Decoding Oxyanion Aqueous Solvation Structure - ACS Publications

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B: Liquids, Chemical and Dynamical Processes in Solution, Spectroscopy in Solution

Decoding Oxyanion Aqueous Solvation Structure: A Potassium-Nitrate Example at Saturation Hsiu-Wen Wang, Lukas Vlcek, Joerg C. Neuefeind, Katharine Page, Stephan Irle, John Michael Simonson, and Andrew G. Stack J. Phys. Chem. B, Just Accepted Manuscript • DOI: 10.1021/acs.jpcb.8b05895 • Publication Date (Web): 10 Jul 2018 Downloaded from http://pubs.acs.org on July 17, 2018

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The Journal of Physical Chemistry

Decoding Oxyanion Aqueous Solvation Structure: A Potassium-Nitrate Example at Saturation Hsiu-Wen Wang,†,* Lukas Vlcek,† Joerg C. Neuefeind,‡ Katharine Page,‡ Stephan Irle,§ J. Michael Simonson,‡ and Andrew G. Stack†,* †

Chemical Sciences Division, ‡Spallation Neutron Source, §Computational Sciences & Engineering

Division; Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN 37830. AUTHOR INFORMATION Corresponding Author *Andrew G. Stack or Hsiu-Wen Wang: [email protected] or [email protected]

ACS Paragon Plus Environment

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ABSTRACT

The ability to probe the structure of a salt solution at the atomic scale is fundamentally important for our understanding of many chemical reactions and their mechanisms. The capability of neutron diffraction to “see” hydrogen (or deuterium) and other light isotopes is exceptional for resolving the structural complexity around the dissolved solutes in aqueous electrolytes. We have made measurements using oxygen isotopes on aqueous nitrate to reveal a small hydrogen-bonded water coordination number (3.9 ± 1.2) around a nitrate oxyanion. This is compared to estimates made using the existing method of nitrogen isotope substitution and those of computational simulations (>5-6 water molecules). The low water coordination number, combined with a comparison to classical molecular dynamics simulations, suggest that ion pair formation is significant. This insight demonstrates the utility of experimental diffraction data for benchmarking atomistic computer simulations, enabling the development of more accurate intermolecular potentials.


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1. INTRODUCTION Despite decades of study, the atomic-level structure of solvated oxyanions (e.g., nitrate, carbonate, and aluminate) remains a topic of intense discussion. The open questions include solvent coordination numbers, extent of ion pair/cluster formation, solvation structural rigidity, and residence times. Further inquiries about the nature of salt solutions at or above their solubility limits revolve around the formation of larger scale structures (e.g., contact, solvent-shared, or solvent-separated ion-pairs or solute clusters), which ultimately determine the mechanisms of conformational changes, chemical reactions, and nucleation processes. Although the macroscopic concepts of hydration enthalpy and activityconcentration relationships have been applied to advance our understanding of ion hydration and pair formation within the construct of solution thermodynamics,1-2 they cannot be used to infer reliably the atomic-scale structures and reactions. The ability to capture a salt solution’s atomic-scale structure is critically important to conceptualize and understand non-classical behaviors during crystal nucleation and growth, observations of which have been attributed to the formation of stable pre-nucleation clusters in the aqueous phase.3-5 The dynamically ordered liquid-like oxyanion polymer (DOLLOP) discovered in supersaturated CaCO3 solutions is a well-known example of this concept.3,6 This contrasts with classical nucleation theory where nucleation rate is limited by the size of a critical nucleus, or perhaps even simple ion association/ion-pairing as a rate limiting step.7-9 (De)Solvation processes also underlie many natural and industrial phenomena, including (bio)mineralization, climate change, drug synthesis, and environmental remediation, etc. In recent years, theoretical exploration of solvation processes has relied heavily on molecular dynamics (MD) simulations and led to substantial progress in our understanding of the microscopic driving forces responsible for hydration dynamics and ion pairing. Less attention has been paid to the experimentally-derived radial distribution functions (RDFs) using X-ray and neutron diffraction


