optimization of process parameters and dissolution kinetics of nickel and cobalt from lateritic...

Research ArticleReceived: 22 August 2013 Revised: 19 November 2013 Accepted article published: 10 December 2013 Published online in Wiley Online Library:

(wileyonlinelibrary.com) DOI 10.1002/jctb.4288

Optimization of process parametersand dissolution kinetics of nickel and cobaltfrom lateritic chromite overburden usingorganic acidsSupratim Biswas,a∗ Suparna Chakraborty,b Mahua Ghosh Chaudhuri,b

Pataki C Banerjee,b Siddhartha Mukherjeea and Rajib Deya

Abstract

BACKGROUND: Leaching kinetics of the roasted (at 600◦C) chromite overburden of Sukinda mines Orissa, India, was studiedwith optimized data generated through response surface methodology (RSM) coupled with Box-Behnken design (BBD). Theeffects of oxalic, citric and gluconic acid concentration (50–150 mmol L−1), reaction temperature (60◦ to 80◦C) and period (upto 3 h) on metal (nickel and cobalt) dissolution were examined.

RESULTS: Extraction of nickel and cobalt to the extent of 63.61% and 44.33%, respectively, was achieved using 150 mmol L−1

oxalic acid at 80◦C in 3 h; compared with other acids, oxalic acid leached more of the metals. Associated apparent activationenergy for Ni was 74 kJ mol−1, and that for cobalt was 84.37 kJ mol−1 during the first hour, and 80.99 kJ mol−1 for the remainingperiod since cobalt leaching followed biphasic kinetics.

CONCLUSION: Dissolution of nickel and cobalt from the roasted chromite overburden was highly dependent on the amenabilityof ore minerals to organic acid attack. Nickel leaching data fit the three-dimensional diffusion mechanism of the type GinstlingBrounsthein (GB) equation while a mixed kinetic model consisting of spherical geometry and the GB equation was followedfor cobalt. This work presents maximum recovery of nickel and cobalt from chromite overburden using organic acid reportedto date.c© 2013 Society of Chemical Industry

Supporting information may be found in the online version of this article.

Keywords: leaching kinetics; response surface methodology; optimization; organic acid

INTRODUCTIONContinuous depletion of high grade ore deposits and theever increasing demand for strategic metals have compelledmetallurgists to find other sources of metals and the avenuesto retrieve them from these sources. There is no primary sourceof either nickel or cobalt in India.1 Some quantities of thesemetals are obtained as by-products of copper production but themajor amount is imported to meet domestic demand. A promisingsource of these metals could be the lateritic chromite overburdenof Sukinda, Orissa, India, which contains 0.4–0.9% nickel and0.02–0.05% cobalt.2–4 Owing to the complex mineralogy ofthis overburden, extraction of metal from this source is achallenging task. In terms of the valuable metals content, thechromite overburden is the major reserve – more preciselythe sole source of nickel in India.2,3 Nickel-containing ores aregenerally of two types: (i) sulphidic and (ii) lateritic (oxidic). Thesulphidic types are utilized industrially for extraction of nickelthroughout the globe mostly by a pyrometallurgical route, butthe lateritic types are hardly utilized because of their complexmineralogy, and hence remain as unutilized waste. In laterite ores,

nickel is associated with the goethite phase, a highly crystallinehydrated iron oxide, which makes it very cost intensive torecover nickel employing conventional metallurgical techniques.Industrially, standard grade nickeliferous laterites are processedby the following techniques: high pressure acid leaching, Caronprocess and (ferronickel and nickel) smelting; usually, these aresmelted with high slag volume causing high energy consumption

and operational costs.5–7

As an alternative, biohydrometallurgical processes may beconsidered, which address both economic and environmentalrestrictions. Leaching of such ores with heterotrophic fungi

∗ Correspondence to: Supratim Biswas, Department of Metallurgical and MaterialEngineering, Jadavpur University, Kolkata-700032 India.E-mail: [email protected]

a Department of Metallurgical and Material Engineering, Jadavpur University,Kolkata 700032, India

b School of Materials Science and Nanotechnology, Jadavpur University, Kolkata700032, India

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www.soci.org S Biswas et al.

involves participation of fungal metabolic acids.8,9 In recenttimes, substantial achievements have been made in the fieldof metal extraction from low-grade non-sulphidic ores usingdifferent fungal species having the potential to produce organicacids (which are good chelating agents) facilitating complexationof metals.10,11 However, commercial application involvingbiohydrometallurgical processing has been less successful withlimonite ores characterized by high iron content in the formof goethite (FeO.OH); a number of studies involving dissolutionkinetics of iron oxides (viz. hematite, goethite) by organic acids

have been conducted by several groups.12–14 Among the organicacids used, oxalic, citric and gluconic are the most effective becausethese are solvent reagents.14,15 In the present case, the dissolutionbehaviour of nickel and cobalt from lateritic chromite overburdenof Sukinda mines using synthetic organic acids (independentof microorganisms) was studied. Dissolution behavior of thedifferent metals from the lateritic ore is dependent on severalfactors such as type and concentrations of organic acid, leachingtemperature, and time. Hence prior to kinetic study with the ore,it is always required to optimize these influencing parametersso that the best recovery can be achieved. In the presentstudy, design and optimization of these process parametersfollowed by kinetic study was carried out using response surfacemethodology (RSM) to understand the dissolution behavior ofNi and Co.

