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Molecular modeling studies of oleate adsorption on iron oxides
Applied Surface Science 295 (2014) 115–122
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Molecular modeling studies of oleate adsorption on iron oxides Swagat S. Rath a , Nishant Sinha b , Hrushikesh Sahoo a , Bisweswar Das a,∗ , Barada Kanta Mishra a a b
CSIR-Institute of Minerals and Materials Technology, Bhubaneswar, India Accelrys K.K, Bengaluru, India
a r t i c l e
i n f o
Article history: Received 26 July 2013 Received in revised form 4 January 2014 Accepted 5 January 2014 Available online 13 January 2014 Keywords: Density functional theory Adsorption energy Iron oxide Flotation
a b s t r a c t Comparative studies of oleate interaction with hematite, magnetite and goethite using density functional calculations are presented. The approach is illustrated by carrying out geometric optimization of oleate on the stable and most exposed planes of hematite, magnetite, and goethite. Interaction energies for oleate-mineral surface have been determined, based on which, magnetite is found to be forming the most stable complex with oleate. Trend as obtained from the quantum chemical calculations has been validated by contact angle measurements and flotation studies on hematite, magnetite and goethite with sodium oleate at different pH and collector concentrations. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Flotation of mineral particles not only depends on hydrodynamic aspects, but also on the appropriate selection of different reagent combinations such as collectors, depressants, dispersants, and frothers. A major role is played by the collector, which gets adsorbed on the target mineral selectively, thereby enhances its hydrophobicty and floatability. Similarly, depressants perform their roles by getting adsorbed on selective mineral surfaces and making the surface hydrophilic. However, frothers do not adsorb on the mineral surface, but are responsible for the attachment of mineral surface to the air bubble by making a stable froth. Considering the involvement of many chemical, thermodynamic, and steric factors in the mineral-reagent interaction, its study becomes important while selecting the right reagent for the flotation process. Oleic acid and sodium oleate are the most commonly used collectors for the flotation of iron bearing minerals. Several studies on oleate–hematite interactions suggested that the oleate adsorption on hematite mainly depends on solution pH [1–3]. These studies revealed that hematite flotation exhibits the maximum recovery at neutral pH, whereas the adsorption of oleate on hematite is optimum at acidic pH. In this context, a systematic fundamental study of hematite flotation was carried out by Kulkarni and Somasundaran [4], who explained hematite flotation based on adsorption kinetics and solution chemistry of the oleate with hematite. Yap
∗ Corresponding author. Tel.: +91 6742379334; fax: +91 674 2567650. E-mail address: [email protected] (B. Das). 0169-4332/$ – see front matter © 2014 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.apsusc.2014.01.014
et al. [5] indicated that oleate adsorption at the hematite/water interface is due to the process involving both chemisorption and physical adsorption. Recently, Haselhuhn et al. [6] have reported that the value of zeta potential of hematite changes due to the presence of several impurities present in the solution that are detrimental to iron concentration processes. The mode of interaction between the collector and mineral surface is primarily carried out by batch adsorption or flotation experiments. The mechanism of interaction between the collector and minerals at the solid–liquid interface has been assessed through Attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) technique. In this technique in-situ adsorption and desorption of collector interactions at different conditions have been monitored [7]. Although several studies on oleate–hematite interactions have appeared in the literature, no formal study of adsorption or flotation of two other major iron oxides namely, magnetite (Fe3 O4 ) and goethite (FeOOH) is reported adequately to the best of our knowledge. Most of the studies on magnetite are related to sorption reactions between ionic species and synthesized magnetite particles in aqueous solution [8,9]. In fact, fundamental studies related to adsorption, electrokinetics measurement, and flotation of pure goethite are also limited [10]. Most of the Indian iron ore mines contain a significant amount of hematite and goethite with a small proportion of magnetite. In this connection, no systematic flotation study has been carried out involving these minerals to understand their response [11,12]. These main iron bearing minerals have wide difference in their properties, structures and moreover in their responses to mineral beneficiation. The structural difference plays a major role while attempting to enrich iron values from natural
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ores using froth flotation technique. It is, therefore, interesting to study the collector adsorption and flotation behaviour of different iron oxide minerals. Molecular modeling study has become an important tool in fundamental chemical research to predict structures, energies and other properties of molecules. Based on several physical and chemical properties of the molecules and the interaction energies involved, it is now possible to give a deep insight into physical and chemical phenomena involved in the process and hence provide the understanding of the mechanism even without detailed experimental studies. Many workers have successfully used molecular modeling techniques in designing tailor made flotation reagents. In this context, Pradip and Rai have carried out extensive work on molecular modelling to study selective flotation and selective flocculation-dispersion of minerals [13–18]. They have mostly used the force field and semi-empirical approach for the energy minimization of the structures. Recently, Jain et al. [19] have used density functional theory calculation to screen reagents for difficult to treat alumina rich iron ore slimes. Leal Filho et al. [20] have used molecular modelling techniques to study the capacity of starch and ethyl-cellulose in depression of calcite from apatite. Bag et al. [21,22] have employed semi-empirical methods to study the interaction of fatty acids with iron, and xanthate ions with copper using HOMO–LUMO approach. The present investigation deals with the density functional theory which is employed to study the adsorption of oleate ion on various cleavage planes of the major iron oxides such as hematite (Fe2 O3 ), magnetite (Fe3 O4 ), and goethite (FeOOH). Geometric optimization has been carried out for the oleate-mineral complexes, and the corresponding interaction energies have been determined. Subsequently, contact angle measurements and flotation experiments have been carried out in order to validate the ab-initio quantum chemical calculation. The main objective of the study is to find out the most efficient interactions that take place between oleate ions and iron oxides present in the Indian iron ore. It is believed that flotation of iron ore will be adapted sooner or later given the dwindling grade of the ore and poor liberation. In this context, DFT calculations would assume importance in order to design specific reagents and also ascertain adsorption potential of flotation reagents on mineral surfaces.
Fig. 1. Bulk lattice structures of (a) hematite, (b) magnetite, and (c) goethite.
structural convergence of 0.03 eV/Å, which led to changes in the energy less than 0.03 eV. 2.2. Models for iron oxide surface Bulk hematite and magnetite structures were modeled using experimental lattice constants and positions as available from the structural database in Materials Studio 6.1. Goethite structure was modeled using the lattice data available in literature [30]. The structures of bulk oxides are shown in Fig. 1 and lattice constants are listed in Table 1. Respective surface cells were created at the principal cleavage planes as reported in literature as well as the most predominant planes as obtained from XRD studies of the samples used for flotation. All the surfaces were modeled using slabs consisting of 4 to 6 layers and a 30 A˚ vacuum along the c-axis. The stability of magnetite planes (1 1 1), (0 0 1), and (1 1 0) were determined using the surface energies of these surfaces. The surface energy is calculated using the formula: Esurface =
2. Materials and methods 2.1. Simulation details In this work, we employ the gradient-corrected periodic density functional theory (DFT) [23] using CASTEP [24] as implemented in Materials Studio 6.1 [25], to examine the interaction energies of oleate with hematite, magnetite, and goethite surfaces. The gradient corrections of the exchange and correlation energies are carried out using exchange correlation functional developed by Perdew–Bukke–Ernzerhof (PBE) [26]. The core electrons and the nuclei of the atoms were described using Vanderbilt ultrasoft pseudo potential along with a plane-wave basis set with a cutoff energy of 400 eV [27]. A 5 × 5 × 1 Monkhorst–Pack k-point grid was used to model the first Brillouin zone [28]. Increasing the kpoint grid size to 6 × 6 × 1 did not change the total energy by more than 0.03 eV. Electronic minimization during the optimization was carried out using the Pulay density mixing scheme [29]. The geometrical optimizations were carried out without any restrictions on spin. The wave functions were converged to within 10−5 eV, and the geometry was optimized until the forces on all the atoms were less than 0.05 eV/Å. The test calculations on different substrates were carried out with an electronic convergence of 1 × 10−6 eV, and a
(Esurface − Ebulk ) A
where Esurface is the energy of the cleaved system, Ebulk is the energy of the bulk magnetite and A is the surface area of the cleaved surface. Esurface is normalized by the ratio of the number of atoms in the bulk and in the surface. The (1 1 1), (0 0 1), and (1 1 0) surfaces were modeled using 4, 5, and 6 layer slabs, respectively. The numbers ˚ of layers were chosen such that each slab has thickness of ∼9 A. Increasing the slab thickness by 2 layers in each case changed the surface energy by less than 2.082 × 10−3 J/m2 . It is thus, indicating that 4–6 layers are sufficient to model surface energy. The number of atoms in each ab initio cell along with top and side views are provided in the Supplementary Information section. Table 1 Lattice constants of hematite, magnetite and goethite. Lattice parameters optimized with COMPASS force fields are shown in parentheses. Mineral
Hematite
Magnetite
Goethite
Crystallographic system a [Å] b [Å] c [Å] ˛ [0 ] ˇ[0 ] [0 ]
Hexagonal 5.035(5.053) – 13.748(13.397) 90 90 120
Cubic 8.396(8.243) – – 90 90 90
Orthorhombic 9.956(9.85) 3.021(3.05) 4.608(4.705) 90 90 90
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Fig. 2. Optimized oleate ion with partial Mulliken charges.
