# One-, Two-, and Three-Parameter Isotherms, Kinetics, and Thermodynamic Evaluation of Co(II) Removal from Aqueous Solution Using Dead Neem Leaves

Authors: Cornelius Tsamo; Abba Paltahe; Daniel Fotio; Tore Atangana Vincent; Wassansa Francois Sales
Journal: International Journal of Chemical Engineering
 (2019)

---

## Abstract

Water pollution by heavy metals like Co(II) is particularly of concern because of their persistence in the environment, toxicity, and ability to bioaccumulate in organisms. In this study, the influence of contact time at three initial concentration, pH, adsorbent dose, temperature, and kinetics, thermodynamics, and one-, two-, and three-parameter isotherm modeling of the adsorption of Co(II) on neem leaves (DNL) was investigated. The adsorbent was characterized using FTIR, TGA-DSC, EDX, and nitrogen adsorption-desorption. DNL is composed of many Co(II) surface-binding groups and a BET surface area of 0.2783 m2/g dominated by meso- and macropores. Equilibrium was attained in 10 minutes for the three concentrations with a removal efficiency of 85–97%. ∆G° of −5.424 to −6.068 KJ/mol at 25 to 60°C, respectively, indicated spontaneous adsorption with increasing temperature. D-R adsorption energies of 0.649 to 2.433 KJ/mol revealed physical adsorption. Maximum adsorption capacity of 9.201–523.900 mg/g was obtained by Freundlich and Jovanovic isotherms. Adsorption was very favourable as evident by the high Kiselev equilibrium constant (11.652–172.78 L/mg) and very low RL values of 0.001–0.026. Adsorption occurred by repulsive mechanism as indicated by Fowler–Guggenheim and Hill–de Boer negative interaction energies (−16.182 to −90.163 and −111.102 to −3328.86 KJmol−1, respectively), confirming maximum Co(II) adsorption at pH 3. Results can be used in the design of an efficient adsorption system using neem leaves which is very efficient in removing low and high levels of heavy metals like cobalt ions from wastewater.


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## Body

## 1. Introduction

The increase of the world population with their accompanying needs has led to a boom in new technologies to satisfy these needs. However, the development of these new technologies has led to increase need of natural resources. The exploitation of these natural resources and the use of new technologies are greatly affecting the environment worldwide. Unfortunately, freshwater which represent<1% of the total water on Earth and used for all activities by humans [1, 2] receives most of the pollution problems linked to exploitation of natural resources and development of new technologies. Water pollution by the group of pollutants called heavy metals is on the rise worldwide and is particularly of concern because of their persistence in the environment, toxic in trace amounts, and ability to induce severe oxidative stress and ability to bioaccumulate in organisms [2]. One of such heavy metal is cobalt whose principal man made sources in the environmental are cobalt-bearing ores mining and processing, use of cobalt-containing sludge or phosphate fertilizers on soil, the disposal of cobalt-containing waste, and atmospheric deposition from activities such as the burning of fossil fuels and smelting and refining of metal [3]. This metal has significant health effects on humans even in trace amount as indicated in Table 1 [4]. Due to cobalt toxicity at very low levels (Table 1), there is need to develop appropriate technology that can effectively remove cobalt from solution even at very low concentrations. Currently, many water treatment technologies such as precipitation, coagulation-flocculation, sedimentation, flotation, filtration, membrane processes, electrochemical processes, biological processes, adsorption, and ion exchange have been tested with different efficiencies [5]. Most developing countries lack technical and economic means to apply most of these technologies. Thus, there is a need for a very simple technology that can be designed at low cost and applied even at very local level even with no electricity. Many studies have reported that adsorption is the most promising treatment technology because of its potential efficiency, ability to remove very low levels of pollutant, low energy consumption, high selectivity, easy operation, and ability to separate various chemical compounds [6, 7]. However, the efficiency of adsorption is highly dependent on the solid adsorbent responsible for fixing the pollutant on its surface.Table 1
Summary of effects of cobalt exposure [4].
Organ system
Toxicity levels reported
Reported effects
Pulmonary
0.015–0.13 mg Co/m3
Pulmonary compromise, pulmonary inflammation, granulomatous lung disease, restrictive lung disease, pulmonary fibrosis, fibrosing alveolitis, asthma-like syndrome
Hematological
∼1 mg Co/kg/day
Increased levels of erythrocytes and hemoglobin, i.e., polycythemia (levels normalize 9–15 days after cessation)
Cardiovascular
0.04 mg Co/kg/day to 0.14 mg Co/kg/day
Beer-drinkers’ cardiomyopathy, sinus tachycardia, left ventricular failure, cardiogenic shock, diminished myocardial compliance, absence of myocardial response to exercise or catecholamine, enlarged heart, pericardial effusion, extensive intracellular changes (changes in the myofibers, mitochondria, glycogen, and lipids), pathological changes in myocardiaum including proliferative interstitial tissue, swollen muscle fibers, and focal degeneration.
Gastrointestinal
0.04 mg Co/kg/day
Nausea, vomiting, diarrhea,
Hepatic effects
0.04 mg Co/kg/day
Central hepatic necrosis, increased serum bilirubin, increase aspartate aminotransferase (AST), alanine aminotransferase (ALT), lactic acid dehydrogenase (LDH), increase creatine phosphokinase, increase ornithine carbamyl transferase, isocitric dehydrogenase, and aldolase
Endocrine
0.066 mg Co/kg/day
Histological morphology: irregular follicles, decreased follicular size, goiter, hypothyroidism, thyroid hypoplasia, thyroid hypertrophy, thyroid hyperplasia, thyroid firmness
Dermatological
0.014 mg/kg/day
Allergic dermatitis, eczema flares,
Ophthalmological
1.3 mg Co/kg/day
Severe visual disturbance (optic atrophy, impaired choroidal perfusion), implant-related chorio-retinal cobalt toxicity, patchy degeneration of the photoreceptor-retinal pigment epithelium (RPE) complex, toxic retinopathy
Neurological
Serum levels > 0.01 mg
Memory impairment, altered mental status, deafness, vertigo, seizures, tremors
Psychiatric
Serum levels > 0.01 mg
Depression
High genotoxicity on A. cepa plant was reported for all the water samples from industrial effluents of Sandub area, Dakahlia, Egypt, and correlated with the presence of some heavy metals (Pb, Zn, Co, Cd, and Cu) [20]Activated carbon has been the most widely used adsorbent in water and wastewater treatment, but its use has some major drawbacks resulting from its high production cost and the need for regeneration accompanied by management of resulting sludge [8]. There is therefore the need worldwide for low-cost adsorbents such as clay [8], Musa paradisiaca and Ipomoea batatas peels [9, 10], leaf-based adsorbents [11], and modified chitosan [12] for heavy metals and other contaminants adsorption from water and wastewater. There is particularly an increasing trend towards the use of waste biomass materials as adsorbents for heavy metal removal from water and wastewater because of their abundant availability and low cost, with relatively high fixed carbon, presence of porous structure, and high content in cellulose, lignin, hemicellulose, etc. with good functional groups that can bind heavy metals [7, 13, 14]. Researchers are showing growing interest on adsorbents from leaf-based materials (in raw or modified from) because they are cheap and available in all parts of the world in very large quantities with very little use [11]. They contain hydroxyl, carboxyl, carbonyl, amino, and nitro groups which can serve as binding sites for pollutants during adsorption. Most important they require very few preparation stages.Neem tree (Azadirachta indica) is a distinctive mahogany tree dominant in the Southeast Asia regions but also found in different countries worldwide. Its product has been widely used in solving variety of problems in relation to public health, agriculture, environmental pollution, and population control. The leaves have been tested for heavy metals [15–17] and organic contaminants [18, 19] remediation from the environment although the numbers of such studies are very limited. Neem leaf powder has diverse types of surface functional groups and although it does not have a highly porous structure, biosorption might occur mainly through chemical sorption with the presence of functional groups and ion exchange [17].Published works on the use of neem leaves to remove cobalt ions from water and wastewater could not be found in the literature. This study was therefore aimed at evaluating the influence of process parameters, one-, two-, and three-parameter isotherms, kinetics, and thermodynamics of Co(II) removal from the aqueous solution using neem leaves.


## 2. Materials and Methods

### 2.1. Collection, Treatment, and Characterization of Neem Leaves Adsorbent

Collection was done in front of the laboratory as there are dispersed on every empty space. They were taken to the laboratory, washed with distilled water, and dried in an oven at 105°C for 24 hours. The dried sample was then crushed and grinded to powder. This powder was washed several times with distilled water until the leaves were not more sending out the yellow colouration. They were then dried in open air inside the laboratory for five days (average temperature in the laboratory was 33°C), abbreviated as (DNL) and used for characterization and adsorption studies without further treatment.The chemical and surface compositions were determined using energy dispersive X-y analysis (EDX) (Shimadzu, XRF-1800, Japan) and Fourier-transform infrared spectroscopy (FTIR) (FTIR, iS50 RAMAN, Thermo Scientific, USA) analyses. For FTIR, the peaks obtained were then compared with those of neem leaves and other biomass samples reported in the literature for identification. The different phase transformations were investigated using the differential scanning calorimetry-thermogravimetric (DSC-TGA) techniques (SDT Q600 V20.9 Build 20, TGA-DTA, TA Instruments, USA). Porosity characteristics were determined by gas adsorption using nitrogen adsorption-desorption at the liquid nitrogen temperature (−195, 800°C) (Micromeritics tristar 3000 apparatus, USA).


### 2.2. Adsorption Test

HCl (35% w/w), NaOH (granulated), cobalt(II) sulfate heptahydrate salt, and ammonia solution (25% w/w) used were all essential laboratory reagents from Scharlab S. L., Spain. Adsorption experiments were conducted in a capped 250 mL conical flask using 100 mL solution of Co(II). The contents of the flask which included Co(II) of desired concentration and given mass of DNL was stirred on a heating plate at different time intervals. The influence of contact time was studied at three initial Co(II) concentrations (10, 100, and 500 mg/L), pH (3–8), DNL mass (0.05–0.4), and temperature (25–60°C). After predetermined intervals, the solution was filtered using Whatman filter paper No 1, and the equilibrium concentration of Co(II) remaining in solution determined using a UV/visible spectrophotometer (spectro 23RS, labo med.inc) at 400 nm (predetermined) by complexing with concentrated aqueous ammonia. All pH adjustments were done using 0.1 M solution of NaOH and HCl each. The amount of Co(II) removed was calculated using [21–23].(1)Amount CoIIremoved=Ci−CfVm,%CoIIremoved=Ci−CfCf×100,where Ci and Cf (mg/L) are the initial and equilibrium concentrations, respectively, V (L) is the volume of the Co(II) solution, m (g) is the mass of DNL used, and the amount removed is noted qe (mg/g).


### 2.3. Adsorption Kinetics Modeling

Kinetic parameters were determined by applying the pseudofirst-order, pseudosecond-order, and intraparticle diffusion (Weber–Morris) models.The Lagergren pseudofirst-order kinetic model in linearized form is given by the following equation [24]:(2)lnqe−qt=lnqe−k1t,where qt is the adsorption capacity (mg/g) at time t (min), qe is the equilibrium adsorption capacity (mg/g), and K1 is the pseudofirst-order equilibrium rate constant (min−1) determined from a plot of lnqe−qt versus t.Ho’s linearized pseudosecond-order kinetic model is described by the following equation [25]:(3)tqt=1k2qe2+tqe.The equilibrium adsorption capacity (qe) and the second-order constant (k2) can be determined experimentally from the slope and intercept of plot t/qt versus t.The Weber–Morris equation is given as [26](4)qt=kidt1/2+C,where qt (mg·g−1) is the amount adsorbed at time t (min), kid (mg·g−1 min1/2) is the rate constant of intraparticle diffusion, and C is the intercept obtained from a straight line plot of qt versus t1/2.