Response surface methodology (RSM) is a modern, widelyaccepted method of statistical analysis with advantages overtraditional factorial methods. It is a powerful mathematicaland effective statistical technique for designing experiments,building models and analyzing the effect of multiple variablesalone or in combination. Rapid optimization of processes witha minimal number of experiments for a multivariable systemhas been successfully done using RSM, unlike one-factor at atime (OFAT) methods or orthogonal experimental analysis (OEA).The present study was undertaken to investigate the kineticsof metal recovery from the roasted chromite overburden underoptimal conditions.16,17 Leaching parameters such as temperature,various fungal metabolic acids (citric, gluconic and oxalic), andtheir concentrations (50, 100 and 150 mmol L−1) along with theduration of leaching were investigated. Since initial experimentsshowed better recovery of metals from the roasted (at 600◦C)overburden,2,3 the present study was carried out with roastedsamples. After identifying the most efficient organic acid forleaching both nickel and cobalt from the overburden, the effectiveparameters were screened using a BBD two-level factorial designand then optimization of the significant parameters was carriedout using RSM to maximize metal recovery from the overburdenby organic acid. The independent variables selected were: (i)concentration of organic acid (A), (ii) temperature of leaching (B)and (iii) duration of leaching (C).

EXPERIMENTALMaterialsThe chromite overburden was collected from a major mining site,the Kaliapani open cast mines of Orissa Mining Corporation atSukinda Valley, Orissa, India. The highly weathered overburden isrich in oxides of iron and contains minor amounts of chromium,nickel and cobalt. Approximately 5 kg of the ore sample wassubjected to jaw crushing followed by roll crushing. The crushedore was subjected to sieve analysis and a size range of –75 + 53µm was taken for further work. A portion of the ore sample was

placed in an alumina boat, and treated at 600◦C in a horizontaltube furnace for 5 h for oxidation roasting; the method wasstandardized on the basis of DT-TGA analysis. Organics acids andother chemicals used in this study were of analytical grade andobtained from E. Merck, India.

Characterization of the Chromite overburdenMorphological and phase analysis of the roasted and leachedore residues were carried out using a field emission scanningmicroscope (FESEM- Hitachi model no. S4800) and X-ray powerdiffractometer (XRD-Rigaku Ultima-III X-ray diffractometer) withBragg–Brentano geometry and Cu-kα radiation (λ = 0.154 nm).The samples were scanned at a rate of 2◦ min−1 from 10 to 80◦.

Chemical analysis of the roasted chromite overburdenChemical analysis of the raw and roasted ore was done followinga conventional chemical digestion method as described in aprevious publication2 (see section S1of Supplementary Materials).

Leaching of chromite overburden using organic acidsLeaching experiments using organic acids were carried out intriplicate using analytical grade citric, oxalic and gluconic acids.Acid concentrations of 50–150 mmol L−1 were prepared withdeionized water. Each experiment was carried out in a 250 mLErlenmeyer flask with 100 mL acid solution and ore (2% pulpdensity) at constant temperature in a closed water bath underconstant stirring conditions at temperatures 60, 70, and 80◦C.All leaching experiments were carried out for a period of 3 h atatmospheric pressure.

Statistical approachIt is always important to understand the influence of processparameters on the response factor. In general, it demands a set ofexperiments whose number increases rapidly with increase in thenumber of process parameters. Box–Behnken design (BBD) is avery useful tool to reduce the total number of experiments withoutloss of generality as it can provide a second-order polynomialmodel as a function of the independent process parameters withthe minimum number of experimental runs. The optimizationmethod consists of the following steps: executing the statisticallydesigned experiments, evaluating the regression coefficients ina mathematical model, predicting the response, optimizing theinfluencing factors, and validating and confirming the model. Thenumber of experiments (N) necessary for the development of BBDis defined as

N = 2k (k–1) + C0

where k is the number of factors and C0 is the number of centralpoints.