During structural optimization, only top layer of the surface cells was allowed to relax while fractional coordinates of the rest of the atoms were frozen. The reagent oleate ion was created in a periodic ˚ It was then optimized with calculation setting cell of 30 × 30 × 60 A. as discussed above. The oleate ion was allowed to relax fully during the optimization stage. The optimized oleate ion along with the partial Mulliken charges on the constituent atoms is shown in Fig. 2. 2.3. Mineral-reagent complex In order to determine the most likely adsorption configuration of oleate on the mineral surfaces, we have used Adsorption Locator module in Accelrys Materials Studio. Adsorption Locator identifies possible adsorption configurations by carrying out Monte Carlo searches of the configurational space of the substrateadsorbate system as the temperature is slowly decreased. The simulated annealing procedures in Adsorption Locator were done with the COMPASS force field [31] in the temperature range of 300–500 K. The charges used here were force field assigned. In order to validate the efficacy of COMPASS force field for these minerals, the values of lattice constants after geometry optimization (Table 1) were compared with the experimental values. The predicted lattice constants were found to be within 5% of
Fig. 4. XRD pattern of hematite, magnetite and goethite.
the experimental values. The overall annealing was done in 3 cycles of 15,000 steps each. In the Monte Carlo approach of sampling different ‘poses’ on the surface, the conformer, translation, and rotation steps were used with a probability of 0.33 each.
Fig. 3. Reflected microphotographs of hematite, magnetite and goethite.
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The input structure of the oleate-mineral complex was created by docking the optimized oleate ion on the mineral surface considering the fact that Fe ions form an octahedral structure. Bonds were formed between the Fe atom(s) available on the top layer of the mineral surface with two oxygen atoms of the oleate ion. Different adsorption configurations of oleate over the three oxide surfaces were investigated. Here, only the most stable configuration is reported. The total adsorption energies (Eads ) for oleate over the mineral surfaces were calculated using the following expression: Eads = Ecomplex − (Eadsorbate + Emineral ) where Ecomplex , Eadsorbate and EMineral refer to the total interaction energy of the adsorbate (oleate) with the mineral surface system (coordination complex environments of ions on specific crystal faces), the adsorbate, and the bare oxide surface, respectively. Negative adsorption energies imply more exothermic adsorption and stronger metal–adsorbate binding. 2.4. Experimental 2.4.1. Sample Handpicked hematite, magnetite, and goethite samples were obtained from different iron ore mines of Odisha. Reflected micrographs of the samples are presented in Fig. 3. Hematite sample (H) shows very minor inclusion of silicate (S) phases. Magnetite (M) sample also shows small inclusions of clay (C) and hematite (H) phases. Similarly, silicate (S) and hematite (H) phases are observed in the goethite (G) sample. The solid samples were crushed and ground in a laboratory ball mill. The ground hematite samples were subjected to wet high intensity magnetic separators till a high purity sample was obtained. Similarly, the ground magnetite sample was separated in low intensity magnetic separator, to remove the associated gangue constituents
such as silica and alumina. The goethite samples were selectively chosen from the mines site and then processed in a ball mill for reduction in particle size. The chemical analysis of the sample indicates that the iron oxide content in all the three samples varies between 97.5 and 99%. All chemical analyses of the samples were carried out by standard wet chemical methods. 2.4.2. Contact angle and XRD The X-ray diffraction study was carried out by Philips X-ray diffractometer using Mo target to investigate the predominant planes present in the powdered ore samples that were subsequently used for flotation studies. Contact angle measurements were carried out using Phoenix 300 (Surface Electro Optics) instrument. Mineral samples were treated with different concentration of sodium oleate solution, and thin pellets were made using KBr press. 2.4.3. Flotation methods All the flotation studies were carried out by using Denver D12 sub aeration flotation machine with 2 liter capacity cell. The direct flotation studies were carried out by using sodium oleate as the collector and MIBC as the frother. Ground sample of hematite, magnetite, and goethite were sieved, and the size fractions of −100 + 45 m were subjected to flotation studies. The flotation experiments were carried out after conditioning with the collector for a fixed period of time at 25% solids concentration. The conditioning time, collector and frother concentration were kept constant for each mineral under study. After required time of conditioning, froths were collected for a period of 3 min. The concentrate and tailings were collected separately, dried, weighed, and analyzed to assess the product yield and recovery. The effect of reagent concentration and pH were evaluated for all the three minerals.
Fig. 5. Optimized structures of different cleavage planes of hematite, magnetite and goethite. Surface Fe atoms are colored in yellow.
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3. Results and discussion 3.1. Molecular modeling studies The first step in the flotation process is adsorption of oleate onto the mineral surface. In this study single crystal surfaces of these minerals were selected. The most stable surfaces for the three mineral were chosen based on previously published results: hematite (0 0 1) [32], magnetite (1 1 1) [33], and goethite (0 1 0) [34]. While the most stable surfaces for hematite and goethite are well established, there is still ambiguity regarding the most stable surface of magnetite. In the case of magnetite, there are some reports that (0 0 1) or (1 1 0) surfaces are more stable [35,36]. In order to ascertain the most stable surface for magnetite, we have calculated the surface energies of (1 1 1), (0 0 1), and (1 1 0) surfaces of magnetite using DFT and shown in Table 2. The surface energies of the respective surfaces follow the trend: (1 1 1) < (1 1 0) < (0 0 1). Based on this analysis, the (1 1 1) surface of magnetite is treated as the most stable surface. In addition to the most stable surfaces, we have also looked at adsorption on the respective predominant planes as obtained in
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Table 2 Surface energy of different cleavage planes of magnetite. Surface
Surface energy (× 10−3 ), J/m2
Magnetite (1 1 1) Magnetite (0 0 1) Magnetite (1 1 0)
646 1239 832
XRD. This is because recent studies on scheelite [37,38] show that adsorption can take place on the more exposed surfaces. Our XRD results, as shown in Fig. 4, indicates that for magnetite, two most ˚ and (1 1 0) [d: 1.483 A]; ˚ for exposed surfaces are (3 1 1) [d: 2.53 A] ˚ and (1 1 0) [d: 2.510 A]; ˚ and hematite they are (1 0 4) [d: 2.702 A] ˚ and (3 0 1) [d: 2.694 A]. ˚ All for goethite they are (1 0 1) [d: 4.187 A] cleavage surfaces of the three minerals viz. hematite, magnetite, and goethite are shown in Fig. 5. Adsorption Locator module in Accelrys Materials Studio was used to generate the most stable configuration of oleate over the mineral surfaces. In all the cases considered here, oleate was found to adsorb through the oxygen atoms with the Fe atom in the lowest energy states. The inputs from the force field calculations were used
Fig. 6. Most stable adsorption configurations for oleate with different cleavage planes of hematite, magnetite and goethite.
