Mineral-Water Interface Structure of Xenotime - ACS Publications

Aug 6, 2018 - at DOI: XXXXXXX. Measured xenotime structure .... https://github.com/xraypy/tdl (Accessed Aug 6, 2018). 18. Trainor, T. P.; Templeton, A...
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C: Surfaces, Interfaces, Porous Materials, and is published by the American Chemical Society. 1155 Catalysis Sixteenth Street N.W., Washington, DC 20036 Subscriber access provided by Kaohsiung Medical Published by American University Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to

Mineral-Water Interface Structure of Xenotime is published by the American Chemical Society.{100} 1155 (YPO4) Sixteenth Street N.W., Washington, DC 20036 Subscriber access provided by Kaohsiung Medical Published by American University Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to

Andrew G. Stack, Joanne E. Stubbs, Sriram Goverapet Srinivasan, Santanu Roy,is Vyacheslav published by the American Society. 1155 S. Bryantsev,Chemical Peter J Eng, Sixteenth Street N.W., Washington, DC 20036 Subscriber access provided by Kaohsiung Medical Published by American University Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to

Radu Custelcean, Alexander D Gordon, and Cole R. Hexel published by the American J. Phys. Chem. C,is Just Accepted Chemical Society. 1155 Manuscript • DOI: 10.1021/acs.jpcc.8b04015 Sixteenth Street N.W., • Publication Date (Web): 08 Aug 2018 Washington, DC 20036

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Figure 4. Structure of the best fit to the CTR data. a) View along the bulk [010] (surface [100]) direction. Yttriums/cation impurities are shown in cyan, phosphorus in gray, oxygens on phosphate in red, and oxygens on water in black. The black arrows indicate the direction of rotation and translation of surface phosphates and cations in the relaxed best fit structure; annotations showing the magnitude of the relaxations are in picometers and degrees. Bond lengths for ordered water to surface sites are labeled on the left side of the figure (also in pm). The ellipsoid size and dimensions correspond to 70% probability for atom positions given the best-fit temperature factor. The waters show a range of motion flattened relative to surface normal. b) View along bulk [001] (surface [010]). 100x125mm (150 x 150 DPI)

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Figure 5. Lowest energy structure from DFT simulations, viewed along the a) [010] and b) [001] directions. Bond lengths are listed in picometers. Atom colors are the same as described in Figure 4. Water is bonded to surface yttriums, or donates a hydrogen bond to surface phosphates. 90x130mm (150 x 150 DPI)

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Mineral-Water Interface Structure of Xenotime (YPO4) {100}

Andrew G. Stack1*, Joanne E. Stubbs2, Sriram G. Srinivasan1, Santanu Roy1, Vyacheslav S. Bryantsev1, Peter J. Eng2,3, Radu Custelcean,1 Alexander D. Gordon1,4, Cole R. Hexel1

1. Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, 378316110, U.S.A. 2. Center for Advanced Radiation Sources, University of Chicago, Chicago, Illinois 60439, USA 3. James Franck Institute, University of Chicago, Chicago, Illinois 60439, USA 4. Current Address: Signature Science, LLC, Austin, TX * Corresponding author Corresponding author e-mail address: [email protected] Corresponding author phone number: 1-865-574-8450

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Abstract: Crystal Truncation Rod (CTR) measurements and Density Functional Theory (DFT) calculations were performed to determine the atomic structure of the mineralwater interface of the {100} surface of xenotime (nominally YPO4). This mineral is important because it incorporates a variety of rare earth elements into its crystal structure, which are critical materials necessary for a variety of renewable and energy efficient technologies. Current beneficiation techniques are not highly selective for REE ore minerals and large amounts go to waste; this is a first step towards designing more efficient beneficiation. Evidence is found for minor relaxation of the surface within the top-most monolayer with little or no relaxation in subsurface layers. Justification for ordered water at the interface is found, where water binds to surface cations and donates hydrogen bonds to surface phosphates. The average bond lengths between cations and oxygens on water are 228 pm in the best fit to the CTR data, versus 243 and 251 pm for the DFT. No agreement on water positions bound to surface phosphates is obtained. Overall, the findings suggest that ligands used in beneficiation with a single anionic head group, such as fatty acids, will have limited selectivity for xenotime relative to undesirable minerals.

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INTRODUCTION Rare earth elements (REE) are critical materials necessary for a variety of renewable and energy efficient technologies, such as wind turbine transmissions, electric vehicle traction motors, and phosphors for lighting.1 Yet, beneficiation of REE ore minerals using flotation is a difficult process where as much as half of the total rare earth elements in the ore go to waste.2 Research on this subject is often focused on empirical optimizations of the processes that determine the efficiency of a froth flotation, the primary method used for REE separations. In flotation, a surfactant known as a “collector” is adsorbed to a suspension of crushed ore. The goal is to make the surface of a target ore mineral more hydrophobic, whereas other ligands (“suppressors”) are used to make a gangue (waste) mineral surfaces more hydrophilic. Bubbles are introduced to the suspensions and the hydrophobic ore mineral particles segregate to the air-water interface and rise with the bubbles. Optimizations of this process include the adsorption isotherms of the surfactants, solution pH, zeta potentials of the minerals that makes up the ore body, and contact angle measurements.3 However, with a few notable exceptions,4,5 there is a dearth of fundamental information about the molecular-level structure, reactivity and reaction mechanisms of the relevant mineral-water interfaces involved in this process. Obtaining this fundamental understanding would allow us to identify the specific surface sites, if any, onto which surfactants bind during complexation and give a confirmed starting structure for rational design of new ligands that are more efficient at causing REE ore minerals to float while simultaneously being more selective for REE ore minerals over gangue. For example, this more fundamental approach has been applied to prevent scale-forming mineral nucleation,6 and has been used very successfully for liquid-liquid extraction to separate dissolved cesium-137 from waste streams.7 As an initial step towards creating that fundamental understanding for REE ore mineral flotation, here we have conducted Crystal Truncation Rod (CTR) measurements on the {100} surface of the mineral xenotime (YPO4) in solutions of varying pH, fit a mineral-water interface structure to the measured data, and compared the structure from the fit to Density Functional Theory (DFT) calculations. The results are a baseline to guide the design of new ligands with enhanced selectivity for REE ore minerals. Xenotime (nominally YPO4) was chosen as a study mineral because it is not currently processed as ore but may be attractive to produce as a co-product. In particular, its crystal structure often incorporates the heavier REEs (HREEs) as impurities.8 HREEs are more valuable because they tend to have higher supply risk1 and are more useful. Specifically, REE content in xenotime is ~85% heavier REEs such as terbium and dysprosium,9,10 both rated as having critical supply risk and highly important to clean energy.1 More generally, studying xenotime increases our understanding of how the surface structures of ionically-bonded minerals, and particularly phosphates, relax and react with aqueous solutions. Past CTR studies have focused on phosphate minerals with monovalent and divalent constituent cations: archerite (KH2PO4)11-13 and fluorapatite (Ca5(PO4)3F),14,15 respectively. This is the first CTR study we know of where both of the mineral's constituent ions are trivalent. The different surface relaxation behaviors of minerals containing ions of differing valency are contrasted and discussed in the results with the goal of beginning to describe structure-reactivity relationships. METHODS 3 ACS Paragon Plus Environment