In this study the experimental design consisted of 17 trialsand the value of the dependent response was the mean ofthree replicates. The BBD was performed with three chosen,independent variables at three levels coded as −1 (low), 0 (centralpoint), and 1 (high) as shown in Table 1. The relationship betweenthe response and the independent variables can be fitted by asecond-order quadratic polynomial equation:

Y (response) = X + a1A + a2B + a3C + a4AB + a5BC

+ a6AC + a7A2 + a8B2 + a9C2

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Table 1. Range and coded parameter levels of experimental variables used to leach chromite overburden for Box–Behnken design

Lower Higher −1 0 +1

1 Concentration of organic acid mmol L –1 A 50 150 50 100 150

2 Temperature of leaching ◦C B 60 80 60 70 80

3 Duration of leaching Min C 20 180 20 100 180

where Y represents the response (% metal recovery), X is a constant,ai (i = 1 to 9) are the coefficients for linear and quadratic interactioneffects, respectively, and A, B and C are the chosen independentvariables. According to statistical theory, the three-factor (k = 3)three-level, and five central points (C0 = 5) BBD needs 17 sets ofexperiments (N = 17). The software Design-Expert (version 8.0.7.1,)was applied to design and analyze the experiments. The analysisof variance (ANOVA) was employed to determine the statisticalsignificance and competency of the model. Using Design-Expert8.0.7.1 the relationship between the responses and the levelsof each variable could be allegorized actively by expressing thefitted polynomial equation in the form of a three-dimensional (3D)surface plot.

Study of reaction kineticsTo study the reaction kinetics, another set of experimentswas conducted with optimized (determined statistically)parameters (which were the organic acid type, concentrationof acid and duration of leaching), where maximum metalrecovery was attained. The procedure followed was similarto that mentioned above; from separate 250 mL Erlenmeyerflasks, samples were withdrawn at intervals of 20 min to 3 h.The isothermal models tested in this study are presented inEquations (1)–(12).18

α2 = kt Parabolic (D1) (1)

α + (1–α) ln (1–α) = kt Valensi Barrer (D2) (2)

1–2/3 α– (1–α)2/3 = kt Ginstling Brounsthein (D3) (3)

[1– (1–α)1/3]2 = kt Jander (D4) (4)

[(1 + α)1/3 –1

]2 = kt Anti Jander (D5) (5)

[(1–α)1/3 –1

]2 = kt Zhuralevet al. (D6) (6)

α = kt Linear Growth (CG1) (7)

[1– (1–α)1/2] = kt Cylindrical (CG2) (8)

[1– (1–α)1/3] = kt Spherical (CG3) (9)

[– ln (1–α)

] = kt First − order Chemical Reaction (R1) (10)

[(1–α)−1/2 –1

] = kt One&Half − order Chemical Reaction (R2)

(11)[(1–α)−1 –1

] = kt Second − order Chemical Reaction (R3)

(12)In the above equations D, CG and R stand for diffusion, con-

tracting geometry and chemical reaction controlled mechanism,respectively. The equations represent the different mechanismsof the kinetics of reaction at the solid–liquid interface. In order to

identify the mechanism(s) of leaching, reduced time analysis wascarried out. For a particular mechanism,

g (α) = kt (I)

α is the fractional conversion ranging from 0 to 1, where g (α) isthe functional form representing a reaction mechanism, t is thetime, k is the rate constant.

For say α = 0.4g (α0.4) = kt0.4 (II)

t0.4 is the time required for 0.4 fraction of conversion. Dividing (I)by (II), we get

g (α) /g (α0.4) = t/t0.4 = θ ′ (III)

where θ ′ is the reduced time a dimensionless quantity. Reactionrate constant k is a function of mechanism and temperature.

Analytical determinationsAll leached liquors were analyzed by an atomic absorptionspectrophotometer (AAS) (Perkin Elmer, Aanalyst 200) in air-acetylene flame (see section S2 of Supplementary Materials).

RESULTS AND DISCUSSIONCharacterization of the chromite overburdenThe chemical analysis of the raw chromite overburden and itsroasted derivative is presented in Table 2, which shows elevationof metal percentage after roasting of the ore at 600◦C due tothe loss of moisture and other volatile fractions upon oxidativeroasting. The temperature for oxidation roasting was selected onthe basis of the TG-DTA analysis of the raw chromite overburdenreported in our previous work.3 It shows that the effect of oxidationroasting (at 600◦C) of the raw ore at atmospheric pressure ismarked by the transformation of goethite to hematite, which isdue to dehydroxylation at temperatures 292.38 and 355◦C dueto release of absorbed water. Similar observations were madeby Swamy et al. and Schwertmann et al.6,19 It is also evidentthat some structural changes occurred due to the followingreaction:

2FeO.OH → Fe2O3 + H2O

The samples (roasted ore and the roasted ore residues treatedwith different acids at different temperatures) were analyzed byX-ray diffractometer to understand how the change in mineralogyaffects metal leaching. The XRD study confirms non-existenceof separate nickel bearing mineral phase in the raw chromiteoverburden. The presence of both chromite and quartz wasobserved in roasted samples. XRD analysis of the residues ofroasted chromite overburden leached with either of the threedifferent organic acids, shows loss as well as reduction in therelative intensity of hematite peaks indicating efficient leachingof nickel (Fig. 1(a)); the XRD results also suggest better leaching

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Table 2. Percentage of major metallic elements present in chromite overburden

Percentage of different metals

Type of chromite overburden Ni Co Fe Cr Mn Al Mg LOI

Raw sample* 0.87 0.03 48.88 1.88 0.37 2.72 0.68 9.45

Roasted sample 0.97 0.04 51.79 1.9 0.61 6.22 1.54 —

(a)