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Table 3 Adsorption energy of mineral surfaces with oleate. Mineral
Density (g/cc)
Hematite
5.25
Magnetite
5.2
Goethite
4.85
Surface (0 0 1) (1 0 4) (1 1 0) (1 1 1) (3 1 1) (1 1 0) (0 1 0) (1 0 1) (3 0 1)
Table 4 Adsorption energy of mineral surfaces with oleate.
Oleate Eads (kJ/mol)
Adsorption mode
−279 −46 −299 −432 −239 −332 −185 −169 −169
1 1 2 2 2 2 1 1 2
(O, O) (O) (O, O) (O, O) (O, O) (O, O) (O, O) (O, O) (O, O)
for a more accurate DFT calculation using CASTEP. Oleate, like other organic carboxylate ions, adsorbs on the metal surfaces through oxygen atoms. During the adsorption process sodium oleate easily dissociates into sodium and oleate ion, which is adsorbed on the mineral surface. Fig. 6 shows the most stable adsorption configurations for oleate on the mineral surfaces considered here. Over the goethite surfaces considered here, oleate prefers to bind in a mono-dentate (1 (O, O)) configuration over (0 1 0) and (1 0 1) surfaces such that both its oxygen atoms bind to a surface Fe atom. The binding energy over (0 1 0) and (1 0 1) surfaces are calculated to be −185 and −169 kJ/mol, respectively (Table 3). This is also evident from the average Fe O bond length which is 1.96 A˚ and ˚ respectively (Fig. 6-C1 and C2). In case of goethite (3 0V1), 2.05 A, as two surface Fe atoms sit close to each other, oleate binds in a bi-dentate (2 (O, O)) configuration. The binding energy on this surface (Eads = −169 kJ/mol) is weaker than (0 1 0) but same as that
Mineral surface
OleateEads (kJ/mol)
Hematite (1 1 0) Magnetite (1 1 1) Goethite (0 1 0)
−98 −106 −163
on (1 1 0) surface of goethite. Clearly, for goethite the binding of oleate is strongest on the most stable surface i.e. (0 1 0). Table 4 As shown in Fig. 6(B1–B3), oleate is predicted to bind in a bidentate (2 (O, O)) configuration over all the magnetite surfaces studied here i.e. (1 1 1), (3 1 1), and (1 1 0). While in case of magnetite (1 1 1), the two surface Fe atoms (to which the oxygen atoms of oleate bind) are in the same plane, in the other two cases one of the Fe atoms is in the second layer. One of the Fe O bonds is, thus, larger in case of magnetite (3 1 1) and (1 1 0). For oleate adsorbed over magnetite (3 1 1), the two Fe O bonds are 1.93 A˚ and 2.29 A˚ (Fig. 6B2). Similarly, for magnetite (1 1 0), the two Fe O bonds are ˚ In contrast, over magnetite (1 1 1), the two Fe O 1.92 A˚ and 2.22 A. ˚ This results in strongest adsorption bonds are 1.93 A˚ and 1.84 A. of oleate over magnetite (1 1 1) surface (Eads = −432 kJ/mol). This is followed by magnetite (1 1 0) and (3 1 1) with adsorption energies of −332 kJ/mol and −239 kJ/mol, respectively (Table 3). It should be noted here that over magnetite, oleate prefers to bind to the most stable surface plane i.e. (1 1 1). Herein we have studied adsorption of oleate over three hematite surfaces: (0 0 1), (1 0 4), and (1 1 0). Over the (0 0 1) surface oleate prefers to bind in mono-dentate (1 (O, O)) configuration such that both the oxygen atoms of oleate bind to the same Fe atom on the ˚ surface (Fig. 6-A1). The Fe O bond lengths are 1.97 A˚ and 2.00 A.
Fig. 7. Density of states graphs for oleate and its complexes with (A) hematite (1 1 0), (B) magnetite (1 1 1), and (C) goethite (0 1 0).
S.S. Rath et al. / Applied Surface Science 295 (2014) 115–122
The binding energy for (0 0 1) is calculated to be −279 kJ/mol. Over hematite (1 0 4), oleate adsorbs via one oxygen atom at an atop site (1 (O)) such that Fe O bond is 1.99 A˚ (Fig. 6A2). This leads to a weakly bound complex with adsorption energy of −46 kJ/mol. In the case of hematite (1 1 0) surface, oleate binds to the surface in a bi-dentate (2 (O, O)) configuration as there are two Fe atoms close to each other on this surface. The bi-dentate configuration results in stronger binding energy of−299 kJ/mol. The Fe O bonds are 1.96 A˚ and 1.98 A˚ long (Fig. 6A3). Clearly, in case of hematite, oleate does not adsorb most strongly on the most stable surface i.e. (0 0 1). It is, instead, one of the most exposed surface i.e. (1 1 0), where oleate adsorption is the strongest. This is in contrast with the other two minerals considered here, magnetite and goethite, where oleate adsorbs on the most stable surface planes. Among the three minerals, adsorption strength of oleate follows the following trend: Magnetite (1 1 1) > Hematite (1 1 0) > Goethite (0 1 0). Interaction energies for water molecules getting adsorbed on the mineral surfaces (only for the surfaces most active for oleate adsorption) were also calculated. As evident from Tables 3 and 4, interaction energy for reagent-mineral adsorption is stronger (more negative) compared to that for water-mineral adsorption. This suggests that the reagent would replace water on the mineral surface. The trend can also be explained by analysing the density of states (DOS) for free and adsorbed oleate. As shown in Fig. 7, the lowest electronic states (corresponding to s orbitals) for oleate is located at −21 and −18 eV. As oleate adsorbs and bonding orbitals on oxygen atoms are stabilized, the position of lowest electronic states is shifted to lower values. In case of goethite (0 1 0), the shift is minimal. The lowest energy states are at −22.8 eV and −20.0 eV. This lower stabilization is responsible for weakest binding over goethite (0 1 0). In case of magnetite (1 1 1), which binds oleate most strongly, the lowest energy states are at −23.5 eV and −21.3 eV. For hematite (1 1 0), the lowest energy states are shifted to −23.0 eV and −20.9 eV.
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Fig. 8. Flotation of hematite, magnetite and goethite with respect to sodium oleate concentration.
Fig. 9. Flotation of hematite, magnetite and goethite as a function of pH.
3.2. Results of flotation studies
3.3. Contact angle measurements
Flotation studies were carried out to study the effect of sodium oleate concentration for the recovery of hematite, magnetite, and goethite. Sodium oleate concentration was varied from 56 to 280 g/t and experiments were conducted at natural pH. As seen in Fig. 8, flotation recovery corresponding to the three minerals follows the order: magnetite > hematite > goethite. A maximum of 98% magnetite could be obtained at a concentration of 280 g/t compared to 92 and 26% in case of hematite and goethite respectively. Similarly, in order to understand the effect of pH on the recoveries of the three minerals, flotation experiments were carried out at sodium oleate concentration of 280 g/t while the pH was varied from 5 to 9 (Fig. 9). For magnetite and hematite, maximum recovery was observed at around neutral pH, where as it decreased drastically at alkaline pH. Morgan et al. [39] got similar correlation between pH and recovery for hematite flotation. However, goethite showed its best recovery at a pH of 8.5. The binding energies obtained from density functional calculations correlate with the trend as obtained from flotation experiments. Our experiments indicate that it is easiest to float magnetite while goethite is most difficult to float. It is evident that in case of magnetite, even though the density is similar to that of hematite, better flotation occurs due to stronger binding energy of oleate. Goethite, on the other hand, is most difficult to float because of weaker binding energy. Thus, while the overall flotation process could depend on many factors, adsorption strength of the collector over the mineral surface appears to be an important contributor.