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Sample Structure. Xenotime has a tetragonal structure (space group I41/amd) that typically displays prismatic morphologies consisting of {100} and {101} surfaces. The sample used here was from Bahia, Brazil and morphology is dominated by {100} surfaces. This surface consists of periodically bonded chains of cations (yttrium and impurities) and phosphate along the [001] and [010] directions. The structure and temperature factors of the crystal were determined at 173 K using a Bruker Apex single crystal X-ray diffractometer operated at 50 kV and 30 mA. The structure was refined on F2 using the SHELXTL software package. Absorption corrections were applied empirically based on multiple scans using SADABS. All atoms were refined anisotropically. The obtained unit cell dimensions are a = b = 6.8971(10) Å, c = 6.0326(9) Å, Z = 4. This is in excellent agreement with a published crystal structure for xenotime, a = b = 6.8947 Å, c = 6.0274 Å.16 The differences are likely due to the impurity content, which can be highly variable between samples, or perhaps differences in measurement temperature. Measured temperature factors were: oxygen Uiso = 0.0207, phosphorus Uiso = 0.0132, yttrium+impurity Uiso = 0.0076. These also compare favorably to the literature data of 0.01191, 0.00785, and 0.00576, respectively.16 To prepare for the CTR measurement, the sample was cored roughly perpendicular to the {100} growth surfaces to create a disc 5 mm diameter, 3 mm tall. The crystal was aligned within 0.06° of the {100} surface using a custom-built jig that allows for transfer of orientation from an X-ray diffractometer to grinding and polishing equipment. The sample was then ground and polished using diamond films and pastes, followed by colloidal silica suspension and cleaning with acetone, ethanol, and DI water. After polishing, sample root-mean-square roughness measured by atomic force microscopy was ~1 nm (2 × 2 µm image). Elemental Analysis. The rare earth elemental composition was determined using quadrupole inductively coupled plasma mass spectrometry (ICP-MS). The sample was digested using a Discovery SP Microwave (C.E.M. Corporation). A 200 mg sub fraction of material was placed into a 35mL Teflon lined quartz vessel along with 5ml of Optima© grade nitric acid (Thermo Fisher Scientific). The sample was digested for 10 minutes at a temperature of 200 oC and a pressure of less than 100 PSI. No visible material remained after digestion. A sub aliquot was diluted to yield a maximum signal in counting mode on the secondary electron multiple. For analysis, the sample solution was aspirated using a 100 uL/minute PFA nebulizer (Elemental Scientific Incorporated, ESI) through a PC3 (Elemental Scientific Incorporated, ESI) introduction system cooled to 2 o C. A XSeries2, (Thermo Fisher Scientific) ICP-MS was operated in collision cell technology (CCT) mode using 4% H/He mixed collision cell gas to determine the rare earth element ratios. Individual elemental ratios were method blank subtracted and mass bias corrected against natural abundance isotopic standards. The results are shown in Figure 1. Crystal Truncation Rod Measurements. Crystal Truncation Rod measurements were conducted at beamline 13-BM-C at the Advanced Photon Source. X-rays with an incident energy of 15 keV (λ = 0.8266 Å) were focused horizontally with a water-cooled, side deflecting Rowland circle Si (111) monochromator and vertically with a dynamically 4 ACS Paragon Plus Environment

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bent, 1 m-long Rh-coated Si mirror to 0.4 mm by 0.07 mm (horizontal by vertical) at the center of a Newport Kappa six (4 + 2) circle diffractometer. Scattered X-ray intensity was measured using a Dectris PILATUS 100k pixel array detector (Dectris, Inc.). Instrument control was performed using the SPEC software (Certified Scientific Software, Cambridge, MA, USA). The incident beam intensity was monitored with N2-filled ion chambers. Specular data were collected with the direction of the miscut perpendicular to the scattering plane and off-specular data were collected at 2° fixed incidence angle. Diffraction signals were background-subtracted, integrated, normalized to the incident beam intensity, and corrected for polarization and intersection volume using the Python Data Shell software package.17 Samples were mounted in a thin-film liquid cell enclosed with a 7.5 µm Kapton film.18 A syringe pump was used to inject solution between the sample and the Kapton film, and the system was allowed to react for at least an hour. After this time, the Kapton film was lowered onto the sample to create a thin film of solution on the sample, likely only a few micrometers thick. Evaporation of the film through the Kapton was limited by enclosing the fluid cell in a humid-He filled dome. The He was flowed through two glass bubblers in water prior to reaching the sample cell to increase the humidity. For convenience in measurement and analysis, the unit cell was reset such that the c-direction was perpendicular to the surface, such that asurface = bbulk, bsurface = cbulk, and csurface = abulk. However, to simplify notation for the reader, all Miller indices reported below are the standard crystallographic orientation for xenotime. CTR scattering intensities of twelve rods (including two symmetry-equivalent pairs) were collected at an L interval of ~0.12 in valleys, and an increased point density where intensity changed rapidly near the Bragg peaks. Symmetry equivalent rods were averaged and the quality of their agreement was used to estimate systematic errors. CTR Fitting. Model fitting was performed using the GenX software package using a reduced chi-squared (χ2) as the figure of merit.19-21 A fitting script was created consisting of the bulk slab derived from the XRD (above), with a surface slab consisting of an entire crystallographic unit cell (i.e., 6.8971 × 6.8971 × 6.0326 Å, V = 286.97 Å3, Z = 4). Due to differences in temperature, thermal fluctuation factors from the literature were used initially for bulk phosphorus and oxygen, but fits using the temperature factors measured above were checked and found to be the same within error. Since we cannot distinguish between the temperature factors for yttrium versus cation impurities, these were constrained to be equal. The complex composition of the mineral (Figure 1) was simplified for the purposes of fitting. To do this, an “average cation impurity” was calculated from the different REEs detected in the sample, weighted by the number of counts measured of each relative to yttrium. For simplicity, only elements with 1% or more of the counts relative to the total counts for elements yttrium plus lanthanum through rhenium were considered. The mean atomic number of these impurities is 66, corresponding to dysprosium, which is reasonable since this element is one of the cation impurities with the highest number of counts present in the sample (Figure 1). The simplified formula of the mineral used in fitting is therefore Y1-xDyxPO4. The fraction of cation impurity counts relative to yttrium was used as an initial guess, x = 0.34. However, due to the fact that a simplified composition was used, x was allowed to vary during the fit process. The yttrium and dysprosium impurity cations were forced to occupy 5 ACS Paragon Plus Environment

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equivalent positions. Phosphate molecules were relaxed as a unit, where translation and rotation were allowed, but distortion of the molecule was not. The fitting procedure consisted of building a model of increasing complexity, and evaluating if the improvement in fit quality in the more complex model was justified by the increased number of fit parameters. All fits included as parameters a scale factor, a β roughness parameter,22 cation impurity content (x above), and an isotropic cation temperature factor. The contribution to the CTR signal from bulk water was disregarded – a simplification justified because disordered bulk water does not contribute to offspecular CTRs and the specular rod is expected to be minimally affected given the thin water layer and heavy element content of the substrate. Fit parameters were constrained to obey the plane-group symmetry of the (100) plane of the bulk mineral. Anisotropic temperature factors were included for ordered water molecules, but no other species. Uncertainties for free parameters were estimated by determining the range of evaluated parameter values where χ2 was less than 5% larger than the best-fit χ2. Density Functional Theory Calculations. Density functional theory (DFT) calculations were performed using the VASP software.23-26 The valence electronic states were expanded in a basis of plane waves and the core-valence interaction was described using the Projector Augmented Wave (PAW) method.27,28 For Y, the semi-core 4s and 4p states were treated as valence states. We used a plane wave kinetic energy cutoff of 600eV and the Perdew-Burke-Ernzerhof (PBE) generalized gradient approximation (GGA) functional29,30 to describe the exchange correlation interactions. The DFT-D3 method of Grimme31 was used to describe the van der Waal’s interactions between the Y3+ and PO43- ions. For the bulk calculations, the Brillouin zone was sampled using a 4×4×4 Monkhorst-Pack k-point mesh. Use of a larger 8×8×8 k-point mesh resulted in less than 0.5 meV change in the total energy. For bulk and surface calculations, all atoms in the system were allowed to relax. Geometry optimizations were deemed converged when the forces on all the atoms fell below 0.01 eV Å-1. During optimization, the Self-ConsistentField (SCF) convergence threshold was set to 10-5 eV and a Pulay mixing scheme32 as implemented in VASP was used for charge density mixing in the SCF procedure. An additional method we tested is PBEsol, a revised PBE GGA functional developed to improve equilibrium properties of densely-packed solids.33 We tested it without inclusion of van der Waal’s corrections. We found that both DFT methods give lattice parameters that are in excellent agreement with experimental lattice parameters as shown in Table 1, with the largest error of 0.25%. However, the PBE-D3 method is known to predict the structure of liquid water in closer agreement with experiments compared to the PBEsol functional,34,35 making it a more suitable functional for this study. We have also examined the PBE036,37 hybrid density functional (with D3 van der Waal’s correction) to reproduce structural parameters and benchmark the performance of the computationally less expensive PBE-D3 method. In addition to xenotime (Table 1), computations were expanded to two crystalline hydrates of Y3+, [Y(OH2)9](EtOSO2)338 and [Y(OH2)9](CF3SO3)3,39 for assessing the ability of PBE-D3 and PBE0-D3 to reproduce experimental Y−Owater bond distances in the solid state. A detailed comparison of bond distances presented in Supporting Information indicates that PBE-D3 and PBE0-D3 are equally capable to reproducing Y−Owater bond distances, with a standard deviation between the X-ray diffraction data and both DFT methods less than 2.5 pm. This justifies 6 ACS Paragon Plus Environment

