Molecular Treatment of Nano-Kaolinite Generations - Inorganic

Article Cite This: Inorg. Chem. XXXX, XXX, XXX−XXX

pubs.acs.org/IC

Molecular Treatment of Nano-Kaolinite Generations Attila Táborosi,†,⊥ Robert K. Szilagyi,*,‡ Balázs Zsirka,† Orsolya Fónagy,§ Erzsébet Horváth,*,† and János Kristóf∥ †

Institute of Environmental Engineering, University of Pannonia, P.O. Box 158, Veszprem 8201, Hungary Department of Chemistry and Biochemistry, Montana State University, P.O. Box 173400, Bozeman, Montana 59717, United States § Department of General and Inorganic Chemistry, University of Pannonia, P.O .Box 158, Veszprem 8201, Hungary ∥ Department of Analytical Chemistry, University of Pannonia, P.O. Box 158, Veszprem 8201, Hungary ‡

S Supporting Information *

ABSTRACT: A procedure is developed for defining a compositionally and structurally realistic, atomic-scale description of exfoliated clay nanoparticles from the kaolinite family of phylloaluminosilicates. By use of coordination chemical principles, chemical environments within a nanoparticle can be separated into inner, outer, and peripheral spheres. The edges of the molecular models of nanoparticles were protonated in a validated manner to achieve charge neutrality. Structural optimizations using semiempirical methods (NDDO Hamiltonians and DFTB formalism) and ab initio density functionals with a saturated basis set revealed previously overlooked molecular origins of morphological changes as a result of exfoliation. While the use of semiempirical methods is desirable for the treatment of nanoparticles composed of tens of thousands of atoms, the structural accuracy is rather modest in comparison to DFT methods. We report a comparative survey of our infrared data for untreated crystalline and various exfoliated states of kaolinite and halloysite. Given the limited availability of experimental techniques for providing direct structural information about nano-kaolinite, the vibrational spectra can be considered as an essential tool for validating structural models. The comparison of experimental and calculated stretching and bending frequencies further justified the use of the preferred level of theory. Overall, an optimal molecular model of the defect-free, ideal nano-kaolinite can be composed with respect to stationary structure and curvature of the potential energy surface using the PW91/SVP level of theory with empirical dispersion correction (PW91+D) and polarizable continuum solvation model (PCM) without the need for a scaled quantum chemical force field. This validated theoretical approach is essential in order to follow the formation of exfoliated clays and their surface reactivity that is experimentally unattainable. quantum mechanical methods.9,12−17,10,18−22 We wish to emphasize that only a rather limited set of modeling tools has been validated for exfoliated clay nanoparticles in contrast to crystalline clays, despite their emerging industrial interest.23−25 If we consider biomacromolecules as examples for soft materials and clay nanoparticles for hard materials, we can analogously define primary, secondary, and tertiary structures for the latter. The primary structure corresponds to the organization of [SiO4] and [AlO6] units that in kaolinite form honeycomb-like building blocks. Specific to the kaolinite family,

1. INTRODUCTION As the separation of layers (delamination) and the elimination of crystalline order (exfoliation) take place in phylloaluminosilicates, experimental techniques are lacking for following structural and compositional changes on going from an ordered crystalline to a molecular phase. This would be essential in modernizing the experimental design of working with exfoliated clay particles from a trial and error approach toward rationalized design principles. Computational modeling can fill this gap by providing atomic-scale electronic and geometric structural descriptions as well as energetics of clay reactivity. In several studies, we and others provided compelling evidence for the power of empirical force field,1−4 semiempirical,5−11 and © XXXX American Chemical Society

Received: April 1, 2018

A

DOI: 10.1021/acs.inorgchem.8b00877 Inorg. Chem. XXXX, XXX, XXX−XXX

Article

Inorganic Chemistry

have e-HO− groups regardless of whether they are attached to a Si4+ or an Al3+ ion, while at acidic pH e-H2O groups may be present. Independent of the pH, the e-H2O group coordinates to Al3+ ion at A- and C-chain sites, while the a-O2− groups remain nonprotonated. At acidic pH, e-HO− is attached to the Si4+ center without the presence of Si4+−e-H2O coordination. Follow-up computational simulations paralleled the above predictions with some peculiarities with respect to the protonation state of a-O2− ions. A DFT study of uranyl ion adsorption on kaolinite28 using periodic slab models indicated that all groups are protonated at the (01) edge to give Al3+coordinated e-H2O groups, e-HO− coordinated to the Si4+ ion, and, in contrast to models from crystal growth theory, a-HO− groups between Al3+ and Si4+ sites. A more detailed ab initio molecular dynamic investigation29 into the atomic-scale structure of kaolinite edges in the presence of explicit water solvation focused on the (01), (10̅ ), and (10) edges. They found evidence for the presence of both five- and six-coordinate Al sites at (01) and (10) edges, while only the latter was observed for the (1̅0) edge. On the basis of an analysis of the H-bonding network formed during the simulations, it was proposed that the T sheet is terminated by e-HO− groups at all edges, in agreement with the crystal growth theory predictions. Furthermore, the a-O2− ions at the (01) and (10) edges are converted to e-HO− or even to e-H2O, while they remain nonprotonated at the (1̅0) edge. The s-HO− groups become protonated to give e-H2O at (01) and (1̅0) edges but remain eHO− at the (10) edge. A more recent study of the (01) edge in montmorillonite and kaolinite using ab initio molecular dynamics estimated the acidity constant of surface groups.30 It was found that stable edge sites include Si−(e-HO−) and Al−(e-H2O/e-HO−) coordination environments at the (01) edge. A comparison of experimental and calculated acidity constants for Si−(eHO−) (pKa = 6.9) and Al−(e-HO−) (pKa = 5.7) are in qualitative agreement with experimental findings; therefore, the study assigned these to be the dominant acidic sites at the edges. In contrast, the pKa value for Si−(e-H2O) coordination is negative (−6.7), while the pKa value of Al−(e-H2O) is predicted to be 0.2. Moreover, an acid−base titration study of kaolinite31 revealed the presence of amphoteric edges, which was explained by the e-HO− groups at the Al sites adopting various protonation states. It was found that, in addition to a modest ion-exchange process between H+ and Na+ ions, the protonation and deprotonation of (e-HO−) groups at Al sites take place in the acidic and alkaline regions, respectively. The protonation of Si−(e-HO−) groups is not likely to happen above a pH of 3.5; thus, the silica surfaces remain anionic. Further increase in the pH renders Si−(e-HO−) groups deprotonated at above pH ∼8. The pH of “zero net proton charge” (ZNPC) state of kaolinite was identified to be pH ∼6.0−6.5 that we approximate in our models. Clay nanoparticle suspensions at pH values higher than those of the ZNPC state can trigger deprotonation of (e-HO−) groups at both the Si and Al sites, which results in negative edge charges at both the O and T sheets. In parallel to the protonation state of nano-kaolinite edges from the literature, we provide an overview of experimental vibrational features from Fourier transform infrared (FTIR) spectroscopy for both crystalline and exfoliated phases.32−36 This nondestructive, rapid, and efficient structural technique has a crucial importance in characterizing nano-kaolinite particles, given that the crystalline order along the ‘c’

these honeycombs together define tetrahedral (T) and octahedral (O) sheets. The sheets are covalently connected through shared apexes to form TO layers. The ways the strong interlayer hydrogen bonds hold the TO layers together define their secondary structure. Their tertiary structure can be correlated with the stunning morphological variability of TO layers that can be manifested in chips, platelets, half-tubes, bowls, or scrolls depending on composition, nanoparticle size, and importantly the experimental conditions of preparation. The goals of the current work were to develop and validate atomic scale, quantum chemical computational models for generations of nano-kaolinite with ideal, defect-free composition. Using these models, we have successfully described the primary and secondary structural features and reactivity of nano-kaolinite particles18,19,21,22 that have proven to be elusive for experimental structural interrogation tools with the exception of vibrational spectroscopy. We lean on the latter technique in the given study as well, since it provides us with a direct experimental handle to rigorously validate the computational models, their stationary structures, and characteristic stretching/bending vibrational modes. A foundation of the given work has been reported for molecular cluster models employing cationic (Na+ and Mg2+) termination.19 These models were developed by employing coordination chemical principles for selected inner-sphere environments and their outer spheres. For surface adsorption and reactivity, the foci of interest are the central Al and Si honeycombs. From a systematic validation of 3D crystalline and 2D slab periodic models and computational level of theories, we found that all evaluated density functionals (GGA, hybrid GGA, meta-GGA) gave comparable structures with less than 0.1 Å and 5° deviations for bond lengths and angles, respectively. However, this agreement was only achievable for the nano-kaolinite molecular cluster models as long as a large triple-ζ quality basis set was used (def2TZVP).21 Not surprisingly, the research questions to be tackled with molecular cluster models quickly grew out of applicability of our “zero generation” models. We needed neutral, preferably proton-terminated computational models, where structural optimization and chemical reactivity studies can be carried out without any artificial geometric constraints for the peripheral neutralizing charges.22 Taking advantage of symmetry and order in the crystalline phase, we formulate mathematical rules here for constructing models for clay nanoparticles for any arbitrary generation of molecular clusters, where the generation rank is defined by the number of spheres of Al and Si honeycombs considered for the reactive part of the nanoparticle. A nontrivial task for the model construction was the definition of the protonation states of kaolinite nanoparticle edges. The bridging oxides (b-O2−), apical oxides (a-O2−), inner hydroxides (i-HO−), and surface hydroxides (s-HO−) of the “bulk phase” have well-defined protonation states. However, the dangling oxide ions and hydroxide groups at the edge of the nanoparticle can remain deprotonated (e-O2−), be singly protonated (e-HO−), or form an edge-coordinated water (e-H2O) ligand. A relevant experimental study by White et al.26 employed crystal growth theory to characterize the edge sites in phylloaluminosilicates. They organized the similar sites into “chains” (A−C) and considered the protonation states of the corresponding sites within a broad pH range. The A- and C-chains are equivalent to (1̅1, 1̅0, 1̅1̅) edges, while the B chain describes the (01, 01)̅ edges.27 At neutral pH, all B-chain sites B