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methods. Diffraction methods effectively measure the structural pair correlations in solution, can potentially bring direct insight into hydration state, and provide a valuable source for validation of molecular simulations and force field parameterization.10 Interpretation of experimental RDF is, however, difficult and sometimes impossible, due to the low scattering weights of solute species (concentration is limited by the solubility) and the fact that the information about pair correlations between different atomic species is combined into a single total RDF. Enderby and co-workers have devoted extensive effort to address the structural problem of the ion-water system by diffraction techniques,11-12 and suggest that neutron diffraction with isotope substitution (NDIS) can overcome much of the unfavorable complexity encountered in multi-component solution systems. The NDIS approach allows the isolation of specific pair correlation functions for the study of hydration structures, and ion pairing/clustering. Despite being well-established, the practical difficulties underlying NDIS experiments have limited their application. Although almost every nucleus with a contrast has been measured, many data sets are 20-30 years old, whereas modern neutron sources have higher fluxes and better resolution. A combined analysis of NDIS data based on atomistic simulations has only recently been defined, raising the possibility of using this technique to evaluate and parameterize computational models quantitatively; examples include salts in null or HDO water,13-15

nat

Ca/44Ca of CaCl2-D2O solutions,10,16 and a few

studies including anions, such as 14N/15N and 35Cl/37Cl.17-19 The potential of the NDIS approach to offer an experimental measure of the atomic-scale structure unavailable by other means is highly valuable.10,20-22 Here, we use KNO3 (in D2O) solution as a representative case, using two different substitutions of nitrogen (natN/15N) and oxygen (natO/18On) isotopes on N and On sites of the NO3- anion. This is the first NDIS experiment involving oxygen isotopes on a solute, since it has only recently been discovered that the scattering-length contrast between

nat

O and

18

O is 0.204(3) fm,23 nearly 6 times


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greater than the previously accepted value by Sears et al.,24 and thus sufficient for this type of study. More than just new NDIS data, we use a theoretical approach previously developed but never applied,25 and compare our measurements to those predicted by classical MD simulations. Given the debate over the reaction mechanisms of nucleation described above in the CaCO3 system, there is an urgent need for experimental data to validate the computational models resulting in the very different perspectives on the reaction mechanisms of nucleation: classical vs. non-classical, pre-nucleation clusters vs. ion pairing. The high-resolution nitrate oxyanion NDIS data presented here can be used to validate these models, and to develop more robust predictive capabilities. While we use aqueous nitrate as a test system, the nature of nitrate-water interactions is itself intrinsically important in a variety of environmental and industrial fields, such as in the manufacturing of nitrate-based fertilizers or explosives, in the glassmaking industry, in nuclear reprocessing, as well as for mitigating nitrate aerosols as climate change drivers.26-28 One core concept in the design of new and less energy intensive methods (e.g., crystallization via ligand coordination29) relies in part on the knowledge of the hydration and speciation of the nitrate anion. Comprehensive reviews2,25,30-31 have shown contrasting experimental observations (neutron/X-ray diffraction, NMR, IR, and Raman) regarding the hydration structure of NO3-. These led to the conclusion that interactions between water and NO3- are relatively weak.2 MD simulations (performed mostly at low salt concentrations, < ~1 m) of NO3- hydration suggest the sensitivity of computed RDFs to the chosen interaction potentials (force fields), and dramatically different coordination numbers, 6-20, have been reported.25,30,32-39 A relevant issue for nitrate salt solution hydration is the potential for ion-pair (metal-ligand) formation based on the arguments of monotonically decreasing in activity coefficients with increasing salt concentrations.25,40-42 Figure 1 depicts proposed structures with 3,43 6,19,43 and 544 water molecules coordinated around NO3-


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configured based on concentrated NaNO3(aq) diffraction data, the disparity is likely due to ignorance of ion-pairing propensity.