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our choice of a computationally less expensive PBE-D3 method for predicting the structure of the xenotime-water interface. For calculations on surfaces, a vacuum spacing of 18 Å in the surface normal direction was utilized. Adsorption of water was studied on the most stable (100) surface, modeled using a slab with four YPO4 layers and thickness of 12.8 Å. The surface was decorated symmetrically with one water molecule per metal ion on both sides of the slab. Thus, for every water molecule on one end of the slab, a symmetrically equivalent water molecule was present on the other side of the slab. A water molecule in the gas phase was used as the reference to compute the adsorption energies. Calculations on a water molecule in the gas phase were carried out in a 15 × 15 × 15 Å box. Minima hopping simulations40 were performed to obtain a plausible structure of the first few layers of water molecules on the xenotime (100) surface. To increase the computational efficiency, these simulations used a reduced plane wave kinetic energy cutoff of 400eV and the Brillouin zone was sampled using the Γ point approximation. The {100} surface was represented using a two-layer slab, containing two YPO4 formula units each. During the simulation, all the surface atoms were held frozen. Simulations were initiated from two different initial configurations containing six water molecules on the surface. Two of these water molecules were bound to the surface metal ion in their optimal configurations obtained from water adsorption calculations, while the other four water molecules were distributed randomly around these two water molecules in one simulation and pre-optimized in another simulation. In the latter case, the initial structure was obtained from a series of optimizations following sequential addition of water molecules oriented as to maximize the number of hydrogen bonds among themselves and with the surface phosphate anions. The simulations were run until 25-40 new local minima were identified by the minima hopping algorithm. The lowest energy structure of water molecules identified from these simulations was transferred symmetrically to the top and bottom of the four layers thick slab (containing 8 YPO4 formula units). Finally, a geometry optimization was performed on this structure using the same simulation settings as described at the beginning of this section. The initial configuration of a system with four H2O on each side is obtained from a system with six H2O by removing two outermost H2O. RESULTS AND DISCUSSION CTR Experiments and Fitting. In the CTR experiments, the pH of the overlying solution was varied to determine if the mineral-water interface structure changed with solution composition. As shown in Figure 2, there are no substantive changes in the CTR signal observed with varying pH. This result contrasts with that of another phosphate mineral, archerite (KH2PO4 or KDP), in which changes in CTR profile shapes were observed depending on the pH of the solution exposed to the mineral surface.13 Rather than simple surface roughening, the CTR profile changes on KDP were interpreted as being due to changes in the relative occupancies of potassium and dihydrogen phosphate. In another ionically-bonded system, calcite (CaCO3), there is some evidence that CTR profiles might be modified by ion sorption,41 but varying pH alone does not alter specular CTR profiles.42

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The absence of significant changes to the CTR profiles with varying pH raises questions about the origin of surface charge on xenotime, since the data indicate that the average {100} mineral-water interface structure does not change significantly regardless of the acidity of the solution. This is despite the fact that the pH range here should span the measured points of zero charge: i.e., measured isoelectric points (IEPs) for xenotime commonly fall within in the range of pH 3-5,43-45 but an IEP as high as pH 7 has been measured.46 One possibility to explain the variation in measured isoelectric point that has been raised is varying impurities in the mineral, perhaps leading to differing charge in the constituent ions.47 Regardless, at pH 2.5 the surface should be positively charged, a pH 4, the surface could be neutral or perhaps charged, and at pH 8.5 the surface should have a negative charge since all the zeta potential measurements listed above are below that. The magnitude of the measured zeta potentials at pH 8.5 range from ~-20 to -60 mV.43-45 The lack of variation of the data in Figure 2 suggests that the average mineral-water interface structure does not change substantially regardless of the surface charge, consistent with the small magnitude of the zeta potential measurements. One possible explanation for these is that the surface sites responsible for the surface charge are nonterrace regions, such as monomolecular steps and defects. Metadynamics classical molecular dynamics simulations on other ionically-bonded salts show a complex sorption behavior, even for potential determining ions.48-50 If species adsorbed to step edges dominate the measured surface charges and isoelectric points, it would not show up in the CTR measurement unless they occurred in an ordered array. In order to fit the atomic structure of the interface, only the pH 8.5 data was used because it was more extensive than either of the data sets collected at lower pHs. A bulktermination was initially applied, and the only fit parameters were the scale factor, roughness term,22 and the Y/Dy proportions. As shown in Figure 3, this fit contains substantial discrepancies from the experimental data with χ2 = 7.42. The [02L], [11L], and [22L] rods are particularly ill-fit by a bulk-like termination. Allowing the top molecular layer of the xenotime surface to relax substantially improves the fit with χ2 = 3.74. The relaxation of the top layer included: allowing occupancies less than the stoichiometric value, translation and rotation of phosphate molecules, translation of Y/Dy cations, and variation in the temperature factors. Translation and rotation were allowed to change atom positions in the y and z directions (i.e., parallel to the [001] and [100] directions of the bulk unit cell, respectively), but not the x direction (parallel to [010] in the bulk cell), which was forbidden by crystal symmetry. A second substantial improvement in the fit, with χ2 = 2.65, is made by including two ordered water molecules per surface unit cell, one bound to each of the surface Y/Dy cations. Since water is sometimes observed donating hydrogen bonds to surface oxyanions in MD simulations,5153 and other ordered water has been found at interfaces in CTR studies,53 we added two additional water molecules bound to the surface phosphates to see if this resulted in an improved fit. The movement of these new water molecules was restricted because of the crystallographic symmetry, but the overall fit did improve again with a χ2 = 1.87. An interesting effect occurs when anisotropic thermal fluctuations are included for the top layer water molecules so that the lateral fluctuations are allowed to vary independently of those perpendicular to the interface. The result is an ellipsoid that is flattened in the direction perpendicular to the surface (see final model in Figure 4), and the goodness-offit improves to χ2 = 1.74. To explain this, it is possible that the uncertainty on the lateral 8 ACS Paragon Plus Environment

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positions of the water is larger because the spatial resolution is lower laterally than perpendicular to the surface. In CTR spatial resolution is governed in part by the maximum momentum transfer (Q) for the data points measured. In the data set presented here the maximum surface-normal Q exceeds the maximum in-plane Q, thus the spatial resolution is likely lower laterally than perpendicular to the interface. Ultimately however, we believe the flattened ellipsoids reflect a more realistic description of a timeaveraged spatial location of a water molecule. Similar morphologies have been reported before in centroid MD simulations and other CTR fits,54-56,51 and can only be determined using both specular and off-specular crystal truncation rods. Increasing the complexity of the fit by allowing the temperature factors on oxygens hydrogen-bonded to water on the top layer of phosphates to vary independently of the other oxygens on the top layer phosphates improves the fit again with a χ2 = 1.66. This is justified from molecular dynamic simulations of BaSO4 that show that the oxygens on oxyanions bound to liquid water may have a larger range of motion that those bound to other atoms in the solid.51 Further improvements to the fit (described below) required substantially more fit parameters and resulted in minimal improvements in the goodness-of-fit, thus we consider this the best fit. The structure is shown in Figure 4, and parameter values are given in Table 2. A modification of the fit that we attempted was to allow a second monomolecular layer of cations and phosphate molecules to relax. The fit is only improved trivially, with χ2 = 1.64, despite an increase in the number of fit parameters by four (cation dy, dz; phosphate dy, dz). Because of this, we consider the best fit as the one above where only one layer of the mineral surface relaxes. The extent of relaxation observed in this study is smaller than a previous study on another phosphate mineral, fluorapatite. E.g., surface phosphates on the fluorapatite {100}-water interface retreat towards the bulk on average by 34 pm,14 whereas the average relaxation perpendicular to the surface here is 21 pm. Another study has found justification for relaxation of four layers in the fluorapatite {100} surface,15 which is consistent with the large relaxations observed in Park et al.,14 whereas here we find relaxation of only a single layer is found to be justified. In contrast to fluorapatite, the {101} surface of KDP surface phosphates have been found to relax by only 4 pm normal to the interface and surface potassiums by 10 pm.12 This finding is supported by an ab initio molecular dynamics simulation that showed minimal relaxation of the surface.57 The movement of the potassium is similar to the minor relaxation of the surface cations on the xenotime surface, +1 pm, and phosphates, +2 pm (Table 2). Structurally, KDP contains periodically-bonded chains of K+ and H2PO4-,58 similar to those in xenotime along the bulk [001] (surface [010]) direction, Figure 4b). This may explain the minimal surface relaxation of these two materials compared to fluorapatite. Alternately, the minimal surface relaxation found here on xenotime may result from the trivalent charge on the yttrium, phosphate and some of the cation impurities. Perhaps the strong electrostatic attraction between the constituent ions leads to a stronger inter-ion interaction and limits the effectiveness of water, protons or other species for altering these sites. The view that there is a stronger ionic bond in xenotime relative to other phosphate minerals is supported by their relative melting temperatures: xenotime melts at 1995 °C,59 fluorapatite at 1200 °C60 and KDP at 253 °C.61 One important question is the significance of the occupancy changes for the top surface layer. The fitted occupancy of the surface cations is 0.96 ± 0.05, which is 9 ACS Paragon Plus Environment

