for Cotton Seed DelintingIJMER
 
Study & Testing Of Bio-Composite Material Based On Munja Fibre
Study & Testing Of Bio-Composite Material Based On Munja FibreStudy & Testing Of Bio-Composite Material Based On Munja Fibre
Study & Testing Of Bio-Composite Material Based On Munja FibreIJMER
 
Hybrid Engine (Stirling Engine + IC Engine + Electric Motor)
Hybrid Engine (Stirling Engine + IC Engine + Electric Motor)Hybrid Engine (Stirling Engine + IC Engine + Electric Motor)
Hybrid Engine (Stirling Engine + IC Engine + Electric Motor)IJMER
 
Fabrication & Characterization of Bio Composite Materials Based On Sunnhemp F...
Fabrication & Characterization of Bio Composite Materials Based On Sunnhemp F...Fabrication & Characterization of Bio Composite Materials Based On Sunnhemp F...
Fabrication & Characterization of Bio Composite Materials Based On Sunnhemp F...IJMER
 
Geochemistry and Genesis of Kammatturu Iron Ores of Devagiri Formation, Sandu...
Geochemistry and Genesis of Kammatturu Iron Ores of Devagiri Formation, Sandu...Geochemistry and Genesis of Kammatturu Iron Ores of Devagiri Formation, Sandu...
Geochemistry and Genesis of Kammatturu Iron Ores of Devagiri Formation, Sandu...IJMER
 
Experimental Investigation on Characteristic Study of the Carbon Steel C45 in...
Experimental Investigation on Characteristic Study of the Carbon Steel C45 in...Experimental Investigation on Characteristic Study of the Carbon Steel C45 in...
Experimental Investigation on Characteristic Study of the Carbon Steel C45 in...IJMER
 
Non linear analysis of Robot Gun Support Structure using Equivalent Dynamic A...
Non linear analysis of Robot Gun Support Structure using Equivalent Dynamic A...Non linear analysis of Robot Gun Support Structure using Equivalent Dynamic A...
Non linear analysis of Robot Gun Support Structure using Equivalent Dynamic A...IJMER
 
Static Analysis of Go-Kart Chassis by Analytical and Solid Works Simulation
Static Analysis of Go-Kart Chassis by Analytical and Solid Works SimulationStatic Analysis of Go-Kart Chassis by Analytical and Solid Works Simulation
Static Analysis of Go-Kart Chassis by Analytical and Solid Works SimulationIJMER
 
High Speed Effortless Bicycle
High Speed Effortless BicycleHigh Speed Effortless Bicycle
High Speed Effortless BicycleIJMER
 
Integration of Struts & Spring & Hibernate for Enterprise Applications
Integration of Struts & Spring & Hibernate for Enterprise ApplicationsIntegration of Struts & Spring & Hibernate for Enterprise Applications
Integration of Struts & Spring & Hibernate for Enterprise ApplicationsIJMER
 
Microcontroller Based Automatic Sprinkler Irrigation System
Microcontroller Based Automatic Sprinkler Irrigation SystemMicrocontroller Based Automatic Sprinkler Irrigation System
Microcontroller Based Automatic Sprinkler Irrigation SystemIJMER
 
On some locally closed sets and spaces in Ideal Topological Spaces
On some locally closed sets and spaces in Ideal Topological SpacesOn some locally closed sets and spaces in Ideal Topological Spaces
On some locally closed sets and spaces in Ideal Topological SpacesIJMER
 
Intrusion Detection and Forensics based on decision tree and Association rule...
Intrusion Detection and Forensics based on decision tree and Association rule...Intrusion Detection and Forensics based on decision tree and Association rule...
Intrusion Detection and Forensics based on decision tree and Association rule...IJMER
 
Natural Language Ambiguity and its Effect on Machine Learning
Natural Language Ambiguity and its Effect on Machine LearningNatural Language Ambiguity and its Effect on Machine Learning
Natural Language Ambiguity and its Effect on Machine LearningIJMER
 
Evolvea Frameworkfor SelectingPrime Software DevelopmentProcess
Evolvea Frameworkfor SelectingPrime Software DevelopmentProcessEvolvea Frameworkfor SelectingPrime Software DevelopmentProcess
Evolvea Frameworkfor SelectingPrime Software DevelopmentProcessIJMER
 
Material Parameter and Effect of Thermal Load on Functionally Graded Cylinders
Material Parameter and Effect of Thermal Load on Functionally Graded CylindersMaterial Parameter and Effect of Thermal Load on Functionally Graded Cylinders
Material Parameter and Effect of Thermal Load on Functionally Graded CylindersIJMER
 
Studies On Energy Conservation And Audit
Studies On Energy Conservation And AuditStudies On Energy Conservation And Audit
Studies On Energy Conservation And AuditIJMER
 
An Implementation of I2C Slave Interface using Verilog HDL
An Implementation of I2C Slave Interface using Verilog HDLAn Implementation of I2C Slave Interface using Verilog HDL
An Implementation of I2C Slave Interface using Verilog HDLIJMER
 
Discrete Model of Two Predators competing for One Prey
Discrete Model of Two Predators competing for One PreyDiscrete Model of Two Predators competing for One Prey
Discrete Model of Two Predators competing for One PreyIJMER
 

More from IJMER (20)

A Study on Translucent Concrete Product and Its Properties by Using Optical F...
A Study on Translucent Concrete Product and Its Properties by Using Optical F...A Study on Translucent Concrete Product and Its Properties by Using Optical F...
A Study on Translucent Concrete Product and Its Properties by Using Optical F...
 
Developing Cost Effective Automation for Cotton Seed Delinting
Developing Cost Effective Automation for Cotton Seed DelintingDeveloping Cost Effective Automation for Cotton Seed Delinting
Developing Cost Effective Automation for Cotton Seed Delinting
 
Study & Testing Of Bio-Composite Material Based On Munja Fibre
Study & Testing Of Bio-Composite Material Based On Munja FibreStudy & Testing Of Bio-Composite Material Based On Munja Fibre
Study & Testing Of Bio-Composite Material Based On Munja Fibre
 
Hybrid Engine (Stirling Engine + IC Engine + Electric Motor)
Hybrid Engine (Stirling Engine + IC Engine + Electric Motor)Hybrid Engine (Stirling Engine + IC Engine + Electric Motor)
Hybrid Engine (Stirling Engine + IC Engine + Electric Motor)
 
Fabrication & Characterization of Bio Composite Materials Based On Sunnhemp F...
Fabrication & Characterization of Bio Composite Materials Based On Sunnhemp F...Fabrication & Characterization of Bio Composite Materials Based On Sunnhemp F...
Fabrication & Characterization of Bio Composite Materials Based On Sunnhemp F...
 
Geochemistry and Genesis of Kammatturu Iron Ores of Devagiri Formation, Sandu...
Geochemistry and Genesis of Kammatturu Iron Ores of Devagiri Formation, Sandu...Geochemistry and Genesis of Kammatturu Iron Ores of Devagiri Formation, Sandu...
Geochemistry and Genesis of Kammatturu Iron Ores of Devagiri Formation, Sandu...
 
Experimental Investigation on Characteristic Study of the Carbon Steel C45 in...
Experimental Investigation on Characteristic Study of the Carbon Steel C45 in...Experimental Investigation on Characteristic Study of the Carbon Steel C45 in...
Experimental Investigation on Characteristic Study of the Carbon Steel C45 in...
 
Non linear analysis of Robot Gun Support Structure using Equivalent Dynamic A...
Non linear analysis of Robot Gun Support Structure using Equivalent Dynamic A...Non linear analysis of Robot Gun Support Structure using Equivalent Dynamic A...
Non linear analysis of Robot Gun Support Structure using Equivalent Dynamic A...
 