### 2.4. Adsorption Thermodynamic Parameters

Gibbs free energy (∆G), enthalpy (∆H), and entropy (∆S) are vital thermodynamic parameters required for proper assessment of any adsorption process [27]. Gibbs free energy determines the spontaneous character of the adsorption (∆G < 0 for spontaneous process), while enthalpy values indicate the endothermic or exothermic nature of the process (∆H < 0 is exothermic and ∆H > 0 is endothermic). Positive values of ∆S indicate increased randomness at solid-liquid interphase during the sorption processes, hence increased adsorption performance. These properties were calculated by employing the following equations:(5)ΔG=−RTlnK,lnK=ΔSR−ΔHRT,where R is the ideal gas constant (kJ·mol−1 K−1) and T is the temperature (K). The enthalpy change (∆H) and the entropy change (∆S) are calculated from a plot of lnK versus 1/T.K is calculated from (6)K=CadsCe,Cads=Co−Ce,where K is the equilibrium constant, Ce is the equilibrium (mg/L) at temperature T, Co is the initial Cr(VI) concentration (mg/L), and Cads is the concentration of Cr(VI) in the adsorbent at equilibrium (mg/L) at temperature T.


### 2.5. Adsorption Isotherms

One-, two-, and three-parameter isotherm models were used to evaluate adsorption performance of Co(II) adsorption on DNL. These isotherms and their nonlinear, linear, plotting forms, and characteristic parameters are summarized in Table2.Table 2
One-, two-, and three-parameter isotherm models tested.
Isotherm/Reference
Nonlinear form
Linear form
Plot
Characteristic parameters
One-parameter isotherm
Henry’s [28]
q
e = KHECe
q
e = KHECe
q
e vs. Ce
K
HE = Henry’s adsorption constant
Two-parameter isotherms
Freundlich [29]
q
e = KFC1/n
lnqe = ln KF + 1/n lnCe
lnqe vs. lnCe
K
F = adsorption capacity (mg/g)(L/mg)1/n
1/n = adsorption intensity
Jovanovic [28]
lnqe = ln qmax − KJCe
lnqe vs. Ce
q
max = maximum adsorbate uptake
K
J = Jovanovic constant
Langmuir-1
q
e
/
q
m
=
b
C
e
/
1
+
b
C
e [30]
1
/
q
e = 1/bqmCe+1/qm
1
/
q
e vs. 1/Ce
q
m = maximum adsorbate uptake
Langmuir-2
C
e
/
q
e
=
1
/
b
q
m
+
C
e
/
q
m
C
e
/
q
e
vs.
C
e
b = Langmuir equilibrium constant (L/mg)
Langmuir-3
q
e = −qe/bCe+qm
q
e vs. qe/Ce
Langmuir-4
q
e
/
C
e = −bqe + bqm
q
e
/
C
e vs. qe
Langmuir-5
1
/
C
e = bqm1/qe − b
1
/
C
e
vs.
1
/
q
e
Temkin [31]
q
e = Bln AT.Ce
q
e = Bln AT + Bln Ce
q
e vs. ln Ce
A
T: equilibrium binding constant (L/mg) bT = RT/B = adsorption energy (kJ/mol)
Elovich [32]
q
e
/
q
m = KECeexp(−qe/qm)
ln
q
e
/
C
e = ln KEqm − qe/qm
ln
q
e
/
C
e vs. qe
q
m = maximum adsorbate uptake
K
E = Elovich equilibrium constant (L/mg)
Dubinin–Radushkevich (D-R) [28]
q
e
=
X
m
exp
−
K
ε
2
ln
q
e
=
ln
X
m
−
K
ε
2
ln
q
e
vs.
ε
2
X
m = adsorption capacity (mg/g)
K = constant related to the adsorption energy (mol2·kJ−2)
Fowler–Guggenheim [33]
K
FG
C
e = θ/1−θexp2θW/RT
ln
C
e
1
−
θ
/
θ = −ln KFG + 2θW/RT
ln
C
e
1
−
θ
/
θ vs. Ɵ
K
FG = Fowler–Guggenheim equilibrium constant (L/mg)
W = is interaction energy between adsorbed molecules (KJmol−1)
Kiselev [34]
K
1
C
e = θ/1−θ1+knθ
1
/
C
e
1
−
θ = K1/θ + k1kn
1
/
C
e
1
−
θ vs. 1/θ
k
1 = Kiselev equilibrium constant (L/mg)
k
n = constant of complex formation between adsorbed molecules
Hill–de Boer [35, 36]
K
1
C
e = θ/1−θ exp (θ/1−θ − K2θ/RT)
ln
C
e
1
−
θ
/
θ − θ/1−θ = −ln K1 − K2θ/RT
ln
C
e
1
−
θ
/
θ − θ/1−θ vs. Ɵ
K
1 = Hill–de Boer constant (L/mg)
K
2 = energetic constant of the interaction between adsorbed molecules (kJmol−1)
Langmuir–Freundlich [37]
ln(qm/qe − 1) = ln KG − Nbln Ce
ln(qm/qe − 1) vs. ln Ce
K
G = saturation constant (mg/L)
N
b = cooperative binding constant
Flory–Huggins [28]
lnθ/Co = ln KFH + n ln(1 − θ)
lnθ/Co vs. ln(1 − θ)
n = number of adsorbates occupying adsorption sites
K
FH = Flory–Huggins equilibrium constant (L/mg)
Harkin–Jura [28]
1
/
q
e
2 = B/A – (1/A) ln Ce
1
/
q
e
2 vs. ln Ce
B and A are Harkin–Jura constants
Halsey [38]
q
e = (KH/Ce)1/nH
lnqe = 1/nH ln KH – 1/nHln Ce
lnqe vs. ln Ce
K
H and nH are Halsey isotherm constants
Three-parameter isotherm
Redlich–Peterson [28]
q
e = KRCe/1+aRCebR
ln(KRCe/qe – 1) = bRln Ce + ln(aR)
ln(KRCe/qe – 1) vs. ln Ce
K
R, Redlich–Peterson isotherm constant (Lg−1) used to obtain the maximum value of the correlation coefficient aR = constant (L/mg)
b
R = exponent that lies between 0 and 1


## 2.1. Collection, Treatment, and Characterization of Neem Leaves Adsorbent

Collection was done in front of the laboratory as there are dispersed on every empty space. They were taken to the laboratory, washed with distilled water, and dried in an oven at 105°C for 24 hours. The dried sample was then crushed and grinded to powder. This powder was washed several times with distilled water until the leaves were not more sending out the yellow colouration. They were then dried in open air inside the laboratory for five days (average temperature in the laboratory was 33°C), abbreviated as (DNL) and used for characterization and adsorption studies without further treatment.The chemical and surface compositions were determined using energy dispersive X-y analysis (EDX) (Shimadzu, XRF-1800, Japan) and Fourier-transform infrared spectroscopy (FTIR) (FTIR, iS50 RAMAN, Thermo Scientific, USA) analyses. For FTIR, the peaks obtained were then compared with those of neem leaves and other biomass samples reported in the literature for identification. The different phase transformations were investigated using the differential scanning calorimetry-thermogravimetric (DSC-TGA) techniques (SDT Q600 V20.9 Build 20, TGA-DTA, TA Instruments, USA). Porosity characteristics were determined by gas adsorption using nitrogen adsorption-desorption at the liquid nitrogen temperature (−195, 800°C) (Micromeritics tristar 3000 apparatus, USA).


## 2.2. Adsorption Test

HCl (35% w/w), NaOH (granulated), cobalt(II) sulfate heptahydrate salt, and ammonia solution (25% w/w) used were all essential laboratory reagents from Scharlab S. L., Spain. Adsorption experiments were conducted in a capped 250 mL conical flask using 100 mL solution of Co(II). The contents of the flask which included Co(II) of desired concentration and given mass of DNL was stirred on a heating plate at different time intervals. The influence of contact time was studied at three initial Co(II) concentrations (10, 100, and 500 mg/L), pH (3–8), DNL mass (0.05–0.4), and temperature (25–60°C). After predetermined intervals, the solution was filtered using Whatman filter paper No 1, and the equilibrium concentration of Co(II) remaining in solution determined using a UV/visible spectrophotometer (spectro 23RS, labo med.inc) at 400 nm (predetermined) by complexing with concentrated aqueous ammonia. All pH adjustments were done using 0.1 M solution of NaOH and HCl each. The amount of Co(II) removed was calculated using [21–23].(1)Amount CoIIremoved=Ci−CfVm,%CoIIremoved=Ci−CfCf×100,where Ci and Cf (mg/L) are the initial and equilibrium concentrations, respectively, V (L) is the volume of the Co(II) solution, m (g) is the mass of DNL used, and the amount removed is noted qe (mg/g).


## 2.3. Adsorption Kinetics Modeling

Kinetic parameters were determined by applying the pseudofirst-order, pseudosecond-order, and intraparticle diffusion (Weber–Morris) models.The Lagergren pseudofirst-order kinetic model in linearized form is given by the following equation [24]:(2)lnqe−qt=lnqe−k1t,where qt is the adsorption capacity (mg/g) at time t (min), qe is the equilibrium adsorption capacity (mg/g), and K1 is the pseudofirst-order equilibrium rate constant (min−1) determined from a plot of lnqe−qt versus t.Ho’s linearized pseudosecond-order kinetic model is described by the following equation [25]:(3)tqt=1k2qe2+tqe.The equilibrium adsorption capacity (qe) and the second-order constant (k2) can be determined experimentally from the slope and intercept of plot t/qt versus t.The Weber–Morris equation is given as [26](4)qt=kidt1/2+C,where qt (mg·g−1) is the amount adsorbed at time t (min), kid (mg·g−1 min1/2) is the rate constant of intraparticle diffusion, and C is the intercept obtained from a straight line plot of qt versus t1/2.


## 2.4. Adsorption Thermodynamic Parameters

Gibbs free energy (∆G), enthalpy (∆H), and entropy (∆S) are vital thermodynamic parameters required for proper assessment of any adsorption process [27]. Gibbs free energy determines the spontaneous character of the adsorption (∆G < 0 for spontaneous process), while enthalpy values indicate the endothermic or exothermic nature of the process (∆H < 0 is exothermic and ∆H > 0 is endothermic). Positive values of ∆S indicate increased randomness at solid-liquid interphase during the sorption processes, hence increased adsorption performance. These properties were calculated by employing the following equations:(5)ΔG=−RTlnK,lnK=ΔSR−ΔHRT,where R is the ideal gas constant (kJ·mol−1 K−1) and T is the temperature (K). The enthalpy change (∆H) and the entropy change (∆S) are calculated from a plot of lnK versus 1/T.K is calculated from (6)K=CadsCe,Cads=Co−Ce,where K is the equilibrium constant, Ce is the equilibrium (mg/L) at temperature T, Co is the initial Cr(VI) concentration (mg/L), and Cads is the concentration of Cr(VI) in the adsorbent at equilibrium (mg/L) at temperature T.