(b)

Figure 1. (a). X-ray diffraction pattern of roasted chromite overburdenresidues leached with different organic acids. (b). X-ray diffraction patternof roasted chromite overburden residues leached with 150 mmol L–1 oxalicacid as a function of temperature.

of metal values (nickel and cobalt) with oxalic acid than citric andgluconic acid (Fig. 1(a)). From Fig. 1(b), it is evident that maximumloss of hematite peaks occurred in experiments carried out at 80◦Cthus making it a more effective leaching temperature than theother two temperatures (60 and 70◦).6,7,20

Figure 2 shows FESEM images of organic acid leached residuesof roasted chromite overburden. The micrographs of the leachedroasted ore residues show a decrease in particle size andan increase in roughness and erosion along with decrease inagglomeration thus accounting for deformation of microstructuredue to acid attack; the changes were in decreasing order fromFig. 2(a) to 2(c). The FESEM images in Fig. 2 suggest that oxalic acid

is the most efficient in recovering metal among the three organicacids used, in agreement with the AAS data.21,22

Effect of type and concentration of acid on metal leachingPrevious studies have shown that various organic acids producedby fungi exhibit differences in respect of effectiveness in dissolvingmetals from laterite minerals.10,11,15,16 This study was initiated totest the efficiency of metal recovery (Ni and Co) from chromiteoverburden with solutions of oxalic, citric and gluconic acid in 3h. It is evident from the results that increasing acid concentration(Fig. 3(a) and 3(b)) and leaching period (Fig. 4(a) and 4(b)) had apositive effect on the recovery of both nickel and cobalt; the oxalicacid solution extracted both metals most efficiently, followed bygluconic acid in the case of nickel, and citric acid in the caseof cobalt. The highest rate of both nickel and cobalt leachingwas achieved during the first 3 h, beyond which no significantextraction was achieved. Hence all onward experiments wereconducted for 3 h. The results showed that metals recoveryincreased with increase in acid concentration, and was mostefficient with 150 mmol L−1, the highest concentration used in thisstudy, for all three types of organic acid used. At this concentration,63.61%, 15.33% and 20.18% of nickel was leached by oxalic, citricand gluconic acid, respectively; while in the case of cobalt, therespective recoveries were 44.33%, 19.79% and 17.1% (Table S-5in Supplementary Materials shows recovery of metals as a functionof organic acids and corresponding concentrations).

Effect of temperature on metal leachingIn order to study the extraction of metals at different temperatures,experiments were conducted at 60, 70 and 80◦C with oxalic acid(150 mmol L−1) for 3 h, yielding 35.28, 48.55 and 63.4% nickel,respectively, with respective values for Co of 25.89, 27.57 and44.33%. Evaluation of the nature of heterogeneous reactions of thistype can be obtained by estimating the temperature dependenceof the leaching rates. The results presented in Fig. 4(a) and 4(b)show that leaching rates are influenced by temperature, i.e. therate of reaction increased with increase in temperature. The figuresalso show that the reaction rates for roasted chromite overburdeninitially rise sharply, and then taper off. This phenomenon mightbe due to the fact that dissolution of metal increased withincrease in temperature because a rise in temperature causesenhancement of the transfer of the reactant to the interface of theheterogeneousreaction site due to a higher diffusion rate of theconstituent’s fraction.2 The best results were obtained at 80◦C forboth metals.

Optimization of variablesThe variables studied were as follows: (i) concentration of organicacid (A), (ii) duration of leaching (C) and (iii) temperature ofleaching (B) each of which was assessed at three coded levels(–1, 0, +1) as shown in Table 1. To determine the optimum value



(a) (b) (c)

Figure 2. FESEM micrographs of roasted chromite overburden leached with 150 mmol L–1 (a) oxalic; (b) citric and (C) gluconic acid at 80◦C.

Figure 3. Percentage recovery of (a) nickel; (b) cobalt using three different organic acids at three different concentrations at 80◦C and 2% (w/v) pulpdensity.

(a) (b)

Figure 4. Fraction of (a) nickel; (b) cobalt dissolved vs. time at different temperatures using 150 mmol L–1 oxalic acid and 2% (w/v) pulp density.