Contact angle of the three minerals were measured in order to study their wettability nature and thereby validate the DFT results. Sodium oleate solutions of different concentrations were allowed to adsorb on the minerals, and corresponding contact angles with water were measured. As shown in Fig. 10, contact angles for each mineral increase as the oleate concentration increases. Beyond an oleate concentration of 200 g/t, contact angle doesn’t change much. At all concentrations of oleate, contact angle of magnetite is higher compared to the other two, which suggests that it adsorbs oleate
Fig. 10. Contact angle of hematite, magnetite and goethite with water.
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the best and develops significant hydrophobic character. Contact angle of goethite doesn’t increase beyond 41◦ , which explains why it doesn’t float well even at a sodium oleate concentration of 300 g/t. These results are in agreement with the DFT simulation results. 4. Conclusion Plane wave density functional calculations were carried out to study the interaction of oleate with hematite, magnetite, and goethite. Possible adsorption configurations for oleate on most stable and most exposed surfaces of these metal oxide surfaces were determined by carrying out Monte Carlo searches of the configurational space of the substrate-adsorbate system using COMPASS force field, followed by ab-initio calculations. Adsorption energy calculations reveal that among all the mineral surfaces considered here, the most active surfaces for adsorption for each mineral were: magnetite (1 1 1), hematite (1 1 0), and goethite (0 1 0). Among these surfaces, oleate binds strongest on magnetite (1 1 1) followed by hematite (1 1 0) and goethite (0 1 0) with the adsorption energies of −432, −299, and −185 kJ/mol, respectively. Density of states calculations supported the metal-adsorbate binding phenomenon in terms of the shifts in the lowest electronic states. It is also noted that while in case magnetite and goethite the adsorption occurs over the most stable surfaces, in case of hematite it occurs on the one of the most exposed surface as indicated in XRD. The flotation studies of the three iron minerals show that, under identical conditions, the flotation recovery of magnetite is higher compared to hematite and goethite as predicted by the DFT results. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.apsusc.2014. 01.014. References [1] A.H. Peck, L.H. Ruby, M.E. Wadsworth, An infrared study of the flotation of hematite with oleic acid and sodium oleate, T. AIME (1966) 235–301. [2] J.G. Paterson, T. Salman, Adsorption of sodium oleate on cupric and ferric hydroxides, Trans. IMM 79 (1970) c91–c102. [3] M.I. Pope, D.I. Sutton, The correlation between froth flotation response and collector adsorption from aqueous solution. Part I. Titanium dioxide and ferric oxide conditioned in oleate solutions, Powder Technol. 7 (1973) 271–279. [4] R.D. Kulkarni, P. Somasundaran, Flotation chemistry of hematite–oleate system, Colloid Surf. 1 (1980) 387–405. [5] S.N. Yap, R.K. Mishra, S. Raghavanand, D.W. Fuerstenau, The adsorption of oleate from aqueous solution onto hematite, in: P.H. Tewari (Ed.), Adsorption from Aqueous Solutions, Plenum Press, New York, 1981, pp. 119–142. [6] H.J. Haselhuhn, S. Ennis, T.C. Eisele, S.K. Kawatra, Water chemistry effects on zeta potential of concentrated hematite ore, in: SME Annual Meeting, Feb. 24–27, 2013, Denver, CO, 2013, pp. 13–147, Preprint. [7] E. Potapova, Studies on the Adsorption of Flotation Collectors on Iron Oxides, Licentiate Thesis, Luleå University of Technology, Luleå, Sweden, 2009. [8] P. Roonasi, Adsorption and Surface Reaction Properties of Synthesized Magnetite Nano-Particles, Licentiate Thesis, Luleå University of Technology, Luleå, Sweden, 2007. [9] X. Zhou, S. Ni, X. Wang, F. Wu, Adsorption of sodium oleate on nano-sized Fe3O4 particles prepared by co-precipitation, Curr. Nanosci. 3 (2007) 259–263. [10] R.F. Jung, R.O. James, T.W. Healy, Adsorption, precipitation and electrokinetics processes in the iron oxide goethite–oleic acid-oleate system, J. Colloid Interf. Sci. 118 (1987) 463–472.
[11] B. Das, S. Prakash, S.K. Biswal, P.S.R Reddy, V.N. Misra, Studies on the beneficiation of Indian iron ore slimes using flotation technique, in: Centenary of Flotation Symposium, 5–9 June 200, Brisbane, Australia, 2005. [12] A. Vidyadhar, N. Kumari, R.P. Bhagat, Adsorption mechanism of mixed collector systems on hematite flotation, Miner. Eng. 26 (2012) 102–104. [13] Pradip, B. Rai, Design of tailor-made surfactants for industrial applications using a molecular modeling approach, Colloid Surf. 205 (2002) 139–148. [14] Pradip, B. Rai, Molecular modeling and rational design of flotation reagents, Int. J. Miner. Process 72 (2003) 95–110. [15] Pradip, B. Rai, T.K. Rao, S. Krishnamurthy, Vetrivel F R., J. Mielczarski, Molecular modeling of interactions of diphosphonic acid based surfactants with calcium minerals, Langmuir 18 (2002) 932–940. [16] B. Rai, Pradip, Design of highly selective industrial performance chemicals: a molecular modeling approach, Mol. Simulat. 34 (2008) 1209–1214. [17] B. Rai, Pradip, Rational design of selective industrial performance chemicals based on molecular modeling computations, in: B. Rai (Ed.), Molecular Modeling for the Design of Novel Performance Chemicals and Materials, 1st ed., CRC Press, Boca Raton, FL, 2012. [18] B. Rai, P. Sathish, J. Tanwar, Pradip, K.S. Moon, D.W. Fuerstnau, A molecular dynamics study of the interaction of oleate and dodecylammonium chloride surfactants with complex aluminosilicate Minerals, J. Colloid Interf. Sci. 362 (2011) 510–516. [19] V. Jain, B. Rai, U.V. Waghmare, Pradip, Molecular modeling based selection and design of selective reagents for beneficiation of alumina rich iron ore slimes, in: Proceedings XXVI International Mineral Processing Congress, New Delhi, India, 2005, pp. 2258–2269. [20] L.S. Leal Filho, P.R. Seidl, J.C.G. Correla, L.C.K. Cerqueira, Molecular modelling of reagents for flotation processes, Miner. Eng. 13 (2000) 1495–1503. [21] B. Bag, B. Das, B.K. Mishra, Geometrical optimization of structure of carboxylic acids vis-à-vis their effectiveness towards iron ore flotation, Miner. Metall. Process. 26 (2009) 226–232. [22] B. Bag, B. Das, B.K. Mishra, Geometrical optimization of xanthate collectors with copper ions and their response to flotation, Miner. Eng. 24 (2011) 760–765. [23] P. Hohenberg, W. Kohn, Inhomogeneous electron gas, Phys. Rev. 136 (1964) B864–B871. [24] S.J. Clark, M.D. Segall, C.J. Pickard, P.J. Hasnip, M.J. Probert, K. Refson, M.C. Payne, First principles methods using CASTEP, Z. Kristallogr. 220 (2005) 567–570. [25] Materials studio release notes, Release 6.1, San Diego: accelrys Software Inc., 2012. [26] J.P. Perdew, K. Bukke, M. Ernzerhof, Generalized gradient approximation made simple, Phys. Rev. Lett. 77 (1996) 3865–3868. [27] D. Vanderbilt, Optimally smooth norm-conserving pseudopotentials, Phys. Rev. B 32 (1985) 8412–8415. [28] H.J. Monkhorst, J.D. Pack, Special points for rillouin-zone integrations, Phys. Rev. B 13 (12) (1976) 5188–5192. [29] P. Pulay, Convergence acceleration of iterative sequences. The case of scf iteration, Chem. Phys. Lett. 73 (1980) 393–398. [30] R.M. Cornell, U. Schwertmann, The Iron Oxides: Structure, Properties, Reactions, Occurrences and Uses, 2nd ed., Wiley VCH Verlag GmbH and Cop, Weinhem, 2003. [31] H. Sun, COMPASS: an ab Initio force-field optimized for condensed-phase applications-overview with details on alkane and benzene compounds, J. Phys. Chem. B 102 (1998) 7338–7364. [32] X.G. Wang, W. Weiss, S.K. Shaikhutdinov, M. Ritter, M. Petersen, F. Wagner, The hematite (␣-Fe2O3) (0 0 0 1) surface: evidence for domains of distinct chemistry, Phys. Rev. Lett. 81 (1998) 1038–1041. [33] G.J. Martin, R.S. Cutting, D.J. Vaughan, M.C. Warren, Bulk and key surface structures of hematite, magnetite, and goethite: a density functional theory study, Am. Mineral. 94 (2009) 1341–1350. [34] J. Rakovan, U. Becker, M.F. Hochella Jr., Aspects of goethite surface microtopography, structure, chemistry, and reactivity, Am. Mineral 84 (1999) 884–894. [35] T. Yang, X. Wen, J. Ren, Y. Li, J. Wang, C. Huo, Surface structures of Fe3 O4 (1 1 1), (1 1 0), and (0 0 1): a density functional theory study, J. Fuel Chem. Technol. 38 (2010) 121–128. [36] T.K. Kundu, K.H. Rao, S.C. Parker, Atomistic simulation studies of magnetite surface structures and adsorption behavior in the presence of molecular and dissociated water and formic acid, J. Colloid Interf. Sci. 295 (2006) 364–373. [37] Y.H. Hu, Z.Y. Gao, W. Sun, X.W. Liu, Anisotropic surface energies and adsorption behaviors of scheelite crystal, Colloid Surf. A 415 (2012) 439–448. [38] Z.Y. Gao, W. Sun, Y.H. Hu, X.W. Liu, Surface energies and appearances of commonly exposed surfaces of scheelite crystal, Trans. Nonferr. Metal 23 (2013) 2147–2152. [39] L.J. Morgan, K.P. Ananthapadmanabhan, P. Somsundaran, Oletae adsorption on hematite: problems and methods, Int. J. Miner. Process. 18 (1986) 139–152.