## 2.5. Adsorption Isotherms

One-, two-, and three-parameter isotherm models were used to evaluate adsorption performance of Co(II) adsorption on DNL. These isotherms and their nonlinear, linear, plotting forms, and characteristic parameters are summarized in Table2.Table 2
One-, two-, and three-parameter isotherm models tested.
Isotherm/Reference
Nonlinear form
Linear form
Plot
Characteristic parameters
One-parameter isotherm
Henry’s [28]
q
e = KHECe
q
e = KHECe
q
e vs. Ce
K
HE = Henry’s adsorption constant
Two-parameter isotherms
Freundlich [29]
q
e = KFC1/n
lnqe = ln KF + 1/n lnCe
lnqe vs. lnCe
K
F = adsorption capacity (mg/g)(L/mg)1/n
1/n = adsorption intensity
Jovanovic [28]
lnqe = ln qmax − KJCe
lnqe vs. Ce
q
max = maximum adsorbate uptake
K
J = Jovanovic constant
Langmuir-1
q
e
/
q
m
=
b
C
e
/
1
+
b
C
e [30]
1
/
q
e = 1/bqmCe+1/qm
1
/
q
e vs. 1/Ce
q
m = maximum adsorbate uptake
Langmuir-2
C
e
/
q
e
=
1
/
b
q
m
+
C
e
/
q
m
C
e
/
q
e
vs.
C
e
b = Langmuir equilibrium constant (L/mg)
Langmuir-3
q
e = −qe/bCe+qm
q
e vs. qe/Ce
Langmuir-4
q
e
/
C
e = −bqe + bqm
q
e
/
C
e vs. qe
Langmuir-5
1
/
C
e = bqm1/qe − b
1
/
C
e
vs.
1
/
q
e
Temkin [31]
q
e = Bln AT.Ce
q
e = Bln AT + Bln Ce
q
e vs. ln Ce
A
T: equilibrium binding constant (L/mg) bT = RT/B = adsorption energy (kJ/mol)
Elovich [32]
q
e
/
q
m = KECeexp(−qe/qm)
ln
q
e
/
C
e = ln KEqm − qe/qm
ln
q
e
/
C
e vs. qe
q
m = maximum adsorbate uptake
K
E = Elovich equilibrium constant (L/mg)
Dubinin–Radushkevich (D-R) [28]
q
e
=
X
m
exp
−
K
ε
2
ln
q
e
=
ln
X
m
−
K
ε
2
ln
q
e
vs.
ε
2
X
m = adsorption capacity (mg/g)
K = constant related to the adsorption energy (mol2·kJ−2)
Fowler–Guggenheim [33]
K
FG
C
e = θ/1−θexp2θW/RT
ln
C
e
1
−
θ
/
θ = −ln KFG + 2θW/RT
ln
C
e
1
−
θ
/
θ vs. Ɵ
K
FG = Fowler–Guggenheim equilibrium constant (L/mg)
W = is interaction energy between adsorbed molecules (KJmol−1)
Kiselev [34]
K
1
C
e = θ/1−θ1+knθ
1
/
C
e
1
−
θ = K1/θ + k1kn
1
/
C
e
1
−
θ vs. 1/θ
k
1 = Kiselev equilibrium constant (L/mg)
k
n = constant of complex formation between adsorbed molecules
Hill–de Boer [35, 36]
K
1
C
e = θ/1−θ exp (θ/1−θ − K2θ/RT)
ln
C
e
1
−
θ
/
θ − θ/1−θ = −ln K1 − K2θ/RT
ln
C
e
1
−
θ
/
θ − θ/1−θ vs. Ɵ
K
1 = Hill–de Boer constant (L/mg)
K
2 = energetic constant of the interaction between adsorbed molecules (kJmol−1)
Langmuir–Freundlich [37]
ln(qm/qe − 1) = ln KG − Nbln Ce
ln(qm/qe − 1) vs. ln Ce
K
G = saturation constant (mg/L)
N
b = cooperative binding constant
Flory–Huggins [28]
lnθ/Co = ln KFH + n ln(1 − θ)
lnθ/Co vs. ln(1 − θ)
n = number of adsorbates occupying adsorption sites
K
FH = Flory–Huggins equilibrium constant (L/mg)
Harkin–Jura [28]
1
/
q
e
2 = B/A – (1/A) ln Ce
1
/
q
e
2 vs. ln Ce
B and A are Harkin–Jura constants
Halsey [38]
q
e = (KH/Ce)1/nH
lnqe = 1/nH ln KH – 1/nHln Ce
lnqe vs. ln Ce
K
H and nH are Halsey isotherm constants
Three-parameter isotherm
Redlich–Peterson [28]
q
e = KRCe/1+aRCebR
ln(KRCe/qe – 1) = bRln Ce + ln(aR)
ln(KRCe/qe – 1) vs. ln Ce
K
R, Redlich–Peterson isotherm constant (Lg−1) used to obtain the maximum value of the correlation coefficient aR = constant (L/mg)
b
R = exponent that lies between 0 and 1


## 3. Results and Discussion

### 3.1. Adsorbent Characteristics

The averaged results of EDX analysis show that DNL are composed principally of carbon, oxygen silicon, iron, aluminium, potassium, calcium, and trace amounts of Ti, Na, P, S, and Cl (Table3). The relatively high content of silicon and aluminum is probably due to contamination from Maroua clay soil as these leaves were collected from the soil surface where it had spent some time. The over 85% carbon and oxygen content confirms the bionature of this material. Similar EDX results of [39] showed that neem leaf powder contains mainly C and O and small amounts of Ca, Mg, K, P, and S.Table 3
Chemical composition of DNL.
Element
C
O
Mg
Al
Si
Cl
K
Ca
Ti
Fe
Na
P
S
Mass (%)
56.67
28.76
0.76
2.51
4.88
0.14
1.57
1.51
0.39
3.02
0.28
0.22
0.24FTIR analysis characterizes materials and is especially useful in recognizing inorganic mixtures. Also like Raman spectroscopy, FTIR can provide the molecular and structural information about organic and inorganic materials [8, 40]. The FTIR spectrum of DNL from 4000 to 400 cm−1 is shown in Figure 1. The intense peak at 3282.73 cm−1 is the O-H in the oxygen-containing functional groups [18, 41], while peaks 2849.91 and 2918.26 cm−1 are CH2 stretching bands generally indicating the presence of waxes [41]. The band at 1725.29 is due to COO− and C=O groups contained in the structure of cellulose, hemicelluloses, and lignin and common components of plant materials [18, 41]. The peaks at 1516.37 and 1602.22 cm−1 show the presence of C–C and C–O stretching in the aromatic ring indicating the presence of lignin [41]. This was also confirmed by peaks 1235.42, 1315.12, 1374.79, and 1436.58 cm−1 which are C–H and O–H bending frequencies indicating lignin presence [41]. Peak 1030.98 cm−1 indicate the aliphatic C–O–C group, while peak 1158.80 cm−1 is assigned to alcohol C–O stretches, all representing oxygenated functional groups of cellulose and hemicellulose [41]. The band at 530.45 cm−1 is assigned to Fe-O and Fe2O3 Si-O-Al stretching as those at 466.02, 425.76, and 416.59 cm−1 are assigned to Si-O-Si bending [40].Figure 1
FTIR spectrum of DNL.Thermo-gravimetric and differential scanning calorimetric analysis (DSC-TGA) profile of the DNL is shown in Figure2. There are four weight loss regions corresponding to a total loss of 87% for heating up to 1000°C. Step one involves a weight loss of about 8% in the temperature range of 50°C to 195°C, resulting mainly from the release of moisture and volatile matter [42, 43]. The second step shows steep weight loss of about 46% in the temperature range from 195°C to 395°C. In step three, about 28% weight loss is observed from 39°C to about 550°C. The total weight loss from steps two and three (195°C to 550°C) represents over 75%. These two steps constitute the devolatilization process which is the major step in all thermochemical conversion process involving biomass [43]. This involves the liberation of volatile hydrocarbon due to rapid thermal decomposition of hemicelluloses, cellulose, and part of lignin. The fourth step with a weight loss of about 4% occurred from 550°C to about 1000°C was due primarily to the steady decomposition of the remaining heavy components mainly from lignin [43].Figure 2
TG/DSC decomposition profile of DNL.The nitrogen adsorption-desorption isotherm is presented in Figure3. This isotherm is type IV isotherm model according to the IUPAC classification [44] characterized by monolayer formation (presence of micropores), presence of hysteresis (H1 or H2), indicating meso- and macropores, and formation of few multilayer. The neem leaves showed a very small BET surface area of 0.2783 m2/g, BJH adsorption-desorption cumulative volume of pores of 0.002205 cm³/g, BET calculated adsorption average pore width of 79.5352 Å, BJH adsorption average pore diameter of 873.637 Å, and BJH desorption average pore diameter of 561.250 Å. This confirms the type IV isotherm as well as the dominance of meso- and macropores for DNL. The negative values adsorbed are observed between relative pressure values from 0.49 to 0.89. As pressure increases, there is an increased uptake of adsorbate as pores become filled, but an inflection point (points of the curve where the curvature changes its sign) typically occurs near completion of the first monolayer. Usually, BET theory is applied to obtain the specific surface area of microporous materials [45], but the BET surface area of 0.2783 m2/g shows that the few micropores available were easily filled and could not take part in the adsorption process at indicated pressures. However, with further increase in pressure there was desorption and the surface of the material was free for further adsorption.Figure 3
Nitrogen adsorption-desorption isotherm of DNL.


### 3.2. Influence of Process Parameters, Kinetics, and Thermodynamics of Co(II) Adsorption by DNL

The effect of contact time was studied at three initial cobalt (II) initial concentration (10, 100, and 500 mg/L), and the results are presented in Figure4(a) where it is observed that the biosorption of Co(II) on DNL is very rapid in the first 5 minutes (84.5%, 88.5%, and 97% for 10, 100, and 500 mg/L, respectively) before slowing down to attain equilibrium in 10 minutes (84.95%, 89.56%, and 97.13% for 10, 100, and 500 mg/L, respectively). These isotherms all observed the L isotherm model of Giles and Nakha [46] where the initial slope is very high exhibiting a high affinity of Co(II) for the solid adsorbent. This high affinity is due to the presence of many Co(II) binding groups such as COO−, C=O, O-H, C–O, C–O–C, Si-O-Al, and Fe-O groups of DNL as shown by FTIR analysis (Figure 1) originating from DNL cellulose, hemicellulose, and lignin content. These results are very high compared to those of [47] who obtained 14% and 28% of Co(II) adsorption on natural inorganic materials bentonite and tripoli in 5 minutes. The calculated kinetic parameters are presented in Table 4 where it is seen that Co(II) adsorption on DNL is best described by the pseudosecond-order kinetic model with coefficient of correlations greater than 99% (0.9998, 1.000, and 1.000 for 10, 100, and 500 mg/L, respectively) and strong correlation between calculated and experimental equilibrium amounts adsorbed. These results are similar to those of [47] who obtained coefficient of correlations of 1.000 and 0.998 for the pseudosecond-order kinetic model of Co(II) adsorption on natural inorganic materials bentonite and tripoli.Figure 4
Influence of process parameters (a) contact time, (b) pH, (c) DNL dose, and (d) temperature.
(a)
(b)
(c)
(d)Table 4
Kinetic parameters for Co(II) adsorption on DNL.
Models
Parameters
10 mg/L
100 mg/L
500 mg/L
Pseudofirst-order
k
1 (min)
−0.031
0.0004
0.028
q
e, c (mg/g)
0.052
1.112
2.167
q
e, ex (mg/g)
8.541
90.452
487.086
R
2
0.8281
0.0006
0.7971
Pseudosecond-order
k
2 (g/mg/min)
0.269
0.139
0.055
q
e, c (mg/g)
8.157
89.286
476.190
q
e, ex (mg/g)
8.541
90.452
487.086
R
2
0.9998
1.000
1.000
Intraparticle diffusion (Weber–Morris)
k
id (mg/g/min1/2)
0.051
0.046
0.353
C (mg/g)
8.646
89.158
484.33
R
2
0.6472
0.0227
0.9754
q
e, c and qe, ex are, respectively, calculated and experimental equilibrium amounts adsorbed.Results of the influence of pH are shown in Figure4(b). There is a decrease in amount adsorbed as pH is varied from 3 to 7. Cobalt is probably present in its free ionic form at pH 3. Thus, a decrease adsorption from pH 3.0 to pH 7.0 can be explained by the type and ionic state of the carboxyl functional groups (probably more dominant in DNL) that have a pKa value around 3.7. At pH values lower than pKa, carboxylate groups are mainly protonated resulting in a lower uptake. At pH values higher than pKa, more functional groups carry negative charge and the positively charged cobalt ions will be bound, increasing uptake [48]. However, at pH of 8 there is a remarkable increase of up to 97%. As pH turned basic, it was observed that there was the formation of Co(II) precipitate probably as hydroxides, thus responsible for high adsorption.The effect of adsorbent dose was studied from 0.05 to 0.4 g, and the results are given in Figure4(c). It can be seen that the amount adsorbed increases with increase in the quantity of DNL dose up to a maximum of 0.3 g of DNL, followed by a decrease at 0.4 g. Increase in adsorption is due to the increase in surface area, and hence the number of active sites. However, the decrease in adsorption with increase in the mass of DNL may be due to particle aggregation which may lead to a decrease in total surface area and an increase in diffusional path length [49].The dependence of adsorption on temperature was studied from 25–60°C, and the results are presented in Figure4(d), while the calculated thermodynamic parameters are shown in Table 5. From calculated ∆G° values (−5.424, −5.505, −5.607, and −6.068 KJ/mol at 25, 35, 40, and 60°C, respectively), it is observed that increase in temperature has little influence on Co(II) adsorption by DNL. This was also the findings of [47] for Co(II) adsorption on natural inorganic materials bentonite and tripoli. The slight increase, however, may be due to the creation of new active sites resulting from heating. This may equally be resulting from the acceleration of some originally slow adsorption steps, enhancing the mobility of adsorbate from the bulk solution towards the adsorbent surface [50]. The negative ∆G° values show that Co(II) adsorption on DNL is spontaneous, and the overall process is endothermic as evident from the positive enthalpy value. Equally, the positive value of the entropy shows that there is increased randomness at solid-liquid interphase during the sorption processes, hence enhancing the process.Table 5
Thermodynamic parameters at 100 mg/L initial Co(II) concentration.
Temperature (K)
∆G° (KJ/mol)
∆H° (KJ/mol)
∆S° (KJ/mol K)
298
−5.424
+0.275
+0.023
308
−5.505
313
−5.607
333
−6.068