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essentially the stoichiometric value. However, the fitted occupancy of the surface phosphates is 0.81 ± 0.06. The direct interpretation of this result is that the surface is partially cation-terminated. However, other possibilities include that the surface is only cation-terminated at monomolecular steps or defects in the crystal structure, or that cations preferentially adsorb onto the surface in ordered sites. The stoichiometric surface16 is 4.8 phosphate sites per nm2, so 20% phosphates “missing” is nearly one phosphate molecule per nm. To evaluate these possibilities, we first examine the surface roughness calculated in the final fit, which was 0.156 and given the unit cell thickness (6.8971 Å), corresponds roughly to an RMS roughness of 3.23 Å,22 smaller than the monolayer thickness of 3.45 Å (see Table 2 for final fit parameters). Given the low roughness, the source of the occupancy changes is not likely to be due to steps or other defects (although to a certain extent the roughness and occupancy fit parameters are anticorrelated). However, the fit quality suffers somewhat with χ2 = 1.90 if the occupancy of the surface sites is forced to the stoichiometric value and the fit is re-optimized. Regardless of the source, the magnitude of the occupancies is consistent with site densities for adsorbed species derived from previous, element-specific CTR measurements,62 suggesting that partial dissolution of the xenotime followed by readsorption of the cations is plausible. If the surface does have 20% of its phosphates “missing,” the remaining cations may have ordered water associated with them. To account for this, in the fits above we did not allow the oxygen bonded to the cation directly below the phosphate to change its occupancy, which should have the effect of introducing some ordered water regardless of which site terminates the surface. If this oxygen occupancy is allowed to vary the fit quality is degraded with χ2 = 1.72. Our finding that the surface is somewhat phosphate-depleted contrasts with previous work on the occupancies of the surface sites in phosphate minerals where the fits indicated cation-depleted layers. The fitted occupancies for potassium in KDP varied from 0.7-0.85,63 and calcium occupancies in fluorapatite were 0.84.14 The origin of this effect is not clear, but may be due, at least in part, to correlation with the roughness and temperature factors. That is, to a certain extent one could model a rough or partly disordered surface as having partial occupancies or elevated temperature factors. As mentioned in the introduction, an understanding of the structure of water at the interface is critical for the rational design of ligands selective for REE ore minerals. This is because any ligand coordinating the mineral surface will likely need to displace the water bound to the surface. In the best fit (Figure 4, Table 2), the water molecules bound to the cations are located 228 pm from the surface yttriums/dysprosiums, which is close to the xenotime Y-O bulk bond lengths of 231 and 238 pm, marking this structure as plausible. The water molecules bound to the surface phosphates are 265 pm from the oxygens on the surface phosphates, significantly longer than the bulk values. This is due to the fact that these waters are hydrogen-bonded to the oxygens on the surface phosphates. (X-rays are unfortunately not responsive to hydrogen positions and only the oxygen positions are measured.) Fitted temperature factors are much larger for the waters bound to the phosphates than to the surface cations, indicating the range of motion of these waters are larger. This may be due to a combination of factors. The first is a steric effect, where the waters bound to surface cations are more constrained in their motion due to the neighboring surface phosphates. The second is the increased number of degrees of freedom, i.e., the oxygens on the water bound to phosphates do so through a 10 ACS Paragon Plus Environment

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The Journal of Physical Chemistry

hydrogen atom (i.e., a hydrogen bond) and thus can be expected to have more flexibility in their position. Also, we find the evidence that the top-most oxygen on the surface phosphate itself has a larger temperature factor than others, consistent with this interpretation. A second issue with respect to the ordered water is its occupancy. We find an occupancy of the water bound to cations of 0.59 ± 0.32 and for that bound to the surface phosphates of 1.81 ± 0.62 (Table 2). These are sufficiently different from 1 to require some explanation. One possibility, mentioned above, is that this reflects an imperfect model of the interface and that the fit routine is adjusting the occupancy of ordered water to reflect electron density due to some ion adsorbed to the interface. Supporting this argument is the fact that the relative coordination numbers of waters bound to cations and phosphate are not consistent with the occupancy of the surface sites discussed above, where the surface on average was fit as being phosphate-depleted. A second possibility is that the water structure is more complex than the simple two-site model used here, e.g., that the water bound to the surface phosphates has been convoluted with other types of ordered water at the interface. Lastly, it could be that the occupancy values are more-orless accurate and that the fitted occupancy values indicate that surface phosphates are coordinated by either 1 or 2 waters (with 1.81 as the ensemble average), and some surface cations do not have any bound water. The former is fairly reasonable, but we view it as unlikely that “bare” cations exist on the surface. On balance, we view the most likely scenario is that the fitted occupancy values for the ordered water are due to a simplified model of the interface that lacks adsorbed species, and a more complex water structure than what the model fit supports. When we consider the implications of the water positions for selective ligand chelation, our data suggest that targeting the surface cations is the more viable strategy, since these waters have a smaller temperature factor and are therefore likely wellordered. A viable strategy may be to design a ligand that coordinates cation sites on xenotime specifically by displacing these waters. The waters bound to the surface phosphates are likely too disordered, or the structure of the water too simplistic, to create a site for binding of a ligand that is selective for xenotime. DFT Calculations in Vacuum. To better understand the origin of the {100} surface relaxation in solvent, we initially computed the magnitude of surface relaxation in vacuum. To quantify the structural changes upon the formation of a surface, the mean, minimum and maximum P-O and Y-O bond lengths were computed. The difference between the P-O and Y-O distances in each layer of the surface and bulk xenotime can be described using equation (2) (shown for the P-O bond in the first layer): ∆୔ି୓ = ୪ୟ୷ୣ୰ଵ

ౢ౗౯౛౨భ

ቀ୰ౌషో:౗౬ౝ ି୰ౘ౫ౢౡ ౌషో:౗౬ౝ ቁ×ଵ଴଴

(2)

୰ౘ౫ౢౡ ౌషో:౗౬ౝ

where r୔ି୓:ୟ୴୥ is the average P-O bond length in the first layer of the (100) surface and

ୠ୳୪୩ r୔ି୓:ୟ୴୥ is the average P-O bond length in bulk. The variation in the P-O and Y-O distances within a layer can be computed as a percentage of the average P-O and Y-O distances in the same layer using equation (3) (shown for the P-O bond length in the first layer)

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δ୔ି୓ =

ౢ౗౯౛౨భ

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ౢ౗౯౛౨భ

ቀ୰ౌషో:ౣ౗౮ ି୰ౌషో:ౣ౟౤ ቁ×ଵ଴଴

(3)