Contents lists available at ScienceDirect
Applied Surface Science journal homepage: www.elsevier.com/locate/apsusc
Molecular modeling studies of oleate adsorption on iron oxides Swagat S. Rath a , Nishant Sinha b , Hrushikesh Sahoo a , Bisweswar Das a,∗ , Barada Kanta Mishra a a b
CSIR-Institute of Minerals and Materials Technology, Bhubaneswar, India Accelrys K.K, Bengaluru, India
a r t i c l e
i n f o
Article history: Received 26 July 2013 Received in revised form 4 January 2014 Accepted 5 January 2014 Available online 13 January 2014 Keywords: Density functional theory Adsorption energy Iron oxide Flotation
a b s t r a c t Comparative studies of oleate interaction with hematite, magnetite and goethite using density functional calculations are presented. The approach is illustrated by carrying out geometric optimization of oleate on the stable and most exposed planes of hematite, magnetite, and goethite. Interaction energies for oleate-mineral surface have been determined, based on which, magnetite is found to be forming the most stable complex with oleate. Trend as obtained from the quantum chemical calculations has been validated by contact angle measurements and flotation studies on hematite, magnetite and goethite with sodium oleate at different pH and collector concentrations. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Flotation of mineral particles not only depends on hydrodynamic aspects, but also on the appropriate selection of different reagent combinations such as collectors, depressants, dispersants, and frothers. A major role is played by the collector, which gets adsorbed on the target mineral selectively, thereby enhances its hydrophobicty and floatability. Similarly, depressants perform their roles by getting adsorbed on selective mineral surfaces and making the surface hydrophilic. However, frothers do not adsorb on the mineral surface, but are responsible for the attachment of mineral surface to the air bubble by making a stable froth. Considering the involvement of many chemical, thermodynamic, and steric factors in the mineral-reagent interaction, its study becomes important while selecting the right reagent for the flotation process. Oleic acid and sodium oleate are the most commonly used collectors for the flotation of iron bearing minerals. Several studies on oleate–hematite interactions suggested that the oleate adsorption on hematite mainly depends on solution pH [1–3]. These studies revealed that hematite flotation exhibits the maximum recovery at neutral pH, whereas the adsorption of oleate on hematite is optimum at acidic pH. In this context, a systematic fundamental study of hematite flotation was carried out by Kulkarni and Somasundaran [4], who explained hematite flotation based on adsorption kinetics and solution chemistry of the oleate with hematite. Yap
∗ Corresponding author. Tel.: +91 6742379334; fax: +91 674 2567650. E-mail address: [email protected] (B. Das). 0169-4332/$ – see front matter © 2014 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.apsusc.2014.01.014
et al. [5] indicated that oleate adsorption at the hematite/water interface is due to the process involving both chemisorption and physical adsorption. Recently, Haselhuhn et al. [6] have reported that the value of zeta potential of hematite changes due to the presence of several impurities present in the solution that are detrimental to iron concentration processes. The mode of interaction between the collector and mineral surface is primarily carried out by batch adsorption or flotation experiments. The mechanism of interaction between the collector and minerals at the solid–liquid interface has been assessed through Attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) technique. In this technique in-situ adsorption and desorption of collector interactions at different conditions have been monitored [7]. Although several studies on oleate–hematite interactions have appeared in the literature, no formal study of adsorption or flotation of two other major iron oxides namely, magnetite (Fe3 O4 ) and goethite (FeOOH) is reported adequately to the best of our knowledge. Most of the studies on magnetite are related to sorption reactions between ionic species and synthesized magnetite particles in aqueous solution [8,9]. In fact, fundamental studies related to adsorption, electrokinetics measurement, and flotation of pure goethite are also limited [10]. Most of the Indian iron ore mines contain a significant amount of hematite and goethite with a small proportion of magnetite. In this connection, no systematic flotation study has been carried out involving these minerals to understand their response [11,12]. These main iron bearing minerals have wide difference in their properties, structures and moreover in their responses to mineral beneficiation. The structural difference plays a major role while attempting to enrich iron values from natural
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ores using froth flotation technique. It is, therefore, interesting to study the collector adsorption and flotation behaviour of different iron oxide minerals. Molecular modeling study has become an important tool in fundamental chemical research to predict structures, energies and other properties of molecules. Based on several physical and chemical properties of the molecules and the interaction energies involved, it is now possible to give a deep insight into physical and chemical phenomena involved in the process and hence provide the understanding of the mechanism even without detailed experimental studies. Many workers have successfully used molecular modeling techniques in designing tailor made flotation reagents. In this context, Pradip and Rai have carried out extensive work on molecular modelling to study selective flotation and selective flocculation-dispersion of minerals [13–18]. They have mostly used the force field and semi-empirical approach for the energy minimization of the structures. Recently, Jain et al. [19] have used density functional theory calculation to screen reagents for difficult to treat alumina rich iron ore slimes. Leal Filho et al. [20] have used molecular modelling techniques to study the capacity of starch and ethyl-cellulose in depression of calcite from apatite. Bag et al. [21,22] have employed semi-empirical methods to study the interaction of fatty acids with iron, and xanthate ions with copper using HOMO–LUMO approach. The present investigation deals with the density functional theory which is employed to study the adsorption of oleate ion on various cleavage planes of the major iron oxides such as hematite (Fe2 O3 ), magnetite (Fe3 O4 ), and goethite (FeOOH). Geometric optimization has been carried out for the oleate-mineral complexes, and the corresponding interaction energies have been determined. Subsequently, contact angle measurements and flotation experiments have been carried out in order to validate the ab-initio quantum chemical calculation. The main objective of the study is to find out the most efficient interactions that take place between oleate ions and iron oxides present in the Indian iron ore. It is believed that flotation of iron ore will be adapted sooner or later given the dwindling grade of the ore and poor liberation. In this context, DFT calculations would assume importance in order to design specific reagents and also ascertain adsorption potential of flotation reagents on mineral surfaces.