### 3.3. Adsorption Isotherm

#### 3.3.1. One-Parameter Isotherm

(1) Henry’s Isotherm. This model assumes that the amount of surface adsorbate is proportional to the partial pressure of the gas adsorbate. It also used to describe adsorption of adsorbate at very low concentrations such that all adsorbate molecules are secluded from their nearest neighbours [28]. From Table 6, this isotherm describes Co(II) adsorption DNL with correlation coefficients of unity for all tested initial concentrations. The Henry isotherm model also showed best fit against Langmuir-1, Langmuir-2, Langmuir-3, Langmuir-4, Freundlich, Temkin, and Dubinin–Radushkevich isotherms for the adsorption of malachite green with orange peels [51].Table 6
One-, two-, and three-isotherm parameters for the adsorption of Co(II) on DNL.
Isotherm/parameters
Tested concentrations
10 mg/L
100 mg/L
500 mg/L
One-parameter isotherm
Henry’s isotherms
K
HE
1.000
1.000
1.000
R
2
1.000
1.000
1.000
Two-parameter isotherms
Freundlich
K
F (mg/g)(L/mg)1/n
9.201
118.203
523.900
n
−5.112
−8.446
−35.088
R
2
0.9993
0.9992
0.9995
Jovanovic
q
max (mg/g)
10.171
100.655
500.196
K
J
0.120
0.011
0.002
R
2
1.000
1.000
1.000
Langmuir-1
q
m (mg/g)
6.988
80.000
476.190
b (L/mg)
3.756
0.893
2.625
R
L
0.026
0.011
0.001
R
2
0.9971
0.9967
0.9982
Langmuir-2
q
m (mg/g)
6.983
80.000
476.190
b (L/mg)
3.739
0.893
2.625
R
L
0.026
0.011
0.001
R
2
0.9999
1.000
1.000
Langmuir-3
q
m (mg/g)
6.990
79.95
472.700
b (L/mg)
3.757
0.896
2.618
R
L
0.026
0.011
0.001
R
2
0.9979
0.9974
0.9983
Langmuir-4
q
m (mg/g)
6.987
79.895
472.647
b (L/mg)
3.749
0.894
2.614
R
L
0.026
0.011
0.001
R
2
0.9979
0.9974
0.9983
Langmuir-5
q
m (mg/g)
6.986
79.927
472.571
b (L/mg)
3.746
0.893
2.614
R
L
0.026
0.011
0.001
R
2
0.9971
0.9967
0.9982
Temkin
A
T (L/mg)
0.004
2.026E−05
3.978E−17
b
T (kJ/mol)
−1.515
−0.234
−0.179
R
2
0.9995
0.9993
0.9996
Two-parameter isotherms
Elovich
q
m (mg/g)
1.368
9.470
13.459
K
E (L/mg)
0.008
7.072E−05
5.375E−16
R
2
0.9997
0.9995
0.9996
Dubinin–Radushkevich
X
m (mg/g)
7.388
84.041
479.048
K (mol2 kJ−2)
−0.0845
−1.1855
−0.4736
E (kJ/mol)
2.433
0.649
1.027
R
2
0.9965
0.9941
0.9964
Fowler–Guggenheim
K
FG (L/mg)
6.155E − 05
2.108E − 08
4.759E − 31
W (kJ/mol)
−16.182
−24.254
−90.163
R
2
0.9996
0.9995
0.9996
Kiselev
k
1 (L/mg)
25.186
11.652
172.78
k
n
1.331
1.191
1.044
R
2
0.9942
0.9933
0.9961
Hill–de Boer
K
1 (L/mg)
2.922E − 14
2.015E − 39
0
K
2 (kJ/mol)
−111.102
−269.609
−3328.866
R
2
0.9988
0.9978
0.998
Langmuir–Freundlich
K
G (mg/L)
0.268
1.139
0.740
N
b
0.995
1.011
1.367
R
2
0.9975
0.9966
0.9972
Harkin–Jura
A
−178.571
−33333.333
−5000000
B
2.07E + 00
2.00E + 00
2.00E + 01
R
2
0.9988
0.9988
0.9995
Halsey
K
H
84635.961
3.201E + 17
2.584E + 95
n
H
5.11247444
8.44594595
35.0877193
R
2
0.9993
0.9992
0.9995
Flory–Huggins
n
0.216
0.1184
0.0289
K
FH (L/mg)
0.057
0.007
0.002
R
2
0.9994
0.9992
0.9995
Three-parameter isotherm
Redlich–Peterson
K
R (Lg−1)
18
33
131
a
R (L/mg)
1.104
0.083
0.068
b
R
1.674
1.505
1.407
R
2
1.000
1.000
1.000


#### 3.3.2. Two-Parameter Isotherms

(1) Freundlich Model. The Freundlich model describes multilayer removal process which takes place on the heterogeneous surface [29]. By definition, the adsorption intensity, n, is less than unity [35]. This model fits the adsorption of Co(II) on DNL with coefficient of correlations greater than 99% for the three initial concentrations with high values of KF (9.2, 118, and 523 (mg/g)(L/mg)1/n for 10, 100, and 500 mg/L) which are adsorption capacities (Table 6). This performance is due to the presence of heterogeneous groups on the DNL surface as evident from FTIR results (Figure 1) and confirmed by this isotherm model analysis. These groups are all good binding sites for Co(II). Similar to the results, Freundlich isotherm amongst many other applied isotherm models also best described lead (II) ions adsorption from aqueous solutions in the study that used coir dust and its modified extract resins as adsorbents [28].(2) Langmuir Model. The Langmuir model assumes uniform energies of adsorption onto the monolayer surface and no interaction of adsorbate on the surface [30]. Five linear forms can be obtained as shown in Table 5. The separation factor, RL, which is considered as a more reliable indicator of the adsorption is defined by the following equation: (7)RL=11+bC0,where b (L/mg) is the Langmuir constant and C0 (mg/L) is the initial concentration of the solute. For favourable adsorption, 0 < RL < 1, while RL > 1, RL = 1, and RL = 0, respectively, describe unfavorable, linear, and irreversible adsorption [9].The adsorption of Co(II) on DNL was linearized with five Langmuir models, and the calculated parameters are presented in Table6. All the five models fit the adsorption of Co(II) on DNL with same values of Langmuir equilibrium constant (b), RL and R2 > 99%. The high b and low RL values indicate a very favourable Co(II) adsorption on DNL. However, Langmuir-2 showed better fitting with highest correlation coefficient. The highest adsorption capacities were equally obtained for Langmuir-1 and Langmuir-2. According to [52] Langmuir-1 and Langmuir-2 are the most used Langmuir isotherm models because of the minimized deviations from the fitted equation resulting in the best error distribution. The fitness of Langmuir models also indicate that Co(II) adsorption on DNL occurred on a monolayer homogenous surface.(3) Jovanovic Model. The model is based on the same assumptions as in the Langmuir model, but predicts in addition the possibility of some mechanical contacts between the adsorbate and adsorbent [28]. The adsorption capacities obtained (10.171, 100.655, and 500.196 mg/g for 10, 100, and 500 mg/L) are higher than for the Langmuir model (Table 6). The R2 are all unity for the three Co(II) initial concentrations showing the adequacy of model in describing Co(II) adsorption on DNL. Jovanovic isotherms was also shown to generate a straight line curve that best fitted the sorption of Fe2+, Mg2+, and Zn2+ ions on the metallophthalocyanine film [53]. The decreasing values of Jovanovic constant (KJ) with increasing initial concentration (0.120 at 10 mg/L, 0.011 at 100 mg/L, and 0.002 at 500 mg/L) indicate that with increasing initial concentration there is very little contact time between Co(II) and DNL before adsorption. At higher initial concentrations, there is an important driving force due to the increased concentration necessary to overcome all mass transfer resistances of the pollutant between the aqueous and solid phases thus increasing the adsorption [50]. All surface coverage values were calculated using adsorption capacities from this model.(4) Temkin Model. Temkin model assumes that the heat of adsorption of the adsorbates in the layer decreases linearly rather than logarithmically with coverage due to adsorbent-adsorbate interactions and that adsorption is characterized by a uniform distribution of the binding energies, up to some maximum binding energy [31]. This model equally fits Co(II) adsorption on DNL with R2 values greater than 99%. Similarly, results were also obtained by other authors using miswak leaves to adsorb methylene blue [28]. The bT (adsorption energy (kJ/mol)) values −1.515, −0.234, and −0.179 KJ/mol (Table 6) show that physisorption was responsible for Co(II) adsorption on DNL [49].(5) Elovich Model. The Elovich model is based on the kinetic principle assuming that the adsorption sites increase exponentially with adsorption, which implies a multilayer adsorption [32]. Despite the fitness of this model for Co(II) adsorption on DNL from R2 values (Table 6), the calculated adsorption capacities were very low. This is probably due to the fact this model describes multilayer adsorption indicating migration from one layer to another. Elovich isotherm model has been reported also to describe the adsorption of Cu(II) on chitin compared to other tested models but with R2 of 0.808 [28].(6) Dubinin–Radushkevich (D-R) Model. It is an empirical generally applied to express adsorption mechanism with Gaussian energy distribution onto heterogeneous surfaces [28]. The significance of applying Dubinin–Radushkevich model is to determine apparent adsorption energy, E (kJ/mol) which is given by (8)E=12K,K is a constant related to the adsorption energy (mol2·kJ−2).If the value ofE is between 8 and 16 kJ/mol, ion exchange is the main sorption process in the system. If the value is lower than 8 kJ/mol, physical sorption is the main sorption mechanism, and if the value is greater than 16 kJ/mol, it may be chemisorption [49]. D-R represented a good fit for Co(II) adsorption on DNL (R2 > 99%) (Table 6), indicating the involvement of heterogeneous sites. All obtained adsorption energies were lower than 8 kJ/mol (Table 6) showing that the process was physical. These results are consistent with other studies on cobalt adsorption [54, 55].(7) Fowler–Guggenheim Model. This isotherm takes the lateral interaction of the adsorbed molecules into account [33]. The heat of adsorption increases linearly with loading. If the interaction between the adsorbed molecules is attractive (that is, W is positive), the heat of adsorption will increase with loading and this is due to the increased interaction between adsorbed molecules as the loading increases. This means that if the measured heat of adsorption shows an increase with respect to loading, it indicates the positive lateral interaction between adsorbed molecules. However, if the interaction among adsorbed molecules is repulsive (that is W is negative), the heat of adsorption shows a decrease with loading. When there is no interaction between adsorbed molecules (that is, W = 0), this Fowler–Guggenheim equation will reduce to the Langmuir equation. W is the interaction energy between adsorbed molecules (kJ·mol−1). From Table 6, it can be seen that this model describes Co(II) adsorption on DNL. The entire W values are negative, becoming more negative with increasing loading or increasing initial concentration indicating that the heat of adsorption shows a decrease with loading due to repulsive interaction among adsorbed molecules. Other authors [56] also reported that the Fowler–Guggenheim model best described Cr (VI), Mn(II), Fe(II), and Cu(II) on activated carbons from agricultural wastes but with positive W values. This difference may be due to reaction conditions as well as the composition of the different materials used.(8) Kiselev Model. The Kiselev adsorption isotherm equation also known as the localized monomolecular layer model [34] is only valid for surface coverage θ > 0.68 [28]. The lowest θ value obtained was 0.82 for this study at all the tested initial concentrations. This model also described Co(II) adsorption on DNL with R2 values greater than 99%. Values of k1 which represent equilibrium constant are very high for the three concentrations as well as kn values which represent constant of complex formation between adsorbed molecules, confirming the high adsorption of Co(II) on DNL. The study of [57] equally demonstrated the fitness of Kiselev adsorption isotherm for cadmium adsorption using novel water treatment residual nanoparticles with R2 > 99%.(9) Hill–de Boer Model. This model equation describes the case where there is mobile adsorption and lateral interaction among adsorbed molecules [35, 36]. A positive K2 means attraction between adsorbed species and a negative value means repulsion; that is, the apparent affinity is increased with loading when there is attraction between adsorbed species, and it is decreased with loading when there is repulsion among the adsorbed species. When there is no interaction between adsorbed molecules (that is, K2 = 0). From Table 6, all the K2 values are negative meaning Co(II) adsorption on DNL occurs by repulsive mechanism, confirming Fowler–Guggenheim model results and maximum Co(II) adsorption at pH 3. This was also the findings of other works [57, 58] using nanoparticles of water treatment residual and granular activated carbon.(10) Langmuir–Freundlich Model. This isotherm fuses both Langmuir and Freundlich isotherms together [37]. It offers a flexible analytical framework for modeling both Langmuir and Freundlich type sorption effects. The cooperative binding constant (Nb) obtained (0.995 at 10 mg/L, 1.011 at 100 mg/L, and 1.367 at 500 mg/L) indicate increase tendency of adsorption with increasing initial Co(II) concentration as many Co(II) ions are available to react with DNL surface groups (Table 6). Equally, there is increase in saturation constant (KG) with increasing initial Co(II) concentration indicating the ease of accumulation at the surface with increasing initial concentration due to rapid occupation of active sites permitting additional ions to accumulate on the surface. The fact that R2 for this model is high (>99%) (Table 6) confirms that adsorption of Co(II) on the DNL surface involves homogenous and heterogeneous sites.(11) Flory–Huggins Model. It describes the degree of surface coverage characteristics of the adsorbate on the adsorbent [28]. This isotherm model can express the feasibility and spontaneity of an adsorption process by applying ∆G = −RTlnKFH. From Table 6, all KFH are positive, indicating negative Gibbs free energy (∆G), hence spontaneity of the adsorption process stemming from high Co(II) occupancy of the DNL surface (surface coverage values calculated based on maximum adsorption capacity values from Jovanovic isotherm ranged from 85 to 92% for this study). Results of this model also reveal that the number of adsorbates occupying adsorption sites (n) decrease with increase Co(II) initial concentration. At higher initial concentration, there is a scramble by many ions for existing adsorption sites, whereas at lower initial concentration there is the availability of sites to fewer ions. This trend was also obtained in another study on the biosorption of zinc from aqueous solution using coconut coir dust [28].(12) Harkin–Jura. This model assumes the possibility of multilayer adsorption on the surface of absorbents having heterogeneous pore distribution [38]. Results of this model are shown in Table 6 with R2 values > 99% confirming the heteroporosity nature of the DNL surface and the possibility of multilayer adsorption of Co(II) on its surface. Similar findings were also reported by other authors [28] who showed in their study that the Harkin–Jura isotherm model had a better fit to the adsorption data than Freundlich, Halsey, and Temkin isotherm models in their investigation of the adsorptive removal of reactive black 5 from wastewater using bentonite clay, confirming the heteroporosity of the adsorbent. BET studies in this work showed that DNL contain micro-, meso-, and macropores.(13) Halsey. This model like Harkin–Jura is suitable for multilayer adsorption an adsorption on a heterogeneous surface. With R2 values > 99%, Halsey isotherm results also confirm the heterogeneous nature of the DNL surface and the possibility of multilayer adsorption of Co(II) on its surface. Some works [28] have also reported the good fit of experimental data to the Halsey isotherm model for adsorption of methyl orange on pinecone-derived activated carbon and pb2+ ion on coconut shell carbon. This good fit attest the heterogeneous distribution of activate sites and multilayer on tested adsorbents. The heterogeneous distribution of activate sites for DNL is indicated by the presence of different groups such as COO−, C=O, O-H, C–O, C–O–C, Si-O-Al, and Fe-O as shown by FTIR analysis (Figure 1).