ౢ౗౯౛౨భ

୰ౌషో:౗౬ౝ

Due to the symmetry of a four-layer {100} slab, the top and the second layers are equivalent to the bottom and the third layer, respectively. Table 3 presents the maximum, minimum, and average P-O and Y-O distances in bulk and in the first two layers of the (100) plane. Compared to their bulk positions, the phosphate groups on a surface exposed to vacuum are displaced outwards by 8.4 pm, while the Y3+ ions are displaced inwards by 4.9 pm, a larger change than observed in the CTR fits in solution. A much more modest change in the positions occur for the Y3+ (0.6 pm) and PO43- (0.2 pm) ions in second layer. As a result, the average interlayer spacing between the surface and subsurface YPO4 layers is increased to 347.5 pm from its bulk value of 345.7 pm. The P-O bond to the oxygen atom pointing away from the surface has become shorter (152 pm), while the P-O bond to the oxygen atoms lying in the plane of the (100) surface (157 pm) and to the oxygen atom pointing into surface (158 pm) has become longer than the bulk P-O bond length (155 pm). Relaxation of the P-O bonds in the surface phosphates is associated with a reduction in the average Y-O distances on the surface by 1 pm and an increase in the Y3+-Y3+ distance by 8 pm compared to bulk. Only very small changes in the P-O bond length and Y-O distances are observed in the sub-surface layer (Table 3). We note that the results do not change substantially if we increase the slab thickness from four to eight YPO4 layers. The largest change is observed for the outermost Y3+ ions that are displaced inwards by an additional 0.2 pm, while all the other ions are displaced by < 0.1 pm. DFT calculations of water adsorption. To study adsorption of ordered water on the {100} surface, we added a total of six water molecules to the surface. To obtain a plausible structure, a minima hopping algorithm40 was employed, as described in the Methods Section. Although calculations were carried out beginning from two different initial structures of water molecules, upon optimization, the lowest lying arrangement of water molecules from both simulations converged to the same structure, as seen in Figure 5. The displacement of the surface atoms with six water molecules is mostly similar to that observed with four water molecules on the surface (Table 4). In contrast, the displacement pattern with only two water molecules is somewhat different and resembles more closely what is observed in vacuum. This underscores the importance of adding extended water layers beyond 100% coverage for a more realistic representation of the mineral-water interface. In the presence of six water molecules, the surface Y3+ and phosphate ions are pulled away from the surface by 1.4 and 1.1 pm, respectively, a more modest change compared to ion displacement in vacuum. The six water molecules are arranged in three distinct layers above the surface. The first layer contains two water molecules, each bound to a surface yttrium ion with bond lengths of 243 (Y1) and 251 (Y2) pm. These are slightly extended relative to the bulk Y-O bond lengths (231 and 238 pm). The water molecule bound to Y1 forms hydrogen bonds with the water molecules in the second and outer layers. On the other hand, the water molecule bound to Y2 forms hydrogen bonds with water molecules in the second layer and with the water molecule bound to Y1. The second water layer consists of two water molecules that are bound to surface phosphate groups via hydrogen bonds. The Owater-Ophosphate distance to the two 12 ACS Paragon Plus Environment

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water molecules are 257 and 259 pm, which are slightly shorter than the best fit CTR distance of 265 pm. The Owater-Owater distance in liquid water, at 280 pm,64 is longer than these indicating that the hydrogen bonds that water makes with the surface phosphates are likely stronger than those in liquid water. Such a strengthening of the hydrogen bonds with surface oxygen atoms has been routinely observed in simulations of water molecules atop oxide surfaces, along with some measurements using inelastic neutron scattering.65,66 The computed adsorption energy per water molecule (EAd) on the (100) surface are given in Table 5. EAd decreases with increasing the number of water molecules that are adsorbed onto the surface from -98 kJ/mol for one water molecule per surface Y3+ to 87 kJ/mol for three water molecules per surface Y3+. This is within a typical range of computed water adsorption energies for the most stable surfaces of other minerals, such as calcite and bastnaesite.5 Comparison between DFT structure and CTR best fit. The minimized DFT structure contains some interesting features (Figure 5) that are directly comparable to the CTR fits above. The first is that the xenotime surface displays minimal relaxation compared to the bulk structure, with almost no perturbation of the second monolayer below the surface. This is very similar to the best fits for the CTR data. Second, the CTR fit and DFT results with four and six water molecules are in agreement that all of the top layer atoms moved away from the bulk. Furthermore, the magnitudes of the movements in the DFT are also very similar to those of the CTR best fit: the cations moved by 1.4 pm in the DFT and by 1 pm in the CTR. The surface phosphates moved by 1.1 pm in the DFT and by 2 pm in the CTR. Lateral movements of the cations were in agreement in direction and had only a small discrepancy in magnitude (4, 5 pm in the DFT vs. 6 pm in the CTR). The lateral positions of the phosphates differed both in magnitude and direction however. In the DFT, the phosphates P1 and P2 moved away from each other by 2 pm (as viewed in Figure 5a), whereas in the CTR fits, they move towards each other by 6 pm. Similarly, the rotational relaxation of the phosphates are different between the CTR fit and the DFT minimized structure. In the CTR fit, the P1 and P2 have their top-layer oxygens tilt towards each other by 1.77° ± 2.20 (Figure 4), albeit with a large uncertainty, whereas in the DFT they tilt away from each other by 0.8° on average (Figure 5). It is likely that the differences in relaxation of the phosphates are due to the fact that the DFT did not include the crystal symmetry restrictions that the CTR fits did, but also that the CTR fits reflect an ensemble average of the thermal motions undergone by the water at room temperature and includes bulk water, whereas the DFT is a minimized energy calculated at 0 K and includes no bulk water. The most significant discrepancy between the CTR and DFT structures is in the positions of the water bound to the surface sites. While the waters bound to surface cations are quite similar in position, their bond distances vary somewhat: 228 pm in the CTR vs. 243, 251 pm in the PBE-D3. Note that changing from the PBE-D3 functional to the hybrid PBE0-D3 functional does not eliminate the discrepancy, leading to Y−Owater bond distances that are on average shorter compared to PBE-D3 bond distances by only 3.5 pm (240 and 247 pm). This is in line with the difference between PBE-D3 and PBE0D3 for Y−Owater bond distances in crystalline hydrates [Y(OH2)9](EtOSO2)3 and [Y(OH2)9](CF3SO3)3 (see the Supporting Information for a detailed comparison). Since Y−Owater bond distances in crystalline hydrates obtained with both DFT methods are in 13 ACS Paragon Plus Environment

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excellent agreement with crystallographic distances (the standard deviation is less than 2.5 pm), we may attribute a larger discrepancy between the CTR and DFT bond distances to a limited number of interfacial water molecules used in DFT calculations. The distances between water and the surface phosphates are more similar: the CTR fit yields an Ophosphate-Owater distance of 265 pm whereas the DFT minimization results in 257, 259 pm. Viewed along the [010] direction (Figure 4a, 5a), the positions of these waters are similar between theory and experiment, but viewed along [001] (figure 4b, 5b), the positions are quite different. This is because in the best fit model these water molecules were assigned to special positions in which only surface normal motion is allowed by the plane group symmetry of the surface. While the best fit to the CTR used water positions located between phosphates, the DFT placed the water molecules almost directly above phosphates. A CTR fit with a third water on the mirror plane that bisects the phosphates resulted in a lower χ2, but this third water layer refined to a distance too far above the phosphates for H-bonding and had thermal parameters so large that its position could not be reliably determined. It is not clear at this time which is a more correct portrayal of the interface, the DFT or the CTR best fit model. Certainly, the issues mentioned above regarding the differences in what the DFT calculations represents (a few monolayers of water adsorbed at 0 K for an ideal surface with no defects) vs. CTR (ensemble average, but with limited power to resolve individual waters) are likely playing a role. In the future, we will resolve these issues through ab initio molecular dynamics simulation of xenotime-water interface with larger water coverage at 298 K. The abundance of water and the treatment of its dynamical nature are expected to provide more accurate description of hydrogen-bonding dynamics between water and the mineral surface and may resolve the discrepancy between the simulation and the experiment, but obtaining precise agreement between atomic-scale simulation and CTR data remains difficult.51,53 Despite the discrepancies, however, there are a number of commonalities in the water positions found with DFT and CTR. First, the most important conclusion is that the DFT and CTR mostly agree that there is a single water molecule coordinating the surface cations. Second, the DFT water positions suggest that the large occupancy in the CTR fit for water bound to the phosphates (1.8 ± 0.6) may reflect a more complex water structure than is resolvable via CTR. Regardless, the CTR and DFT are in good agreement that there is one water bound to each surface cation, whereas the positions and occupancy of water bound to surface phosphates are more uncertain, though both DFT and CTR point to the binding of structured water to surface phosphates. Given the discrepancies, the natural course is to evaluate how well the DFT structure matches the CTR data. To do this, after correcting for the slight lattice mismatch in the DFT structure likely due to the minimal slab thickness, we fit the DFT structure directly to the CTR data, fitting only the scale factor, roughness, impurity/yttrium composition, and thermal fluctuation factors for adsorbed water. After correcting for the lattice mismatch, and keeping all the other fit parameters the same, the χ2 of the resultant fit was 5.17, which is slightly better than the fit from a bulk-like termination, without ordered water (6.96 from above). Given that the major differences between the CTR fit in the DFT structure were dominantly in the water positions, we further obtained a fit where the top layer of xenotime surface sites was allowed to relax, but water positions were frozen in the DFT positions. This fit was somewhat better, with χ2 = 4.28, but still not comparable to the best fits where water was allowed to relax freely. 14 ACS Paragon Plus Environment