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Inorganic Chemistry

of the vibrational features in nano-kaolinite,37−44,22 since band positions and intensities show variations depending on sample source, morphology, and experimental conditions for exfoliation (Table S2). In nano-kaolinite, the two peaks at 3667−3670 and 3648− 3653 cm−1 show reduced intensity and may even disappear upon exfoliation in comparison to crystalline samples. In some cases, a new peak may appear at 3645 or 3657 cm−1.37,39,41 The positions of peaks corresponding to ν(i-HO−) and ν(s-HO−) are 3620 and 3695 cm−1, respectively, generally blue shifted by a few wavenumbers. The δ(HO) band at 940 cm−1 usually decreases in intensity or can also disappear upon exfoliation.44 For example, Franco et al. observed an intensity decrease for the ν(HO) and δ(HO) bands as a result of delamination by ultrasound treatment of kaolinite.45 The apical ν(Si−O) band at 1099−1107 cm−1 usually shifts to higher wavenumbers by 5−15 cm−1, and a new band appears at 1090−1092 cm−1, while the bands at 1008 and 1033 cm−1 remain unchanged.37,41 The shift of the ν(Si−O) band to higher frequencies is also an indication of the exfoliation of kaolinite.45 Despite the substantial experimental data, a computational vibrational analysis lags in assisting spectral assignment due to its modest accuracy to date. A good starting point to correlate experimental and calculated vibrational spectra is the work of Bougeard et al. with modest applicability for the characterization of kaolinite organo complexes due to considerable inaccuracies in calculated ν(HO) and δ(HO) band positions and intensities.46 Benco et al. were the first to provide theoretical insights into vibrational spectra of an exfoliated TO layer.47 In addition to the crystalline models of kaolinite and dickite, they also simulated a slab periodic model for a single TO layer using quantum molecular dynamics simulation. As we also found for the nonperiodic cluster models,18 they proposed the presence of a folded-in or parallel H−O bond with the TO layer for an ideal, defect and external chemical environment free model, which oscillates between the horizontal and vertical orientations. Their vibrational analysis of the hydroxide stretching indicated the presence of an envelope of three bands that can be broken down into four different modes with differences between dickite and kaolinite crystal models. The ν(i-HO−) modes for the isolated TO layer, dickite, and kaolinite were calculated to be 3860, 3865, and 3880 cm−1,47 respectively, which is a range of values that cannot be reconciled with the rather unperturbed position of this band from experiments (3625 ± 5 cm−1, Tables S1 and S2). Depending on the orientation of the s-HO− group, its stretching frequency was either blue-shifted by approximately 100 cm−1 or red-shifted by 80 cm−1 relative to the i-HO− band (3860 cm−1) for the perpendicular (3960 cm−1) or the horizontal (3780 cm−1) position, respectively. An experimentally relevant correlation was recognized with respect to direct structural information from vibrational spectroscopy, since the ν(HO) frequencies decrease monotonically with the length of the OH···O distance in H bonding. For a hydroxide group involved in three H bonds, the stretching frequency correlates with the averaged distance over all three OH···O bonds. Another notable effort for characterizing crystalline kaolinite at the quantum chemical level was by the developers of the Crystal suite of software for periodic systems,48 who employed a hybrid DFT B3LYP method to resolve four ν(HO) modes but overestimated the band positions by 200−250 cm−1. However, using ideal, defect-free models, they were not able to resolve the controversial Raman-active, fifth ν(HO) mode that

crystallinity direction is eliminated upon exfoliation. Conventional powder X-ray diffraction (XRD) techniques are no longer applicable for gaining information about interlayer distances. However, there is a price to be paid when FTIR is used for nano-kaolinite, which is essential due to the elimination of the quasi-3-fold symmetry of the reactive hydroxide groups resulting in spectral shifts and significant intensity variations, which we will discuss here. We can recognize characteristic changes to band intensity ratios and broadening; however, the interpretation of these changes and deviations from reference values are not straightforward. An added complication is the presence of inhomogeneity in defect sites and morphology; thus, all experimental spectra shall be considered to a varied degree of mixture of states. This is well represented by the most characteristic stretching and deformation vibrational modes for crystalline (Table S1) and exfoliated kaolinite (Table S2) samples. Despite its limitations, to date the most insightful technique is undoubtedly FTIR spectroscopy to study the reactive hydroxide groups and defect sites (given that they are in high enough concentration). Raman scattering spectroscopy is also applicable; however, it is not considered a routine measurement for the nano-kaolinite. The Raman intensities of stretching and deformation modes of hydroxide groups are rather small due to the group’s small polarizability; the requirement for using a liquid N2 cooled CCD detector and custom-designed optics further limits its applicability. It is a proposal of the given study that the assignment and interpretation of spectral features can greatly benefit from computational modeling that in turn can translate spectra into structural information. In the case of the crystalline sample (all data in Table S1 assume book-type morphology), the three s-HO− groups and one i-HO− group contribute to four sharp bands that can be observed in the hydroxide stretching region, ν(HO), of 3620− 3697 cm−1. The ν(i-HO−)band is at 3620 cm−1, and the three ν(s-HO−) bands are the coupled stretching modes at 3695− 3697 (intense in-phase symmetric stretching), 3668−3670, and 3649−3652 cm−1 (all three are weak out-of-phase stretching bands). Exclusively in the case of highly ordered kaolinites, a fifth stretching band can be observed at 3686 cm−1 for ν(sHO−), which is usually infrared inactive but Raman active. The deformation mode of the surface hydroxides, δ(s-HO−), is observed at 930−940 cm−1, while the inner hydroxide band, δ(i-HO−), is at 914 cm−1. The corresponding hydroxide translation bands can be found in the ranges of 790−795 and 754−755 cm−1. Furthermore, bands are observed for the Si−O stretching at 1115−1120 cm−1 for the Si−(a-O2−) bonds and 1084 and 1055−1056 cm−1 for the Si−(b-O2−) bonds. Si−(bO2−)−Si in-plane stretching can be found at 1033−1034 and 1000−1010 cm−1. The Si−(b/a-O2−) deformation (δ(SiO)) is found at 740−800 cm−1. Perturbations to band positions and intensities encode structural and even compositional changes that can be correlated with atomic-scale structural information. Upon exfoliation, the TO layers undergo morphological changes, as individual layers separate and edges curl up and potentially form nanoscrolls. This affects the bond lengths and angles within the TO structure, which has also been recognized at the atomic level from computational studies.18 As a consequence, the s-HO− groups lose their H-bonding with bO2− ions from the neighboring T sheet of an adjacent TO layer; thus, they engage in a complex network of weak interactions with the external chemical environment.21 These structural changes upon exfoliation greatly complicate the interpretation C


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Inorganic Chemistry

Table 1. Summary of Composition (Oxide Content, w/w %), Mass Loss on Heating (ign loss, w/w %), Contaminations and Mineral Compositions (w/w %), Kaolinite/Halloysite ratio (K/H), Specific Surface Area (SSA, m2 g−1), and Hinckley Indices (HI) for the Studied Clay Samples kaolin (K) sample SiO2 Al2O3 Fe2O3 K2O Na2O MgO CaO TiO2 ign loss quartz K:H:other other minerals SSA HI label

Dillon, MT 54 23 9 0.4 0.1 0.2 0.5 0.9 8.28 >0 n/a hematite, ilmenite n/a 1.5 DK-9

Petény, Hungary 56 22 7 1.1 0.1 0.6 0.3 n/a 8.46 >0 n/a muscovite, orthoclase, albite, siderite 20.4 1.4 PK-7

Surmin, Poland 52.1 34.1 0.60 0.60 0.10 0.10 0.10 0.60 11.80 12 83:0:4 muscovite, orthoclase 10.3 1.4 SuK-0.6

Zettlitz, Czech Republic

Szegilong, Hungary

46.23 36.76 0.88 0.66 n/a 0.28 0.80 0.05 13.36 2 91:0:7 muscovite

46.73 33.94 3.21 0.22 0.10 0.15 0.55 0.06 14.12 3 46:49:2 feldspar

19.4 0.8 ZK-0.9

31.3 0.3 SzK-3.2

Fluka, Germany 47.06 37.34 0.46 0.34 0.08 n/a n/a 0.35 11.61 3 94:0:2 muscovite, orthoclase 8.2 1.3 FK-0.5

Halloysite (H) Balikesir, Turkey 46.55 37.10 0.53 0.03 0.03 0.23 0.08 0.04 13.31 1 4:95:0

105.6 n/d H-0.5

was washed using toluene at room temperature for 2 h to ensure maximum exfoliation. The exfoliated nano-kaolinite samples were washed with acetone, 2-propanol, and deionized water to reduce the surface-adsorbed intercalation reagents. Before the samples were dried and powdered, they were repeatedly exposed to 5% H2O2 aqueous solution to eliminate adsorbed organic compounds. In parallel with untreated kaolinite/halloysite samples, we also carried out the exfoliation of acid-washed samples due to the presence of transition-metal (especially iron) oxides, as was evident from the red, salmon, and light pink colors of DK-9, PK-7, and SzK-3, respectively. These samples were acid washed using warm (30 °C) concentrated HCl (35−37%) and stirred in a closed vessel for 6 h. Upon acid treatment, they were rinsed with deionized water until reaching neutral pH, centrifuged, and dried at 110 °C. Powder XRD (Figure S1) and FTIR (Figures S8, S9, and S12) measurements confirmed a negligible effect of the brief and nonaggressive acid treatment on crystallinity and banding (HI) and on the unperturbed nature of various hydroxide groups. The exfoliated nanoclay samples were further characterized by scanning and transmission electron microscopy imaging, as has already been reported in our previous publications.22,25,42−44 2.3. FTIR Spectra and Deconvolution of Spectral Features. FT-IR spectra were recorded on a Bruker Vertex 70 type spectrometer at the Surfaces and Nanostructures Laboratory, University of Pannonia, Veszprem, Hungary, using a diamond Bruker Platinum Attenuated Total Reflectance (ATR) sample stage. The spectra were recorded with a resolution of 2 cm−1 using a room-temperature deuterated triglycine sulfate (DTGS) detector by averaging 512 scans. After careful consideration of baseline subtraction, the spectra were fit using a mixture of Gaussian and Lorentzian line shapes as implemented in PeakFit (Seasolve, Version 4.12).53 The number of peaks was determined by the number of minima in second-derivative spectra. Smoothing to the spectra was applied to less than a 5% level of the Savitzky−Golay algorithm. With the exception of high-Fe-content samples, the baseline correction did not pose any mentionable challenges. The most reasonable final fits are provided in Figures S7− S13 and Tables S4−S6. Given the large number of peaks and corresponding spectral intensities (defined by total area under a resolved feature versus peak amplitude only), we calculated an intensity-weighted frequency value as a holistic index to characterize a specific spectral region. Due to a multitude of variables that were beyond our control, including but not limited to degree of exfoliation, partial rearrangement of exfoliated nanoclays to delaminated pseudocrystalline particles, particle size distribution, flexibility of the

is assigned to the inner hydroxide. Disagreements between experiment and theory were also observed for the δ(Si−O−Si) band in the 1000−1100 cm−1 range. Thus, to date the experimentally sound reproduction of vibrational spectra has not yet been achieved due to both the dependence of the results on the level of theory and the composition of the computational models employed.