Figure 1. Schematic representation of local NO3--H2O coordination based on descriptions by Caminiti et al.43 in (A) and (B), Neilson and Enderby 44 in (C), and Kameda et al.19 in (B). Orange-shaded cones represent possible fluctuations of H-bonds (thick black/white line) or extension of H2O arrangements by local reorientation.

2. EXPERIMENTAL METHODS Solution Preparation. In the present work, three 3.4 m KNO3 solutions are used: natural-KNO3, K15NO3, and KN18O3. Two isotopically enriched samples, K15NO3 (99.7% 15N, >98% purity, CIL Inc.) and KN18O3 (>80% 18On, >98% purity, CIL Inc.), and one natural KNO3 (natural abundance of natN and nat

On) of reagent grade (99.999% purity, Sigma-Aldrich) were first dried in the vacuum oven attached to

a positive pressure N2 glove box at 110 ºC for 24 hours. This drying step removes physisorbed H2O molecules from sample powders, prior to dissolving into D2O water (99.99% D, 100% purity, SigmaAldrich). KNO2 arising from manufacturing processes in the isotopically labeled samples appears to be the dominated impurities. Detailed methods of the concentration control and elimination of the impurity phase are given in Supporting Information 1. Table S1 summarizes the stoichiometric composition of each prepared solution, along with atomic fraction and number densities. Neutron Diffraction. Solutions were sealed into cylindrical quartz NMR tube (507-PP-7QTZ, Wilmad-LabGlass), and loaded in the sample shifter carousel at the Nanoscale Ordered MAterials Diffractometer (NOMAD) instrument at the Spallation Neutron Source (SNS), Oak Ridge National Laboratory (ORNL), as described by Neuefeind et al.45 For each solution, scattering data were collected


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in 40 minute frames at room temperature in an Ar atmosphere for a total of 10 hours at 60 Hz setting. The beamline’s autoreduction software45 was used to normalize data, and perform the NDIS difference analyses. We emphasize here that both N- and On-NDIS are challenging experiments. At the studied concentration (3.4 m), the contrast on the N substitution is ~6.9 microbarns/sr/atom, i.e., 1.7% of the total scattering. The contrast on the On substitution is ~1.4 microbarns/sr/atom, i.e., 0.4% of the total scattering–an exceptionally challenging experiment. This effect can be seen in Figure 2A, where the overall difference intensities (circle symbols) are about 5 times smaller for On-NDIS data, given the same noise level at the high-q region. The pair of solutions prepared must to be accurate in concentration within hundreds of ppm to achieve desirable accuracy. NDIS First-Order Difference Analysis. The concept behind NDIS difference analysis is to study a pair of samples that are identical in all respects, except that the isotope of one of the elements has been changed. With the use of isotopes, by means of the dependence of the neutron coherent scattering length (bcoh), partial structure factors can be obtained directly from the first-order difference approach that comprises: (i) subtraction between two total structure factors, ‫ܨ‬ሺ‫ݍ‬ሻ, from diffraction data involving isotope substitutions (generating a Δ‫ܨ‬ሺ‫ݍ‬ሻ; Fig. 2A), and (ii) Fourier transformation of the as-obtained ∆‫ܨ‬ሺ‫ݍ‬ሻ intensities into the real-space signal, i.e., the first-order difference RDF ∆‫ܩ‬ሺ‫ݎ‬ሻ (Fig. 2B). The notations for

nat

N/15N and

nat

On/18On substitutions on NO3- are ∆‫ܨ‬ே ሺ‫ݍ‬ሻ and ∆‫ܨ‬ை೙ ሺ‫ݍ‬ሻ, and their Fourier

transforms are ∆‫ܩ‬ே ሺ‫ݎ‬ሻ and ∆‫ܩ‬ை೙ ሺ‫ݎ‬ሻ, respectively. Fundamentals on difference analysis, data reduction, and comparison to the published N-NDIS work19 are given in Supporting Information 2, 3 and 4, respectively. Simulations. Classical MD simulations were performed using LAMMPS in the NPT ensemble at ambient conditions, and with the equations of motion integrated using the Verlet algorithm in 1 fs time step. The temperature (298.15 K) and pressure (1 atm) were maintained using the Nose-Hoover