of these variables, response surface methodology (RSM), using aBox–Behnken design (BBD) was adopted. Using the relationship inTable 1, the actual levels of the variables for each experiment in thedesign matrix along with their coded values and correspondingresponse are summarized in Table S-6 (Supplementary Materials).The statistical results of ANOVA for response surface quadraticmodels for nickel and cobalt are presented in Table 3, which showsthat the respective model F-values were 56.26 and 44.75 for Ni andCo, respectively, which imply that the model is significant. Thereis only a 0.01% chance that a ‘model F-value’ of this magnitudewould occur due to noise. The prob > F values for the modelswhich were less than 0.05 (<0.0001) indicate model terms are

significant with a confidence interval of 95%. In the case of nickel,A, B, C, AB, BC, A2 and B2 and in the case of cobalt A, B, C AC, BC, A2

and B2 are significant model terms. As per Table 3 the values of R2

are evaluated as 0.986 and 0.982 while those of the R2adj coefficient

are 0.968 and 0.96 for Ni and Co recovery models, respectively. Inthe present study, R2 and R2

adj coefficients ensured satisfactoryadjustment of the quadratic model to the experimental data. The‘adequate precision’ measures the signal to noise ratio. A ratiogreater than 4 is desirable. Our study exhibits a ratio of 25.21 and22.00 for Ni and Co recovery, respectively, indicating an adequatesignal. The coefficient of variance (CV) for Ni and Co recoverypercentage was found to be (in %) 11.53 and 11.97. The ratio of



Table 3. Statistical results of the ANOVA

Statistical results Nickel Cobalt

Model F-value 56.26 44.55

Model prob > F < 0.05 < 0.05

R-squared 0.9864 0.9828

CV% 11.53 11.97

Adjusted R-squared 0.9688 0.9608

Adequate precision 25.213 21.962

standard deviation to the mean value of the observed responseexpressed as CV% is indicative of the degree of reproducibility ofthe model. The models showed no lack of fit and an adequateprecision value giving a measure of the ‘signal-to-noise ratio’ inthe range 22–25, indicating an adequate signal.

Nickel and cobalt recovery modelData obtained from the 17 batch runs were analyzed using theDesign Expert 8.0.7.1 software and the following second-orderquadratic model for Ni and Co recovery (%) was obtained.

YNi % = +18.08 + 9.8A + 7.68B + 15.86C + 3.4AB–0.34AC

+ 6.94BC + 7.23A2 + 3.68B2 + 1.13C2 (IV)

YCo % = +11.38 + 4.19A + 4.90B + 9.96C + 0.64AB–4.12AC

+ 4.34BC + 6.99A2 + 2.28B2 + 1.08C2 (V)

The significance of each individual coefficient was determinedby their corresponding P-value calculated statistically. SmallerP-values indicate higher significance of the correspondingcoefficient. Model terms with P-values <0.05, including theindependent variables A, B, C and the interacting variables AB,AC, as well as quadratic variables of A2 and C2 in case of Ni whileAC, BC as well as quadratic variables A2 and B2 in the case of Cowere considered as significant variables.

The normal probability and residual plots for nickel and cobaltleaching models are presented in Fig. S-1 to S-4 (Section S3 inSupplementary Materials). According to the statistical modelingperformed, the optimal conditions for nickel recovery were:organic acid concentration 150 mmol L−1, leaching temperature76.15◦C and leaching duration 174.35 min. For cobalt recoverythe optimal conditions were: organic acid concentration 150mmol L−1, leaching temperature 77.4◦C and leaching duration175.26 min. Figure 5(a) shows the second-order 3D responsesurface plot along with contour plot (Fig. 5(c)) for nickel recovery(%) as a function of duration of leaching and concentration oforganic acid; in Fig. 5(b) % Ni recovery is shown along with thecontour plot (Fig. 5(d)) as a function of temperature of leachingand concentration of organic acid. Similarly, Fig. 6(a) shows thesecond-order 3D response surface plot along with contour plot(Fig. 6(c)) for % cobalt recovery as a function of duration ofleaching and temperature of leaching; in Fig. 6(b) % Co recoveryis shown along with the contour plot (Fig. 6(d)) as a function ofduration of leaching and concentration of organic acid. From Figs5(a) and (b) and 6(a) and (b)) it is evident that with increase inconcentration of organic acid, leaching temperature and leaching

Figure 5. Surface plots of Ni recovery (%) versus (a) duration of leaching and concentration of organic acid; (b) temperature of leaching and concentrationof organic acid. Contour plot of Ni recovery (%) versus (c) duration of leaching and concentration of organic acid; (d) temperature of leaching andconcentration of organic acid.



Figure 6. Surface plots of Co recovery (%) versus (a) duration of leaching and temperature of leaching; (b) duration of leaching and concentration oforganic acid. Contour plot of Co recovery (%) versus (c) duration of leaching and temperature of leaching; (d) duration of leaching and concentration oforganic acid.

duration the recovery percentage of both Ni and Co increased. Themaximum recovery of both Ni and Co under optimum conditionsas shown in Table S-5 is in agreement with results obtained fromtwo-dimensional contour plots of Ni and Co shown in Figs 5 and 6(c) and (d).