2. EXPERIMENTAL AND COMPUTATIONAL DETAILS 2.1. List of Samples. A list of samples and their crystallinity indices, Fe contents, and sources of origin is summarized in Table 1. Labels H and K represent halloysite and kaolinite minerals, respectively, in their crystalline, untreated natural form. The prefix “n” in front of H or K indicates an exfoliated, nanoparticle state. Oxidative and acidic surface treatments are indicated by “+H2O2” and “+HCl” suffixes, respectively. The suffix “+Q” stands for extended heat treatment. The number separated by a dash stands for the Fe content (Fe w/w %). Abbreviations used for sample origins are as follows: Fluka kaolin from Sigma-Aldrich/Germany Lot No. BCBF3412 V (F), Surmin, Poland (Su), Zettlitz (Sedlecký), Czech Republic (Z), Szegilong, Hungary (Sz), Felső petény, Hungary (P), and Dillon, MT, USA (M) and a hydrated form of halloysite from Balikesir, Turkey (T). The Hinckley index (HI)49−51 cannot be determined for halloysite due to the missing characteristic XRD peaks owing to its thick-walled nanoscroll morphology. Furthermore, the HI is known to be distorted in the presence of quartz, feldspar, illite, smectite, and iron oxides/gels;52 however, its use is widespread for characterizing ordering and crystallinity. The three major groups of crystallinity/ ordered states of the given samples are as follows: (i) HI < 0.6 is not ordered, (ii) 0.7 < HI < 1.0 is moderately ordered, and (iii) HI > 1.0 represents high crystallinity. 2.2. Exfoliation Procedures. The employed synthetic procedure to prepare exfoliated nano-kaolinite samples were as reported earlier.42,22 In brief, a precursor is prepared first by mixing CH3COOK (KAc) and crystalline kaolinite/halloysite in a 30:70 mass ratio, in ambient air for 3 days. Afterward, the kaolinite−KAc intercalate was dried at 110 °C for 12 h and immediately exchange-intercalated with ethylene glycol (EG) using contact heating and stirring at 150 °C under an Ar atmosphere for 2 h. The dried kaolinite−EG intercalate was then subjected to another step of exchange intercalation with hexylamine (HA) at room temperature and stirring under an Ar atmosphere. The HA treatment was repeated twice for kaolinite and three times for halloysite. The resulting dried kaolinite−HA intercalate D


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Inorganic Chemistry

Figure 1. First three generations (G1−G3) of molecular cluster models for nano-kaolinite with groups, ions, and centroid identified for the central Al and Si honeycombs in G1 (A), edge regions defined for G2 (B), and the largest (G3) model (C) treated at the quantum level. TO layer and morphological variability, and the presence of Fe and other transition-metal structural ions, we will limit the detailed analysis only for the characteristic ν(Si−O) region, while the results for all other spectral ranges are summarized in Table S7. 2.4. Computational Modeling. The initial structures of all computational models were based on the experimental crystal structure of kaolinite54 that included refined H atomic positions. The model construction steps for any generation of a nano-kaolinite model are described in the first part of the Results and Discussion. Extreme care was taken to map the protonation state dependence of the potential energy surface while maintaining charge neutrality in all models. Figure 1A illustrates the inner sphere of the Al and Si honeycombs that were used to evaluate the structural differences among the semiempirical and DFT methods employed in the given study. The surface hydroxide groups were labeled as α- and β-s-HO− groups to differentiate between their geminal (α) or vicinal (β) positions, respectively, relative to the closest i-HO− group. Furthermore, the proximal (p) and distal (d) labels differentiate between hydroxyl groups pointing inward or outward, respectively, relative to the centroids of the central Al or Si honeycombs. The latter honeycombs are defined by the six surface hydroxides (XsO) and six bridging oxides (XbO), respectively. Figure 1B defines the two-digit Miller indices used for characterizing the edges of an ideal (defectfree) hexagonal nano-kaolinite particle. Figure 1C illustrates the largest (third-generation) nano-kaolinite molecule that can be treated at a semiempirical quantum chemical level for a reasonable computational cost. The computational levels of theory considered included pure-GGA (PW9155,56), meta-GGA (TPSS57,58), and hybrid-GGA (B3LYP59,60) functionals. Previously we have emphasized the importance of employing a triple-ζ quality basis set, such as def2TZVP;61,62 however, we demonstrate here that a smaller double-ζ quality basis set with polarization functions (SVP63,64) approaches well the basis set saturation limit with respect to potential energy surface and its first and second derivatives. In addition to the highest level of theory, we also carried out semiempirical calculations using the PM7 Hamiltonian65 with polarizable continuum model (COSMO,66,67 ε = 78) as implemented in MOPAC201668 and the density functional tightbinding approach (DFTB69) in the code DFTB+.70 In the ab initio DFT calculations, we used both Grimme’s dispersion correction (D71,72) and polarizable continuum model (PCM73,74) with default water solvent parameters as in the Gaussian09 suite of programs.75 The vibrational analysis was carried out for the entire secondgeneration (G2) model upon unconstrained structural optimization. Given that lower-generation models have an excessive edge/surface

ratio relative to experimentally studied nanoparticles, we only used the Hessian matrix elements (achieved by the ReadForceConstant keyword) without reconverging the wave function for the atoms that belong to the inner-sphere Al and Si honeycombs ([Al6(s-HO−)12(iHO−)4(a-O2−)8Si6(a-O2−)12]; Figure 1A). For the sake of completeness, Figure S6 provides the spectral comparison of the entire model and the inner-sphere Al and Si honeycombs only. The experimental line shape was approximated by a Gaussian (G)−Lorentzian (L) Amplitude Sum function from Peakfit53 with ratio G:L = 1. Visualizations of the molecular structures were carried out using ChemCraft76 and DS ViewerPro77 programs. Additional electronic supporting information with atomic positional coordinates of each model discussed and electronic spreadsheets for spectral analysis are provided at 10.5281/zenodo.1195746.

3. RESULTS AND DISCUSSION 3.1. Mathematical Rules Governing the Composition of Molecular Cluster Models. The periodicity of the kaolinite crystal structure was exploited to define a set of mathematical rules that determine the number, charge, and atomic positions of (i) Al3+ and Si4+ cations, (ii) b-O2−, a-O2−, i-HO−, and s-HO− anions and groups, and (iii) neutralizing counterions (protons here) at the edges of the nanoparticle. These rules can be employed to define any generation (as defined by the number of concerted Al and Si honeycomb spheres) of a nano-kaolinite in an automated procedure for symmetry-adapted positions of each atomic center. 3.1.1. Number of Cations. The first three generations of nano-kaolinite models contain 24, 72, and 144 Al3+ and Si4+ ions, respectively. These numbers can be correlated with the number of Al and Si honeycombs of 1, 7, and 19, respectively. A graphical fit (see Figure S2) defines a second-order analytical relationship among the Al3+ and Si4+ numbers (NAl3+, NSi4+) and the generation ranking (i): NAl3+, NSi4+ = 6(i + 1)i. The number of cations define the total cationic charge as the sum of qAl3+ = +18(i + 1)i and qSi4+ = +24(i + 1)i. 3.1.2. Number of Oxides and Hydroxides. Let us consider the number of O2− anions in the first three generations, such as 72 (G1), 198 (G2), and 378 (G3). As illustrated in Figure S2, the relationship between the generation ranking (i) and the number of oxide anions (NO2−) is less trivial though: NO2− = 9(3i + 5)i with a negative charge contribution of qO2− = −18(3i E


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Inorganic Chemistry

Table 2. Ionic Compositions (Al3+, Si4+, O2−, and H+) as a Function of Generation Rankinga and the Size of the Quantum Description Defined by the Total Number of Electrons O2− Al G1 G2 G3 G4 Gi a

N q N q N q N q N q

3+

12 +36 36 +108 72 +216 120 +360 6(i + 1)i 18(i + 1)i

Si

4+

12 +48 36 +144 72 +288 120 +480 6(i + 1)i 24(i + 1)i

−

s-HO

i-HO

24

8

−

a-O2−

b-O2−

H+

16

24

44

66

84

126

32 +32 88 +88 168 +168 272 +272 4(3(i + 1) + 2)i

−144 66

22 −396

126

42 −756

204

68

136 −1224 9(3(i + 1) + 2)i −18(3(i + 1) + 2)i

204

total no. of electrons

overall charge

960

−28

2700

−56

5220

−84

8520

−112

(390i + 570)i

−28i

N and q represent the number of ions and total charge associated with them, respectively, and i is the generation rank.