Fig. 1. Bulk lattice structures of (a) hematite, (b) magnetite, and (c) goethite.
structural convergence of 0.03 eV/Å, which led to changes in the energy less than 0.03 eV. 2.2. Models for iron oxide surface Bulk hematite and magnetite structures were modeled using experimental lattice constants and positions as available from the structural database in Materials Studio 6.1. Goethite structure was modeled using the lattice data available in literature [30]. The structures of bulk oxides are shown in Fig. 1 and lattice constants are listed in Table 1. Respective surface cells were created at the principal cleavage planes as reported in literature as well as the most predominant planes as obtained from XRD studies of the samples used for flotation. All the surfaces were modeled using slabs consisting of 4 to 6 layers and a 30 A˚ vacuum along the c-axis. The stability of magnetite planes (1 1 1), (0 0 1), and (1 1 0) were determined using the surface energies of these surfaces. The surface energy is calculated using the formula: Esurface =
2. Materials and methods 2.1. Simulation details In this work, we employ the gradient-corrected periodic density functional theory (DFT) [23] using CASTEP [24] as implemented in Materials Studio 6.1 [25], to examine the interaction energies of oleate with hematite, magnetite, and goethite surfaces. The gradient corrections of the exchange and correlation energies are carried out using exchange correlation functional developed by Perdew–Bukke–Ernzerhof (PBE) [26]. The core electrons and the nuclei of the atoms were described using Vanderbilt ultrasoft pseudo potential along with a plane-wave basis set with a cutoff energy of 400 eV [27]. A 5 × 5 × 1 Monkhorst–Pack k-point grid was used to model the first Brillouin zone [28]. Increasing the kpoint grid size to 6 × 6 × 1 did not change the total energy by more than 0.03 eV. Electronic minimization during the optimization was carried out using the Pulay density mixing scheme [29]. The geometrical optimizations were carried out without any restrictions on spin. The wave functions were converged to within 10−5 eV, and the geometry was optimized until the forces on all the atoms were less than 0.05 eV/Å. The test calculations on different substrates were carried out with an electronic convergence of 1 × 10−6 eV, and a
(Esurface − Ebulk ) A
where Esurface is the energy of the cleaved system, Ebulk is the energy of the bulk magnetite and A is the surface area of the cleaved surface. Esurface is normalized by the ratio of the number of atoms in the bulk and in the surface. The (1 1 1), (0 0 1), and (1 1 0) surfaces were modeled using 4, 5, and 6 layer slabs, respectively. The numbers ˚ of layers were chosen such that each slab has thickness of ∼9 A. Increasing the slab thickness by 2 layers in each case changed the surface energy by less than 2.082 × 10−3 J/m2 . It is thus, indicating that 4–6 layers are sufficient to model surface energy. The number of atoms in each ab initio cell along with top and side views are provided in the Supplementary Information section. Table 1 Lattice constants of hematite, magnetite and goethite. Lattice parameters optimized with COMPASS force fields are shown in parentheses. Mineral
Hematite
Magnetite
Goethite
Crystallographic system a [Å] b [Å] c [Å] ˛ [0 ] ˇ[0 ] [0 ]
Hexagonal 5.035(5.053) – 13.748(13.397) 90 90 120
Cubic 8.396(8.243) – – 90 90 90
Orthorhombic 9.956(9.85) 3.021(3.05) 4.608(4.705) 90 90 90
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Fig. 2. Optimized oleate ion with partial Mulliken charges.
During structural optimization, only top layer of the surface cells was allowed to relax while fractional coordinates of the rest of the atoms were frozen. The reagent oleate ion was created in a periodic ˚ It was then optimized with calculation setting cell of 30 × 30 × 60 A. as discussed above. The oleate ion was allowed to relax fully during the optimization stage. The optimized oleate ion along with the partial Mulliken charges on the constituent atoms is shown in Fig. 2. 2.3. Mineral-reagent complex In order to determine the most likely adsorption configuration of oleate on the mineral surfaces, we have used Adsorption Locator module in Accelrys Materials Studio. Adsorption Locator identifies possible adsorption configurations by carrying out Monte Carlo searches of the configurational space of the substrateadsorbate system as the temperature is slowly decreased. The simulated annealing procedures in Adsorption Locator were done with the COMPASS force field [31] in the temperature range of 300–500 K. The charges used here were force field assigned. In order to validate the efficacy of COMPASS force field for these minerals, the values of lattice constants after geometry optimization (Table 1) were compared with the experimental values. The predicted lattice constants were found to be within 5% of
Fig. 4. XRD pattern of hematite, magnetite and goethite.
the experimental values. The overall annealing was done in 3 cycles of 15,000 steps each. In the Monte Carlo approach of sampling different ‘poses’ on the surface, the conformer, translation, and rotation steps were used with a probability of 0.33 each.
Fig. 3. Reflected microphotographs of hematite, magnetite and goethite.
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The input structure of the oleate-mineral complex was created by docking the optimized oleate ion on the mineral surface considering the fact that Fe ions form an octahedral structure. Bonds were formed between the Fe atom(s) available on the top layer of the mineral surface with two oxygen atoms of the oleate ion. Different adsorption configurations of oleate over the three oxide surfaces were investigated. Here, only the most stable configuration is reported. The total adsorption energies (Eads ) for oleate over the mineral surfaces were calculated using the following expression: Eads = Ecomplex − (Eadsorbate + Emineral ) where Ecomplex , Eadsorbate and EMineral refer to the total interaction energy of the adsorbate (oleate) with the mineral surface system (coordination complex environments of ions on specific crystal faces), the adsorbate, and the bare oxide surface, respectively. Negative adsorption energies imply more exothermic adsorption and stronger metal–adsorbate binding. 2.4. Experimental 2.4.1. Sample Handpicked hematite, magnetite, and goethite samples were obtained from different iron ore mines of Odisha. Reflected micrographs of the samples are presented in Fig. 3. Hematite sample (H) shows very minor inclusion of silicate (S) phases. Magnetite (M) sample also shows small inclusions of clay (C) and hematite (H) phases. Similarly, silicate (S) and hematite (H) phases are observed in the goethite (G) sample. The solid samples were crushed and ground in a laboratory ball mill. The ground hematite samples were subjected to wet high intensity magnetic separators till a high purity sample was obtained. Similarly, the ground magnetite sample was separated in low intensity magnetic separator, to remove the associated gangue constituents
such as silica and alumina. The goethite samples were selectively chosen from the mines site and then processed in a ball mill for reduction in particle size. The chemical analysis of the sample indicates that the iron oxide content in all the three samples varies between 97.5 and 99%. All chemical analyses of the samples were carried out by standard wet chemical methods. 2.4.2. Contact angle and XRD The X-ray diffraction study was carried out by Philips X-ray diffractometer using Mo target to investigate the predominant planes present in the powdered ore samples that were subsequently used for flotation studies. Contact angle measurements were carried out using Phoenix 300 (Surface Electro Optics) instrument. Mineral samples were treated with different concentration of sodium oleate solution, and thin pellets were made using KBr press. 2.4.3. Flotation methods All the flotation studies were carried out by using Denver D12 sub aeration flotation machine with 2 liter capacity cell. The direct flotation studies were carried out by using sodium oleate as the collector and MIBC as the frother. Ground sample of hematite, magnetite, and goethite were sieved, and the size fractions of −100 + 45 m were subjected to flotation studies. The flotation experiments were carried out after conditioning with the collector for a fixed period of time at 25% solids concentration. The conditioning time, collector and frother concentration were kept constant for each mineral under study. After required time of conditioning, froths were collected for a period of 3 min. The concentrate and tailings were collected separately, dried, weighed, and analyzed to assess the product yield and recovery. The effect of reagent concentration and pH were evaluated for all the three minerals.