Static Analysis of Go-Kart Chassis by Analytical and Solid Works Simulation
Static Analysis of Go-Kart Chassis by Analytical and Solid Works SimulationStatic Analysis of Go-Kart Chassis by Analytical and Solid Works Simulation
Static Analysis of Go-Kart Chassis by Analytical and Solid Works Simulation
 
High Speed Effortless Bicycle
High Speed Effortless BicycleHigh Speed Effortless Bicycle
High Speed Effortless Bicycle
 
Integration of Struts & Spring & Hibernate for Enterprise Applications
Integration of Struts & Spring & Hibernate for Enterprise ApplicationsIntegration of Struts & Spring & Hibernate for Enterprise Applications
Integration of Struts & Spring & Hibernate for Enterprise Applications
 
Microcontroller Based Automatic Sprinkler Irrigation System
Microcontroller Based Automatic Sprinkler Irrigation SystemMicrocontroller Based Automatic Sprinkler Irrigation System
Microcontroller Based Automatic Sprinkler Irrigation System
 
On some locally closed sets and spaces in Ideal Topological Spaces
On some locally closed sets and spaces in Ideal Topological SpacesOn some locally closed sets and spaces in Ideal Topological Spaces
On some locally closed sets and spaces in Ideal Topological Spaces
 
Intrusion Detection and Forensics based on decision tree and Association rule...
Intrusion Detection and Forensics based on decision tree and Association rule...Intrusion Detection and Forensics based on decision tree and Association rule...
Intrusion Detection and Forensics based on decision tree and Association rule...
 
Natural Language Ambiguity and its Effect on Machine Learning
Natural Language Ambiguity and its Effect on Machine LearningNatural Language Ambiguity and its Effect on Machine Learning
Natural Language Ambiguity and its Effect on Machine Learning
 
Evolvea Frameworkfor SelectingPrime Software DevelopmentProcess
Evolvea Frameworkfor SelectingPrime Software DevelopmentProcessEvolvea Frameworkfor SelectingPrime Software DevelopmentProcess
Evolvea Frameworkfor SelectingPrime Software DevelopmentProcess
 
Material Parameter and Effect of Thermal Load on Functionally Graded Cylinders
Material Parameter and Effect of Thermal Load on Functionally Graded CylindersMaterial Parameter and Effect of Thermal Load on Functionally Graded Cylinders
Material Parameter and Effect of Thermal Load on Functionally Graded Cylinders
 
Studies On Energy Conservation And Audit
Studies On Energy Conservation And AuditStudies On Energy Conservation And Audit
Studies On Energy Conservation And Audit
 
An Implementation of I2C Slave Interface using Verilog HDL
An Implementation of I2C Slave Interface using Verilog HDLAn Implementation of I2C Slave Interface using Verilog HDL
An Implementation of I2C Slave Interface using Verilog HDL
 
Discrete Model of Two Predators competing for One Prey
Discrete Model of Two Predators competing for One PreyDiscrete Model of Two Predators competing for One Prey
Discrete Model of Two Predators competing for One Prey
 

Recently uploaded

Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptxUse of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptxLoriGlavin3
 
Sample pptx for embedding into website for demo
Sample pptx for embedding into website for demoSample pptx for embedding into website for demo
Sample pptx for embedding into website for demoHarshalMandlekar2
 
WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brandgvaughan
 
The State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxThe State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxLoriGlavin3
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsPixlogix Infotech
 
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024BookNet Canada
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLScyllaDB
 
Time Series Foundation Models - current state and future directions
Time Series Foundation Models - current state and future directionsTime Series Foundation Models - current state and future directions
Time Series Foundation Models - current state and future directionsNathaniel Shimoni
 
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxThe Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxLoriGlavin3
 
unit 4 immunoblotting technique complete.pptx
unit 4 immunoblotting technique complete.pptxunit 4 immunoblotting technique complete.pptx
unit 4 immunoblotting technique complete.pptxBkGupta21
 
Take control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteTake control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteDianaGray10
 
Ryan Mahoney - Will Artificial Intelligence Replace Real Estate Agents
Ryan Mahoney - Will Artificial Intelligence Replace Real Estate AgentsRyan Mahoney - Will Artificial Intelligence Replace Real Estate Agents
Ryan Mahoney - Will Artificial Intelligence Replace Real Estate AgentsRyan Mahoney
 
DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenHervé Boutemy
 
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptxMerck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptxLoriGlavin3
 
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptxPasskey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptxLoriGlavin3
 
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024BookNet Canada
 
What is DBT - The Ultimate Data Build Tool.pdf
What is DBT - The Ultimate Data Build Tool.pdfWhat is DBT - The Ultimate Data Build Tool.pdf
What is DBT - The Ultimate Data Build Tool.pdfMounikaPolabathina
 
Generative AI for Technical Writer or Information Developers
Generative AI for Technical Writer or Information DevelopersGenerative AI for Technical Writer or Information Developers
Generative AI for Technical Writer or Information DevelopersRaghuram Pandurangan
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfAlex Barbosa Coqueiro
 
Moving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdfMoving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdfLoriGlavin3
 

Recently uploaded (20)

Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptxUse of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
 
Sample pptx for embedding into website for demo
Sample pptx for embedding into website for demoSample pptx for embedding into website for demo
Sample pptx for embedding into website for demo
 
WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brand
 
The State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxThe State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptx
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and Cons
 
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQL
 
Time Series Foundation Models - current state and future directions
Time Series Foundation Models - current state and future directionsTime Series Foundation Models - current state and future directions
Time Series Foundation Models - current state and future directions
 
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxThe Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
 
unit 4 immunoblotting technique complete.pptx
unit 4 immunoblotting technique complete.pptxunit 4 immunoblotting technique complete.pptx
unit 4 immunoblotting technique complete.pptx
 
Take control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteTake control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test Suite
 
Ryan Mahoney - Will Artificial Intelligence Replace Real Estate Agents
Ryan Mahoney - Will Artificial Intelligence Replace Real Estate AgentsRyan Mahoney - Will Artificial Intelligence Replace Real Estate Agents
Ryan Mahoney - Will Artificial Intelligence Replace Real Estate Agents
 
DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache Maven
 
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptxMerck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
 
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptxPasskey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptx
 
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
 
What is DBT - The Ultimate Data Build Tool.pdf
What is DBT - The Ultimate Data Build Tool.pdfWhat is DBT - The Ultimate Data Build Tool.pdf
What is DBT - The Ultimate Data Build Tool.pdf
 
Generative AI for Technical Writer or Information Developers
Generative AI for Technical Writer or Information DevelopersGenerative AI for Technical Writer or Information Developers
Generative AI for Technical Writer or Information Developers
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdf
 
Moving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdfMoving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdf
 