Table 3. Comparison of Key Internal Coordinates for the Central Al and Si Honeycombs in the G2 Model of Exfoliated NanoKaolinite as a Function of Basis Set and Type of Density Functional Employed density functional, basis set values relative to PW91/SVP PW91/SVP s-HO− orientationa XfHO···O−H(αp-s-HO−) (deg) XfHO···O−H(βd- s-HO−) (deg) XfHO···O−H(βp- s-HO−) (deg) XfHO···O−H(αd- s-HO−) (deg) XfHO···O−H(βp- s-HO−) (deg) XfHO···O−H(βd- s-HO−) (deg) Al−O(s-HO−) (Å) Al−O(i-HO−) (Å) Al−O(s-HO−)−Al (deg)

NNENEN 4 175 85 175 88 176 1.91(0) 1.92(0) 101(0) 103(1)

Al−s-O2− (Å) O(s-HO−)···O−H(i-HO−) (deg) b-O2−···H(i-HO−) (Å) b-O2−···H−O(i-HO−) (deg)

1.96(1) 134 2.59 137

Si−O(a-O2−) (Å) Si−O(b-O2−) (Å) Si−O(b-O2−)−Si (deg)

1.66(0) 1.65(1) 137(1) 134(2)

PW91/def2TZVP

TPSS/SVP

O-Sheet Internal Coordinates NNENEN NEENEN +2 +4 −2 −55 +3 −3 −1 +2 +1 −4 −2 −26 −0.01(0) −0.01(1) −0.01(0) +0.00(1) 0(0) 0(1) 0(1) +1(1) Intersheet Internal Coordinates 0.00(2) −0.01(1) +1 0 +0.03 −0.13 +4 +15 T-Sheet Internal Coordinates −0.02(0) −0.01(0) +0.02(0) −0.01(1) +4(1) +1(0) +1(2) 0(6)

TPSS/def2TZVP

B3LYP/SVP

B3LYP/def2TZVP

NEENEN +3 −71 −1 −2 0 −1 −0.01(1) −0.01(0) 0(0) +1(1)

NEENEE +5 −56 −4 −4 −6 −59 −0.02(1) −0.01(0) +1(1) +2(0)

NEENEE +9 −58 −2 −6 −5 −60 −0.03(1) −0.01(0) +1(1) +3(0)

−0.01(2) +1 −0.01 ++9

0.00(2) +3 +0.03 +4

−0.01(5) −3 0.02 +7

−0.02(0) −0.02(0) +4(0) +1(4)

−0.01(0) −0.01(1) +3(0) −3(5)

−0.03(0) −0.03(0) +6(0) −3(4)

N stands for nucleophilic or “folded in” orientation, while E stands for electrophilic or “erected” orientation relative to the plane of the O-sheet (see ref 21. for discussion on s-HO− group orientation).

a

+ 5)i. The number of protons for surface and inner hydroxide groups in the first three generations are 32 (G1), 88 (G2), and 168 (G3), which results in an analytical relationship of NH+ = 4(3i + 5)i with qH+ = +4(3i + 5)i positive charge contribution. A further breakdown of the anionic groups allows us to exactly define the number of surface hydroxides (3(3(i + 1) + 2)i), inner hydroxides (1(3(i + 1) + 2)i), apical oxides (2(3(i + 1) + 2)i), and bridging oxides (3(3(i + 1) + 2)i) as a function of generation ranking (i) that correlate with their number of ligands coordinated to an Al3+ or a Si4+ center. Table 2 provides a comprehensive overview for the number and charge contributions of each ions and groups of a nano-kaolinite particle corresponding to the first four generations and in any generation ranking.

The mathematical rules for the composition and charge in Table 2 define an overall anionic nanoparticle with a charge of −28i for the ith generation that needs to be neutralized in order to construct a defect-free, neutral nanoparticle with coordinatively saturated cationic sites. An alkali-metal and alkaline-earthmetal cation-based neutralization has been explored,18,19 and it was found that use of Na+ and Mg2+ ions is ideal with respect to size and ionic/covalent interactions with the nano-kaolinite edges. Admittedly, introduction of a field of cations around the nanoparticle can limit the application of the molecular cluster model in exploring potential energy surfaces and guiding experimental work. 3.2. Validation of an Economical Double-ζ Basis Set with Polarization Functions (SVP). Earlier, we pressed for F


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complementary study, we also employed the PM6 semiempirical Hamiltonian81 without the polarizable continuum solvent model as implemented in Gaussian09 with a more robust potential energy mapping algorithm in comparison to that in MOPAC2016. In both cases, we observed unreasonable redox chemistry, i.e. formation of O−O bonds (peroxide groups), and hydrogenation of Al or Si sites, which indicated that neither of the semiempirical Hamiltonians are robust enough to handle the highly negatively charged nanoparticle without departing from an experimental sound potential energy surface. An ab initio protonation state analysis would be the ideal; however, due to the complexity of the protonation potential energy surface, we utilized literature examples for the initial placement of protons. 3.3.2. Literature-Guided Protonation State Analysis. First, we considered the composition of the nano-kaolinite model as a guide to where to place and how many protons to neutralize the G2 nanoparticle. All dangling Al3+ and Si4+ ions from the peripheral sphere (second outer sphere relative to the central honeycombs) were replaced by a single proton or a pair of protons, respectively. The distance between protons was set to be at least 1.5 Å (initial G2-B; Supporting Information). While all heavy atoms were kept frozen, the PM7/COSMO method was used to refine the positions of the manually added protons only with frozen heavy-atom positions. The optimized G2-B model (Supporting Information) featured numerous coordinated water (e-sH2O) molecules at all edges, e-aH2O/e-bH2O at the (10) edge, and e-bHO− formed at all the edges. The closest match to literature examples can be achieved when 24 protons are added to e-sHO− (e-sH2O), 8 protons to e-aO2− (e-aHO−), and 24 protons to e-bO2− (e-bHO−) (initial G2-C structure; Supporting Information). It was remarkable to realize that this protonation state is a stationary structure and no tautomerism was detected. The optimized G2-C structure was approximately 340 kJ mol−1 lower than G2-B at the PM7/COSMO level. Thus, we establish a rule for the number and location of protons in an arbitrary generation (Gi) of nano-kaolinite, such as i(4[a-O2−] + 12[b-O2−] + 12[s-HO−]) to give 12i surfacebound H2O at the O sheet, 12i bridging HO− at the T sheet, and 4i apical HO− between the O and T sheets. 3.3.3. Monte Carlo Refinement of Protonated Edges. In order to further evaluate the robustness of the literature-guided protonation procedure for neutralization of the nano-kaolinite molecule, we applied various magnitudes of random displacements to the atomic positional coordinates of all the 56 neutralizing protons in the range of 0.1−0.5 Å displacements in 0.1 Å steps and at least five times for each step. Structural perturbations with less than 0.5 Å displacements all converged back to the initial protonation state of the neutral G2 nanoparticle model (optimized G2-C; Figure 2A). However, when the magnitude of random displacements was increased to 0.5 Å, we obtained two different structures (G2-C1 and G2-C2) that were more stable (ΔESCF = −104 and −65 kJ mol−1, respectively) than the optimized G2-C. Despite the considerable energetic differences, the structural differences are small, since in G2-C1 two pairs of e-bHO− groups interacted and exchanged protons to form e-bO2− and e-aH2O at the (10) edge, e-bO2− and e-aH2O at the (01) edge, and e-sHO− and eiH2O at (10̅ ) (Figure 2B). The structural changes are almost the same in the G2-C2 (Figure 2C) structure, but only one pair of e-bO2− and e-H2O groups is formed at the (10) edge. Interestingly, when the energies of G2-C1 and G2-C2 structures were evaluated at a higher level using single-point density

the need for at least a triple-ζ quality basis set for reasonable geometric structure, relative energies, and reactivity regardless of the employed density functional theory. As summarized in the column of number of electrons in Table 2, the G2 model is already borderline computationally prohibitive in routine work due to the presence of close to several thousands of electrons. We carried out an exploration of additional basis sets78,79 with the goal of saving computational cost for structural optimizations and vibrational analysis at a full ab initio quantum level for the G2 model. Table 3 reports the results for only the most relevant levels of theory. The atomic positional coordinates for each optimized structure are provided in the Supporting Information. In order to guide the eye, the results obtained at the reference PW91/SVP level of theory are given in absolute values (second column in Table 3), while the rest are given as relative values to the reference. As described earlier for molecular cluster models with explicit cationic counterions,18,19,21 all bond lengths and bond angles deviate only by less than 0.03 Å and 6°, respectively, regardless of the density functinal theory employed. However, intermolecular distances and angles for secondary structural features and those related to the morphology of the nanoparticle now show considerable deviations, especially in the orientation of the s-HO− groups (nucleophilic/folded in versus for electrophilic/erected) and position of the i-HO− group. The key observation related to the given study is the small (0.02 Å and 3°) to negligible (0.01 Å and 1°) difference between the previously considered saturated triple-ζ quality basis set (def2TZVP) and a smaller double-ζ quality basis set (SVP). The computational time is reduced to merely 5% (Figure S3) when using the smaller, yet still saturated, basis set with respect to geometry. It is also important to highlight that the computational time saving allowed for completing vibrational analysis for the entire G2 model without any truncation or simplification (see below). 3.3. Protonation State of Nano-Kaolinite Edges. In earlier studies,80,18,21 we demonstrated that the first-generation (G1) model is too small to describe the structure and energetics of either Al or the Si honeycombs. Therefore, we use the second-generation model (G2) in the given study, where the inner-sphere honeycombs are surrounded by six outer-sphere honeycombs that are appropriately terminated according to the basic rules of coordination chemistry.18 As shown in Table 2, this procedure results in uncompensated negative charges (−28i, where i represents the generation rank). Earlier19 we achieved neutralization using Na+ and Mg2+ ions at fixed positions as replacements for peripheral Al3+ and Si4+ ions, respectively. Hereby, we define general rules for the protonation of edge oxide and hydroxide groups to give a neutral nanoparticle using various strategies in close agreement of experimental and computational considerations discussed in the Introduction. 3.3.1. Ab Initio Protonation State Analysis. A trivial approach to evaluate the energetically most favorable protonation state of the edges of nano-kaolinite particles using the G2 model is to consider the completely deprotonated G2 model. This highly charged model with a total charge of −56 was soaked in a bath of water molecules with 673 molecules (G2-A structure; see the Supporting Information). Given the computational cost, we selected the PM7 semiempirical Hamiltonian65 with COSMO solvation model67 that has been shown to give reasonable structures and even energetics for crystalline and nano-kaolinite.19,21 As a G


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Inorganic Chemistry

Figure 3. Changes in the protonation states (highlighted with thick circles) at the nano-kaolinite edges among G2-D (A), G2-D1 and G2D2 (B and C), G2-E (D), G2-E1 and G2-E2 (E and F) structures using the PW91+D/SVP/PCM method, with partial (only the edge H+) and fully optimized structures (a = apical, s = surface, i = inner, b = bridging). Only the O-sheet configuration is shown here for the sake of clarity (see Figure S4 for both honeycombs).