Fig. 5. Optimized structures of different cleavage planes of hematite, magnetite and goethite. Surface Fe atoms are colored in yellow.
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3. Results and discussion 3.1. Molecular modeling studies The first step in the flotation process is adsorption of oleate onto the mineral surface. In this study single crystal surfaces of these minerals were selected. The most stable surfaces for the three mineral were chosen based on previously published results: hematite (0 0 1) [32], magnetite (1 1 1) [33], and goethite (0 1 0) [34]. While the most stable surfaces for hematite and goethite are well established, there is still ambiguity regarding the most stable surface of magnetite. In the case of magnetite, there are some reports that (0 0 1) or (1 1 0) surfaces are more stable [35,36]. In order to ascertain the most stable surface for magnetite, we have calculated the surface energies of (1 1 1), (0 0 1), and (1 1 0) surfaces of magnetite using DFT and shown in Table 2. The surface energies of the respective surfaces follow the trend: (1 1 1) < (1 1 0) < (0 0 1). Based on this analysis, the (1 1 1) surface of magnetite is treated as the most stable surface. In addition to the most stable surfaces, we have also looked at adsorption on the respective predominant planes as obtained in
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Table 2 Surface energy of different cleavage planes of magnetite. Surface
Surface energy (× 10−3 ), J/m2
Magnetite (1 1 1) Magnetite (0 0 1) Magnetite (1 1 0)
646 1239 832
XRD. This is because recent studies on scheelite [37,38] show that adsorption can take place on the more exposed surfaces. Our XRD results, as shown in Fig. 4, indicates that for magnetite, two most ˚ and (1 1 0) [d: 1.483 A]; ˚ for exposed surfaces are (3 1 1) [d: 2.53 A] ˚ and (1 1 0) [d: 2.510 A]; ˚ and hematite they are (1 0 4) [d: 2.702 A] ˚ and (3 0 1) [d: 2.694 A]. ˚ All for goethite they are (1 0 1) [d: 4.187 A] cleavage surfaces of the three minerals viz. hematite, magnetite, and goethite are shown in Fig. 5. Adsorption Locator module in Accelrys Materials Studio was used to generate the most stable configuration of oleate over the mineral surfaces. In all the cases considered here, oleate was found to adsorb through the oxygen atoms with the Fe atom in the lowest energy states. The inputs from the force field calculations were used
Fig. 6. Most stable adsorption configurations for oleate with different cleavage planes of hematite, magnetite and goethite.
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Table 3 Adsorption energy of mineral surfaces with oleate. Mineral
Density (g/cc)
Hematite
5.25
Magnetite
5.2
Goethite
4.85
Surface (0 0 1) (1 0 4) (1 1 0) (1 1 1) (3 1 1) (1 1 0) (0 1 0) (1 0 1) (3 0 1)
Table 4 Adsorption energy of mineral surfaces with oleate.
Oleate Eads (kJ/mol)
Adsorption mode
−279 −46 −299 −432 −239 −332 −185 −169 −169
1 1 2 2 2 2 1 1 2
(O, O) (O) (O, O) (O, O) (O, O) (O, O) (O, O) (O, O) (O, O)
for a more accurate DFT calculation using CASTEP. Oleate, like other organic carboxylate ions, adsorbs on the metal surfaces through oxygen atoms. During the adsorption process sodium oleate easily dissociates into sodium and oleate ion, which is adsorbed on the mineral surface. Fig. 6 shows the most stable adsorption configurations for oleate on the mineral surfaces considered here. Over the goethite surfaces considered here, oleate prefers to bind in a mono-dentate (1 (O, O)) configuration over (0 1 0) and (1 0 1) surfaces such that both its oxygen atoms bind to a surface Fe atom. The binding energy over (0 1 0) and (1 0 1) surfaces are calculated to be −185 and −169 kJ/mol, respectively (Table 3). This is also evident from the average Fe O bond length which is 1.96 A˚ and ˚ respectively (Fig. 6-C1 and C2). In case of goethite (3 0V1), 2.05 A, as two surface Fe atoms sit close to each other, oleate binds in a bi-dentate (2 (O, O)) configuration. The binding energy on this surface (Eads = −169 kJ/mol) is weaker than (0 1 0) but same as that
Mineral surface
OleateEads (kJ/mol)
Hematite (1 1 0) Magnetite (1 1 1) Goethite (0 1 0)
−98 −106 −163
on (1 1 0) surface of goethite. Clearly, for goethite the binding of oleate is strongest on the most stable surface i.e. (0 1 0). Table 4 As shown in Fig. 6(B1–B3), oleate is predicted to bind in a bidentate (2 (O, O)) configuration over all the magnetite surfaces studied here i.e. (1 1 1), (3 1 1), and (1 1 0). While in case of magnetite (1 1 1), the two surface Fe atoms (to which the oxygen atoms of oleate bind) are in the same plane, in the other two cases one of the Fe atoms is in the second layer. One of the Fe O bonds is, thus, larger in case of magnetite (3 1 1) and (1 1 0). For oleate adsorbed over magnetite (3 1 1), the two Fe O bonds are 1.93 A˚ and 2.29 A˚ (Fig. 6B2). Similarly, for magnetite (1 1 0), the two Fe O bonds are ˚ In contrast, over magnetite (1 1 1), the two Fe O 1.92 A˚ and 2.22 A. ˚ This results in strongest adsorption bonds are 1.93 A˚ and 1.84 A. of oleate over magnetite (1 1 1) surface (Eads = −432 kJ/mol). This is followed by magnetite (1 1 0) and (3 1 1) with adsorption energies of −332 kJ/mol and −239 kJ/mol, respectively (Table 3). It should be noted here that over magnetite, oleate prefers to bind to the most stable surface plane i.e. (1 1 1). Herein we have studied adsorption of oleate over three hematite surfaces: (0 0 1), (1 0 4), and (1 1 0). Over the (0 0 1) surface oleate prefers to bind in mono-dentate (1 (O, O)) configuration such that both the oxygen atoms of oleate bind to the same Fe atom on the ˚ surface (Fig. 6-A1). The Fe O bond lengths are 1.97 A˚ and 2.00 A.
Fig. 7. Density of states graphs for oleate and its complexes with (A) hematite (1 1 0), (B) magnetite (1 1 1), and (C) goethite (0 1 0).