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thermostat and barostat. The Coulombic interactions were treated using the particle-particle particlemesh method. The bonds and angles in H2O and NO3- were kept rigid, and the interactions within the solution were represented by a non-polarizable force field combining the Lennard-Jones potential and Coulombic interactions between point charges located at atomic sites. Optimization of force field parameters against experimental NDIS data were performed and details are given in Supporting Information 5.

3. RESULTS AND DISCUSSION The NDIS-based approach reduces a single diffraction data set from a total of 15 partial structure factors for this system into 5 partials from NDIS data pairs. Information contained is different in each isotope substitution and is advantageous for exploring weak solvation structures since it eliminates many of the contributions that are not of interest (e.g., those of water to itself). The difference in scattering between the natN/15N solutions reveals 5 partial structure factors with respect to only the nitrate-N site, i.e., N-Ow, N-D, N-K, N-N, and N-On. In contrast, the difference for the

nat

On/18On solutions contains 5 different

structure factors, i.e., On-Ow, On-D, On-K, On-On, and On-N. Figure 2A shows the measured NDIS intensities (circle symbols) with the normalization implied for the self-consistency of NO3 intramolecular coordination. In diffraction experiments, waves scattered by any molecules with defined geometry will result in the periodic oscillation form factor at the high-q side of the intensity pattern (Fig. 2A), and this can be theoretically calculated (yellow lines in Fig. 2A) based on geometrical model functions ܵ௜௡௧௥௔ ሺ‫ݍ‬ሻ12,19,44 (details in Supporting Information 2). Figure 2B shows Fourier transformed RDF ∆‫ܩ‬ሺ‫ݎ‬ሻ patterns. The component containing only intermolecular distance correlations (bottom panel in Fig. 2B) is obtained via Fourier transformation of the intensity function with the NO3 geometry removed. The value of intramolecular N-On (1.253(5) Å) and On-On (2.170(8) Å) distances obtained from a geometrical model agrees well with previously reported studies.19,31,34-35,44,46 The intermolecular


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interactions in ∆‫ܩ‬ሺ‫ݎ‬ሻ appear clearly at r > 1.8 Å, and the peak at 1.9(2) Å in ∆‫ܩ‬ை೙ ሺ‫ݎ‬ሻ can be readily assigned to the nearest neighbor D-bonds (OnD in Fig. 2B). This D-bonding interaction is observed unambiguously for the first time experimentally, and conforms to the reported length estimates (~1.8-2.3 Å) from MD simulations.21,25,32-37,47-49 Integration under this peak results 1.3(4) D atoms that are ை

coordinated in the immediate vicinity of each On site (݊஽೙ ), suggesting that each On accepts 1-2 D-bonds from nearby D2O molecules (estimated limit of ±0.4 is based on Nyquist sampling). The On isotope substitution is valuable since the coordination environment of the oxyanion is provided by the nearest neighbors around oxygen sites, as opposed to the second nearest neighbors by the central nitrogen. For example, there is no clear indication of the first minimum value in the intermolecular ∆‫ܩ‬ே ሺ‫ݎ‬ሻ curve on nitrogen-labeled solutions, due to the partial overlap of ND and NOw RDFs (Fig. 2B). In fact, as mentioned above, the interpretation of ND/Ow distances and solvation structures sketched from the experimental data have been interpreted quite variously (Fig. 1). This data clearly show why adequate measurement of deuterium and water coordination can only be made from oxygen isotope substitutions on the nitrate-On site due to the absences of any potential distance overlapping. Similarly, the K+NO3contact ion-pair distances25,42 are also excluded in this distance range on oxygen-labeled solutions (KOn = ~ 2.8 Å, and KN = ~ 3.3 Å). The 3.9 ± 1.2 hydrogen-bonded water coordination obtained ை

solely from ݊஽೙ (1.3×3 for 3 On sites per nitrate) is significantly smaller than any reported MD predictions (> 6) performed at low salt concentrations (see Supporting Information 6 for detailed discussion), which indicates the replacement of water molecules by K+ ions as ion pairs cannot be ignored at the concentration studied here (i.e., at solubility limits).