#### 3.3.3. Three-Parameter Isotherm

(1) Redlich–Peterson Model. This isotherm model is an empirical isotherm incorporating three parameters. It combines elements from both Langmuir and Freundlich equations, therefore represent adsorption equilibrium over a wide range of concentration of adsorbate which is applicable in either homogenous or heterogeneous systems [28]. The values of the calculated parameters for this three-parameter isotherm model (KR, Redlich–Peterson isotherm constant (Lg−1) used to obtain the maximum value of the correlation coefficient, aR = constant (L/mg) and bR = exponent that lies between 0 and 1) are shown in Table 6. R2 value of unity was obtained at KR of 18 Lg−1 for 10 mg/L, 33 Lg−1 for 100 mg/L, and 131 Lg−1 for 500 mg/L, indicating the ease of adsorption with increasing initial concentration. Redlich–Peterson approaches the Freundlich isotherm model as bR tends to zero and to Langmuir as bR is close to one [5]. However, the fact that all bR values were greater than 1 (Table 6) suggest that this model does not describe Co(II) adsorption on DNL.


## 3.1. Adsorbent Characteristics

The averaged results of EDX analysis show that DNL are composed principally of carbon, oxygen silicon, iron, aluminium, potassium, calcium, and trace amounts of Ti, Na, P, S, and Cl (Table3). The relatively high content of silicon and aluminum is probably due to contamination from Maroua clay soil as these leaves were collected from the soil surface where it had spent some time. The over 85% carbon and oxygen content confirms the bionature of this material. Similar EDX results of [39] showed that neem leaf powder contains mainly C and O and small amounts of Ca, Mg, K, P, and S.Table 3
Chemical composition of DNL.
Element
C
O
Mg
Al
Si
Cl
K
Ca
Ti
Fe
Na
P
S
Mass (%)
56.67
28.76
0.76
2.51
4.88
0.14
1.57
1.51
0.39
3.02
0.28
0.22
0.24FTIR analysis characterizes materials and is especially useful in recognizing inorganic mixtures. Also like Raman spectroscopy, FTIR can provide the molecular and structural information about organic and inorganic materials [8, 40]. The FTIR spectrum of DNL from 4000 to 400 cm−1 is shown in Figure 1. The intense peak at 3282.73 cm−1 is the O-H in the oxygen-containing functional groups [18, 41], while peaks 2849.91 and 2918.26 cm−1 are CH2 stretching bands generally indicating the presence of waxes [41]. The band at 1725.29 is due to COO− and C=O groups contained in the structure of cellulose, hemicelluloses, and lignin and common components of plant materials [18, 41]. The peaks at 1516.37 and 1602.22 cm−1 show the presence of C–C and C–O stretching in the aromatic ring indicating the presence of lignin [41]. This was also confirmed by peaks 1235.42, 1315.12, 1374.79, and 1436.58 cm−1 which are C–H and O–H bending frequencies indicating lignin presence [41]. Peak 1030.98 cm−1 indicate the aliphatic C–O–C group, while peak 1158.80 cm−1 is assigned to alcohol C–O stretches, all representing oxygenated functional groups of cellulose and hemicellulose [41]. The band at 530.45 cm−1 is assigned to Fe-O and Fe2O3 Si-O-Al stretching as those at 466.02, 425.76, and 416.59 cm−1 are assigned to Si-O-Si bending [40].Figure 1
FTIR spectrum of DNL.Thermo-gravimetric and differential scanning calorimetric analysis (DSC-TGA) profile of the DNL is shown in Figure2. There are four weight loss regions corresponding to a total loss of 87% for heating up to 1000°C. Step one involves a weight loss of about 8% in the temperature range of 50°C to 195°C, resulting mainly from the release of moisture and volatile matter [42, 43]. The second step shows steep weight loss of about 46% in the temperature range from 195°C to 395°C. In step three, about 28% weight loss is observed from 39°C to about 550°C. The total weight loss from steps two and three (195°C to 550°C) represents over 75%. These two steps constitute the devolatilization process which is the major step in all thermochemical conversion process involving biomass [43]. This involves the liberation of volatile hydrocarbon due to rapid thermal decomposition of hemicelluloses, cellulose, and part of lignin. The fourth step with a weight loss of about 4% occurred from 550°C to about 1000°C was due primarily to the steady decomposition of the remaining heavy components mainly from lignin [43].Figure 2
TG/DSC decomposition profile of DNL.The nitrogen adsorption-desorption isotherm is presented in Figure3. This isotherm is type IV isotherm model according to the IUPAC classification [44] characterized by monolayer formation (presence of micropores), presence of hysteresis (H1 or H2), indicating meso- and macropores, and formation of few multilayer. The neem leaves showed a very small BET surface area of 0.2783 m2/g, BJH adsorption-desorption cumulative volume of pores of 0.002205 cm³/g, BET calculated adsorption average pore width of 79.5352 Å, BJH adsorption average pore diameter of 873.637 Å, and BJH desorption average pore diameter of 561.250 Å. This confirms the type IV isotherm as well as the dominance of meso- and macropores for DNL. The negative values adsorbed are observed between relative pressure values from 0.49 to 0.89. As pressure increases, there is an increased uptake of adsorbate as pores become filled, but an inflection point (points of the curve where the curvature changes its sign) typically occurs near completion of the first monolayer. Usually, BET theory is applied to obtain the specific surface area of microporous materials [45], but the BET surface area of 0.2783 m2/g shows that the few micropores available were easily filled and could not take part in the adsorption process at indicated pressures. However, with further increase in pressure there was desorption and the surface of the material was free for further adsorption.Figure 3
Nitrogen adsorption-desorption isotherm of DNL.


## 3.2. Influence of Process Parameters, Kinetics, and Thermodynamics of Co(II) Adsorption by DNL

The effect of contact time was studied at three initial cobalt (II) initial concentration (10, 100, and 500 mg/L), and the results are presented in Figure4(a) where it is observed that the biosorption of Co(II) on DNL is very rapid in the first 5 minutes (84.5%, 88.5%, and 97% for 10, 100, and 500 mg/L, respectively) before slowing down to attain equilibrium in 10 minutes (84.95%, 89.56%, and 97.13% for 10, 100, and 500 mg/L, respectively). These isotherms all observed the L isotherm model of Giles and Nakha [46] where the initial slope is very high exhibiting a high affinity of Co(II) for the solid adsorbent. This high affinity is due to the presence of many Co(II) binding groups such as COO−, C=O, O-H, C–O, C–O–C, Si-O-Al, and Fe-O groups of DNL as shown by FTIR analysis (Figure 1) originating from DNL cellulose, hemicellulose, and lignin content. These results are very high compared to those of [47] who obtained 14% and 28% of Co(II) adsorption on natural inorganic materials bentonite and tripoli in 5 minutes. The calculated kinetic parameters are presented in Table 4 where it is seen that Co(II) adsorption on DNL is best described by the pseudosecond-order kinetic model with coefficient of correlations greater than 99% (0.9998, 1.000, and 1.000 for 10, 100, and 500 mg/L, respectively) and strong correlation between calculated and experimental equilibrium amounts adsorbed. These results are similar to those of [47] who obtained coefficient of correlations of 1.000 and 0.998 for the pseudosecond-order kinetic model of Co(II) adsorption on natural inorganic materials bentonite and tripoli.Figure 4
Influence of process parameters (a) contact time, (b) pH, (c) DNL dose, and (d) temperature.
(a)
(b)
(c)
(d)Table 4
Kinetic parameters for Co(II) adsorption on DNL.
Models
Parameters
10 mg/L
100 mg/L
500 mg/L
Pseudofirst-order
k
1 (min)
−0.031
0.0004
0.028
q
e, c (mg/g)
0.052
1.112
2.167
q
e, ex (mg/g)
8.541
90.452
487.086
R
2
0.8281
0.0006
0.7971
Pseudosecond-order
k
2 (g/mg/min)
0.269
0.139
0.055
q
e, c (mg/g)
8.157
89.286
476.190
q
e, ex (mg/g)
8.541
90.452
487.086
R
2
0.9998
1.000
1.000
Intraparticle diffusion (Weber–Morris)
k
id (mg/g/min1/2)
0.051
0.046
0.353
C (mg/g)
8.646
89.158
484.33
R
2
0.6472
0.0227
0.9754
q
e, c and qe, ex are, respectively, calculated and experimental equilibrium amounts adsorbed.Results of the influence of pH are shown in Figure4(b). There is a decrease in amount adsorbed as pH is varied from 3 to 7. Cobalt is probably present in its free ionic form at pH 3. Thus, a decrease adsorption from pH 3.0 to pH 7.0 can be explained by the type and ionic state of the carboxyl functional groups (probably more dominant in DNL) that have a pKa value around 3.7. At pH values lower than pKa, carboxylate groups are mainly protonated resulting in a lower uptake. At pH values higher than pKa, more functional groups carry negative charge and the positively charged cobalt ions will be bound, increasing uptake [48]. However, at pH of 8 there is a remarkable increase of up to 97%. As pH turned basic, it was observed that there was the formation of Co(II) precipitate probably as hydroxides, thus responsible for high adsorption.The effect of adsorbent dose was studied from 0.05 to 0.4 g, and the results are given in Figure4(c). It can be seen that the amount adsorbed increases with increase in the quantity of DNL dose up to a maximum of 0.3 g of DNL, followed by a decrease at 0.4 g. Increase in adsorption is due to the increase in surface area, and hence the number of active sites. However, the decrease in adsorption with increase in the mass of DNL may be due to particle aggregation which may lead to a decrease in total surface area and an increase in diffusional path length [49].The dependence of adsorption on temperature was studied from 25–60°C, and the results are presented in Figure4(d), while the calculated thermodynamic parameters are shown in Table 5. From calculated ∆G° values (−5.424, −5.505, −5.607, and −6.068 KJ/mol at 25, 35, 40, and 60°C, respectively), it is observed that increase in temperature has little influence on Co(II) adsorption by DNL. This was also the findings of [47] for Co(II) adsorption on natural inorganic materials bentonite and tripoli. The slight increase, however, may be due to the creation of new active sites resulting from heating. This may equally be resulting from the acceleration of some originally slow adsorption steps, enhancing the mobility of adsorbate from the bulk solution towards the adsorbent surface [50]. The negative ∆G° values show that Co(II) adsorption on DNL is spontaneous, and the overall process is endothermic as evident from the positive enthalpy value. Equally, the positive value of the entropy shows that there is increased randomness at solid-liquid interphase during the sorption processes, hence enhancing the process.Table 5
Thermodynamic parameters at 100 mg/L initial Co(II) concentration.
Temperature (K)
∆G° (KJ/mol)
∆H° (KJ/mol)
∆S° (KJ/mol K)
298
−5.424
+0.275
+0.023
308
−5.505
313
−5.607
333
−6.068