S.S. Rath et al. / Applied Surface Science 295 (2014) 115–122
The binding energy for (0 0 1) is calculated to be −279 kJ/mol. Over hematite (1 0 4), oleate adsorbs via one oxygen atom at an atop site (1 (O)) such that Fe O bond is 1.99 A˚ (Fig. 6A2). This leads to a weakly bound complex with adsorption energy of −46 kJ/mol. In the case of hematite (1 1 0) surface, oleate binds to the surface in a bi-dentate (2 (O, O)) configuration as there are two Fe atoms close to each other on this surface. The bi-dentate configuration results in stronger binding energy of−299 kJ/mol. The Fe O bonds are 1.96 A˚ and 1.98 A˚ long (Fig. 6A3). Clearly, in case of hematite, oleate does not adsorb most strongly on the most stable surface i.e. (0 0 1). It is, instead, one of the most exposed surface i.e. (1 1 0), where oleate adsorption is the strongest. This is in contrast with the other two minerals considered here, magnetite and goethite, where oleate adsorbs on the most stable surface planes. Among the three minerals, adsorption strength of oleate follows the following trend: Magnetite (1 1 1) > Hematite (1 1 0) > Goethite (0 1 0). Interaction energies for water molecules getting adsorbed on the mineral surfaces (only for the surfaces most active for oleate adsorption) were also calculated. As evident from Tables 3 and 4, interaction energy for reagent-mineral adsorption is stronger (more negative) compared to that for water-mineral adsorption. This suggests that the reagent would replace water on the mineral surface. The trend can also be explained by analysing the density of states (DOS) for free and adsorbed oleate. As shown in Fig. 7, the lowest electronic states (corresponding to s orbitals) for oleate is located at −21 and −18 eV. As oleate adsorbs and bonding orbitals on oxygen atoms are stabilized, the position of lowest electronic states is shifted to lower values. In case of goethite (0 1 0), the shift is minimal. The lowest energy states are at −22.8 eV and −20.0 eV. This lower stabilization is responsible for weakest binding over goethite (0 1 0). In case of magnetite (1 1 1), which binds oleate most strongly, the lowest energy states are at −23.5 eV and −21.3 eV. For hematite (1 1 0), the lowest energy states are shifted to −23.0 eV and −20.9 eV.
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Fig. 8. Flotation of hematite, magnetite and goethite with respect to sodium oleate concentration.
Fig. 9. Flotation of hematite, magnetite and goethite as a function of pH.
3.2. Results of flotation studies
3.3. Contact angle measurements
Flotation studies were carried out to study the effect of sodium oleate concentration for the recovery of hematite, magnetite, and goethite. Sodium oleate concentration was varied from 56 to 280 g/t and experiments were conducted at natural pH. As seen in Fig. 8, flotation recovery corresponding to the three minerals follows the order: magnetite > hematite > goethite. A maximum of 98% magnetite could be obtained at a concentration of 280 g/t compared to 92 and 26% in case of hematite and goethite respectively. Similarly, in order to understand the effect of pH on the recoveries of the three minerals, flotation experiments were carried out at sodium oleate concentration of 280 g/t while the pH was varied from 5 to 9 (Fig. 9). For magnetite and hematite, maximum recovery was observed at around neutral pH, where as it decreased drastically at alkaline pH. Morgan et al. [39] got similar correlation between pH and recovery for hematite flotation. However, goethite showed its best recovery at a pH of 8.5. The binding energies obtained from density functional calculations correlate with the trend as obtained from flotation experiments. Our experiments indicate that it is easiest to float magnetite while goethite is most difficult to float. It is evident that in case of magnetite, even though the density is similar to that of hematite, better flotation occurs due to stronger binding energy of oleate. Goethite, on the other hand, is most difficult to float because of weaker binding energy. Thus, while the overall flotation process could depend on many factors, adsorption strength of the collector over the mineral surface appears to be an important contributor.
Contact angle of the three minerals were measured in order to study their wettability nature and thereby validate the DFT results. Sodium oleate solutions of different concentrations were allowed to adsorb on the minerals, and corresponding contact angles with water were measured. As shown in Fig. 10, contact angles for each mineral increase as the oleate concentration increases. Beyond an oleate concentration of 200 g/t, contact angle doesn’t change much. At all concentrations of oleate, contact angle of magnetite is higher compared to the other two, which suggests that it adsorbs oleate
Fig. 10. Contact angle of hematite, magnetite and goethite with water.
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the best and develops significant hydrophobic character. Contact angle of goethite doesn’t increase beyond 41◦ , which explains why it doesn’t float well even at a sodium oleate concentration of 300 g/t. These results are in agreement with the DFT simulation results. 4. Conclusion Plane wave density functional calculations were carried out to study the interaction of oleate with hematite, magnetite, and goethite. Possible adsorption configurations for oleate on most stable and most exposed surfaces of these metal oxide surfaces were determined by carrying out Monte Carlo searches of the configurational space of the substrate-adsorbate system using COMPASS force field, followed by ab-initio calculations. Adsorption energy calculations reveal that among all the mineral surfaces considered here, the most active surfaces for adsorption for each mineral were: magnetite (1 1 1), hematite (1 1 0), and goethite (0 1 0). Among these surfaces, oleate binds strongest on magnetite (1 1 1) followed by hematite (1 1 0) and goethite (0 1 0) with the adsorption energies of −432, −299, and −185 kJ/mol, respectively. Density of states calculations supported the metal-adsorbate binding phenomenon in terms of the shifts in the lowest electronic states. It is also noted that while in case magnetite and goethite the adsorption occurs over the most stable surfaces, in case of hematite it occurs on the one of the most exposed surface as indicated in XRD. The flotation studies of the three iron minerals show that, under identical conditions, the flotation recovery of magnetite is higher compared to hematite and goethite as predicted by the DFT results. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.apsusc.2014. 01.014. References [1] A.H. Peck, L.H. Ruby, M.E. Wadsworth, An infrared study of the flotation of hematite with oleic acid and sodium oleate, T. AIME (1966) 235–301. [2] J.G. Paterson, T. Salman, Adsorption of sodium oleate on cupric and ferric hydroxides, Trans. IMM 79 (1970) c91–c102. [3] M.I. Pope, D.I. Sutton, The correlation between froth flotation response and collector adsorption from aqueous solution. Part I. Titanium dioxide and ferric oxide conditioned in oleate solutions, Powder Technol. 7 (1973) 271–279. [4] R.D. Kulkarni, P. Somasundaran, Flotation chemistry of hematite–oleate system, Colloid Surf. 1 (1980) 387–405. [5] S.N. Yap, R.K. Mishra, S. Raghavanand, D.W. Fuerstenau, The adsorption of oleate from aqueous solution onto hematite, in: P.H. Tewari (Ed.), Adsorption from Aqueous Solutions, Plenum Press, New York, 1981, pp. 119–142. [6] H.J. Haselhuhn, S. Ennis, T.C. Eisele, S.K. Kawatra, Water chemistry effects on zeta potential of concentrated hematite ore, in: SME Annual Meeting, Feb. 24–27, 2013, Denver, CO, 2013, pp. 13–147, Preprint. [7] E. Potapova, Studies on the Adsorption of Flotation Collectors on Iron Oxides, Licentiate Thesis, Luleå University of Technology, Luleå, Sweden, 2009. [8] P. Roonasi, Adsorption and Surface Reaction Properties of Synthesized Magnetite Nano-Particles, Licentiate Thesis, Luleå University of Technology, Luleå, Sweden, 2007. [9] X. Zhou, S. Ni, X. Wang, F. Wu, Adsorption of sodium oleate on nano-sized Fe3O4 particles prepared by co-precipitation, Curr. Nanosci. 3 (2007) 259–263. [10] R.F. Jung, R.O. James, T.W. Healy, Adsorption, precipitation and electrokinetics processes in the iron oxide goethite–oleic acid-oleate system, J. Colloid Interf. Sci. 118 (1987) 463–472.
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