Tannin gel from Ricinus leaves removes Cu and Ni

  • 1. www.ijmer.com International Journal of Modern Engineering Research (IJMER) Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3255-3266 ISSN: 2249-6645 Tannin gel derived from Leaves of Ricinus Communis as an adsorbent for the Removal of Cu (II) and Ni (II) ions from aqueous solution M. Makeswari1, T. Santhi2 Department of chemistry, Karpagam University, Coimbatore 641021, Tamil Nadu, India. ABSTRACT: The biosorption of Cu (II) and Ni (II) ions from aqueous solutions by Tannin gel derived from Leaves of Ricinus Communis was investigated as a function of pH ZPC, Initial pH, adsorbent dose, contact time and metal ion concentration. The aim of this study was to prepare the adsorbent and to find a suitable equilibrium isotherm and kinetic model for the removal of Cu (II) and Ni (II) ions in a batch reactor. The maximum percentage of adsorption for the removal of Cu (II) ion was found to be 76.92% at 7.04 pH and for the removal of Ni (II) ion was 71.74% at 7.12 pH. The adsorption of Cu (II) and Ni (II) ions followed the Pseudo-second-order and Intra particle diffusion rate equations and fits the Langmuir, Freundlich and Frenkel-Halsey-Hill isotherm equations well. The effects of the presence of one metal ion on the adsorption of the other metal ion were investigated in binary and ternary mixture and then the results were compared with single system. We investigate the recovery of the used adsorbent for its reusing is of great importance for environmental and economical reasons. i.e., TGLRC will be recovered by desorption method by using proper desorption agent like H 2O by batch mode study. Activated carbon developed from Ricinus Communis leaves can be an attractive option for heavy metal removal from water and waste water since test reactions made on stimulated waste water sowed better removal percentage of Cu (II) and Ni (II) ions. Keywords: Adsorption; Tannin gel; Ricinus communis leaves; Binary and Tertiary; Desorption. I. INTRODUCTION The pollution of water resources due to the indiscriminate disposal of heavy metals has been causing worldwide concern for the last few decades. It is well known that some metals can have toxic or harmful effects on many forms of life. Among the most toxic metals are chromium (Cr), copper (Cu), lead (Pb), zinc (Zn) and mercury (Hg), which is one of the 11 hazardous priority substances in the list of pollutants contained in the Water Framework Directive (Directive 2000/60/EC) [1]. Many industries discharge heavy metals such as lead, cadmium, copper, nickel and zinc in their wastewaters [2]. Metals such as copper and nickel are known to be essential to plants, humans and animals, but they can also have adverse effects if their availability in water exceeds certain threshold values. Therefore, it is urgent to remove heavy metals such as copper and nickel from wastewater. Although heavy metal removal from aqueous solutions can be achieved by conventional methods, including chemical precipitation, oxidation/reduction, electrochemical treatment, evaporative recovery, filtration, ion exchange and membrane technologies, they may be ineffective or cost-expensive, especially when the metal ion concentrations in solution are in the range of 1–100 mg/L [3, 4]. Recently, adsorption technology has become one of the alternative treatments in either laboratory or industrial scale [5, 6]. There are many adsorbents in use. Activated carbons (AC) are known as very effective adsorbents due to their highly developed porosity, large surface area, variable characteristics of surface chemistry, and high degree of surface reactivity [7]. However, due to their high production costs, these materials tend to be more expensive than other adsorbents. This has led a growing research interest in the production of activated carbons from renewable and cheaper precursors. The choice of precursor largely depends on its availability, cost, and purity, but the manufacturing process and intended applications of the product are also important considerations [8]. Several suitable agricultural by-products (lignocellulosics) including fruit stones, olive waste cake, pine bark, rice husks, pistachio-nut shells and wheat bran have been investigated in the last years as activated carbon precursors and are still receiving renewed attention. In recent years, considerable attention has been focused on the removal of heavy metals from aqueous solution using natural raw materials are an interesting potential source of low-cost adsorbents [9-11]. Tannins, natural biomass containing multiple adjacent hydroxyl groups and exhibiting specific affinity to metal ions, can probably be used as alternative, effective and efficient adsorbents for the recovery of metal ions. During the last years, the interest on biomaterials and specifically in tannins was growing. The term tannins cover many families of chemical compounds. Traditionally they have been used for tanning animal skins, hence their name, but one also finds several of them used as water treatment agents. Their natural origin is as secondary metabolites of plants [12], occurring in the bark, fruit, leaves, etc. While Acacia and Schinopsis bark constitute the principal source of tannins for the leather industry, the bark of other non-tropical trees such as Quercus ilex, suber, and robur, Castanea, and Pinus can also be tannin-rich. Tannin gelification is a chemical procedure that inmobilizes tannins in an insoluble matrix [13, 14] so their properties involving, e.g. metal chelation, are available then in an efficient adsorbing agent. In addition, the resulting material from gelification (sometimes called tannin rigid gel) presents interesting properties from the point of view of resistance, nonflammability or mechanical undeformability [15, 16]. Gelifications of tannins have been widely reported either in scientific literature or in patents. Experimental conditions of gelification may imply the use of formaldehyde or other aldehyde in a basic or acidic environment. Examples of basic gelification are shown in scientific literature previously [17-19] and in patents such as US patent 5,158,711 [20]. Acid gelification is also presented by other researchers [21, 22]. www.ijmer.com 3255 | Page
  • 2. International Journal of Modern Engineering Research (IJMER) www.ijmer.com Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3255-3266 ISSN: 2249-6645 The chemical basis of the tannin gelification is widely reported [23]. Formaldehyde and other aldehydes react with tannins to induce polymerization through methylene bridge linkages at reactive positions on the tannin flavonoid molecules. Agricultural by-products are high volume, low value and underutilized lignocellulosic biomaterials, and contain high levels of cellulose, hemicellulose and lignin. Ricinus communis is a species of flowering plant in the spurge family, Euphorbiaceae. It belongs to a monotypic genus, Ricinus, and subtribe, Ricininae. Ricinus communis grows throughout the drier parts and near drainages of India. Annual production of Ricinus communis is estimated to be more than 1.0 tons globally, of which India accounts for 60% of the production. The adsorption ability of Ricinus communis leaves was previously investigated for the adsorption of Cu 2+ ion and Ni2+ ion from aqueous solution [24, 25]. In this study, Tannin gel has been prepared from the cheap and abundantly available agricultural waste product leaves of Ricinus communis (TGLRC) and applied them to remove heavy metals such as Cu (II) and Ni (II) ions from waste water. The objective of this study is to systematically examine adsorption mechanisms, adsorption isotherms, adsorption kinetics and properties of a tannin gel adsorbent synthesized from leaves of Ricinus communis (TGLRC) for removal of Cu (II) and Ni (II) ions from aqueous solutions. II. MATERIALS AND METHODS Preparation of Adsorbent Tannin extracts The Ricinus communis leaves were obtained from the agricultural form in