Kinetic studyThe optimum conditions for recovery of both metals (Ni, Co) wereconsidered for the kinetic study of metal dissolution, which wasconducted using 150 mmol L−1 oxalic acid as this was found(previous section) to be the most effective concentration forrecovering metals. To determine the optimum kinetic model andthe rate controlling steps in the process of Ni/Co dissolution withthe selected organic acid, the experimental data were analyzed.18

Data were fitted into diffusion, contracting geometry and chemicalreaction controlled mechanisms (Equations (1)–(12)). The multipleregression coefficients (R2) were calculated for each equation andchecked graphically. The reaction rate of nickel dissolution fromchromite overburden ore is controlled by diffusion through aninert product layer, the integrated rate equation being as follows(1 – (2/3) α – (1-α)2/3).23 Analysis of kinetic data from Fig. 4(a)was carried out using the Equations (1)–(12). From the time vs.Ginstling Brounsthein equation (D3) plots (Fig. 7(a)), it can beinferred that the reaction follows the said mechanism, which wasfurther confirmed by Fig. 7(b) where the dissolution kinetic patternof nickel yields straight lines with regression coefficient values (R2)0.989, 0.997 and 0.996 for the three different temperatures (60◦,

70◦ and 80◦C). Nickel dissolution from the chromite overburdenis controlled by diffusion through the hematite matrix which hadbeen developed from an inert goethite matrix upon oxidationroasting at 600◦C as is evident from the regression coefficientvalues. The increase in porosity of particles due to oxidationroasting of raw chromite overburden ore was the key factor takeninto account to describe the behaviour of nickel during its leachingfrom the hematite lattice. Diffusion of organic acids through thepores of hematite was found to be the rate-controlling step.

Data from Fig. 4(b) was used for kinetic analysis of cobalt; fromFigs 8(a), (b) and (c) it can be inferred that dissolution of cobaltfollows a mixed model reaction, i.e. CG1, for the first hour andthen reaction D3 for the subsequent hours. Data plots of (1– (1-α)1/3) (CG1) vs. time (Fig. 8(d)) yield straight lines with regressioncoefficient values (R2) 0.999, 0.995 and 0.999; from the plots of (1–2/3 α – (1– α)2/3) (D3) vs. time (Fig. 8(e)) regression coefficients(R2) 0.999, 0.995 and 0.99 were obtained for the three differenttemperatures (60◦, 70◦ and 80◦C), respectively. Interestingly, thestate of cobalt seems to be quite different and stands out tobe an exclusive event than nickel which exists within a dense-solid matrix, while cobalt exists in a relatively superficial state.During the process of leaching, the rich-in-cobalt manganeseparticles dissolve continuously, liberating Co in the aqueousphase.

CoO(S) + 2H+ → Co2+ + H2O



(a) (b)

Figure 7. (a) Reduced time plot. (b) Plots of 1–2/3–(1–a)2/3 × 10−2 vs. time for different temperatures for nickel recovery.

(a) (b) (c)

(d) (e)

Figure 8. (a) Reduced time plot (at 60◦C); (b) reduced time plot (at 70◦ C); (C) reduced time plot (at 80◦C); (d) Plots of [1–(1–a)1/3] × 10−2 vs. time fordifferent temperatures for cobalt recovery; (e) Plots of 1–2/3–(1–a)2/3 × 10−2 vs. time for different temperatures for cobalt recovery.

Thus, according to the ‘Shrinking Core Model’ the manganesestructures could be conceived of as non-porous particles, shrinkinglayer by layer (directed from the external to the internal) duringleaching.24 Two different time phases of dissolution kinetics couldbe distinguished. During the first 1 h of leaching, the fraction

of cobalt that exists on the external surface of the manganeseparticles dissolves rapidly reaching a fractional conversion ofup to 55% of the total cobalt recovered. During the secondtime phase (after 1 h of leaching), the manganese particles areleached at a very slow rate.25 Table 4 shows slopes and regression



Table 4. Kinetics values obtained from different plots for nickel and cobalt

Nickel Cobalt

Temperature in ◦C

Slope (k) (min−1)

[1–2/3α–(1–α)2/3]

Regression

coefficient (R2)

Slope (k) (min−1)

[1–(1–α)1/3]

Regression

coefficient (R2)

Slope (k) (min−1)

[1–2/3α–(1–α)2/3]

Regression

coefficient (R2)

60 0.88 × 10−8 0.989 0.37 × 10−7 0.999 0.37 × 10−8 0.999

70 0.19 × 10−7 0.997 0.46 × 10−7 0.995 0.11 × 10−7 0.995

80 0.38 × 10−7 0.996 0.59 × 10−7 0.999 0.18 × 10−7 0.99

(a) (b)

Figure 9. Arrhenius plot for extraction of (a) Ni; (b) Co.

coefficients for the kinetic of Ni and Co controlled by the twoequations.

Arrhenius plotThe rate constants for Ni and Co dissolution were calculated fromthe slopes of the plots in Figs 7(b) and 8(d) and (e). Arrheniusplots were constructed which reflected the variation of Ln k vs. 1/Twhere T is temperature in the range 60–80◦C, yielding the straightline shown in Fig. 9(a) and (b). The regression coefficient value (R2)was 0.993 in the case of nickel while for cobalt two values wereobtained: 0.975 (from Equation (9)) and 0.988 (from Equation (3)).The activation energies calculated from the Arrhenius plots were74 kJ mol−1 for Ni and 84.37 (for the first 1 h) and 80.99 (1 honwards up to 3 h) kJ mol−1 for Co. The activation energy of nickelindicates that the leaching of nickel from chromite overburdenore was diffusion controlled. In fact, activation energies lowerthan 83.68 kJ mol−1 have been reported to be representative ofdiffusion through an inert product layer.26,27 Cobalt dissolutionwas partly shrinking core and partly diffusion controlled.