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Using this structure as a starting guess and allowing both the top layer of surface sites and water molecules to relax yielded a fit with χ2 = 1.68, the same fit quality to the “best fit” described above. However, in relaxing the ordered water, the positions of the water molecules are very similar to what is observed in the “best fit” (data not shown). It is also important to note that this fit was allowed to violate the crystal symmetry in direct contradiction with the CTR measurements that showed good agreement among the symmetry equivalent rods. CONCLUSIONS While there are discrepancies in the precise positions of the water and surface sites for the xenotime, the general features of both the best fit for the CTR data and the DFT calculations are consistent. From these we can conclude that the [100] xenotime mineral-water interface contains the following features: Firstly, the xenotime surface relaxation itself is minimal. The former contrasts with results from other phosphate minerals such as fluorapatite14,15 but also other ionically-bonded minerals such as barite,51 calcite42,53,54 but even covalently-bonded minerals such as hematite.67 We speculate that the driving force for this minimal relaxation could be the result of the cations’ large ionic size the trivalent character of xenotime’s constituent ions, or the specific structure of periodically-bonded chains of cations and anions. Secondly, while there are discrepancies between the precise positions of adsorbed water molecules, the general result is that single water molecules adsorb strongly to surface cations and are wellordered, and ordered water donates hydrogen bonds to surface phosphates but its position and occupancy is still unclear, which warrants further investigation of a completely solvated xenotime interface by ab initio molecular dynamics simulations. Due to the single water molecule bound to the surface cations, the implications of this structure for chelation of the mineral surface by ligands and subsequent froth flotation is that single moiety, anionic ligands, such as alkyl carboxylic acids, will likely face a limit in how selective for this mineral they can be. Using such a compound, one could only displace a single water molecule on the surface and if a ligand successfully competes for the lone water molecule’s binding site on an yttrium, it will likely do so on many different cations present on other mineral surfaces. Thus, these will yield poor selectivity for xenotime over gangue minerals. Given the uncertainty in the positions of the water bound to surface phosphates, we also do not recommend using a cationic surfactant that would target the surface phosphates at this time. However, an alternate strategy may be to have multiple-head groups on an anionic ligand that target multiple surface sites in adjacent rows on the mineral. This may allow for xenotime-specific collectors to be designed. ASSOCIATED CONTENT The Supporting Information is available free of charge on the ACS Publications website at DOI: XXXXXXX. Measured xenotime structure, diagrams of structure of [Y(OH2)9](EtOSO2)3 and [Y(OH2)9](CF3SO3)3, and comparison of experimental and DFT Y-Owater bond distances for these. ACKNOWLEDGEMENTS 15 ACS Paragon Plus Environment

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This work was supported by the Critical Materials Institute, an Energy Innovation Hub funded by the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Advanced Manufacturing Office. This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory and National Energy Research Scientific Computing Center, both of which are supported by the Office of Science of the U.S. Department of Energy under contract Nos. DE-AC05- 00OR22725 and DE-AC02-05CH11231, respectively. The single-crystal structural analysis by RC was supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Chemical Sciences, Geosciences, and Biosciences Division. CTR data were collected at GeoSoilEnviroCARS (The University of Chicago, Sector 13), Advanced Photon Source (APS), Argonne National Laboratory (ANL). GeoSoilEnviroCARS is supported by the National Science Foundation - Earth Sciences (EAR - 1634415) and U.S. Department of Energy, Office of Science, Basic Energy Sciences, Chemical Sciences, Geosciences, and Biosciences Division (DE-FG02-94ER14466). This research used resources of the APS, a U.S. Department of Energy (DOE) Office of Science User Facility operated for the DOE Office of Science by ANL under Contract No. DE-AC0206CH11357. CTR data analysis was completed in part with resources provided by the University of Chicago Research Computing Center. We thank Sang Soo Lee and two anonymous reviewers for their constructive comments about drafts of the manuscript. REFERENCES 1. U.S. Department of Energy; U.S. department of energy critical materials strategy; U.S. Department of Energy, Washington D.C., 2011. 2. Pradip. The surface properties and flotation of rare-earth minerals. Ph.D. Dissertation, University of California, Berkeley, 1981. 3. Fuerstenau, M. C.; Jameson, G.; Yoon, R.-H. Froth flotation: a century of innovation. Society for Mining, Metallurgy and Exploration, Inc., Littleton, CO, USA, 2007. 4. Zhang, X.; Du, H.; Wang, X.; Miller, J. D. Surface chemistry considerations in the flotation of rare-earth and other semisoluble salt minerals. Miner. Metall. Proc. 2016, 30, 24-37. 5. Srinivasan, S. G.; Shivaramaiah, R.; Kent, P. R. C.; Stack, A. G., Riman, R. E.; Anderko, A.; Navrotsky, A.; Bryantsev, V. S. A comparative study of surface energies and water adsorption on Ce-bastnästite, La-bastnästite, and calcite via density functional theory and water adsorption calorimetry. Phys. Chem. Chem. Phys. 2017, 19(11), 7820-7832. 6. Bosbach, D.; Coveney, P. V.; Griffin, J. L. W.; Putnis, A.; Risthaus, P.; Stackhouse, S.; Whiting, A. The rational design, synthesis and demonstration of the recognition and binding of a diaza-dioxa-12-crown-4 diphosphonate macrocycle to all crystal growth faces of barium sulfate. J. Chem. Soc., Perkin Trans., 2002, 2, 1238-1245. 7. Bonnesen, P. V.; Delmau, L. H.; Moyer, B. A.; Leonard, R. A. A robust alkaline-side CSEX solvent suitable for removing cesium from Savannah River high level waste. Solvent Extr. Ion Exc. 2000, 18, 1079-1107. 8. Mariano, A. N. Economic geology of rare earth minerals. Rev. Mineral. Geochem., 1989, 21, 309-338. 16 ACS Paragon Plus Environment