Tirupur district (Tamil Nadu). It was airdried and powdered in a grinder. Dried Ricinus communis with the mass of 100 g were mixed with 600 mL of water. Then 5 g of NaOH were added and the mixture was stirred in magnetic stirrer at 90C for 1 h. Solids was separated by filtration and liquid fraction was dried in oven (65C) overnight. The resultant was considered the tannin extract. Tannin gel preparation (TGLRC) Tannin gels were prepared according to the basis of Nakano et al. [17]. Five grams of tannin extract were dissolved in 32mL of NaOH (PANREAC) 0.125 mol L−1 and 30mL of distilled water at 80 ◦C. When mixture was homogeneous, certain amount of aldehyde (Formaldehyde) was added and reaction was kept at the same temperature for 8 h until polymerization was considered completed. Then, the apparent gummy product was lead to complete evaporation of water remain and dried in oven (65º C) overnight. After drying, tannin rigid gels were crushed to small particles. They were washed successively with distilled water and 0.01 molar HNO3 was used to remove unreacted sodium hydroxide. Finally, the adsorbent was dried again in oven. Differences are found between this preparation way and the description made by Yurtsever and Sengil [26], mainly concerning the amount of formaldehyde. Preparation of stock solution Samples of potassium chromate (K2CrO4), copper sulphate penta hydrate (CuSO4.5H2O) and Nickel sulphate hexa hydrate (NiSO.6H2O) was obtained from Aluva, Edayar (specrum reagents and chemicals pvt. Ltd). All other chemicals used in this study were analytical grade and Purchased from Aluva, Edayar (specrum reagents and chemicals pvt. Ltd) A Stock solution of 1000 mg/L was prepared by dissolving accurately weighed amounts of potassium chromate (K2CrO4) in doses of 1000 mL double-distilled water. Working copper and Nickel solutions were prepared just before used by appropriate dilutions of stock solution. Characterization of the adsorbent The point of zero surface charge characteristic of TGLRC was (pH ZPC) determined by using the solid addition method. A Fourier transform infrared spectroscopy (SHIMADZU, IR Affinity-1) with KBr pellet was used to study the functional groups available on the surface of TGLRC, with a scanning range of 4000-400cm-1. The crystalline structure of TGLRC was evaluated by X-ray diffractometer, by using Cu K α radiation (1.54060 Å) at 45 kV and 30 mA with a scan analysis. The concentration of Cu (II) and Ni (II) ions was determined using UV-vis spectrophotometer (SHIMADZU UV2450). Batch adsorption studies The adsorption experiments were carried out in a batch process to evaluate the effect of pH, contact time, adsorbent dose, adsorption kinetics, adsorption isotherm, influence of other metal ions in single and binary system and regeneration of Cu (II) and Ni (II) ions onto TGLRC. Batch equilibrium studies To study the effect of parameters such as adsorbent dose, metal ion concentration and solution pH for the removal of adsorbate on TGLRC, batch experiments were performed. Stock solutions of CuSO4.5H2O and NiSO4.6H2O was prepared and further diluted to the 25 – 200 mg/ L concentrations for the experiments. pH adjustment was fulfilled by adding 0.1 M HCl or 0.1 M NaOH into the solutions with known initial metal concentrations. Batch adsorption experiments were conducted in asset of 250 mL stoppered flasks containing 200 mg adsorbent and 50 mL of metal solutions with different concentrations (25-200 mg / L) at the optimum solution pH. The flasks were agitated using a mechanical orbital shaker, and maintained at room temperature for 2 h at a fixed shaking speed of 120 rpm until the equilibrium was reached. The www.ijmer.com 3256 | Page
  • 3. International Journal of Modern Engineering Research (IJMER) www.ijmer.com Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3255-3266 ISSN: 2249-6645 suspensions were filtered and metal concentrations in the supernatant solutions were measured using a Digital photo colorimeter (model number-313). From the initial and final concentrations, percentage removal can be calculated by use of the formula: 𝑪𝟎 − 𝑪𝒇 % 𝒐𝒇 𝑹𝒆𝒎𝒐𝒗𝒂𝒍 = × 𝟏𝟎𝟎 (𝟏) 𝑪𝟎 where Co is the initial concentration of Cu (II) and Ni (II) ions in mg/L and Cf is the final concentration of Cu (II) and Ni (II) ions in mg/L. The results obtained in batch mode were used to calculate the equilibrium metal uptake capacity. The amounts of uptake of Cu (II) and Ni (II) ions by TGLRC in the equilibrium (qe) were calculated by the following mass-balance relationship: 𝑪𝟎 − 𝑪𝒆 𝒒𝒆 = × 𝑽 (𝟐) 𝑾 where qe is the equilibrium uptake capacity in mg/g, V is the sample volume in liters, Co is the initial metal ion concentration in mg/L, Ce the equilibrium metal ion concentration in mg/L, and W is the dry weight of adsorbent in grams. III. RESULTS AND DISCUSSION Characterization of TGLRC adsorbent Zero point charges (pHZPC) The zero surface charge characteristics of TGLRC were determined by using the solid addition method [27]. The experiment was conducted in a series of 250 mL glass stoppered flasks. Each flask was filled with 50 mL of different initial pH NaN02 solutions and 200 mg of TGLRC. The pH values of the NaN02 solutions were adjusted between 2 to 10 by adding either 0.1 M HNO3 or 0.1 M NaOH. The suspensions were then sealed and shaken for 2 h at 120 rpm. The final pH values of the supernatant liquid were noted. The difference between the initial pH (pH i) and final pH (pHf) values (pH = pHi - pHf) was plotted against the values of pHi. The point of intersection of the resulting curve with abscissa, at which pH of 0, gave the pHzpc. 0.6 pHZPC - TGLRC pHi - pHf 0.4 0.2 0 -0.2 0 5 -0.4 10 Initial pH Figure. 1. Zero point charge of TGLRC. The pHZPC of an adsorbent is a very important characteristic that determines the pH at which the adsorbent surface has net electrical neutrality. Fig.1. shows that the plot between ΔpH, i.e. (pHi – pHf) and pHi for pHZPC measurement. The point of zero charge for TGLRC is found to be 5.12. This result indicated that the pHZPC of TGLRC was depended on the raw material and the activated agency. The zero point charge (pH ZPC = 5.12 for TGLRC) is below the solution pH (pH = 7.04 for Cu (II) and 7.12 for Ni (II) ion adsorption) and hence the negative charge density on the surface of TGLRC increased which favours the adsorption of Cu (II) and Ni (II) ions [28]. FTIR analysis of TGLRC 64 62 TGLRC-Ni 60 58 TGLRC-Cu 56 54 %T 52 TGLRC-B 50 48 46 44 42 40 38 36 4500 4000 3500 3000 2500 2000 1500 1000 500 1/cm Figure. 2. FTIR spectra for TGLRC before and after adsorption of Cu (II) and Ni (II) ions. www.ijmer.com 3257 | Page
  • 4. International Journal of Modern Engineering Research (IJMER) www.ijmer.com Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3255-3266 ISSN: 2249-6645 Surface functional groups were detected by Fourier-transform infrared spectroscopy. The Fig. 2 shows the FTIR spectra of TGLRC before and after adsorption of Cu (II) and Ni (II) ions from aqueous solution. The functional groups of the adsorbents and the corresponding infrared absorption frequency are shown in Table 1. These spectra contain peaks at 34213462 cm-1. This indicates the presence of hydrogen-bonded OH groups. The peak 3421 cm-1 which is originated from TGLRC before adsorption of Cu (II) and Ni (II) ions is shifted to 3462 cm-1 in TGLRC-Cu (after adsorption of Copper) and shifted to 3446 cm-1 in TGLRC-Ni (after adsorption of Nickel). The intense bent at about region 2852-2854 cm-1 for the precursor was attributed to the asymmetric and symmetric vibration modes of methyl and methylene group (C-H group)[29]. The peak around 1647-1653 cm-1 can be assigned to aromatic ring vibrations. The peak at 1018-1047 cm-1 is related to lignin. Therefore it is possible that cellulose, hemicelluloses as well as lignin, having many OH groups in their structure, make up most of the absorbing layer. Table 1. The FTIR spectral characteristics of TGLRC before and after adsorption of Cu (II) and Ni (II) ions. IR Peak Frequencies (cm-1) Assignment ______________________________________________________________________________ 1 3447 Bonded –OH groups 2 2852 Aliphatic C-H groups 3 1647 Aromatic ring vibrations 4 1022 -C-C group ______________________________________________________________________________ X-ray diffraction analysis Intensity 500 400 300 200 100 Intensity 0 40 60 80 100 80 100 80 100 Angle Two Theta 0 Intensity 20 700 600 500 400 300 200 100 20 700 600 500 400 300 200 100 0 40 60 Angle Two Theta 0 20 40 60 Angle Two Theta Figure. 