## 3.3. Adsorption Isotherm

### 3.3.1. One-Parameter Isotherm

(1) Henry’s Isotherm. This model assumes that the amount of surface adsorbate is proportional to the partial pressure of the gas adsorbate. It also used to describe adsorption of adsorbate at very low concentrations such that all adsorbate molecules are secluded from their nearest neighbours [28]. From Table 6, this isotherm describes Co(II) adsorption DNL with correlation coefficients of unity for all tested initial concentrations. The Henry isotherm model also showed best fit against Langmuir-1, Langmuir-2, Langmuir-3, Langmuir-4, Freundlich, Temkin, and Dubinin–Radushkevich isotherms for the adsorption of malachite green with orange peels [51].Table 6
One-, two-, and three-isotherm parameters for the adsorption of Co(II) on DNL.
Isotherm/parameters
Tested concentrations
10 mg/L
100 mg/L
500 mg/L
One-parameter isotherm
Henry’s isotherms
K
HE
1.000
1.000
1.000
R
2
1.000
1.000
1.000
Two-parameter isotherms
Freundlich
K
F (mg/g)(L/mg)1/n
9.201
118.203
523.900
n
−5.112
−8.446
−35.088
R
2
0.9993
0.9992
0.9995
Jovanovic
q
max (mg/g)
10.171
100.655
500.196
K
J
0.120
0.011
0.002
R
2
1.000
1.000
1.000
Langmuir-1
q
m (mg/g)
6.988
80.000
476.190
b (L/mg)
3.756
0.893
2.625
R
L
0.026
0.011
0.001
R
2
0.9971
0.9967
0.9982
Langmuir-2
q
m (mg/g)
6.983
80.000
476.190
b (L/mg)
3.739
0.893
2.625
R
L
0.026
0.011
0.001
R
2
0.9999
1.000
1.000
Langmuir-3
q
m (mg/g)
6.990
79.95
472.700
b (L/mg)
3.757
0.896
2.618
R
L
0.026
0.011
0.001
R
2
0.9979
0.9974
0.9983
Langmuir-4
q
m (mg/g)
6.987
79.895
472.647
b (L/mg)
3.749
0.894
2.614
R
L
0.026
0.011
0.001
R
2
0.9979
0.9974
0.9983
Langmuir-5
q
m (mg/g)
6.986
79.927
472.571
b (L/mg)
3.746
0.893
2.614
R
L
0.026
0.011
0.001
R
2
0.9971
0.9967
0.9982
Temkin
A
T (L/mg)
0.004
2.026E−05
3.978E−17
b
T (kJ/mol)
−1.515
−0.234
−0.179
R
2
0.9995
0.9993
0.9996
Two-parameter isotherms
Elovich
q
m (mg/g)
1.368
9.470
13.459
K
E (L/mg)
0.008
7.072E−05
5.375E−16
R
2
0.9997
0.9995
0.9996
Dubinin–Radushkevich
X
m (mg/g)
7.388
84.041
479.048
K (mol2 kJ−2)
−0.0845
−1.1855
−0.4736
E (kJ/mol)
2.433
0.649
1.027
R
2
0.9965
0.9941
0.9964
Fowler–Guggenheim
K
FG (L/mg)
6.155E − 05
2.108E − 08
4.759E − 31
W (kJ/mol)
−16.182
−24.254
−90.163
R
2
0.9996
0.9995
0.9996
Kiselev
k
1 (L/mg)
25.186
11.652
172.78
k
n
1.331
1.191
1.044
R
2
0.9942
0.9933
0.9961
Hill–de Boer
K
1 (L/mg)
2.922E − 14
2.015E − 39
0
K
2 (kJ/mol)
−111.102
−269.609
−3328.866
R
2
0.9988
0.9978
0.998
Langmuir–Freundlich
K
G (mg/L)
0.268
1.139
0.740
N
b
0.995
1.011
1.367
R
2
0.9975
0.9966
0.9972
Harkin–Jura
A
−178.571
−33333.333
−5000000
B
2.07E + 00
2.00E + 00
2.00E + 01
R
2
0.9988
0.9988
0.9995
Halsey
K
H
84635.961
3.201E + 17
2.584E + 95
n
H
5.11247444
8.44594595
35.0877193
R
2
0.9993
0.9992
0.9995
Flory–Huggins
n
0.216
0.1184
0.0289
K
FH (L/mg)
0.057
0.007
0.002
R
2
0.9994
0.9992
0.9995
Three-parameter isotherm
Redlich–Peterson
K
R (Lg−1)
18
33
131
a
R (L/mg)
1.104
0.083
0.068
b
R
1.674
1.505
1.407
R
2
1.000
1.000
1.000


### 3.3.2. Two-Parameter Isotherms

(1) Freundlich Model. The Freundlich model describes multilayer removal process which takes place on the heterogeneous surface [29]. By definition, the adsorption intensity, n, is less than unity [35]. This model fits the adsorption of Co(II) on DNL with coefficient of correlations greater than 99% for the three initial concentrations with high values of KF (9.2, 118, and 523 (mg/g)(L/mg)1/n for 10, 100, and 500 mg/L) which are adsorption capacities (Table 6). This performance is due to the presence of heterogeneous groups on the DNL surface as evident from FTIR results (Figure 1) and confirmed by this isotherm model analysis. These groups are all good binding sites for Co(II). Similar to the results, Freundlich isotherm amongst many other applied isotherm models also best described lead (II) ions adsorption from aqueous solutions in the study that used coir dust and its modified extract resins as adsorbents [28].(2) Langmuir Model. The Langmuir model assumes uniform energies of adsorption onto the monolayer surface and no interaction of adsorbate on the surface [30]. Five linear forms can be obtained as shown in Table 5. The separation factor, RL, which is considered as a more reliable indicator of the adsorption is defined by the following equation: (7)RL=11+bC0,where b (L/mg) is the Langmuir constant and C0 (mg/L) is the initial concentration of the solute. For favourable adsorption, 0 < RL < 1, while RL > 1, RL = 1, and RL = 0, respectively, describe unfavorable, linear, and irreversible adsorption [9].The adsorption of Co(II) on DNL was linearized with five Langmuir models, and the calculated parameters are presented in Table6. All the five models fit the adsorption of Co(II) on DNL with same values of Langmuir equilibrium constant (b), RL and R2 > 99%. The high b and low RL values indicate a very favourable Co(II) adsorption on DNL. However, Langmuir-2 showed better fitting with highest correlation coefficient. The highest adsorption capacities were equally obtained for Langmuir-1 and Langmuir-2. According to [52] Langmuir-1 and Langmuir-2 are the most used Langmuir isotherm models because of the minimized deviations from the fitted equation resulting in the best error distribution. The fitness of Langmuir models also indicate that Co(II) adsorption on DNL occurred on a monolayer homogenous surface.(3) Jovanovic Model. The model is based on the same assumptions as in the Langmuir model, but predicts in addition the possibility of some mechanical contacts between the adsorbate and adsorbent [28]. The adsorption capacities obtained (10.171, 100.655, and 500.196 mg/g for 10, 100, and 500 mg/L) are higher than for the Langmuir model (Table 6). The R2 are all unity for the three Co(II) initial concentrations showing the adequacy of model in describing Co(II) adsorption on DNL. Jovanovic isotherms was also shown to generate a straight line curve that best fitted the sorption of Fe2+, Mg2+, and Zn2+ ions on the metallophthalocyanine film [53]. The decreasing values of Jovanovic constant (KJ) with increasing initial concentration (0.120 at 10 mg/L, 0.011 at 100 mg/L, and 0.002 at 500 mg/L) indicate that with increasing initial concentration there is very little contact time between Co(II) and DNL before adsorption. At higher initial concentrations, there is an important driving force due to the increased concentration necessary to overcome all mass transfer resistances of the pollutant between the aqueous and solid phases thus increasing the adsorption [50]. All surface coverage values were calculated using adsorption capacities from this model.(4) Temkin Model. Temkin model assumes that the heat of adsorption of the adsorbates in the layer decreases linearly rather than logarithmically with coverage due to adsorbent-adsorbate interactions and that adsorption is characterized by a uniform distribution of the binding energies, up to some maximum binding energy [31]. This model equally fits Co(II) adsorption on DNL with R2 values greater than 99%. Similarly, results were also obtained by other authors using miswak leaves to adsorb methylene blue [28]. The bT (adsorption energy (kJ/mol)) values −1.515, −0.234, and −0.179 KJ/mol (Table 6) show that physisorption was responsible for Co(II) adsorption on DNL [49].(5) Elovich Model. The Elovich model is based on the kinetic principle assuming that the adsorption sites increase exponentially with adsorption, which implies a multilayer adsorption [32]. Despite the fitness of this model for Co(II) adsorption on DNL from R2 values (Table 6), the calculated adsorption capacities were very low. This is probably due to the fact this model describes multilayer adsorption indicating migration from one layer to another. Elovich isotherm model has been reported also to describe the adsorption of Cu(II) on chitin compared to other tested models but with R2 of 0.808 [28].(6) Dubinin–Radushkevich (D-R) Model. It is an empirical generally applied to express adsorption mechanism with Gaussian energy distribution onto heterogeneous surfaces [28]. The significance of applying Dubinin–Radushkevich model is to determine apparent adsorption energy, E (kJ/mol) which is given by (8)E=12K,K is a constant related to the adsorption energy (mol2·kJ−2).If the value ofE is between 8 and 16 kJ/mol, ion exchange is the main sorption process in the system. If the value is lower than 8 kJ/mol, physical sorption is the main sorption mechanism, and if the value is greater than 16 kJ/mol, it may be chemisorption [49]. D-R represented a good fit for Co(II) adsorption on DNL (R2 > 99%) (Table 6), indicating the involvement of heterogeneous sites. All obtained adsorption energies were lower than 8 kJ/mol (Table 6) showing that the process was physical. These results are consistent with other studies on cobalt adsorption [54, 55].(7) Fowler–Guggenheim Model. This isotherm takes the lateral interaction of the adsorbed molecules into account [33]. The heat of adsorption increases linearly with loading. If the interaction between the adsorbed molecules is attractive (that is, W is positive), the heat of adsorption will increase with loading and this is due to the increased interaction between adsorbed molecules as the loading increases. This means that if the measured heat of adsorption shows an increase with respect to loading, it indicates the positive lateral interaction between adsorbed molecules. However, if the interaction among adsorbed molecules is repulsive (that is W is negative), the heat of adsorption shows a decrease with loading. When there is no interaction between adsorbed molecules (that is, W = 0), this Fowler–Guggenheim equation will reduce to the Langmuir equation. W is the interaction energy between adsorbed molecules (kJ·mol−1). From Table 6, it can be seen that this model describes Co(II) adsorption on DNL. The entire W values are negative, becoming more negative with increasing loading or increasing initial concentration indicating that the heat of adsorption shows a decrease with loading due to repulsive interaction among adsorbed molecules. Other authors [56] also reported that the Fowler–Guggenheim model best described Cr (VI), Mn(II), Fe(II), and Cu(II) on activated carbons from agricultural wastes but with positive W values. This difference may be due to reaction conditions as well as the composition of the different materials used.(8) Kiselev Model. The Kiselev adsorption isotherm equation also known as the localized monomolecular layer model [34] is only valid for surface coverage θ > 0.68 [28]. The lowest θ value obtained was 0.82 for this study at all the tested initial concentrations. This model also described Co(II) adsorption on DNL with R2 values greater than 99%. Values of k1 which represent equilibrium constant are very high for the three concentrations as well as kn values which represent constant of complex formation between adsorbed molecules, confirming the high adsorption of Co(II) on DNL. The study of [57] equally demonstrated the fitness of Kiselev adsorption isotherm for cadmium adsorption using novel water treatment residual nanoparticles with R2 > 99%.(9) Hill–de Boer Model. This model equation describes the case where there is mobile adsorption and lateral interaction among adsorbed molecules [35, 36]. A positive K2 means attraction between adsorbed species and a negative value means repulsion; that is, the apparent affinity is increased with loading when there is attraction between adsorbed species, and it is decreased with loading when there is repulsion among the adsorbed species. When there is no interaction between adsorbed molecules (that is, K2 = 0). From Table 6, all the K2 values are negative meaning Co(II) adsorption on DNL occurs by repulsive mechanism, confirming Fowler–Guggenheim model results and maximum Co(II) adsorption at pH 3. This was also the findings of other works [57, 58] using nanoparticles of water treatment residual and granular activated carbon.(10) Langmuir–Freundlich Model. This isotherm fuses both Langmuir and Freundlich isotherms together [37]. It offers a flexible analytical framework for modeling both Langmuir and Freundlich type sorption effects. The cooperative binding constant (Nb) obtained (0.995 at 10 mg/L, 1.011 at 100 mg/L, and 1.367 at 500 mg/L) indicate increase tendency of adsorption with increasing initial Co(II) concentration as many Co(II) ions are available to react with DNL surface groups (Table 6). Equally, there is increase in saturation constant (KG) with increasing initial Co(II) concentration indicating the ease of accumulation at the surface with increasing initial concentration due to rapid occupation of active sites permitting additional ions to accumulate on the surface. The fact that R2 for this model is high (>99%) (Table 6) confirms that adsorption of Co(II) on the DNL surface involves homogenous and heterogeneous sites.(11) Flory–Huggins Model. It describes the degree of surface coverage characteristics of the adsorbate on the adsorbent [28]. This isotherm model can express the feasibility and spontaneity of an adsorption process by applying ∆G = −RTlnKFH. From Table 6, all KFH are positive, indicating negative Gibbs free energy (∆G), hence spontaneity of the adsorption process stemming from high Co(II) occupancy of the DNL surface (surface coverage values calculated based on maximum adsorption capacity values from Jovanovic isotherm ranged from 85 to 92% for this study). Results of this model also reveal that the number of adsorbates occupying adsorption sites (n) decrease with increase Co(II) initial concentration. At higher initial concentration, there is a scramble by many ions for existing adsorption sites, whereas at lower initial concentration there is the availability of sites to fewer ions. This trend was also obtained in another study on the biosorption of zinc from aqueous solution using coconut coir dust [28].(12) Harkin–Jura. This model assumes the possibility of multilayer adsorption on the surface of absorbents having heterogeneous pore distribution [38]. Results of this model are shown in Table 6 with R2 values > 99% confirming the heteroporosity nature of the DNL surface and the possibility of multilayer adsorption of Co(II) on its surface. Similar findings were also reported by other authors [28] who showed in their study that the Harkin–Jura isotherm model had a better fit to the adsorption data than Freundlich, Halsey, and Temkin isotherm models in their investigation of the adsorptive removal of reactive black 5 from wastewater using bentonite clay, confirming the heteroporosity of the adsorbent. BET studies in this work showed that DNL contain micro-, meso-, and macropores.(13) Halsey. This model like Harkin–Jura is suitable for multilayer adsorption an adsorption on a heterogeneous surface. With R2 values > 99%, Halsey isotherm results also confirm the heterogeneous nature of the DNL surface and the possibility of multilayer adsorption of Co(II) on its surface. Some works [28] have also reported the good fit of experimental data to the Halsey isotherm model for adsorption of methyl orange on pinecone-derived activated carbon and pb2+ ion on coconut shell carbon. This good fit attest the heterogeneous distribution of activate sites and multilayer on tested adsorbents. The heterogeneous distribution of activate sites for DNL is indicated by the presence of different groups such as COO−, C=O, O-H, C–O, C–O–C, Si-O-Al, and Fe-O as shown by FTIR analysis (Figure 1).