Figure 2. Changes in the protonation states at the nano-kaolinite edges (highlighted by thick circles) for models G2-C (A), G2-C1 (B), and G2-C2 (C) structures using the PM7/COSMO method and partial geometry optimization of only the manually added H+ at the edges (a = apical, s = surface, i = inner, b = bridging).

functional theory (PW91+D/SVP/PCM), the relative energies changed to ΔESCF = −41 and +27 kJ mol−1. This shows the limitation of using a semiempirical PM7 method in energetic comparisons. Thus, we considered the full optimization of all the protons (88 centers, G2-D; Figure 3A) at the reference PW91+D/SVP/PCM level, which reversed the tautomerism process at the (10) edge, but maintained the presence of a ebO2−/e-aH2O pair at the (01) edge at ΔESCF = −44 (G2-D1; Figure 3B) and −37 kJ mol−1 (G2-D2; Figure 3C) relative to optimized G2-C (Figure 2A). Due to the variability of the protonation states and corresponding relative energies, we questioned the validity of partial structural optimizations with frozen heavy atoms. Starting from the PM7/COSMO optimized G2-C1, full structural optimizations at the PW91+D/SVP/PCM level resulted in the formation of two pairs of e-iH2O/e-sHO‑ groups from e-iHO−/e-sH2O groups at (10) and (1̅0) edges and one pair of e-aH2O/e-sHO− at the (10) edge with a final optimized energy of ΔESCF = −26 kJ mol−1 (G2-E1, Figure 3E). The G2E2 structure (Figure 3F) resulted in four pairs of e-iH2O/esHO− group formation at (10), (1̅0), and (1̅1̅) edges with lower energy in comparison to G2-E1 (ΔESCF = −84 kJ mol−1). It is important to highlight that the inner- and outer-sphere honeycombs are highly similar in all G2 models. However, there

are considerable differences among the peripheral (dangling) groups at the edges that may cause significant energetic differences. The most common feature of structural optimization is the rotation and displacements of Si tetrahedrons, which results in proton-transfer processes as various e-HO− groups approach or dissociate from each other (Figure 3D, G2-E, versus Figure 3A, G2-D). We find the G2-E2 model (Figure 3F) to be the lowest energy structure with a protonation rule of i(4[a-O2−] + 12[b-O2−] + 10[s-HO−] + 2[i-HO−]), where i stands for the generation ranking. To the credit of earlier reports in the literature, the lowest energy structure (G2-E2) is only different from the literature-based G2-C structure in 4 proton positions (Figure 2A). In G2-E2, the protons are added to 2 e-iHO− groups at (10), 1 e-iHO− group at (10̅ ), and 1 eiHO− group at (1̅1̅) edges. For the sake of a complete analysis, we have carried out a limited Monte Carlo perturbation of the G2-E2 model and found stationary structures for tautomers, but none were found to be lower in energy (see G2-E3-1 and G2E3-2 at ΔESCF = +11 and +17 kJ mol−1; Figure S5). 3.4. Equilibrium Structure of Molecular Cluster Models. For the sake of completeness, we provide the computational results for the first-generation (G1) computaH


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Table 4. Comparison of Key Internal Coordinates for the Central Al and Si Honeycombs for the neutral, G2-D2 Model (see Figure 3C for Protonation State) of Exfoliated Nano-Kaolinite as a Function of a Comprehensive Set of Level of Theory in the Gas Phase and Polarizable Continuum Solvation Model (PCM)a level of theory values relative to PW91+D/SVP/PCM PW91+D/SVP/PCM sHO− orientationa XsHO···O−H(αp-sHO−) (deg) XsHO···O−H(βd-sHO−) (deg) XsHO···O−H(βp-sHO−) (deg) XsHO···O−H(αd-sHO−) (deg) XsHO···O−H(βp-sHO−) (deg) XsHO···O−H(βd-sHO−) (deg) Al−O(s-HO−) (Å) Al−O(i-HO−) (Å) Al−O(s-HO−)−Al (deg)

Al−a-O2− (Å) O(s-HO−)···O−H(i-HO−) (deg) hO···H(i-HO−) (Å) hO2−···H−O(i-HO−) (deg) Si−O(a-O2−) (Å) Si−O(b-O2−)−Si (deg)

PW91/SVP

B3LYP/SVP

B3LYP+D/SVP/PCM

Internal Coordinates at the O Sheet NEENEE NNENEE NNENEE NNENEE 4 −3 +1 +2 94 +73 +53 +42 81 +12 −12 −4 173 −4 −3 +3 87 −5 +3 +1 90 −2 +12 +5 1.90(1) +0.02(2) +0.01(2) −0.01(1) 1.92(1) −0.01(1) −0.02(1) 0.00(2) 99(0) +1(1) +2(1) +1(0) 102(1) 0(1) +1(2) +2(0) Internal Coordinates from the Inner Environment of the TO Layer 1.95(2) −0.01(2) −0.01(1) 0.00(2) 126 +4 +9 +1 2.88 −0.08 −0.09 −0.03 136 +7 +13 −1 Internal Coordinates at the T Sheet 1.66(0) +0.02(1) +0.01(2) −0.01(0) 1.65(1) +0.00(1) −0.01(0) −0.01(1) 144(1) +2(1) +5(0) +2(1) 131(1) +2(1) +3(1) +1(1)

SCC- DFTB

PM7/COSMO

EEEEEE +42 +31 −27 −43 −32 +35 0.00(0) −0.03(0) +8(0) +4(1)

NNNNNN +195 −55 +44 +26 +63 −50 +0.02(3) +0.08(2) +4(1) +33(2)

−0.05(0) +50 −0.02 +17

−0.17(0) +105 +1.54 +5

+0.01(0) −0.02(1) +9(1) +3(1)

−0.12(0) −0.06(0) −4(1) +11(2)

Abbreviations: N, nucleophilic or “folded in” orientation; E, electrophilic or “erected” orientation relative to the plane of the O sheet. For further discussion about s-HO− group orientations and honeycomb centroids XsHO, see ref 21.

a

Figure 4. Definition of the considered structural parameters to determine the curvature (R) of the tubular nano-kaolinite, where d(O) and d(T) represent the diameters of the Al and Si honeycombs, respectively, and h stands for the thickness of the TO sheet.

using updated atomic positional coordinates from scaled displacement vectors of the negative vibrational frequency. Due to already considerable computational costs, we did not investigate further the possibility of using finer integration grids in order to obtained true equilibrium structures. It is important to emphasize that the reproduction of the inner hydroxide position and orientation from the inner environment of the TO layer (middle section, Table 4) and the orientation of the surface hydroxide (top section, Table 4) is critical, since these are sensitive to the external chemical environment18 and thus provide a link between theory and experiment. In addition to the selected internal coordinates in Table 4 describing the coordination geometry of ions and groups of the central honeycombs, we also considered the tertiary structure or morphology of the nano-kaolinite model. Figure 4 graphically illustrates and Table 5 summarizes the honeycomb diameters for both O and T sheets, d(O) and d(T), the thickness of the TO layer as measured by the Al···Si distance (h), and the curvature (R) of the nanoparticle. These notations were adopted from a meticulous analysis of high-resolution TEM images of exfoliated nano-kaolinite with tubular

tional model (Supporting Information) at the PW91+D/SVP/ PCM level; however, the previously observed, unwanted structural changes19,21 were all reproduced. The G1 model should be simply avoided, since the edges or peripheral atoms are electronically too close to the inner-sphere honeycomb. The e-H2O molecules at the O sheet dissociate to form fivecoordinate Al 3+ sites that are rarely detected in the literature.82,83 These results further emphasize the inadequacy of numerous truncated, G1-like molecular cluster models from the literature in modeling the structure and reactivity of nanokaolinite particles. Unconstrained optimizations of an ideal, defect-free G2 nanokaolinite model were carried out at four different levels of theory in order to cover semiempirical quantum chemical methods (wave function based PM7 and density functional tight-binding, DFTB), pure and hybrid GGA density functionals. The PW91-D/SVP/PCM level and both calculations with a hybrid functional (B3LYP) gave small imaginary normal modes (−69 cm−1 at the PW91+D/SVP/PCM level and −45 cm−1 at B3LYP/SVP level) involving groups from the periphery. These modes remained even after repeated restarts I


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Inorganic Chemistry Table 5. Deviation (Δ) of Morphological Descriptorsa Calculated at Various Levels of Theory for the G2 Model of Exfoliated Nano-Kaolinite experimental (HRTEM)84 Δ(PM7/CPCM) Δ(SCC-DFTB) Δ(PW91/SVP) Δ(PW91+D/SVP/PCM) Δ(B3LYP/SVP) Δ(B3LYP+D/SVP/PCM)

d(T) (Å)

d(O) (Å)

h (Å)

R (Å)