3. XRD pattern of TGLRC before and after adsorption of Cu (II) and Ni (II) ions. Adsorption reaction may lead to changes in molecular and crystalline structure of the adsorbent and hence an understanding of the molecular and crystalline structures of the adsorbent and the resulting changes thereof would provide valuable information regarding adsorption reaction. Hence, XRD patterns of the adsorbent before and after adsorption of Cu (II) and Ni (II) ions have been studied. As a representative case the XRD patterns of TGLRC before and after treatment with Cu (II) and Ni (II) ions are shown in Fig. 3. The results indicated that the diffraction profiles of TGLRC before and after adsorption of Cu (II) and Ni (II) ions exhibited broad peaks and the absence of a sharp peak revealed a predominantly amorphous structure, the broad peak seems to be appear at around 2θ = 21, 22, 26 and 28° which was similar to the peak of crystalline carbonaceous structure such as graphite. It is evident from the figure that the XRD pattern of TGLRC loaded with Cu (II) and Ni (II) ions exhibits no variation in the crystal structure and this suggests that the Cu (II) and Ni (II) ions might diffuse into micropores and sorbs mostly by physisorption without altering the structure of the adsorbent. From the XRD analysis for the adsorbent (TGLRC), we concluded that the tannin gel preparation was completed. The above observation corroborated well with batch sorption experiments. Batch adsorption studies Effect of solution pH The zeta-potentials of the TGLRC particles in water were measured at different pH. It was found that TGLRC particles are positively charged at low pH and negatively charged at high pH, having a point of zero charge (pH zpc) at pH 5.12 for TGLRC. Therefore, it can be expected that positively charged metal ions are likely to be adsorbed by the negatively charged TGLRC particles at a pH > ZPC. www.ijmer.com 3258 | Page
  • 5. International Journal of Modern Engineering Research (IJMER) Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3255-3266 ISSN: 2249-6645 Effect of Solution pH 80 70 60 50 TGLRC-Ni TGLRCCu 40 30 20 10 2.52 3.18 4.28 5.14 6.05 7.12 8.04 9.05 0 2.68 3.29 4.38 5.13 6.38 7.04 8.01 9.19 % Adsorption Cu & Ni (II) ions www.ijmer.com Initial pH Figure. 4. Effect of solution pH on the adsorption of Cu (II) and Ni (II) ions on TGLRC. The pH of the aqueous solution has been identified as the most important variable governing metal adsorption onto adsorbents. This is partly due to the fact that hydrogen ions themselves are a strongly competing adsorbate and because the solution pH influences the ionization of surface functional groups. In order to establish the effect of pH on the adsorption of Cu (II) and Ni (II), the batch equilibrium studies at different pH values were carried out in the range of 2–9 (Fig. 4). We note that as the pH of the solution increased from 2.0 to 9.0, the adsorption capacity of TGLRC increased up to pH 7.0 for the adsorption of Cu (II) and Ni (II) ions by TGLRC and then decreased at pH > 6.0. The amount adsorbed increased as pH increased from 2.0 to 7.0 may be due to the presence of negative charge on the surface of the adsorbent that may be responsible for metal binding. However, as the pH is lowered, the hydrogen ions compete with the metal ions for the sorption sites in the sorbent; the overall surface charge on the adsorbent becomes positive and hinds the binding of positively charged metal ions [30]. At pH higher than 7.0, the precipitation of insoluble metal hydroxides takes place restricting the true adsorption studies [31]. However, when the pH of the solution was increased, the uptake of metal ions was increased. It appears that a change in pH of the solution results in the formation of different ionic species, and different carbon surface charge. At pH values lower than 5, the metal ions can enter into the pore structure may be due to its small size. So, an optimized pH of 7.04 for the removal of Cu (II) ions and 7.12 for the removal of Ni (II) ions by TGLRC adsorbent is taken for all the adsorption experiments. % Removal of Cu & Ni (II) ion Effect of contact Time 90 80 70 60 50 40 30 20 10 0 Effect of contact Time TGLRC-Cu TGLRC-Ni 5 10 15 20 25 30 35 40 45 Time (min) Figure. 5. Effect of Contact time on the adsorption of Cu (II) and Ni (II) ions onto TGLRC. The uptake of Cu (II) and Ni (II) ions onto TGLRC as a function of contact time is shown in Fig. 5. The effect of contact time between the adsorbents and Cu (II) and Ni (II) ions showed that the Cu (II) was removed within 45 min by TGLRC and Ni (II) ions was removed within 40 min by TGLRC and remains almost constant even up to an hour. This may be due to the attainment of equilibrium condition at 45 min of contact time for Cu (II) removal with TGLRC and 40 min for the removal of Ni (II) with TGLRC, which are fixed as the optimum contact time. At the initial stage, the rate of removal of Cu (II) and Ni (II) ions was higher, due to the availability of more than required number of active sites on the surface of carbons and became slower at the later stages of contact time, due to the decreased or lesser number of active sites. www.ijmer.com 3259 | Page
  • 6. International Journal of Modern Engineering Research (IJMER) www.ijmer.com Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3255-3266 ISSN: 2249-6645 Effect of adsorbent dose The effect of adsorbent dose on the percentage removal of Cu (II) and Ni (II) ion was studied at initial Cu (II) and Ni (II) ion concentration of 100 mg/L by allowing a contact time of 60 min and at the solution pH of 7.04 for Cu (II) and 7.12 for Ni (II) ions. The results are presented in Fig. 6. It is showed that the percentage removal of Cu (II) and Ni (II) ion increased with increase in adsorbent dose from 200 mg/50mL to1000 mg/50mL. This increase in Cu (II) and Ni (II) ion removal is due to the availability of higher number of Cu (II) and Ni (II) ions per unit mass of adsorbent (TGLRC), i.e., higher metal ions/ adsorbent ratio. Thus, further experiments were carried out using 200 mg of adsorbent per 50 ml of Cu (II) and Ni (II) ion solution, as it exhibits appreciable removal capacity, for the optimization of adsorption parameters. % Removal of Cu & Ni (II) ion Effect of adsorbent dose 100 80 60 TGLRC-Cu 40 TGLRC-Ni 20 0 200 400 600 800 1000 Adsorbent dose (mg /50mL) Figure. 6. Effect of adsorbent dose on the adsorption of Cu and Ni (II) ions by TGLRC. Effect of metal ion concentration Effect of metal ion concentration % Removal of Cu & Ni (II) ion 100 TGLRCCu 80 60 40 20 0 25 50 75 100 125 150 175 200 Concentration of Cu & Ni(II) ion (ppm) Figure. 7. Effect of metal ion concentration on the adsorption of Cu (II) and Ni (II) ions by TGLRC. The effect of initial metal ion concentration on adsorption capacity of TGLRC was carried out at a carbon dosage of 200 mg/ 50 mL, pH 7.04 for Cu (II) ion removal and 7. 