### 3.3.3. Three-Parameter Isotherm

(1) Redlich–Peterson Model. This isotherm model is an empirical isotherm incorporating three parameters. It combines elements from both Langmuir and Freundlich equations, therefore represent adsorption equilibrium over a wide range of concentration of adsorbate which is applicable in either homogenous or heterogeneous systems [28]. The values of the calculated parameters for this three-parameter isotherm model (KR, Redlich–Peterson isotherm constant (Lg−1) used to obtain the maximum value of the correlation coefficient, aR = constant (L/mg) and bR = exponent that lies between 0 and 1) are shown in Table 6. R2 value of unity was obtained at KR of 18 Lg−1 for 10 mg/L, 33 Lg−1 for 100 mg/L, and 131 Lg−1 for 500 mg/L, indicating the ease of adsorption with increasing initial concentration. Redlich–Peterson approaches the Freundlich isotherm model as bR tends to zero and to Langmuir as bR is close to one [5]. However, the fact that all bR values were greater than 1 (Table 6) suggest that this model does not describe Co(II) adsorption on DNL.


## 3.3.1. One-Parameter Isotherm

(1) Henry’s Isotherm. This model assumes that the amount of surface adsorbate is proportional to the partial pressure of the gas adsorbate. It also used to describe adsorption of adsorbate at very low concentrations such that all adsorbate molecules are secluded from their nearest neighbours [28]. From Table 6, this isotherm describes Co(II) adsorption DNL with correlation coefficients of unity for all tested initial concentrations. The Henry isotherm model also showed best fit against Langmuir-1, Langmuir-2, Langmuir-3, Langmuir-4, Freundlich, Temkin, and Dubinin–Radushkevich isotherms for the adsorption of malachite green with orange peels [51].Table 6
One-, two-, and three-isotherm parameters for the adsorption of Co(II) on DNL.
Isotherm/parameters
Tested concentrations
10 mg/L
100 mg/L
500 mg/L
One-parameter isotherm
Henry’s isotherms
K
HE
1.000
1.000
1.000
R
2
1.000
1.000
1.000
Two-parameter isotherms
Freundlich
K
F (mg/g)(L/mg)1/n
9.201
118.203
523.900
n
−5.112
−8.446
−35.088
R
2
0.9993
0.9992
0.9995
Jovanovic
q
max (mg/g)
10.171
100.655
500.196
K
J
0.120
0.011
0.002
R
2
1.000
1.000
1.000
Langmuir-1
q
m (mg/g)
6.988
80.000
476.190
b (L/mg)
3.756
0.893
2.625
R
L
0.026
0.011
0.001
R
2
0.9971
0.9967
0.9982
Langmuir-2
q
m (mg/g)
6.983
80.000
476.190
b (L/mg)
3.739
0.893
2.625
R
L
0.026
0.011
0.001
R
2
0.9999
1.000
1.000
Langmuir-3
q
m (mg/g)
6.990
79.95
472.700
b (L/mg)
3.757
0.896
2.618
R
L
0.026
0.011
0.001
R
2
0.9979
0.9974
0.9983
Langmuir-4
q
m (mg/g)
6.987
79.895
472.647
b (L/mg)
3.749
0.894
2.614
R
L
0.026
0.011
0.001
R
2
0.9979
0.9974
0.9983
Langmuir-5
q
m (mg/g)
6.986
79.927
472.571
b (L/mg)
3.746
0.893
2.614
R
L
0.026
0.011
0.001
R
2
0.9971
0.9967
0.9982
Temkin
A
T (L/mg)
0.004
2.026E−05
3.978E−17
b
T (kJ/mol)
−1.515
−0.234
−0.179
R
2
0.9995
0.9993
0.9996
Two-parameter isotherms
Elovich
q
m (mg/g)
1.368
9.470
13.459
K
E (L/mg)
0.008
7.072E−05
5.375E−16
R
2
0.9997
0.9995
0.9996
Dubinin–Radushkevich
X
m (mg/g)
7.388
84.041
479.048
K (mol2 kJ−2)
−0.0845
−1.1855
−0.4736
E (kJ/mol)
2.433
0.649
1.027
R
2
0.9965
0.9941
0.9964
Fowler–Guggenheim
K
FG (L/mg)
6.155E − 05
2.108E − 08
4.759E − 31
W (kJ/mol)
−16.182
−24.254
−90.163
R
2
0.9996
0.9995
0.9996
Kiselev
k
1 (L/mg)
25.186
11.652
172.78
k
n
1.331
1.191
1.044
R
2
0.9942
0.9933
0.9961
Hill–de Boer
K
1 (L/mg)
2.922E − 14
2.015E − 39
0
K
2 (kJ/mol)
−111.102
−269.609
−3328.866
R
2
0.9988
0.9978
0.998
Langmuir–Freundlich
K
G (mg/L)
0.268
1.139
0.740
N
b
0.995
1.011
1.367
R
2
0.9975
0.9966
0.9972
Harkin–Jura
A
−178.571
−33333.333
−5000000
B
2.07E + 00
2.00E + 00
2.00E + 01
R
2
0.9988
0.9988
0.9995
Halsey
K
H
84635.961
3.201E + 17
2.584E + 95
n
H
5.11247444
8.44594595
35.0877193
R
2
0.9993
0.9992
0.9995
Flory–Huggins
n
0.216
0.1184
0.0289
K
FH (L/mg)
0.057
0.007
0.002
R
2
0.9994
0.9992
0.9995
Three-parameter isotherm
Redlich–Peterson
K
R (Lg−1)
18
33
131
a
R (L/mg)
1.104
0.083
0.068
b
R
1.674
1.505
1.407
R
2
1.000
1.000
1.000