8.93 −0.02 +0.13 +0.29 +0.22 +0.22 +0.23

8.62 +2.39 +0.36 +0.19 +0.12 +0.31 +0.17

4.37 −1.06 −1.22 −1.18 −1.2 −1.2 −1.2

121.5 −139.8 +232.1 −53.0 −53.9 +7.2 −46.2

along diagonal lines in Figure 5A. Quantitatively, this results in an effective surface charge of the central Al honeycomb ([Al6(sHO−)12(i-HO−)2(a-O2−)6]4+) at the O sheet of only +0.25 e−. On the opposite side, the surface charge of the Si honeycomb ([Si6(b-O2−)12(a-HO−)6]18‑) at the T sheet is a dramatic −8.75 e− due to the protruding b-O2− groups. This in combination with a honeycomb−honeycomb distance of 3.2 Å (thickness from Table 5) defines a large dipole of 28.6 D with a negative end pointed at the T sheet. This causes a considerable electrostatic repulsion among the ionic centers of the T sheet that pushes them apart, which in turn triggers the curving of the nano-kaolinite. 3.5. Comprehensive FT-IR Investigation of Crystalline Kaolinite and Exfoliated Nanoparticles. To date, the given comprehensive data from the same laboratory obtained under close to identical experimental conditions for nano-kaolinite/ halloysite samples allow for the critical assessment of spectral changes as a function of degree of exfoliation and rearrangement, morphology, particle size, surface defects, contaminations, and presence of organic intercalating reagents. We compare and contrast in Figure 6 and Figures S7−S13 and Tables S4−S6 nano-kaolinite and nano-halloysite samples with identical primary and secondary structures. Table S3 provides an overview of peak positions in close agreement with those in Tables S1 and S2. Throughout this process, we need to keep in mind that considerable differences are present in their morphologies.42,44 We selected the nano-halloysite (crystalline H-0.5 and exfoliated nH) sample as a reference due to its homogeneous composition with minimal defects and contamination and uniform thin-walled nanoscroll morphology. Organic compounds used in exfoliation stabilize the molecular state; however, upon oxidative cleaning with peroxide (nH+H2O2) pseudocrystallinity emerges due to rearrangement into a delaminated state with a varied degree of order. In parallel with XRD and TEM characterizations,47 this can also be seen by the FTIR spectral changes at the top of Figure 6 by line broadening and shift of bands. Additional samples are organized into three groups for the sake of discussion with regard to contaminations (mineral content and Fe numbers) and structural order (HI index). Group I consists of SuK-0.6 contaminated by quartz with a tubular highly ordered morphology (HI = 1.4), ZK-0.9 with moderate crystallinity, negligible mineral contamination, and tubular morphology (HI = 0.8), and SzK-3.2 with low crystallinity (HI = 0.3), high Fe/ Ti contamination, and pseudohexagonal morphology. Group II contains samples that show high crystallinity (FK-0.5, HI = 1.3 and nanoparticle derivatives) and considerable Fe contamination and pseudohexagonal morphology. In contrast to the previous samples, FK-0.5 readily undergoes rearrangement to adopt a loosely organized delaminated morphology. Group III is composed of high-Fe-content kaolins, such as DK-9 (pseudohexagonal morphology, HI = 1.5) and PK-7 (HI = 1.4). We provide more discussions about the ν(HO) stretching region (Figure 6A) below when considering the result of the atomic level from computations. The greatest benefit of these spectral features is in linking FTIR measurements and computations despite their weak and often poorly resolved features (Figures S7−S13). Their use for direct structural comparison is burdened by superimposing effects including morphological differences, contamination from structural Fe and presence of quartz, sample preparation procedure, and the

a See ref 84 for the mathematical definitions: d = diameters of T and O honeycombs, h = thickness of TO layer, R = radius of curvature. The experimental values are based on high-resolution transmission electron microscopic images.

morphology. 84 Note that a large curvature (R) value corresponds to a flat nano-kaolinite particle (DFTB), while a negative absolute value (PM7) represents an inverted shape (O sheet outside and T sheet inside of a nanoscroll) versus the proposed curvature with O and T sheets forming the inside and outside surfaces, respectively. Table 5 may suggest that the hybrid B3LYP functional provides the best agreement with the experiment; however, we need to keep in mind that our computational model corresponds to an ideal, defect-free nanokaolinite without any absorbed organic molecules used during the exfoliation procedure. The smaller radius and thus tighter curvature for the PW91 calculations can be considered as a limit that a pure TO layer can adopt. As discussed below by the sharp contrast in electrostatic interactions for the T and O sheets, the curvature is reduced by the presence of organic molecules and even water solvation.21 The electrostatic potential maps of the fully optimized G2 nanoparticle provide a clear explanation for the preferred rolling of the nano-kaolinite to form a tubular morphology with the O-sheet facing inside the nanoscroll, in addition to the geometric differences among the tetrahedral Si4+ ion containing T sheet and the octahedral Al3+ ion containing O sheet. The kaolinite crystal has an overall zero effective dipole moment, given that the symmetrically alternating TO layers extinguish the individual dipole moment of the layers. However, upon exfoliation the O sheet becomes dominantly positively charged/electrophilic, while the opposite is true for the T sheet. It is also interesting to note already from Figure 5A that the alternating folded (nucleophilic) and erected (electrophilic) s-HO− groups create a pattern of red- and blue-shared areas

Figure 5. Electrostatic potential map calculated at the reference PW91+D/SVP/PCM level for the G2 model of nano-kaolinite using Merz−Singh−Kollman85,86 electrostatic potential fitted charges: (A) top view of O sheet; (B) bottom view of T sheet. Blue indicates electrophilic sites such as the erected s-HO− groups, while red indicates nucleophilic sites such as the folded s-HO− and the b-O2− groups. J


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reference. An additional consideration is the surface selection rules that fundamentally influence the spectral intensities and band line shapes.87 Therefore, in the experimental section we will focus on the regions corresponding to Si−O stretching modes. The considerably lower reactivity of the T sheet in comparison to the O sheet is a boost to use the Si-based vibrational modes as spectral indicators for structural and compositional change. The band positions and intensity ratios can be well correlated with changes in the degree of exfoliation and rearrangement, as can be seen in Figure 6B. By looking at the overall trends for all the samples, we can recognize that the surface treatment and exfoliation clearly cause a reduction in the intensity ratio of bands (area under the peaks) at 1000 and 1027 ± 5 cm−1. Upon oxidative surface cleaning and rearrangement of the nano-kaolinite layers toward a more ordered, delaminated state, this intensity ratio gradually increases. Spectral broadening and intensity changes are directly related to morphological changes and perturbations due to the Al ↔ Fe substitutions on the O sheet. The tubular/scroll-like morphology (nZK-0.9) shows much less rearrangement than the pseudohexagonal plate/chip morphology (nFK-0.5). The high-Fe-content natural kaolin samples from Group III give the lowest exfoliation efficiency (estimated from XRD peak intensities to be about 60%) among all studied kaolins; thus, there is only a modest variation in the ν(Si−O) region. Furthermore, we observed line shape broadening in the ν(Si−O) region (950−1100 cm−1) as the results of surface modifications and exfoliation, given that the flexibility of the T sheet increases. The heterogeneity of morphological changes are due to “wadded” surfaces and distribution in the curvature of scrolls and tubes. Given that this region has intense spectral features and is least affected by other stretching or bending modes, we defined a similarity index from the intensityweighted frequency average (υ)̅ of resolved spectral features, as summarized in Table 6. The υ̅ values for other spectral regions, but with less straightforwardly interpretable behavior, are shown in Table S7. For example, the υ(OH) region does not ̅ give any meaningful correlation with the above three groups, since changes appear to lack any trend. Similarly, the δ̅(OH) region does not show any trend as a function of surface treatment or at least not more than the uncertainty of baseline subtraction, fitting, and peak deconvolution. For a comprehensive overview, we also provided the changes (Δ in cm−1) in comparison to various references. A negative deviation from the reference can be taken as indicative of greater flexibility of the T sheet due to weaker Si−O bonds and vice versa. There are only partial trends in the υ(Si−O) similarity index ̅ for the crystalline, untreated kaolin samples in the Δ(H-0.5) column of Table 6 due to nonsystematic sample-to-sample variations. However, the nano-kaolinite samples and especially those with acidic or oxidative surface treatment result in more flexibility, as can be followed from the Δ(nH) values in Table 6 (most dominant for Group I and II samples). This can be rationalized by the considerable morphological differences between the well-organized, thin-walled scrolls for nanohalloysite versus the pseudohexagonal, platy nano-kaolinite. It is also remarkable to compare the last column in Table 6, which shows the differences among exfoliated and surface-treated samples in comparison to their crystalline, untreated form. Without exception, the Si−O stretches increase as an indication of a more rigid structure. This is unexpected for the nanokaolinite, given that upon exfoliation particles behave more like

Figure 6. FTIR-ATR spectra of nano-kaolinite and nano-halloysite samples in the (A) HO stretching (3300−4000 cm−1) and (B) SiO stretching and OH and SiOAl bending (650−1350 cm−1) range. Color coding: ν(s-HO−), blue; ν(i-HO−), red; ν(Si−O/Fe-O), orange in (A) and black in (B); ν(Si−O), brown in (A) and red in (B); δ(HO) and δ(SiOAl/Si), green. Band positions are based on second-derivative minima. Approximate positions of ill-resolved features are given in parentheses.

employed energy transmission (heating, stirring, microwave treatment) during exfoliation.47 The morphological variations (pseudohexagonal platelets, chips, scrolls, half-pipes, etc.) directly affect the intra- and intermolecular interactions of the reactive surface hydroxide groups. Thus, their stretching frequencies and intensities can widely vary. The presence of surface-adsorbed organic molecules and any changes in the outer chemical further perturbs the IR bands of the s-HO− groups. This is also true for the position and intensity of i-HO− groups, which can be mistakenly taken as an internal FTIR K


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Inorganic Chemistry Table 6. Comparison of Similarity Index Values (υ̅, cm−1) for the ν(Si−O) Region (950−1200 cm−1) and Relative Values (Δ, cm−1) To Reference Crystalline and Exfoliated States between and within Various Sample Preparations sample

υ̅ (Si−O)

H-0.5 H-0.5+Q nH-0.5 nH-0.5+H2O2

1008 1019 1014 1015

ZK-0.9 nZK-0.9 nZK-0.9+H2O2 SzK-3.2 nSzK-3.2 nSzK-3.2+H2O2 SuK-0.6 nSuK-0.6 nSuK-0.6+H2O2

1008 1014 1011 1010 1011 1015 1005 1014 1018

FK-0.5 nFK-0.5 nFK+HCl nFK+H2O2

1003 1007 1008 1015

PK-7 nPK-7 DK-9 nDK-9+HCl nDK-9

1014 1014 1019 1020 1034

Δ(H-0.5)

Δ(nH)