12 for Ni (II) ion removal by TGLRC, contact time 1 h, temperature 303K for different initial metal ion concentration from 25 to 200 mg/50mL and is shown in Fig. 7. As shown, the amount of metal uptake per unit weight of the adsorbent increases with increasing initial metal ion concentration showing the maximum adsorption capacity of 5.48 mg /50mL to 31.32 for Cu (II) ion removal and the maximum adsorption capacity of 5.53 mg/50mL to 26.57 mg/50mL for Ni (II) ion removal by TGLRC. This is because at higher initial concentrations, the ratio of initial number of moles of metal ions to the available adsorption surface area is high. This may be attributed to an increase in the driving force of the concentration gradient with increase in the initial metal ion concentration [32] . Adsorption isotherms Adsorption isotherm is the most important information which indicates how the adsorbate molecules distribute between the liquid phase and the solid phase when adsorption process reaches on Equilibrium state. When the system is at Equilibrium is of importance in determining the maximum sorption capacity of TGLRC towards metal solution. Equilibrium data are a basic requirement for the design of adsorption systems and adsorption models, which are used for the mathematical description of the adsorption equilibrium of the metal ion by the adsorbent. The results obtained for adsorption of Cu (II) and Ni (II) ions were analyzed by use of well-known models given by the Langmuir, Freundlich, Temkin, Dubinin–Radushkevich, Harkin-Jura and Frenkel-Halsey-Hill adsorption isotherm models [34 - 38]. For the sorption isotherms, initial metal ion concentration was varied whereas solution pH and amount of adsorbent were held constant. The sorption isotherms for Cu (II) and Ni (II) ions were obtained for TGLRC at solution pH 7.04 and pH 7.12, respectively. www.ijmer.com 3260 | Page
  • 7. www.ijmer.com 𝑪𝒆 𝟏 𝑪𝒆 = + 𝒒𝒆 𝒒 𝒎𝒂𝒙 𝒃 𝒒 𝒎𝒂𝒙 International Journal of Modern Engineering Research (IJMER) Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3255-3266 ISSN: 2249-6645 𝑳𝒂𝒏𝒈𝒎𝒖𝒊𝒓 𝒎𝒐𝒅𝒆𝒍 𝟒 𝟏 𝒍𝒐𝒈 𝑪 𝒆 + 𝒍𝒐𝒈 𝑲 𝑭𝒓𝒆𝒖𝒏𝒅𝒍𝒊𝒄𝒉𝒎𝒐𝒅𝒆𝒍 𝒏 𝒒 𝒆 = 𝜷 𝐥𝐧 𝜶 + 𝜷 𝐥𝐧 𝑪 𝒆 𝑻𝒆𝒎𝒌𝒊𝒏 𝒎𝒐𝒅𝒆𝒍 𝐥𝐧 𝒒 𝒆 = 𝐥𝐧 𝑸 𝒎 – 𝑲𝜺 𝟐 𝑫𝒖𝒃𝒊𝒏𝒊𝒏 − 𝑹𝒂𝒅𝒖𝒔𝒉𝒌𝒆𝒗𝒊𝒄𝒉 𝒎𝒐𝒅𝒆𝒍 The mean adsorption energy, E (kJ/mol) is calculated with the help of following equation: 𝟏 𝐄 = −𝟐′ 𝐘 𝟏 𝑩𝟐 𝟏 = – 𝐥𝐨𝐠 𝑪 𝒆 𝑯𝒂𝒓𝒌𝒊𝒏 − 𝑱𝒖𝒓𝒂 𝒎𝒐𝒅𝒆𝒍 𝒒 𝒆𝟐 𝑨 𝑨 𝒍𝒐𝒈 𝒒 𝒆 = 𝐥𝐧 𝒒 𝒆 = 𝟏 𝟏 𝐥𝐧 𝑲 – 𝐥𝐧 𝑪 𝒆 𝒏 𝒏 𝑭𝒓𝒆𝒏𝒌𝒆𝒍 − 𝑯𝒂𝒍𝒔𝒆𝒚 − 𝑯𝒊𝒍𝒍 𝒎𝒐𝒅𝒆𝒍 𝟓 (𝟔) 𝟕 (𝟖) (𝟗) (𝟏𝟎) where Ce is the Cu (II) and Ni (II) ion concentration in the solution (mg/L), qe is the Cu (II) and Ni (II) concentrations in the solid adsorbent (mg/g), q m is the maximum adsorption capacity (mg/g), K f is a constant related to the adsorption capacity (mg1-1/n L1/n/g), b is a constant related to the energy of adsorption (L/g), n is a constant related to the energy of adsorption, α (L/g) is Temkin constant representing adsorbent–adsorbate interactions and β (mgL-1) is another constant related with adsorption heat, ε is the Polanyi potential (kJ 2 mol2) and E (kJ/mol) is the mean adsorption energy. B2 is the isotherm constant, represented by Harkin-Jura isotherm model. The adsorption isotherm parameters for all the six isotherm models are calculated and the values are summarized in Table 2. Table 2. Adsorption isotherm parameters for the adsorption of Cu (II) and Ni (II) ions. Isotherm model Parameters Cu (II) ion Ni (II) ion Langmuir Qm (mgg-1) b (Lmg-1) R2 43.47 0.0160 0.9390 30.303 0.0201 0.9790 Freundlich n Kf (mgg-1) R2 1.8382 3.0690 0.9950 2.3364 3.8994 0.9960 α (Lg-1) β (mgL-1) b R2 0.1093 8.0810 311.73 0.9230 0.3424 5.8130 433.36 0.9690 21.019 0.2 0.625 0.685 19.005 0.2 0.625 0.728 Temkin Dubinin-Radushkevich Harkin-Jura Frenkel–Halsey–Hill Qm (mgg-1) K (x10-5mol2kJ-2) E(kJmol-1) R2 A B R2 1/n K R2 47.619 1.7142 0.840 0.544 0.7231 0.943 58.823 1.8823 0.812 0.428 1.1577 0.996 In the present investigation, the equilibrium data were analyzed using the Langmuir, Freundlich, Temkin, DubininRadushkevich, Harkin-Jura and Frenkel-Halsey-Hill isotherm models. To optimize the design of an adsorption system, it is important to establish the most appropriate isotherm model. The mono-component equilibrium characteristics of adsorption of Cu (II) and Ni (II) ions by TGLRC were described by these six different isotherm models. The experimental equilibrium adsorption data were obtained by varying the concentration of Cu (II) and Ni (II) ions with 200mg/50 mL of TGLRC. The adsorption data obtained by fitting the different isotherm models with the experimental data are listed in Table 2, with the linear regression coefficients, R 2. As seen from Table 2, the Langmuir, Freundlich and Frenkel-Halsey-Hill www.ijmer.com 3261 | Page
  • 8. International Journal of Modern Engineering Research (IJMER) www.ijmer.com Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3255-3266 ISSN: 2249-6645 isotherms were generate a satisfactory fit to the experimental data as indicated by correlation coefficients. This shows the heterogeneity of the surface of TGLRC and the multilayer adsorption nature of the Cu (II) and Ni (II) ions on TGLRC. TGLRC have a homogeneous surface for adsorption of metal ions. The Langmuir isotherm equation is therefore expected to best represent the equilibrium adsorption data. The R 2 values for the Langmuir model are closer to unity than those for the other isotherm models for TGLRC for both Cu (II) ion removal (R2 = 0.939) and for the removal of Ni (II) (R2 = 0.979). Therefore, the equilibrium adsorption of Cu (II) and Ni (II) ions on TGLRC can be represented appropriately by the Langmuir, Freundlich and Frenkel-Halsey-Hill isotherm models in the concentration range studied. Adsorption kinetics The kinetics of adsorbate uptake is important for choosing optimum operating conditions for design purposes. In order to investigate the mechanism of adsorption and potential rate controlling steps such as chemical reaction, diffusion control and mass transport process, kinetic models have been used to test experimental data from the adsorption of Cu (II) and Ni (II) ions onto TGLRC. These kinetic models were analyzed using pseudo-first-order, pseudo-second-order and intraparticle diffusion models, which were respectively presented as follows in Eqs. (11) – (14) [39 – 41]: 𝐥𝐧 𝒒 𝒆 − 𝒒 𝒕 = 𝐥𝐧 𝒒 𝒆 − 𝒌 𝟏 𝒕 𝑷𝒔𝒆𝒖𝒅𝒐 𝒇𝒊𝒓𝒔𝒕 𝒐𝒓𝒅𝒆𝒓 𝒎𝒐𝒅𝒆𝒍 𝒕 𝟏 𝟏 = + 𝒕 𝟐 𝒒𝒕 𝒌𝟐 𝒒𝒆 𝒒𝒆 𝑷𝒔𝒆𝒖𝒅𝒐 𝒔𝒆𝒄𝒐𝒏𝒅 𝒐𝒓𝒅𝒆𝒓 𝒎𝒐𝒅𝒆𝒍 𝒒 𝒕 = 𝒌 𝒊𝒅 𝒕 𝟏/𝟐 + 𝑪 𝒒𝒕 = 𝟏 𝛃𝐥𝐧 𝜶𝜷 + (𝟏𝟏) (𝟏𝟐) 𝑰𝒏𝒕𝒓𝒂 𝒑𝒂𝒓𝒕𝒊𝒄𝒍𝒆 𝒅𝒊𝒇𝒇𝒖𝒔𝒊𝒐𝒏 𝒎𝒐𝒅𝒆𝒍 𝟏 𝜷 𝐥𝐧 𝒕 (𝟏𝟑) 𝑬𝒍𝒐𝒗𝒊𝒄𝒉 𝒎𝒐𝒅𝒆𝒍 (𝟏𝟒) where t is the contact time of adsorption experiment (min); q e (mg/g) and qt (mg/g) are respectively the adsorption capacity at equilibrium and at any time t; k1 (1/min), k2 (g/mg min), α (mg/g min), β (g/mg), kid (mg/g min1/2) are the rate constants for these models, respectively. The correlation coefficients for all the four kinetic models were calculated and the results are shown in Table 3. Table 3. Comparison of the correlation coefficients of kinetic parameters for the adsorption of Cu (II) and Ni (II) ions onto TGLRC. Models Parameters Pseudo first-order model k1 (min-1) qe (mg/g) R2 Pseudo second-order model k2 (g/mg/min) qe (mg/g) h R2 Intra particle diffusion model Elovich model Cu (II) ion 0.1658 173.78 0.677 Ni (II) ion 0.1496 64.71 0.644 0.0004 41.66 0.7005 0.9920 0.0005 38.46 0.8613 0.973 kdif (mg/(g.min1/2)) C R2 3.411 5.044 0.983 3.510 4.063 0.989 A E (mg(g/ min)) b (g/ mg) R2 0.1452 0.3928 0.9110 0.1453 0.6071 0.9530 The adsorption process of Cu (II) and Ni (II) ions can be well fitted by use of the pseudo-second order rate constant for TGLRC. The linear regression coefficient value R2 = 0.992 for Cu (II) and R2 = 0.973 for Ni (II) obtained for pseudosecond-order kinetics was closer to unity than the R2 value (0.677 = Cu (II) ions and 0.644 = Ni (II) ions) for first-order kinetics. This indicates that adsorption of Cu (II) and Ni (II) ions by TGLRC follows pseudo-second-order kinetics. In the intra particle diffusion model, the values of q t were found to be linearly correlated with the values of t 1/2. The linear regression coefficient value R2 = 0.983 for Cu (II) and R2 = 0.989 for Ni (II) obtained for Intra particle diffusion model was closer to unity. The kdif values were calculated by use of correlation analysis. kdif = 3.411 for the removal of Cu (II) ions www.ijmer.com 3262 | Page