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Figure 2. (A) NDIS difference function of normalized structure factor (circle symbols with error bars). The intramolecular NOn and On-On geometrical model fit functions are shown as yellow lines in plot A. (B) The corresponding Fourier transformed RDFs with respect to N (black lines) and On (blue lines) atoms. (C) Intermolecular total N-NDIS RDFs (bold black and red lines from experiment and simulation, respectively), and (D) intermolecular total On-NDIS RDFs (bold blue and red lines from experiment and simulation, respectively). Experimental error bars (grey lines) are given based on Nyquist sampling with 0.02 Å-1 ∆q resolution and 20 Å-1 qmax. All other colored line in plots C and D correspond to the decomposition of total RDF into the contributions of simulated partial RDFs. Associated number in parentheses for each partial RDF represents the weighting contribution (%) to the total observed intensity.

To better understand the peak contributions in experimental RDFs, especially ion pair formation, RDFs obtained from NDIS experiments and calculated from our own classical MD simulations that include both as-implemented original and optimized potential models are shown in Figure S3 and Figures 2C-D, respectively. Optimization of force field parameters for nitrate charge distributions, water-nitrate interactions, as well as interactions between potassium and the nitrate-On site allows the MD model to match the OnD peak intensities and permit the contact ion pair formation. The direct integration and coordination number determined on the selected partial RDFs are summarized in Table S3 for a straightforward comparison with NDIS-based integration. The optimized MD model (Figs. 2CD), in general, captures the peak correlations observed in the experimental data well. However, the N-D RDF is much more pronounced, and the model has difficulty matching the intensity of ~3-4 Å in


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∆‫ܩ‬ே ሺ‫ݎ‬ሻ and ~2-3.5 Å in ∆‫ܩ‬ை೙ ሺ‫ݎ‬ሻ (Figs. 2C-D). One possible source of these discrepancies is from slight variation in concentration between the paired solutions, which includes the two salt solutions that may not have exactly the same molality and/or have different degrees of hydrogen contamination. Demonstration of concentration errors in the context of selected pair-wise contributions based on MD predictions is presented in Figure S4. Using this method, we emphasize the practical difficulties and sensitivities underlying NDIS experiments from the viewpoint of concentration imperfections, e.g., small (< 1% for N substitutions and < 0.1% for On substitutions) H:D ratio imperfections can have appreciable effects on the measured isotope differences. Another source of disagreement can originate from inaccuracies in the force field used in the classical MD simulations. For instance, it can be argued that the mismatch in the distance-range of 2-4 Å of both ∆‫ܩ‬ே ሺ‫ݎ‬ሻ and ∆‫ܩ‬ை೙ ሺ‫ݎ‬ሻ (Figs. 2C-D) is linked to the distinct minima (i.e., over-structuring) present in the simulated N-D (~3.2 Å) and On-D (~2.6 Å) partial RDFs. As shown by Tongraar et al.32 (in their Fig. 2) using QM/MM simulations at the level of B3LYP/MM, it is possible that the first and second peaks of the N-D partial RDF could be merged in a more realistic description, forming thus a rather broad distribution without a distinct minimum. Such a result would possibly improve the match between the experiment and model and eliminate a significant portion of the discrepancy. This discrepancy may indicate that a more flexible model, resulting in a more flexible hydration shell or electron-cloud structure, may be required here, and that a clear definition of the coordination number in the first hydration shell may not be feasible for a weak and distorted nitrate-water interaction. Another source of the observed mismatch is likely coming from underestimating K+NO3- contact pair formation, which contributes to the ~3.3 Å N-K and ~2.8 Å On-K RDF peak intensities. In a previous classical MD study,42 the formation of contact ion-pairs in the first hydration shell of NO3- has been shown to replace 0.8-0.9 first-shell H2O molecules when cations were monovalently coordinated to one On site. This