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9. Jackson, W. D.; Christiansen, G. International strategic minerals inventory summary report—rare earth oxides. U.S. Geological Survey, Circular 930-n, 1993. 10. U.S. Geological Survey National Minerals Information Center. https://minerals.usgs.gov/minerals/pubs/commodity/rare_earths/ (Accessed Aug 6, 2018). 11. Reedijk, M. F.; Hollander, F. F. A.; de Vries, S. A.; Vlieg, E. Liquid order at the interface of KDP crystals with water: Evidence for icelike layers. Phys. Rev. Lett. 2003, 90, 066103 12. de Vries, S. A.; Goedtkindt, P.; Bennett, S. L.; Huisman, W. J.; Zwanenburg, M. J.; Smilgies, D.-M.; De Yoreo, J. J.; van Enckevort, W. J. P.; Bennema, P.; Vlieg E. Surface atomic structure of KDP crystals in aqueous solution: an explanation of the growth shape. Phys. Rev. Lett. 1998, 80, 2229-2232. 13.Vlieg, E.; Deij, M.; Kaminski, D.; Meekes, H.; van Enckevort, W. Towards an atomicscale understanding of crystal growth in solution. Faraday Disc. 2007, 136, 57-69. 14. Park, C.; Fenter, P.; Zhang, Z.; Cheng, L.; Sturchio, N. C. Structure of the fluorapatite (100)-water interface by high-resolution X-ray reflectivity. Am. Mineral. 2004, 89, 1647-1654 15. Pareek, A.; Torrelles, X.; Angermund, K.; Rius, J.; Magdans, U.; Gies, H. Structure of interfacial water on fluorapatite (100) surface. Langmuir, 2008, 24, 2459-2464. 16. Ni, Y.; Hughes, J. M.; Mariano, A. N. Crystal chemistry of the monazite and xenotime structures. Am. Mineral. 1995, 80, 21-26. 17. Github respository for the xray Data analysis Library (Tdl) https://github.com/xraypy/tdl (Accessed Aug 6, 2018). 18. Trainor, T. P.; Templeton, A. S.; Eng, P. J. Structure and reactivity of environmental interfaces: Application of grazing angle X-ray spectroscopy and long-period X-ray standing waves. J. Electron. Spectrosc. Relat. Phenom., 2006, 150, 66-85. 19. Björck, M.; Andersson, G. GenX: an extensible X-ray reflectivity refinement program utilizing differential evolution. J. Appl. Cryst. 2007, 40, 1174-1178. 20. Björck, M. Fitting with differential evolution: an introduction and evaluation. J. Appl. Cryst. 2011, 44, 1198-1204 21. GenX X-ray fitting software. http://genx.sourceforge.net/ (Accessed Aug 6, 2018). 22. Robinson, I. K. Crystal truncation rods and surface roughness. Phys. Rev. B 1986, 33, 3830 23. Kresse, G.; Hafner, J., Ab initio molecular dynamics for liquid metals. Phys. Rev. B 1993, 47, 558-561. 24. Kresse, G.; Hafner, J., Ab initio molecular-dynamics simulation of the liquid-metal– amorphous-semiconductor transition in germanium. Phys. Rev. B B 1994, 49, 1425114269. 25. Kresse, G.; Furthmüller, J., Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 1996, 54, 11169-11186. 26. Kresse, G.; Furthmüller, J., Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comp. Mat. Sci. 1996, 6, 15-50. 27. Blöchl, P. E., Projector augmented-wave method. Phys. Rev. B 1994, 50, 1795317979. 28. Kresse, G.; Joubert, D., From ultrasoft pseudopotentials to the projector augmentedwave method. Phys. Rev. B 1999, 59, 1758-1775. 17 ACS Paragon Plus Environment

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29. Perdew, J. P.; Burke, K.; Ernzerhof, M., Generalized gradient approximation made simple. Phys. Rev. Lett. 1996, 77, 3865-3868. 30. Perdew, J. P.; Burke, K.; Ernzerhof, M., Generalized gradient approximation made simple Phys. Rev. Lett. 1997, 78, 1396-1396. 31. Grimme, S.; Antony, J.; Ehrlich, S.; Krieg, H., A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu. J. Chem. Phys. 2010, 132, 154104. 32. Pulay, P., Convergence acceleration of iterative sequences. The case of scf iteration. Chem. Phys. Lett. 1980, 73, (2), 393-398. 33. Perdew, J. P.; Ruzsinszky, A.; Csonka, G. I.; Vydrov, O. A.; Scuseria, G. E.; Constantin, L. A.; Zhou, X.; Burke, K., Restoring the density-gradient expansion for exchange in solids and surfaces. Phys. Rev. Lett. 2008, 100, 136406. 34. Forster-Tonigold, K.; Groß, A., Dispersion corrected RPBE studies of liquid water. The J. Chem. Phys. 2014, 141, 064501. 35. Mattsson, A. E.; Mattsson, T. R., AM05 Density functional applied to the water molecule, dimer, and bulk liquid. J. Chem. Theory Comput. 2009, 5, 887-894. 36. Perdew, J. P.; Ernzerhof, M. Rationale for mixing exact exchange with density functional approximations. J. Chem. Phys. 1996, 105, 9982- 9985 37. Adamo, C.; Barone, V. Toward reliable density functional methods without adjustable parameters: The PBE0 model. J. Chem. Phys. 1999, 110, 6158–6170. 38. Broach, R.; Williams, J.; Felcher, G.; Hinks, D. A neutron diffraction study of yttrium tris-(ethyl sulfate) nonahydrate, Y(C2H5SO4)3·9H2O Acta Crystallogr. Sect. B 1979, 35, 2317-2321. 39. Harrowfield, J. M.; Kepert, D. L.; Patrick, J. M.; White, A. H. Structure and stereochemistry in 'f-block' complexes of high coordination number. VIII. The [M(unidentate)9] system. Crystal structures of [M(OH2)9] [CF3SO3]3, M = La, Gd, Lu, Y. Aust. J. Chem. 1983, 36, 483-492. 40. Goedecker, S., Minima hopping: An efficient search method for the global minimum of the potential energy surface of complex molecular systems. J. Chem. Phys. 2004, 120, 9911-9917. 41. Heberling, F.; Trainor, T. P.; Luetzenkirchen, J.; Eng, P.; Denecke, M. A.; Bosbach, D. Structure and reactivity of the calcite-water interface. J. Coll. Int. Sci. 2011, 354, 843−857. 42. Fenter, P.; Geissbühler, P.; DiMasi, E.; Srajer, G.; Sorensen, L. B. ; Sturchio, N. C. Surface speciation of calcite observed in situ by high-resolution X-ray reflectivity. Geochim. Cosmochim. Acta 2000, 64, 1221-1228. 
 43. Pereira, C. A.; Peres, A. E. C. Flotation concentration of a xenotime pre-concentrate. Miner. Engr. 1997, 10, 1291-95. 44. Cheng, T.-W.; Holtham, P. N.; Tran, T. Froth flotation of monazite and xenotime. Miner. Engr. 1993, 6, 341-351. 45. Anderson, C. D. Improved understanding of rare earth surface chemistry and its application to froth flotation; Ph.D. Dissertation, Colorado School of Mines; 2015. 46. Cheng, T.-W. The point of zero charge of monazite and xenotime. Miner. Engr. 2000, 13: 105-09. 47. Cheng, T.-W. Technical Note: The point of zero charge of monazite and xenotime. Miner. Engr. 1999, 1, 105-109. 18 ACS Paragon Plus Environment

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48. Stack, A. G.; Raiteri, P.; Gale, J. D. Accurate rates of the complex mechanisms for growth and dissolution of minerals using a combination of rare-event theories. J. Am. Chem. Soc. 2012, 134, 11−14.
 49. Liu, L.-M.; Laio A.; Michaelidis, and A. Initial stages of salt crystal dissolution determined with ab initio molecular dynamics. Phys. Chem. Chem. Phys. 2011, 13, 13162-13166. 50. De La Pierre, M.; Raiteri, A. G.; Stack, A. G.; Gale, J. D. Uncovering the atomistic mechanism for calcite step growth. Angew. Chem. Int’l. Ed. 2017, 56, 8464-8467 51. Bracco, J. N.; Lee, S. S.; Stubbs, J. E.; Eng, P. J.; Heberling, F.; Fenter, P.; Stack, A. G. Hydration structure of the barite (001)-water interface: comparison of x-ray reflectivity with molecular dynamics simulations. J. Phys. Chem. C 2017, 122, 12236-12248 52. Raiteri, P.; Gale, J. D.; Quigley, D.; Rodger, P. M. Derivation of an accurate forcefield for simulating the growth of calcium carbonate from aqueous solution: a new model for the calcite-water interface. J. Phys. Chem. C 2010, 114, 5997 53. Fenter, P.; Kerisit, S.; Raiteri, P.; Gale, J. D. Is the calcite water interface understood? direct comparisons of molecular dynamics simulations with specular X-ray reflectivity data. J. Phys. Chem. C 2013, 117, 5028-5042 54. Heberling, F.; Eng, P.; Denecke, M. A.; Lützenkirchen, J.; Geckeis, H. Electrolyte layering at the calcite(104)–water interface indicated by Rb+- and Se(VI) K-edge resonant interface diffraction. Phys. Chem. Chem. Phys. 2014, 16, 12782-12792. 55. McBriarty, M. E.; von Rudorff, G. F.; Stubbs, J. E.; Eng, P. J.; Blumberger, J.; Rosso, K. M., Dynamic stabilization of metal oxide–water interfaces. J. Am. Chem. Soc. 2017, 139, 2581-2584. 56. McBriarty, M. E.; Stubbs, J. E.; Eng, P. J.; Rosso, K. M. Potential-specific structure at the hematite–electrolyte interface. Adv. Funct. Mater. 2018, 1705618. 57. Stack A. G., Rustad J. R., Land T. A., De Yoreo J. J., Thomas T. N.& Casey W. H. (2004) The growth morphology of the {100} surface of KDP (Archerite) on the molecular scale. J. Phys. Chem. B. 2004, 108, 18284-18290. 58. Harman, P. The morphology of zircon and potassium dihydrogen phosphate in relation to the crystal structure. Acta Cryst. 1956, 9, 721-727. 59. Hikichi, Y.; Nomura, T. Melting temperatures of monazite and xenotime. J. Am. Ceram. Soc. 1987, 70, C-252 - C-253. 60. Walker, P.; Tarn, W. H. Handbook of Metal Etchants. CRC Press, Boca Raton, 1991. 61. CRC Handbook of Chemistry and Physics, 94th edn.; Ed. W. M. Haynes; CRC Press: Boca Raton, FL, 2013 62. Lee, S. S.; Fenter, P.; Park. C.; Sturchio, N. C.; Nagy, K. L. Hydrated cation speciation at the muscovite (001)-water interface. Langmuir, 2010, 26, 16647-16651. 63. Kaminski, D.; Radenovic, N.; Deij, M. A.; van Enckevort, W. J. P.; Vlieg, E. pHdependent liquid order at the solid-solution interface of KH2PO4 crystals. Phys. Rev. B 2005, 72, 24504. 64. Skinner, L. B.; Huang, C.; Schlesinger, D.; Pettersson, L. G. M.; Nilsson, A.; Benmore, C. J., Benchmark oxygen-oxygen pair-distribution function of ambient water from x-ray diffraction measurements with a wide Q-range. J. Chem. Phys. 2013, 138, (7), 074506.