  • 9. International Journal of Modern Engineering Research (IJMER) www.ijmer.com Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3255-3266 ISSN: 2249-6645 and kdif = 3.510 for the removal of Ni (II) ions. The data indicates that the adsorption kinetics follows the pseudo-secondorder rate with intraparticle diffusion as one of the rate determining steps. Influence of other metal ions on the adsorption of Cu (II) and Ni (II) ions. Effect of Ni (II) ions and Cr(III) ions on adsorption of Cu (II) and Ni (II) ions (binary system) Binary system 90 % ads of Cu in presence of Ni. % ads of Cu in presence of Cr. % removal of Cu & Ni (II) ions 80 % ads of Ni in presence of Cu.  % ads of Ni in presence of Cr. 70 60 50 40 30 20 10 0 0 10 20 30 40 0 10 20 30 40 Concentration of other metal ions (ppm) Figure. 8. Effect of other metal ions in binary system on the adsorption of Cu (II) and Ni (II) ions onto TGLRC. The concentration of the Cu (II) ion solution was kept as 100 ppm. The concentration of Ni (II) ion was varied as 10, 20, 30, and 40 ppm. Each solution was placed in a bottle with TGLRC and the pH was adjusted to 7.04. After shaking for 60 min percentage adsorption was calculated. Percentage adsorption decreased from 76.92 to 55.56 % as the concentration of Ni (II) solution was increased. This showed competitive adsorption was, to some extent, taking place between the Cu (II) ions and the Ni (II) ions. The same procedure was repeated for Cu (II) ions in presence of Cr(III) ions. The percentage adsorption of Cu (II) ions decreased to 76.92–58.33% in the presence of Cr(III) ions. This is clearly shown in Fig. 8 for TGLRC. When the same procedure was repeated for the adsorption of Ni (II) ions onto TGLRC at pH 7.12, adsorption decreased to 71.73–53.13 % in the presence of Cu (II) ions and to 71.73–55.81% in presence of Cr(III) ions. This is clearly shown in Fig. 8. Effect of Cu (II), Ni (II) and Cr(III) ions on the adsorption of Cu (II) and Ni (II) ions (tertiary system) Ternary system 90 % removal of Cu & Ni 80 % ads of Cu in presence of Ni & Cr % ads of Ni in presence of Cu &Cr. 70 60 50 40 30 20 10 0 0 10 20 30 40 0 10 20 30 40 Concentration of other metal ions (ppm) Figure. 9. Effect of other metal ions in tertiary system on the adsorption of Cu (II) and Ni (II) ions onto TGLRC. www.ijmer.com 3263 | Page
  • 10. International Journal of Modern Engineering Research (IJMER) www.ijmer.com Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3255-3266 ISSN: 2249-6645 The concentration of Cu (II) ion solution was kept as 100 ppm. The concentrations of Ni (II) and Cr(III) ion solutions were varied as 10, 20, 30, and 40 ppm. Solutions of both Ni (II) ions and Cr(II) ions were added to Cu (II) solution in a bottle with TGLRC and the pH was adjusted to 7.12. After shaking 1 h percentage adsorption was calculated. Percentage adsorption decreased from 76.92 to 62.5 % as the concentrations of Ni (II) ions and Cr(III) ions were increased. This showed competitive adsorption was, to some extent, taking place between the Ni (II) ions, the Cu (II) ions, and the Cr(III) ions. Percentage adsorption of Cu (II) was reduced in the presence of the other metals, as is clearly shown in Fig. 9. The same procedure was repeated for the adsorption Ni (II) ions onto TGLRC at pH 7.12 and percentage adsorption decreased from 71.71-52.17%, as the concentration of Cu (II) and Cr(III) was increased from 10-40 ppm, as illustrated in Fig. 9. A fixed quantity of Cu (II) ions and Ni (II) ions onto TGLRC could only offer a finite number of surface binding sites, some of which would be expected to be saturated by the competiting metal solutions. The decrease in sorption capacity of same activated carbon in target metal solution than that of single metal may be ascribed to the less availability of binding sites. In case of binary and ternary metal solution, the binding site is competitively divided among the various metal ions. It is generally complicated to find a common rule to identify how metal properties affect the competitive sorption. Among various factors that affect the sorption preferences of a sorbent, binding of metal ions on material largely depends on physicochemical properties of metals. The HSAB (hard and soft acids and bases) theory developed by Pearson [42] and extended to activated carbons adsorption by Alfarra et al, [43]. Once acids and bases have been classified as hard or soft, a simple rule of the HSAB principle can be given: hard acids prefer to bond to hard bases, and soft acids prefer to bond to soft bases. Generally, the C– O or C=O bonds are more polar and less polarizable, hence harder than the C–C or C=C bonds. In this concept, the oxygen surface groups of TGLRC are the hard sites that fix hard metal ions. According to this theory, Ni (II), Cu (II) and Cr(III) cations are borderline acids [42]. Changing the experimental conditions, metal ions with a borderline hardness can be biosorbed by the hard sites of TGLRC. The cationic exchange between the oxygenated surface groups (hard base) of TGLRC and borderline acids gives ionic bonds which are more easily dissociated. But the competitive process cannot be explained exactly by the hardness of cations because other effective factors and hardness values of Ni (II), Cu (II) and Cr (III) borderline acids are close each other. % Removal of Cu & Ni (II) ions onto TGLRC Desorption and Reusability 70 60 % Desorption of Cu & Ni (II) ions % of Recycling adsorption of Cu & Ni (II) ions TGLRC-Ni 50 40 TGLRC-Cu 30 20 10 0 2.2 3.22 4.03 5.19 6.2 7.03 8.11 9.1 2.26 3.12 4.08 5.09 6.05 7.12 8.05 9.08 Initial pH Figure. 10. Effect of pH on the desorption and recycling adsorption of Cu (II) and Ni (II) ions. To investigate the possibility of repeated use of the adsorbent, desorption experiments were conducted under batch experimental conditions and desorption efficiencies were showed in Fig. 10. If the adsorbed Cu (II) ion and Ni (II) ion can be desorbed using neutral pH water, then the attachment of the copper and nickel ion of the adsorbent is by weak bonds. To study the effect of solution pH on Cu (II) and Ni (II) ion desorption, 50 mL of distilled water at different pH values (2 - 9) was agitated with 200 mg of TGLRC in a mechanical orbital shaker at room temperature. The pH was adjusted with 0.1 M NaOH and 0.1 M HCl solutions. We could get maximum removal of 59.77% of adsorbed Cu (II) ion for 3.22 pH water and 53.77% of adsorbed Ni (II) ion for 3.12 pH water onto TGLRC, after 2 h of contact time between the loaded matrix and the desorbing agents. After desorption, the adsorbents were further used for adsorption of Cu (II) and Ni (II) ions. The percentage removal of Cu (II) ions was found to be 53.85% for TGLRC at pH 7.04 and the removal of Ni (II) ion was found to be 51.85 % for TGLRC at pH 7.12 (Fig.10). The increase in removal of Cu (II) and Ni (II) ions at pH 8 may be because of precipitation of metal ions in alkaline medium rather than adsorption. www.ijmer.com 3264 | Page
  • 11. www.ijmer.com International Journal of Modern Engineering Research (IJMER) Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3255-3266 ISSN: 2249-6645 IV. CONCLUSION In this work, Tannin gel derived from Ricinus Communis leaves as a sorbent has been proposed to be an efficient and economical alternative in Cu (II) and Ni (II) ion removal from water. The findings herein made us conclude that: (1) Batch sorption studies of Cu (II) and Ni (II) ions showed that the TGLRC can be successfully used to remove Cu and Ni (II) ions from aqueous solution. (2) The adsorption data were well fitted by the Langmuir isotherm model; this is indicative of monolayer adsorption by TGLRC. (3) By applying the kinetic models to the experimental data, it was found that the kinetics of Cu and Ni (II) ion adsorption onto TGLRC followed by the pseudo-second order rate equation and intra particle diffusion is one of the rate limiting step. Results of kinetic studies demonstrated that the Cu and Ni (II) ion adsorption was rapid and efficient. (4) Percentage adsorption of Cu (II) and Ni (II) ions on TGLRC was higher in the single-ion systems than in binary and ternary systems, which is indicative of competitive adsorption among