Chemical vs. biological leaching of chromite overburdenIn the back-drop of our previous studies on bioleaching ofchromite overburden,2,3,28 the present work was carried out tounderstand the mechanism and kinetics of metal (Ni and Co)dissolution from roasted chromite overburden with pure organicacids (free from other organic metabolites secreted by microbes inculture broth during growth) – usually produced by heterotrophicfungi. In previous work we have established that organic acidssecreted by heterotrophic fungi take the lead role in metal

leaching wherein other metabolites present in the culture filtrateact synergistically elevating the level of metal recovery. Oxalicacid was the major acid produced by Aspergillus niger strains,while a known citric acid producer, Aspergillus wentii, was alsoused. Among the leaching processes conducted, culture filtrateleaching (indirect process – carried out in the absence of microbes)exhibited much better results than chemical and direct leaching(i.e. conducted in the presence of microbes). Bioleaching withthe culture filtrate of fungus containing oxalic acid (9.68 g L−1

or 76.78 mmol L−1) extracted more metals (65.02% Ni, 59.81%Co) than chemical leaching (26.27% Ni, 31.3% Co) with the sameconcentration of oxalic acid under identical conditions (80◦C, 2%pulp density, shaking).3 Previous studies on Sukinda chromiteoverburden leaching4,5,20 clearly indicated that there remainssufficient scope of process improvement through optimizationof process parameters that may lead to commercial/industrialprocess development exploiting microbial activity. Culture filtrateleaching, an indirect process, is assumed to be regulated bychemical reaction mechanisms; it is thus obvious that properunderstanding of the reaction mechanism and kinetics of metal(s)dissolution from ore material with organic acids might help processoptimization. This work resolved the isothermal model(s) that isfollowed in the process of chemical leaching of specific metals(Ni/Co) with organic acids and the reaction kinetics of metaldissolution.

CONCLUSIONSDissolution of nickel and cobalt from chromite overburdendepends on the amenability of ore minerals to organic acid attack.



The best dissolution was achieved with 150 mmol L−1 oxalicacid at 80◦C over 3 h. The leaching parameters for both metalswere optimized using RSM coupled with BBD design prior to thekinetic study. Nickel dissolution is diffusion-controlled (GinstlingBrounsthein equation) where the process is associated with thepenetration of organic acids through the porous layers of theiron matrix, which increased substantially (compared with rawchromite overburden leaching) after oxidation roasting. Cobaltwas found to exist in the manganese structures of the lateriticore and its dissolution kinetics followed a mixed model – partly‘Shrinking Core model’ (spherical equation) where the productlayer shrinks layer by layer dissolving the metal in lixiviant solutionup to 1 h, followed by diffusion controlled (Ginstling Brounstheinequation) leaching up to 3 h. The extraction kinetics of metals (Ni,Co) was made on the basis of optimized parameters best fitted formaximum recovery of the metals. Statistical viability of the entireprocess has been established.

This study strongly suggests that chromite overburden fromthe Sukinda mine can be extracted effectively using organicacids or culture filtrate containing the same (especially oxalicacid). There exists all the possibility of developing this processto the commercial level, and isolation of a high-yielding oxalicacid producer might help in this direction. Further study ondown-stream processing of leach liquors is necessary to achievethe goal.

ACKNOWLEDGEMENTThe Authors would like to thank Mr Kaustav Bhattacharjee ofDepartment of Metallurgical and Material Engineering, JadavpurUniversity for his valuable suggestions and help. One of theauthors (SB) would like to thank UGC for providing fellowshipunder the scheme ‘Research Fellowship in Science for MeritoriousStudents’. The Authors would like to express their thanks to ‘DSTNano Mission’ (No.SR/NM/PG-03/2007), for granting fund for theprocurement of the FESEM instrument.

Supporting InformationSupporting information may be found in the online version of thisarticle.

REFERENCES1 Som SK and Joshi R, Ni-enrichment and mass balance in Sukinda

laterites, Jajpur district, Orissa. J Geol Soc India 63:169–180 (2003).2 Biswas S, Dey R, Mukherjee S and Banerjee PC, Bioleaching of nickel

and cobalt from lateritic chromite overburden using the culturefiltrate of Aspergillus niger. Appl Biochem Biotechnol 170:1547–1559(2013).

3 Biswas S, Samanta S, Dey R, Mukherjee S and Banerjee PC, Microbialleaching of chromite overburden from Sukinda mines, Orissa, Indiausing Aspergillus niger. Int J Miner Metal Mater 20:705–712 (2013).