Δ(crystalline)

reference +1

reference +11 +6 +7

Reference reference +11

Group I 0

−1 +3

reference +6 +3 reference +1 +5 reference +9 +13

−7 −7 +1

reference +4 +5 +12

0 −3 +2 −3 +1 −3

Group II −5

Group III +5 −1 +10 +6 +19

literature values and assignments are summarized in the Introduction and Table S1−S2. Our analysis of the dependence of spectra on sample source, crystallinity, contaminations, and particle size, after treatment upon exfoliation, is presented in section 3.5. Here we highlight the comparison of our data for FK-0.5 and DK-9 as the closest pseudohexagonal, platy nanokaolinite to our computational models. They also show representative changes in peak positions and intensities for comparing experiment to theory. An important difference between the experimental nanoparticles and theoretical models is that in the latter we only deal with a stationary structure with a given arrangement of ions and groups. Without Monte Carlo or molecular dynamics calculations that are computationally prohibitive at the most desirable level of ab initio DFT theory we cannot consider the pliability of the TO layer and a distribution of stretching and bending modes. Therefore, we wish to focus on the highest energy ν(HO) region that corresponds to the strongest intramolecular valence-type interaction and also that we have shown to be a sensitive probe of the interplay of TO-layer structure and outer chemical environment. An initial look at the calculated and experimental spectra show an acceptable qualitative agreement between the envelope of vibrational excitation levels and the experimental spectra. This is particularly true regardless of the employed line broadening to the calculated spectra (solid and dashed lines in Figure 7) for the stretching region as long as the PW91, pure GGA functional is used. As observed earlier in the literature (CRYSTAL03),48 the hybrid functional B3LYP blue-shifts the bending spectral features by approximately 20 cm−1. The functional dependence of band positions is even more exaggerated for the high-energy region of ν(HO) modes by at least 100 cm−1 regardless of whether we employ dispersion correction or not (top two calculated spectra in Figure 7). However, it is worth noting the similar effect of dispersion correction and the presence of a polarizable continuum for both B3LYP and PW91 functionals, which is the increased spread of the ν(HO) modes (Δ = 185 → 246 cm−1 for PW91 and 169 → 208 cm−1 for B3LYP). The presence of explicit water solvent molecules at the surface (middle spectra, Figure 7) slightly perturbs ν(i-HO−) by at most 10 cm−1. The small change can be taken as a justification of using the ν(i-HO−) frequency as a diagnostic feature for crystalline kaolinite and nano-kaolinite. A direct comparison of the experimental and calculated spectra using the PW91+D/SVP/PCM level of theory and the assignments of the bands reveals a key difference. Using the ideal, defect-free G2 model of nano-kaolinite we obtain three well-defined ν(HO) modes corresponding to s-HO− stretches parallel (lowest energy) and perpendicular (highest energy) to the TO layer. Between, one can find the i-HO− stretching mode. This energy ordering is maintained at any and all levels of theory that we considered. In contrast, the experimental spectra for nano-kaolinite show only two intense features with numerous weaker peaks or shoulders between that are resolved to a varied extent. In experimental spectra the lower energy feature is assigned to the ν(i-HO−) mode, while the remaining features are assigned to the ν(s-HO−) mode. This would indicate that for a realistic nanoparticle the folded-in or nucleophilic s-HO− with respect to the TO layer and the H bonding network, respectively, should not exist. We have already learned from calculations18,21 that the orientation of the s-HO− groups is greatly influenced by the external chemical environment. Furthermore, experimental results show44 that

reference 0 reference +2 +15

Q represents heat treatment at 150 °C, for 24 h. bSee Table 1 for sample nomenclature.

a

molecules. If we consider the experimental84 and calculated (Table 5) morphologies, the T sheet becomes stretched out and thus accumulates strain, as the nanoparticles curve into bowl, half-pipe, or scroll shapes. This is in contrast to the O sheet, which undergoes a larger scale structural rearrangements as the Al3+ ions sink toward the middle of the TO layer and the surface hydroxide groups rotate and rearrange.18 For samples in Group III with high Fe content, we had explored fitting various ranges (850−1100/1200 cm−1 to 950−1100/1200 cm−1) for the ν(Si−O) range given the presence of Fe-based vibrational modes (1163−1165 cm−1). We found that for a given spectral range the trends remained unchanged, while they varied among various ranges. However, this introduced a somewhat higher uncertainty in defining the baseline, yet it is unambiguous that the surface treatment for DK-9 increased the similarity index. In contrast, the unchanged υ(Si−O) values can be correlated ̅ with the low exfoliation efficiency for both the high Fe content and the unfavorable particle size distribution of crystalline SzK3.2. 3.6. Computational Vibrational Analysis of Molecular Cluster Models. As emphasized before, we employed FTIR spectroscopic data to validate the adequacy of the computational model as well as the accuracy of various levels of theory. While the frequency calculations were calculated for the entire second-generation molecular cluster model, results in this section are only limited for the central honeycombs. These were obtained by considering the upper left corner of the Hessian matrix containing the block of inner-sphere atoms. The L


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Inorganic Chemistry

Figure 7. Comparison of experimental (nDK-9 and nFK-0.5) and calculated vibrational spectra for the stretching (3300−4000 cm−1) and deformation (650−1350 cm−1) regions. Insets on the right-hand side indicate the normal-coordinate displacements for all four IR intense ν(HO) modes: folded-in/horizontal ν(s-HO−), purple; ν(i-HO−), red; erected/perpendicular ν(s-HO−), blue; surface-bound water ν(H2O) to a H-bond acceptor folded-in s-HO− ,green. Color coding for the bending region: ν(SiO), brown; δ(HO) and δ(SiOSi/Al), orange. Solid and dashed lines in the simulated spectra correspond to 50 and 25 cm−1 line broadening, respectively.

upon exfoliation the nano-kaolinite (nano-halloysite in the study) particle is stabilized by adsorbed organic molecules (approximately 0.6 w/w % from thermal analysis)22 employed during the intercalation and exfoliation processes. Upon peroxide treatment, the nano-kaolinite regains its crystalline state, as can be judged by the appearance of a broad powder diffraction peak at slightly larger interlayer distances (lower 2θ diffraction peaks) in comparison to the crystalline kaolinite.44 This would mean that the experimental spectra in Figure 7 without peroxide treatment correspond to a scenario where all s-HO− groups are erected as they interact with organic reagents. It is important to consider here the selection rules for surface vibrations88,89 and the cancellations of the dipole moment change. These contribute to IR inactivity of the folded s-HO− group when it is coupled to the i-HO− group, as they point in opposite directions during an asymmetric, in-phase stretching vibration. However, this is unlikely for the nano-kaolinite, since the TO layer undergoes considerable reorganization and adopts a curved shape even for a small, 2 nm nanoparticle (see radius of curvature R in Table 5); thus, the OH group stretches cannot be parallel with the “ab” plane. Furthermore, the chemical environment can directly influence the orientation and position of the i-HO− group through the open cavity of the Si honeycomb, as has been demonstrated by modeling.21

The deviations of calculated morphological parameters at the PW91+D/SVP/PCM level in Table 3 from experiments were rationalized by the absence of a strongly interacting environment. The curvature of the G2 nanoparticle is 54 Å more and the diameters of the Si and Al honeycombs are 0.3 and 0.2 Å greater, while the height of the TO layer is 1 Å smaller, than the experimental values obtained from TEM images of organic adsorbent stabilized nano-kaolinite particles. These also suggest that a realistic nano-kaolinite model should not have a measurable amount of “pure, defect-free” surface area that is not interacting with the external chemical environment. A closely relevant experimental work aiding the comparison of experimental versus calculated IR spectra for the ν(s-HO−) region is the study of intercalation of a low-crystallinity SzK using hydrazine hydrate (85 w/w %) reagent in aqueous solution with practically 100% efficiency, but only under strictly anaerobic conditions.90,91 Upon exposure to air, the intercalated hydrazine/kaolinite complex spontaneously decomposes to crystalline kaolinite, H2O, NH3, and N2. The decomposition process followed by FTIR measurements aids the assignment of the calculated spectral features. In the intercalated state, the ν(HO) region shows only a single peak at 3626 cm−1 that can be assigned to the overwhelming presence of hydroxide ions in the interlayer space as counterions to hydrazonium [NH2NH3]+ ions. Within a day, the intensity of this single, M


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Inorganic Chemistry sharp band vanishes and a single i-HO− band (3620 cm−1), two intense bands (∼3650 and ∼3690 cm−1), and at least two (∼3668 and 3677 cm−1) s-HO− stretching bands appear. The last four peaks undergo approximately ±5 cm−1 variations during the decomposition period of a few days as the surface reorganizes. There is a new feature emerging at 3600 cm−1, at lower wavenumber than the ν(i-HO−) mode, which could be correlated with the presence of folded-in/horizontal s-HO− groups. However, this band was unambiguously assigned to the presence of weakly interacting water molecules with the TO layer formed during a decomposition process from parallel thermal analytical measurements. Although the agreement between the experimental and PW91+D/SVP/PCM calculated spectra is already remarkable, the definition of a scaling factor can numerically further improve this according to a scaled quantum mechanical force field approach.92−94 Using the two intense experimental peaks and the last two peaks of the calculated spectrum, we can derive a two-point shifting and a scaling factor of −74 cm−1 and 99.4%, respectively, from the midpoints (experimental, 3656 cm−1; calculated, 3730 cm−1) and peak separations (experimental, 74 cm−1; calculated, 121 cm−1) or just a simple singlepoint scaling factor of 98.0%. A comparison of the experimental and the calculated spectra with water-covered nano-kaolinite models clearly indicates the absence of a significant water coordination at the O sheet, given the lack of a strong and characteristic water stretching bend right below the ν(HO) region. As the number of water molecules increases to provide full coverage of the inner-sphere Al honeycomb and both the Al and Si honeycombs, the drastically increased water stretching modes blur out the hydroxides from the OT layer. There is an unexpected peculiarity of the assignment of ν(HO) modes in the presence of surface-bound water that only theoretical calculations can reveal. The highest energy hydroxide stretching for the nanokaolinite was assigned to the s-HO− groups perpendicular to the TO layer (bottom inset, left-hand side of Figure 7). However, this assignment completely changes when the s-HO− group becomes an H-bond donor to a water molecule. As indicated by the top inset on the left-hand side of Figure 7, the highest energy H−O stretch is related to the water molecule from the first explicit solvation shell of the nano-kaolinite. Effectively, this water molecule becomes part of the surface via a remarkably strong H-bonding interaction. This chemical bonding situation can also be illustrated by a compositional change of the explicit solvent molecules becoming part of the nano-kaolinite molecule. The corresponding ν(s-HO−) mode shifts below the ν(s-HO−) mode and strongly mixes with the folded-in ν(s-HO−) mode. These variations have not been discussed in the literature; however, they are chemically meaningful when one considers how the H−O bond energy changes when it becomes involved in H bonding. Deviation from the hypothetical ideal surface without defect sites or adsorbed small organic molecules from the exfoliation process or the presence of explicit solvent molecules may result in even better agreement between calculated and experimental spectra. This is the subject of our future investigations in order to converge the computational results to be able to directly assign specific and/or unique spectral features and their perturbations with compositional and/or structural features.