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65. Kumar, N.; Neogi, S.; Kent, P. R. C.; Bandura, A. V.; Kubicki, J. D.; Wesolowski, D. J.; Cole, D.; Sofo, J. O., Hydrogen bonds and vibrations of water on (110) rutile. J. Phys. Chem. C 2009, 113, 13732-13740. 66. Wang, H.-W.; DelloStritto, M. J.; Kumar, N.; Kolesnikov, A. I.; Kent, P. R. C.; Kubicki, J. D.; Wesolowski, D. J.; Sofo, J. O., Vibrational density of states of strongly h-bonded interfacial water: insights from inelastic neutron scattering and theory. J. Phys. Chem. C 2014, 118, 10805-10813. 67. Trainor, T. P.; Chaka, A. M.; Eng, P. J.; Newville, M.; Waychunas, G. A.; Catalano, J. G.; Brown, Jr. G. E. Structure and reactivity of the hydrated hematite (0001) surface. Surf. Sci. 2004, 573, 204-224.

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Figures

Figure 1. Cation content from acid digestion ICP-MS. The dominant cation is yttrium, with roughly an order of magnitude higher measured quantity than any impurity. Significant amounts of other REEs and heavier elements are detected, with dysprosium being the most abundant impurity.

Figure 2. CTR data as a function of pH for four representative rods. CTR intensity was measured for three different pHs, with no systematic changes in intensity observed.

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Figure 3. CTR data at pH 8.5 and fits. The fit using a bulk termination is a poor description of the data. Units on |Fhkl| are arbitrary, but an internally consistent scale factor was used to allow comparison of relative intensity among rods.

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Figure 4. Structure of the best fit to the CTR data. a) View along the bulk [010] (surface [100]) direction. Yttriums/cation impurities are shown in cyan, phosphorus in gray, oxygens on phosphate in red, and oxygens on water in black. The black arrows indicate the direction of rotation and translation of surface phosphates and cations in the relaxed best fit structure; annotations showing the magnitude of the relaxations are in picometers and degrees. Bond lengths for ordered water to surface sites are labeled on the left side of the figure (also in pm). The ellipsoid size and dimensions correspond to 70% probability for atom positions given the best-fit temperature factor. The waters show a range of motion flattened relative to surface normal. b) View along bulk [001] (surface [010]).

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Figure 5. Lowest energy structure from DFT simulations, viewed along the a) [010] and b) [001] directions. Bond lengths are listed in picometers. Atom colors are the same as described in Figure 4. Water is bound to surface yttriums, or donates a hydrogen bond to surface phosphates.

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Table 1: Variation of lattice parameters of YPO4 with DFT methods. A 4× 4 × 4 Gamma centred k-point mesh and 600 eV plane wave kinetic energy cutoff was used in all the calculations. Method PBE-D3 PBEsol PBE0-D3 Experiment14 Experiment - this work

a (Å) 6.9143 6.8790 6.8512 6.8947 6.8971

c (Å) 6.0429 6.0039 5.9903 6.0274 6.0326

Table 2: Fit parameters for CTR Roughness β Composition: Y(1-x)DyxPO4

0.16 ± 0.03 (3.23 Å RMS roughness) x = 0.26 ± 0.06

Surface Phosphates Occupancy

0.81 ± 0.06

Rotation (degrees)

1.8 ± 2.2

dy or [001] (pm)

-6 ± 3

dz or [100] (pm) P temperature factor (Uiso, Å2 )

+2 ± 2 0.014 ± 0.014

Ophosphate uiso

0.018 ± 0.010 2

Ophosphate-top layer Uiso (Å )

0.08 ± 0.05

Surface Yttrium, Dysprosium Occupancy

0.96 ± 0.05

dy or [001] (pm)

+6 ± 1

dz or [100] (pm)

+1 ± 1

2

Y/Dy, Uiso (Å )

0.013 ± 0.005

Ordered Water: Y/Dy-Owater Owater z height (above Y/Dy) (pm) Y/Dy-Owater distance (pm)

226 ± 13

Occupancy

0.6 ± 0.3

Temperature factor perpendicular to interface, Uperpendicular (Å2 ) Temperature factor parallel to interface, Uparallel (Å2 )

0.06 ± 0.17

228

0.3 ± 0.5

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Ordered Water: Ophosphate-Owater Owater z height (above Y/Dy) (pm) Owater-Ophosphate distance (pm)

265

Occupancy

1.8 ± 0.6 2

Uperpendicular (Å )

326 ± 22

0.4 ± 0.3

2

Uparallel (Å )

0.7 ± 0.3

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Table 3: The P-O and Y-O distances in the bulk and (100) surface of xenotime from the DFT (in vacuum) in picometers. The percentage change in the average Y-O and P-O distances with respect to the bulk, ∆௉ିை and ∆௒ିை is computed using equation (2). The percentage spread in these distances within a given structure with respect to the mean YO and P-O distances in each structure, ߜ௉ିை and ߜ௒ିை , is computed using equation (3). ୟ୴୥ ୟ୴୥ ୫ୟ୶ ୫ୟ୶ ୫୧୬ ୫୧୬ Structure r୔ି୓ rଢ଼ି୓ r୔ି୓ r୔ି୓ rଢ଼ି୓ rଢ଼ି୓ ∆୔ି୓ ∆ଢ଼ି୓ δ୔ି୓ δଢ଼ି୓ Bulk 155 155 155 231 238 235 0.0% 0.0% 0.0% 3.2% (100) 152 158 156 229 241 234 0.6% -0.5% 3.7% 5.2% layer 1 (100) 155 156 155 231 240 235 0.1% 0.1% 0.4% 3.8% layer 2

Table 4. Average displacement of atoms on the (100) surface of xenotime from their bulk positions along [001] direction upon the adsorption of water molecules (pm)a (To clarify, distances here are relative to the (100) surface normal, but for simplicity we report everything relative to the standard crystallographic orientation of xenotime.) Atom

Two water Four water molecules molecules Y, top layer -3.28 1.02 Y, second layer 0.79 0.08 P, top layer 6.61 1.53 P, second layer -0.11 0.75 a Positive values are for the outward direction and vice versa.

Six water molecules 1.39 -0.13 1.10 0.84

Table 5. Adsorption energy per water molecule on the (100) surface of xenotime

EAd (kJ/mol)

Two water molecules -98.4

Four water molecules -92.2

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Six water molecules -86.9

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