4 Behera SK, Panda PP, Singh S, Pradhan N, Sukla LB and MishraBK, Study on reaction mechanism of bioleaching of nickel andcobalt from lateritic chromite overburdens. Int Biodeterior Biodegrad65:1035–1042 (2011).

5 Behera SK, Panda PP, Singh S, Pradhan N, Sukla LB and MishraBK, Extraction of nickel by microbial reduction of lateritic chromiteoverburden of Sukinda, India. Bioresource Technol 125:17–22 (2012).

6 Swamy YV, Kar BB and Mohanty JK, Physico-chemical characterizationand sulphatization roasting of low-grade nickeliferous laterites.Hydrometallurgy 69:89–98 (2003).

7 Swain PK, Roy Chaudhury G and Sukla LB, Dissolution kinetics ofchromite overburden by using mineral acids. Korean J Chem Eng24:932–935 (2007).

8 Mulligan CN and Kamali M, Bioleaching of copper and other metalsfrom low-grade oxidized mining ores by Aspergillus niger. J ChemTechnol Biotechnol 78:497–503 (2003).

9 Brierley CL, Biohydrometallurgical prospects. Hydrometallurgy104:324–328 (2010).

10 Tang JA and Valix M, Leaching of low grade limonite and nontroniteores by fungi metabolic acids. Miner Eng 19:1274–1279 (2006).

11 Coto O, Galizia F, Hernandez I, Marrero J and Donati E, Cobalt andnickel recoveries from laterite tailings by organic and inorganicbio-acids. Hydrometallurgy 94:18–22 (2008).

12 Blesa MA, Marinovich HA, Baumgartner EC and Maroto AJG,Mechanism of dissolution of magnetite by oxalic acid–ferrousion solutions. Inorg Chem 26:3713–3717 (1987).

13 Veglio F, Passariello B, Barbaro M, Plescia P and Marabini AM, Drumleaching tests in the iron removal from quartz using oxalic acid andsulphuric acids. Int J Miner Process 54:183–200 (1998).

14 Panias D, Taxiarchou M, Paspaliaris I and Kontopoulos A, Mechanismsof dissolution of iron oxides in aqueous oxalic acid solutions.Hydrometallurgy 42:257–265 (1996).

15 Ambikadevi VR and Lalithambika M, Effect of organic acids on ferriciron removal from iron-stained kaolinite. Appl Clay Sci 16:133–145(2000).

16 Amiri F, Mousavi SM, Yaghmaei S and Barati M, Bioleaching kinetics of aspent refinery catalyst using Aspergillus niger at optimal conditions.Biochem Eng J 67:208–217 (2012).

17 Hai-yan T, Qing-gui X, Hong-bin X and Yi Z, Optimization ofreaction parameters for the synthesis of chromium methioninecomplex using response surface methodology. Org Process Res Dev17:632−640 (2013).

18 Salmimies R, Mannila M, Kallas J and Hakkinen A, Acidic dissolutionof hematite: kinetic and thermodynamic investigations with oxalicacid. Int J Miner Process 110–111:121–125 (2012).

19 Schwertmann U, Schulze DG and Murad E, Identification of ferrihydritein soils by dissolution kinetics, differential X-ray diffractionand Mossbauer spectroscopy. Soil Sci Soc Am J 46:869–897(1982).

20 Mohapatra S, Bohidar S, Pradhan N, Kar RN and SuklaLB, Microbial extraction of nickel from Sukinda chromiteoverburden by Acidithiobacillus ferrooxidans and Aspergillusstrains. Hydrometallurgy 85:1–8 (2007).

21 Guo Q, Qu JK, Qi T, Wei GY and Han BB, Activation pretreatmentof limonitic laterite ores by alkali-roasting using NaOH. Int J MinerMetall Mater 19:100–105 (2012).

22 Liu XW, Feng YL, Li HR, Yang ZC and Cai ZL, Recovery of valuablemetals from a low-grade nickel ore using an ammonium sulfateroasting-leaching process. Int J Miner Metall Mater 19:377–383(2012).

23 Olanipekun EO, Kinetics of leaching laterite. Int J Miner Process 60:9–14(2000).

24 Levenspiel O, Chemical Reaction Engineering, 2nd edn. John Wiley,New York (1972).

25 Martınez LA, Rodrıguez DMG, Uribe SA, Carrillo PFR and Osuna AJG,Leaching kinetics of iron from low grade kaolin by oxalic acidsolutions. Appl Clay Sci 51:473–477 (2011).

26 Habashi F, Principles of Extractive Metallurgy. Science Publishers Ltd,London, 111–146 (1980).

27 Shon HY and Wadsworth ME, Rate Processes of Extractive Metallurgy.Plenum Press, New York (1986).

28 Biswas S, Samanta S, Dey R, Mukherjee S and Banerjee PC, Microbialextraction of cobalt and nickel from lateritic chromite overburdenusing Aspergillus wentii. Res J Pharm Biol Chem Sci 4:739–750(2013).


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