## 3.3.2. Two-Parameter Isotherms

(1) Freundlich Model. The Freundlich model describes multilayer removal process which takes place on the heterogeneous surface [29]. By definition, the adsorption intensity, n, is less than unity [35]. This model fits the adsorption of Co(II) on DNL with coefficient of correlations greater than 99% for the three initial concentrations with high values of KF (9.2, 118, and 523 (mg/g)(L/mg)1/n for 10, 100, and 500 mg/L) which are adsorption capacities (Table 6). This performance is due to the presence of heterogeneous groups on the DNL surface as evident from FTIR results (Figure 1) and confirmed by this isotherm model analysis. These groups are all good binding sites for Co(II). Similar to the results, Freundlich isotherm amongst many other applied isotherm models also best described lead (II) ions adsorption from aqueous solutions in the study that used coir dust and its modified extract resins as adsorbents [28].(2) Langmuir Model. The Langmuir model assumes uniform energies of adsorption onto the monolayer surface and no interaction of adsorbate on the surface [30]. Five linear forms can be obtained as shown in Table 5. The separation factor, RL, which is considered as a more reliable indicator of the adsorption is defined by the following equation: (7)RL=11+bC0,where b (L/mg) is the Langmuir constant and C0 (mg/L) is the initial concentration of the solute. For favourable adsorption, 0 < RL < 1, while RL > 1, RL = 1, and RL = 0, respectively, describe unfavorable, linear, and irreversible adsorption [9].The adsorption of Co(II) on DNL was linearized with five Langmuir models, and the calculated parameters are presented in Table6. All the five models fit the adsorption of Co(II) on DNL with same values of Langmuir equilibrium constant (b), RL and R2 > 99%. The high b and low RL values indicate a very favourable Co(II) adsorption on DNL. However, Langmuir-2 showed better fitting with highest correlation coefficient. The highest adsorption capacities were equally obtained for Langmuir-1 and Langmuir-2. According to [52] Langmuir-1 and Langmuir-2 are the most used Langmuir isotherm models because of the minimized deviations from the fitted equation resulting in the best error distribution. The fitness of Langmuir models also indicate that Co(II) adsorption on DNL occurred on a monolayer homogenous surface.(3) Jovanovic Model. The model is based on the same assumptions as in the Langmuir model, but predicts in addition the possibility of some mechanical contacts between the adsorbate and adsorbent [28]. The adsorption capacities obtained (10.171, 100.655, and 500.196 mg/g for 10, 100, and 500 mg/L) are higher than for the Langmuir model (Table 6). The R2 are all unity for the three Co(II) initial concentrations showing the adequacy of model in describing Co(II) adsorption on DNL. Jovanovic isotherms was also shown to generate a straight line curve that best fitted the sorption of Fe2+, Mg2+, and Zn2+ ions on the metallophthalocyanine film [53]. The decreasing values of Jovanovic constant (KJ) with increasing initial concentration (0.120 at 10 mg/L, 0.011 at 100 mg/L, and 0.002 at 500 mg/L) indicate that with increasing initial concentration there is very little contact time between Co(II) and DNL before adsorption. At higher initial concentrations, there is an important driving force due to the increased concentration necessary to overcome all mass transfer resistances of the pollutant between the aqueous and solid phases thus increasing the adsorption [50]. All surface coverage values were calculated using adsorption capacities from this model.(4) Temkin Model. Temkin model assumes that the heat of adsorption of the adsorbates in the layer decreases linearly rather than logarithmically with coverage due to adsorbent-adsorbate interactions and that adsorption is characterized by a uniform distribution of the binding energies, up to some maximum binding energy [31]. This model equally fits Co(II) adsorption on DNL with R2 values greater than 99%. Similarly, results were also obtained by other authors using miswak leaves to adsorb methylene blue [28]. The bT (adsorption energy (kJ/mol)) values −1.515, −0.234, and −0.179 KJ/mol (Table 6) show that physisorption was responsible for Co(II) adsorption on DNL [49].(5) Elovich Model. The Elovich model is based on the kinetic principle assuming that the adsorption sites increase exponentially with adsorption, which implies a multilayer adsorption [32]. Despite the fitness of this model for Co(II) adsorption on DNL from R2 values (Table 6), the calculated adsorption capacities were very low. This is probably due to the fact this model describes multilayer adsorption indicating migration from one layer to another. Elovich isotherm model has been reported also to describe the adsorption of Cu(II) on chitin compared to other tested models but with R2 of 0.808 [28].(6) Dubinin–Radushkevich (D-R) Model. It is an empirical generally applied to express adsorption mechanism with Gaussian energy distribution onto heterogeneous surfaces [28]. The significance of applying Dubinin–Radushkevich model is to determine apparent adsorption energy, E (kJ/mol) which is given by (8)E=12K,K is a constant related to the adsorption energy (mol2·kJ−2).If the value ofE is between 8 and 16 kJ/mol, ion exchange is the main sorption process in the system. If the value is lower than 8 kJ/mol, physical sorption is the main sorption mechanism, and if the value is greater than 16 kJ/mol, it may be chemisorption [49]. D-R represented a good fit for Co(II) adsorption on DNL (R2 > 99%) (Table 6), indicating the involvement of heterogeneous sites. All obtained adsorption energies were lower than 8 kJ/mol (Table 6) showing that the process was physical. These results are consistent with other studies on cobalt adsorption [54, 55].(7) Fowler–Guggenheim Model. This isotherm takes the lateral interaction of the adsorbed molecules into account [33]. The heat of adsorption increases linearly with loading. If the interaction between the adsorbed molecules is attractive (that is, W is positive), the heat of adsorption will increase with loading and this is due to the increased interaction between adsorbed molecules as the loading increases. This means that if the measured heat of adsorption shows an increase with respect to loading, it indicates the positive lateral interaction between adsorbed molecules. However, if the interaction among adsorbed molecules is repulsive (that is W is negative), the heat of adsorption shows a decrease with loading. When there is no interaction between adsorbed molecules (that is, W = 0), this Fowler–Guggenheim equation will reduce to the Langmuir equation. W is the interaction energy between adsorbed molecules (kJ·mol−1). From Table 6, it can be seen that this model describes Co(II) adsorption on DNL. The entire W values are negative, becoming more negative with increasing loading or increasing initial concentration indicating that the heat of adsorption shows a decrease with loading due to repulsive interaction among adsorbed molecules. Other authors [56] also reported that the Fowler–Guggenheim model best described Cr (VI), Mn(II), Fe(II), and Cu(II) on activated carbons from agricultural wastes but with positive W values. This difference may be due to reaction conditions as well as the composition of the different materials used.(8) Kiselev Model. The Kiselev adsorption isotherm equation also known as the localized monomolecular layer model [34] is only valid for surface coverage θ > 0.68 [28]. The lowest θ value obtained was 0.82 for this study at all the tested initial concentrations. This model also described Co(II) adsorption on DNL with R2 values greater than 99%. Values of k1 which represent equilibrium constant are very high for the three concentrations as well as kn values which represent constant of complex formation between adsorbed molecules, confirming the high adsorption of Co(II) on DNL. The study of [57] equally demonstrated the fitness of Kiselev adsorption isotherm for cadmium adsorption using novel water treatment residual nanoparticles with R2 > 99%.(9) Hill–de Boer Model. This model equation describes the case where there is mobile adsorption and lateral interaction among adsorbed molecules [35, 36]. A positive K2 means attraction between adsorbed species and a negative value means repulsion; that is, the apparent affinity is increased with loading when there is attraction between adsorbed species, and it is decreased with loading when there is repulsion among the adsorbed species. When there is no interaction between adsorbed molecules (that is, K2 = 0). From Table 6, all the K2 values are negative meaning Co(II) adsorption on DNL occurs by repulsive mechanism, confirming Fowler–Guggenheim model results and maximum Co(II) adsorption at pH 3. This was also the findings of other works [57, 58] using nanoparticles of water treatment residual and granular activated carbon.(10) Langmuir–Freundlich Model. This isotherm fuses both Langmuir and Freundlich isotherms together [37]. It offers a flexible analytical framework for modeling both Langmuir and Freundlich type sorption effects. The cooperative binding constant (Nb) obtained (0.995 at 10 mg/L, 1.011 at 100 mg/L, and 1.367 at 500 mg/L) indicate increase tendency of adsorption with increasing initial Co(II) concentration as many Co(II) ions are available to react with DNL surface groups (Table 6). Equally, there is increase in saturation constant (KG) with increasing initial Co(II) concentration indicating the ease of accumulation at the surface with increasing initial concentration due to rapid occupation of active sites permitting additional ions to accumulate on the surface. The fact that R2 for this model is high (>99%) (Table 6) confirms that adsorption of Co(II) on the DNL surface involves homogenous and heterogeneous sites.(11) Flory–Huggins Model. It describes the degree of surface coverage characteristics of the adsorbate on the adsorbent [28]. This isotherm model can express the feasibility and spontaneity of an adsorption process by applying ∆G = −RTlnKFH. From Table 6, all KFH are positive, indicating negative Gibbs free energy (∆G), hence spontaneity of the adsorption process stemming from high Co(II) occupancy of the DNL surface (surface coverage values calculated based on maximum adsorption capacity values from Jovanovic isotherm ranged from 85 to 92% for this study). Results of this model also reveal that the number of adsorbates occupying adsorption sites (n) decrease with increase Co(II) initial concentration. At higher initial concentration, there is a scramble by many ions for existing adsorption sites, whereas at lower initial concentration there is the availability of sites to fewer ions. This trend was also obtained in another study on the biosorption of zinc from aqueous solution using coconut coir dust [28].(12) Harkin–Jura. This model assumes the possibility of multilayer adsorption on the surface of absorbents having heterogeneous pore distribution [38]. Results of this model are shown in Table 6 with R2 values > 99% confirming the heteroporosity nature of the DNL surface and the possibility of multilayer adsorption of Co(II) on its surface. Similar findings were also reported by other authors [28] who showed in their study that the Harkin–Jura isotherm model had a better fit to the adsorption data than Freundlich, Halsey, and Temkin isotherm models in their investigation of the adsorptive removal of reactive black 5 from wastewater using bentonite clay, confirming the heteroporosity of the adsorbent. BET studies in this work showed that DNL contain micro-, meso-, and macropores.(13) Halsey. This model like Harkin–Jura is suitable for multilayer adsorption an adsorption on a heterogeneous surface. With R2 values > 99%, Halsey isotherm results also confirm the heterogeneous nature of the DNL surface and the possibility of multilayer adsorption of Co(II) on its surface. Some works [28] have also reported the good fit of experimental data to the Halsey isotherm model for adsorption of methyl orange on pinecone-derived activated carbon and pb2+ ion on coconut shell carbon. This good fit attest the heterogeneous distribution of activate sites and multilayer on tested adsorbents. The heterogeneous distribution of activate sites for DNL is indicated by the presence of different groups such as COO−, C=O, O-H, C–O, C–O–C, Si-O-Al, and Fe-O as shown by FTIR analysis (Figure 1).


## 3.3.3. Three-Parameter Isotherm

(1) Redlich–Peterson Model. This isotherm model is an empirical isotherm incorporating three parameters. It combines elements from both Langmuir and Freundlich equations, therefore represent adsorption equilibrium over a wide range of concentration of adsorbate which is applicable in either homogenous or heterogeneous systems [28]. The values of the calculated parameters for this three-parameter isotherm model (KR, Redlich–Peterson isotherm constant (Lg−1) used to obtain the maximum value of the correlation coefficient, aR = constant (L/mg) and bR = exponent that lies between 0 and 1) are shown in Table 6. R2 value of unity was obtained at KR of 18 Lg−1 for 10 mg/L, 33 Lg−1 for 100 mg/L, and 131 Lg−1 for 500 mg/L, indicating the ease of adsorption with increasing initial concentration. Redlich–Peterson approaches the Freundlich isotherm model as bR tends to zero and to Langmuir as bR is close to one [5]. However, the fact that all bR values were greater than 1 (Table 6) suggest that this model does not describe Co(II) adsorption on DNL.


## 4. Conclusion

The adsorption of Co(II) from aqueous solution using neem leaves as a bioadsorbent, an abundantly available waste material was investigated. The determined properties of the biosorbent showed that it has many and varied functional groups on its surface although it possessed low porosity characteristics. Co(II) adsorption on DNL is favourable at acidic pH as it easily precipitates at basic pH. Co(II) adsorption equally demonstrated marginal dependence on temperature. An equilibrium time of 10 minutes was obtained for each of the tested three initial concentrations with the lowest removal efficiency of about 85% for 10 mg/L, 89.56% for 100 mg/L, and 97.13% for 500 mg/L. Pseudosecond-order kinetic model best suited the process. All the tested one- and two-parameter isotherm models described Co(II) adsorption on dead neem leaves variably. Equally, all the tested two-parameter isotherms revealed the homogenous, heterogeneous, and multilayer adsorption on DNL. This was however not the case with Redlich–Peterson isotherm, a three-parameter model. Its greater local availability and hence low cost means it will provide a comparable adsorption capacity per unit cost as it is efficient compared to other tested materials for Co(II) removal (Table7; [54, 55, 59–65]). It was thus concluded that neem leaves can be a suitable, local, and low-cost alternative for elimination of cobalt(II) ions from aqueous solutions.Table 7
Comparison of adsorption capacity of DNL and equilibrium reaction time with other adsorbents for Co(II) adsorption.
Adsorbent
q
m (mg/g)
Equilibrium time (min)
Reference
Lignocellulose/montmorillonite (LMT) nanocomposite
93.43
60
[59]
Activated disordered mesoporous carbons
90%
15
[54]
Untreated peat moss
30.03
60
[60]
Peat moss treated with HNO3
21.51
100
Peat moss treated with NaOH
35.21
15
Thespesia populnea bark activated carbon
26.09
60
[55]
Carbon gel without doping
2.8927
180
[61]
Carbon gel doped with graphite
7.97
Apricot stone activated carbon
111.11
90
[62]
South African coal fly ash
0.40
240
[63]
Magnetic chitosan
27.5
1
[64]
Saudi roasted date pits
6.28
40
[65]
Neem leaves
523
10
This study



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*Source: 6452672-2019-11-27.xml*