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number increased to 1.2-1.5 when cations were shared by two On sites (bidentate coordination type).42 We observed similar competition in our simulations, in which one K+ ion replaces 1-1.5 H2O molecules (Fig. 3). The fact that the experiments were performed with a saturated solution, at which large fluctuations in ion pairing and clustering can occur, imposes high demands on the accuracy of the force field to describe the thermodynamics of dissolution and precipitation. While we have optimized the force field parameters to best match the experimental atom-pair correlations in the solution, accurate reproduction of the phase equilibria would also require a reliable description of the crystal phase. For the latter perspective, it has been shown by Moucka et al.50 that simple non-polarizable force fields optimized for solution phase properties do not describe the crystal thermodynamics well, so a reliable description may be beyond the reach of this model.

Figure 3. MD trajectory snapshots of the first/second water solvation structure around a nitrate anion, showing replacement of water molecules by K+ cations. The van der Waals radius for each atom type is displayed for easy recognition of ion pairing formation. Water-Ow is in red, water-D in white, nitrate-On in orange, nitrite-N in cyan, and K in green. Plot shown at right highlights no nitrate-water interactions immediately above/below the plane of nitrate.

4. CONCLUSION In conclusion, we have benchmarked a case study that resolves oxyanion solvation and ion-pairing structure through a novel application of oxygen isotope neutron diffraction combined with rigorous examination and integration of experimental NDIS data with molecular simulations. A water coordination number of 3.9 ± 1.2 was found around the nitrate ion, which we view as an improvement


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over older estimates since it is interpreted directly from the 1st shell coordination between oxygen on the nitrate and deuterium on water. Analysis of this measurement, taken at the solubility limit, suggests that ion-pair formation significantly reduces the water coordination number. As we show, obtaining precise agreement for the extent of ion pair formation is challenging for atomic-scale simulations, suggesting this data should be used to resolve the discrepancy in reactions mechanisms for solid-phase nucleation predicted by different computational methods.6,8-9 In comparison to spectroscopy methods1,31,40,51-52 or inference implicitly based on macroscopic thermochemistry properties (e.g., activity coefficients1,53), the NDIS approach emerges as a powerful method to quantify solvation and ion pairing in aqueous solutions, and can serve as a rigorous validation of force field quality and parameter optimization, while the simulations can aid in peak assignment and deconvolution in the experimental data. Furthermore, the site-specific ion-water interactions obtained in NDIS approach together with validated modeling theoretically opens the path to molecular-based arguments for macroscopic thermodynamic properties, e.g., salt activity coefficients,54 and cation-anion binary interaction parameters in the Pitzer activityconcentration model.54 The improved understanding and knowledge gained from these activities will enhance our predictive understanding of ion-water interactions, which are ubiquitous in heterogeneous catalysis, environmental remediation, mineral growth and dissolution, and energy storage materials.

ACKNOWLEDGMENT This work is supported by the US Department of Energy (DOE), Office of Science (SC), Office of Basic Energy Sciences (BES), Chemical Sciences, Geosciences, and Biosciences Division. The NOMAD instrument at ORNL's SNS is sponsored by the DOE, SC, BES, Scientific User Facilities Division. ASSOCIATED CONTENT Supporting Information


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The Supporting Information is available free of charge on the ACS Publication websites. Sections 1-7 contains supporting text for materials and methods, including figures and tables. All combined in one PDF file. Notes The authors declare no competing financial interests. REFERENCES (1) (2) (3) (4)

(5) (6) (7)

(8)

(9)

(10)

(11) (12) (13) (14)

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Decoding Oxyanion Aqueous Solvation Structure - ACS Publications

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