the metal ions. (5) Adsorbed Cu (II) and Ni (II)ions can be desorbed from both the adsorbents by use of double distilled water — 59.7 % of adsorbed Cu (II) ions were recovered from TGLRC and 53.7 % of adsorbed Ni (II) ions were recovered from TGLRC at pH 3.22 and pH 3.12, respectively. (6) The experimental studies showed that Tannin gel prepared from leaves of Ricinus Communis could be used as an alternative, inexpensive and effective material to remove high amount of Cu (II) and Ni (II) ions from aqueous solutions. REFERENCES [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] F. Rozada, M. Otero, A. Moran, and A.I. Garcia, Adsorption of heavy metals onto sewage sludge-derived materials, Bioresource Technology, 99, 2008, 6332–6338. K.K. Krishnani, X. Meng, C. Christodoulatos, and V.M. Boddu, Biosorption mechanism of nine different heavy metals onto biomatrix from rice husk,” Journal of Hazardous Materials, 153, 2008, 222–1234. S. Liang, XY. Guo, N.C. Feng, and QH. Tian, Application of orange peel xanthate for the adsorption of Pb 2+ from aqueous solutions, Journal of Hazardous Materials, 170, 2009, 425. R.P. Dhakal, K.N. Ghimiere, K. Inoue, Adsorptive separation of heavy metals from an aquatic environment using orange waste, Hydrometallurgy. 79, 2005, 182. U. Kumar, M. Bandyopadhyay, Sorption of cadmium from aqueous solution using pretreated rice husk, Bioresource Technology, 97, 2006, 104. K.K. Singh, M. Talat, S.H. Hasan, Removal of lead from aqueous solutions by agriculture waste maize bran, Bioresource Technology, 97, 2006, 2124. W. Zhang, QG. Chang, WD. Liu, BJ. Li, WX. Jiang, LJ. Fu, Selecting activated carbon for water and wastewater treatability studies, Environ Prog. 26, 2007, 289. D. Prahas, Y. Kartika, N. Indraswati, and S. Ismadji, Activated carbon from jackfruit peel waste by H3PO4 chemical activation: pore structure and surface charac-terization, Chemical Engineering Journal, 140, 2007, 32. S. Altenor, B. Carene, E. Emmanuel, J. Lambert, J.J. Ehrhardt, and S. Gaspard, Adsorption studies of methylene blue and phenol onto Vetiver roots activated carbon prepared by chemicalactivation, Journal of Hazardous Materials, 165(1–3), 2009, 1029– 1039. A. Demirbas, A. Heavy metal adsorption onto agro-based waste materials: a review, Journal of Hazardous Materials, 157(2–3), 2008, 220–229. F.A. Pavan, A.C. Mazzocato, Y. Gushikem, Removal of methylene blue dye from aqueous solutions by adsorption using yellow passion fruit peel as adsorbent,” Bioresou. Technol. 99(8), 2008, 3162–3165. P. Schofield, D.M. Mbugua, and A.N. Pell, Analysis of condensed tannins: a review, Animal Feed Science and Technology. 91(1), 2001, 21–40. A. Pizzi, Advanced Wood Adhesives Technology, Marcel Dekker, New York. 1994. N.E. Meikleham, A. Pizzi, Acid- and alkali-catalyzed tannin-based rigid foams,” J. of App. Poly. Sci. 53(11), 1994, 1547–1556. G. Tondi, W. Zhao, A. Pizzi, G, Du, V. Fierro, and A. Celzard, Tannin-based rigid foams: a survey of chemical and physical properties, Bioresource Technology, 100(21), 2009a, 5162–5169. W. Zhao, V. Fierro, A. Pizzi, G. Du, A. Celzard, Effect of composition and processing parameters on the characteristics of tanninbased rigid foams, Part II: Physical properties, Materials Chemistry and Physics. 123(1), 2010, 210–217. Y. Nakano, K. Takeshita, T. Tsutsumi, Adsorption mechanism of hexavalent chromium by redox within condensed-tannin gel, Water Research.35(2), 2001, 496–500. Y.H. Kim, Y. Nakano, Adsorption mechanism of palladium by redox within condensed-tannin gel, Water Research. 39(7), 2005, 1324–1330. G. Tondi, C.W. Oo, A. Pizzi, M.F. Thevenon, Metal absorption of tannin-based rigid foams, Ind. Crops. Prod, 29(2–3), 2009b, 336–340. W. Shirato, Y. Kamei, Insoluble tannin preparation process, waste treatment process and adsorption process using tannin, US patent. 5, 158, 1992, 711. G. Vázquez, G. Antorrena, J. González, M.D. Doval, Adsorption of heavy metal ions by chemically modified Pinus pinaster bark, Bioresource Technology, 48(3), 1994, 251–255. G. Vázquez, J. González-Álvarez, S. Freire, M. López-Lorenzo, and G. Antorrena, Removal of cadmium and mercury ions from aqueous solution by sorption on treated Pinus pinaster bark: kinetics and isotherms, Bioresource Technology, 82(3), 2002, 247–251. A. Pizzi, Tannins: major sources, properties, applications, in Monomers, Polymers and Composites from Renewable Resources(eds M.N. Belgacem and Gandini), Elsevier, Amsterdam, Ch 8. 2008. www.ijmer.com 3265 | Page
  • 12. www.ijmer.com [24] [25] [26] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36] [37] [38] [39] [40] [41] [42] [43] International Journal of Modern Engineering Research (IJMER) Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3255-3266 ISSN: 2249-6645 M. Makeswari, T. Santhi, Optimization of Preparation of Activated Carbon from Ricinus communis Leaves by MicrowaveAssisted Zinc Chloride Chemical Activation: Competitive Adsorption of Ni 2+ Ions from Aqueous Solution, Journal of Chemistry, Article ID 314790, 12 pages, doi:10.1155/2013/314790. 2013a. M. Makeswari, and T. Santhi, Use of Ricinus communis leaves as a low cost adsorbent for removal of Cu (II) ions from aqueous solution, Research on chemical intermediates, 39(2), 2013b. M. Yurtsever, I.A. Sengil, Biosorption of Pb(II) ions by modified quebracho tannin resin, Journal of Hazardous Materials, 163(1), 2009, 58–64. A. Kumar, B. Prasad, and I.M. Mishra, Adsorptive removal of acryloinitrile by commercial grade activated carbon: kinetics, equilibrium and thermodynamics, Journal of Hazardous Materials, 152, 2008, 589-600. P. Janos, H. Buchtova, and M. Ryznarova, Sorption of dye from aqueous solution onto fly ash, Water Research. 37, 2003, 49384944. K. Nakanishi, Infrared Absorption Spectroscopy-Practical, Holden-Day, San Francisco, CA,17-57, 1962. J. Chang, R. Law, and C. Chang, Biosorption of lead copper and cadmium by biomass of Pseudomonas aeruginosa, Water Research, 31, 1997, 1651. Z. Elouear, R. Ben Amor, J. Bouzid, N. Boujelben, Use of phosphate rock for the removal of Ni 2+ from aqueous solutions: kinetic and thermodynamics studies, Journal of Environmental Engineering, 135, 2009, 259. I.D. Mall, V.C. Srivastava, N.K. Agarwal, and I.M. Mishra, Removal of congo red from aqueous solution by bagasse fly ash and activated carbon: Kinetic study and equilibrium isotherm analyses, Chemosphere, 61, 2005, 492–501. I. Langmuir, The adsorption of gases on plane surface of glass, mica and platinum, Journal of American chemical society, 40, 1918, 1361 – 1403. H. Freundlich, Uber die adsorption in losungen (Adsorption in solution). Z. Phys. Chem, 57, 1906, 384 - 470. I.A.W. Tan, B.H. Hameed, A.L. Ahmad, Equilibrium and kinetic studies on basic dye adsorption by oil palm fibre activated carbon, Chemical Engineering Journal, 127, 2007, 111–119. M.M. Dubinin, E.D. Zaverina, L.V. Radushkevich, Sorption and structure of activated carbons, I. Adsorption of organic vapours, Zh. Fiz. Khim. 21, 1947, 1351–1362. C.A. Basker, Applicability of the various adsorption models of three dyes adsorption onto activated carbon prepared from waste apricot, Journal of Hazardous Materials, 135B: 2006, 232-241. J. Halsey, Physical adsorption on Non-uniform surfaces, Chem. Phys. 16: 1948, 931. Y.S. Ho, G. Mckay, G. Sorption of dye from aqueous solution by peat, Chemical Engineering Journal, 70, 1998a, 115–124. Y.S. Ho, G. Mckay, Kinetic models for the sorption of dye from aqueous solution by wood, Journal of Environmental Science Health Part B: Process Saf. Environ. Prot, 76(B), 1998b, 184–185. W.J. Weber Jr, J.C. Morris, Kinetics of adsorption on carbon from solution, Journal of Sanitary Engineering Division, 89(2), 1963, 31–60. R.G. Pearson, Hard and soft acids and bases, American journal of Chemical Society,85, 1963, 3533-3539. A. Alfarra, E. Frackowiak, and F. Beguin, The HSAB concept as a means to interpret the adsorption of metal ions onto activated carbons, Applied Surface Science,228, 2004, 84-92. www.ijmer.com 3266 | Page