4. CONCLUSIONS The lack of atomic-scale structural information about nanokaolinites hinders their rationalized design as emerging materials for catalytic, surface support, adsorbent, and separation applications. To overcome this limitation, we developed computational models for several generations of ideal, defect-free nanoparticles using coordination chemical construction rules for defining inner, outer, and peripheral spheres of Al and Si honeycombs. The honeycombs are considered as secondary structure units for nano-kaolinite due to their importance in describing adsorption events. We have shown the validity of the molecular cluster based modeling of nano-kaolinite using semiempirical and ab initio levels of theory. The most reasonable level of ab initio theory with respect to computational cost and accuracy was selected to be the PW91 set of “pure” density functionals with an economical double-ζ quality basis supplemented with polarization functions (SVP), dispersion correction, and a polarizable continuum model employing liquid water based parameters. The PW91+D/SVP/PCM reference level of theory can be readily applied for a G2 generation of nanoparticle of approximately 2 nm size that can already display morphological features, such as experimentally sound curvature. Semiempirical methods allow for the calculation of a G3 generation nano-kaolinite molecule with close to 800 atoms and 5500 electrons, but at a considerable loss of structural and energetic accuracy. In addition to geometric and electronic structures, the G2 model at the reference level can also provide an experimentally sound description of chemical adsorption, dehydration, and dehydroxylation processes as described in our earlier publications.18,19,21,22 Overall, we propose that the properties of exfoliated nano-kaolinite can only be fully described at the atomic level when molecular cluster models are employed that were developed in close correlation with experimental observations. Furthermore, we report here the progress made toward correlating FTIR vibrational spectra with compositional and structural changes that are obscured by experimental limitations. From a systematic comparative study of untreated and exfoliated kaolinite and halloysite samples, we established a database for the perturbations of characteristic FTIR bands (intensity, broadening, shifts) due to variations in the external chemical environment. These spectral changes are triggered by adsorption/desorption of organic molecules, the presence of the contaminating transition metal iron, and most importantly morphological changes. FTIR spectra of natural samples must always be considered as a sum of multiple components that imposes limits on spectral interpretations. However, variation of composition, structure, and the presence of adsorbed molecules for molecular nano-kaolinite models opens up a possibility for interpreting small, but significant, spectral changes. The computational models developed and the reference FTIR spectra compiled in the given work assists us in explaining (i) how chemical environments and morphology affect the intensity and position of hydroxide stretching modes, (ii) why defect sites formed during surface treatment and exfoliations do not show up in an FTIR spectrum despite the fact that their presence is a requirement for chemical reactivity, and (iii) the significant difference between the T/SiO4 and O/ AlO6 faces of a nano-kaolinite particle that results in curved morphology and starkly different behavior as an adsorbent. These differences must be considered when designing a N


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(2) Heinz, H.; Lin, T. J.; Mishra, R. K.; Emami, F. S. Thermodynamically consistent force fields for the assembly of inorganic, organic, and biological nanostructures: The INTERFACE force field. Langmuir 2013, 29 (6), 1754−1765. (3) Cygan, R. T.; Tazaki, K. Interactions of Kaolin Minerals in the Environment. Elements 2014, 10 (3), 195−200. (4) Makó, É.; Kovács, A.; Ható, Z.; Kristóf, T. Simulation assisted characterization of kaolinite-methanol intercalation complexes synthesized using cost-efficient homogenization method. Appl. Surf. Sci. 2015, 357, 626−634. (5) Gorb, L. G.; Aksenenko, E. V.; Adams, J. W.; Larson, S. L.; Weiss, C. A.; Leszczynska, D.; Leszczynski, J. Computational design of clay minerals: hydration of Mg-exchange cation located in ditrigonal cavity. J. Mol. Struct.: THEOCHEM 1998, 425 (1−2), 129−135. (6) Chernia, Z.; Gill, D. Flattening of TMPyP adsorbed on laponite. Evidence in observed and calculated UV-vis spectra. Langmuir 1999, 15 (5), 1625−1633. (7) Miranda, R.; Rios, H.; Delgado, F.; Castro, M.; Cogordan, A.; Salmon, M. Characterization of a bentonitic clay and its application as catalyst in the preparation of benzyltoluenes and oligotoluenes. Appl. Catal., A 2003, 244 (2), 217−233. (8) Letaief, S.; Diaco, T.; Pell, W.; Gorelsky, S. I.; Detellier, C. Ionic Conductivity of Nanostructured Hybrid Materials Designed from Imidazolium Ionic Liquids and Kaolinite. Chem. Mater. 2008, 20 (22), 7136−7142. (9) Guimaraes, L.; Enyashin, A. N.; Seifert, G.; Duarte, H. A. Structural, Electronic, and Mechanical Properties of Single-Walled Halloysite Nanotube Models. J. Phys. Chem. C 2010, 114 (26), 11358− 11363. (10) Lourenco, M. P.; Guimaraes, L.; da Silva, M. C.; de Oliveira, C.; Heine, T.; Duarte, H. A. Nanotubes With Well-Defined Structure: Single- and Double-Walled Imogolites. J. Phys. Chem. C 2014, 118 (11), 5945−5953. (11) da Silva, M. C.; dos Santos, E. C.; Lourenco, M. P.; Gouvea, M. P.; Duarte, H. A. Structural, electronic, and mechanical properties of inner surface modified imogolite nanotubes. Front. Mater. 2015, 2 (16), 1−10. (12) Martorell, B.; Kremleva, A.; Krüger, S.; Rösch, N. Density functional model study of uranyl adsorption on the solvated (001) surface of kaolinite. J. Phys. Chem. C 2010, 114 (31), 13287−13294. (13) Smrcok, L.; Tunega, D.; Ramirez-Cuesta, A. J.; Ivanov, A.; Valuchova, J. The combined inelastic neutron scattering (INS) and solid-state DFT study of hydrogen-atoms dynamics in kaolinitedimethylsulfoxide intercalate. Clays Clay Miner. 2010, 58 (1), 52−61. (14) Solc, R.; Gerzabek, M. H.; Lischka, H.; Tunega, D. Wettability of Kaolinite (001) Surfaces - Molecular Dynamic Study. Geoderma 2011, 169, 47−54. (15) Matusik, J.; Scholtzova, E.; Tunega, D. Influence of Synthesis Conditions on the Formation of a Kaolinite-Methanol Complex and Simulation of its Vibrational Spectra. Clays Clay Miner. 2012, 60 (3), 227−239. (16) Tunega, D.; Bucko, T.; Zaoui, A. Assessment of ten DFT methods in predicting structures of sheet silicates: Importance of dispersion corrections. J. Chem. Phys. 2012, 137 (11), 114105. (17) Greathouse, J. A.; Geatches, D. I.; Pike, D. Q.; Greenwell, C. H.; Johnston, C. T.; Wilcox, J.; Cygan, R. T. Methylene Blue adsorption on the basal surface of kaolinite: structure and thermodynamics from quantum and classical molecular simulation. Clays Clay Miner. 2015, 63 (3), 185−194. (18) Táborosi, A.; Kurdi, R.; Szilágyi, R. K. The positions of inner hydroxide groups and aluminium ions in exfoliated kaolinite as indicators of the external chemical environment. Phys. Chem. Chem. Phys. 2014, 16 (47), 25830−25839. (19) Táborosi, A.; Szilagyi, R. K. Realistic Molecular Cluster Models for Exfoliated Kaolinite. Clay Miner. 2015, 50 (03), 307−327. (20) Presti, D.; Pedone, A.; Mancini, G.; Duce, C.; Tine, M. R.; Barone, V. Insights into structural and dynamical features of water at halloysite interfaces probed by DFT and classical molecular dynamics simulations. Phys. Chem. Chem. Phys. 2016, 18, 2164−2174.

catalytically active kaolinite-based system, which is now aided by the current development of validated molecular cluster models.

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.inorgchem.8b00877. Analytical relationships for generation ranks and model composition; computational benchmarks, calculated vibrational spectra for the entire nanoparticles, exfoliations followed by XRD patterns, deconvoluted spectra, and numerical fitting parameters, and a literature review of characteristic stretching and bending modes of untreated and exfoliated kaolinite and halloysite samples (PDF)

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AUTHOR INFORMATION

Corresponding Authors

*E-mail for R.K.S.: [email protected]. *E-mail for E.H.: [email protected]. ORCID

Robert K. Szilagyi: 0000-0002-9314-6222 Present Address ⊥

A.T. is a postdoctoral research associate at the Institute of Quantum Beam Science, Graduate School of Science and Engineering, Ibaraki University, 2-1-1, Bunkyo, Mito 310-8512, Japan. Author Contributions

A.T. and B.Z. were the lead contributors to the modeling and FTIR work, respectively, and O.F. assisted the sample preparations and FTIR measurements. The experimental work was directed by E.H. and J.K., while the computational modeling was supervised by R.K.S. All authors participated in the analysis of the results and their interpretations. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS Access to powder X-ray diffraction and scanning electron microscopic instrumentation at iCal Laboratory, Montana State University, is acknowledged. Computational efforts were performed in part on the Hyalite High-Performance Computing System, operated and supported by University Information Technology Research Cyberinfrastructure at Montana State University. We acknowledge that financial assistance for travel funds by the Campus Hungary program to O.F. R.K.S. and A.T. were supported by the MTA-ELTE Chemical Structure & Function “Momentum” Laboratory (ID 96122) by the Hungarian Academy of Sciences, Budapest, Hungary (contract no. LP2015-10/2015). The financial support of the GINOP2.3.2-15-2016-00016 and GINOP-2.3.2-15-2016-00053 projects (cofinanced by the Széchenyi 2020 program) is acknowledged. B.Z. is thankful for the support of the Ú NKP-17-3 national excellence program of the Ministry of Human Capacities.

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REFERENCES

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Inorganic Chemistry

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Molecular Treatment of Nano-Kaolinite Generations - Inorganic

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