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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Gold-Standard Chemical Database 137 (GSCDB137): A Diverse Set of Accurate Energy Differences for Assessing and Developing Density Functionals

We present GSCDB137, a rigorously curated benchmark library of 137 data sets (8377 entries) covering main-group and transition-metal reaction energies and barrier heights, (intra- and intermolecular) noncovalent interactions, dipole moments, polarizabilities, electric-field response energies, and vibrational frequencies. Legacy data from GMTKN55 and MGCDB84 have been updated to today's best reference values; redundant or low-quality points were removed, and many new, property-focused sets were added. Testing 29 popular density functional approximations (DFAs) confirms the expected Jacob's-ladder hierarchy overall but also reveals notable exceptions: functional performance for frequencies and electric-field properties correlates poorly with that for other ground-state energetics. ωB97M-V and ωB97X-V are the most balanced hybrid meta-GGA and hybrid GGA, respectively; B97M-V and revPBE-D4 lead the meta-GGA and GGA classes. Double hybrids lower mean errors by about 30% versus their hybrid analogues but demand careful frozen-core, basis set, and spin contamination treatment. GSCDB137 offers a comprehensive, openly documented platform for rigorous validation of DFA and universal machine learning potentials, and training of the next generation of exchange-correlation functionals.

Liang, Jiashu [University of California, Berkeley,↗
DOE OSTI2022

Error quantification of the Arrhenius blending rule for viscosity of hydrocarbon mixtures

Six hundred and seventy-five measurements of dynamic viscosity and density have been used to assess the prediction error of the Arrhenius blending rule for kinematic viscosity of hydrocarbon mixtures. Major trends within the data show that mixture complexity–binary to hundreds of components—and temperature are more important determinants of prediction error than differences in molecular size or hydrogen saturation between the components of the mixtures. Over the range evaluated, no correlation between prediction error and mole fractions was observed, suggesting the log of viscosity truly is linear in mole fraction, as indicated by the Arrhenius blending rule. Mixture complexity and temperature also impact molar volume and its prediction. However, a linear regression between the two model errors explains less than 20% of the observed variation, indicating that mixture viscosity and/or molar volume are not linear with respect to temperature and/or mixture complexity. Extensive discussion of the intermolecular forces and the geometric arrangement of molecules and vacancies in liquids, which ultimately determines its viscosity, is brought into context with the implicit approximations behind the Arrhenius blending rule. The complexity of this physics is not compatible with a simple algebraic correction to the model. However, sufficient data is now available to determine confidence intervals around the prediction of fuel viscosity based on its component mole fractions and viscosities. At -40°C, when all identified components are pure molecules the modeling error is 13.2% of the predicted (nominal) viscosity times the root mean square of the component mole fractions.

10 SYNTHETIC FUELS↗
DOE OSTI2022

Decoding the protein–ligand interactions using parallel graph neural networks

Abstract Protein–ligand interactions (PLIs) are essential for biochemical functionality and their identification is crucial for estimating biophysical properties for rational therapeutic design. Currently, experimental characterization of these properties is the most accurate method, however, this is very time-consuming and labor-intensive. A number of computational methods have been developed in this context but most of the existing PLI prediction heavily depends on 2D protein sequence data. Here, we present a novel parallel graph neural network (GNN) to integrate knowledge representation and reasoning for PLI prediction to perform deep learning guided by expert knowledge and informed by 3D structural data. We develop two distinct GNN architectures: $$\hbox {GNN}_{\mathrm{F}}$$ GNN F is the base implementation that employs distinct featurization to enhance domain-awareness, while $$\hbox {GNN}_{\mathrm{P}}$$ GNN P is a novel implementation that can predict with no prior knowledge of the intermolecular interactions. The comprehensive evaluation demonstrated that GNN can successfully capture the binary interactions between ligand and protein’s 3D structure with 0.979 test accuracy for $$\hbox {GNN}_{\mathrm{F}}$$ GNN F and 0.958 for $$\hbox {GNN}_{\mathrm{P}}$$ GNN P for predicting activity of a protein–ligand complex. These models are further adapted for regression tasks to predict experimental binding affinities and $$\hbox {pIC}_{\mathrm{50}}$$ pIC 50 crucial for compound’s potency and efficacy. We achieve a Pearson correlation coefficient of 0.66 and 0.65 on experimental affinity and 0.50 and 0.51 on $$\hbox {pIC}_{\mathrm{50}}$$ pIC 50 with $$\hbox {GNN}_{\mathrm{F}}$$ GNN F and $$\hbox {GNN}_{\mathrm{P}}$$ GNN P , respectively, outperforming similar 2D sequence based models. Our method can serve as an interpretable and explainable artificial intelligence (AI) tool for predicted activity, potency, and biophysical properties of lead candidates. To this end, we show the utility of $$\hbox {GNN}_{\mathrm{P}}$$ GNN P on SARS-Cov-2 protein targets by screening a large compound library and comparing the prediction with the experimentally measured data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Long timescale solvation dynamics and confinement: The case of non-ionic deep eutectic solvents of lauric acid and N-methylacetamide

Microscopic segregation and molecular heterogeneities in complex liquids are the result of the interplay between different intermolecular forces, all of which contribute to the energy landscape of the system. A consequence of the intricate energy landscape is the nontrivial effect on the solvation dynamics. Here, the impact of molecular heterogeneities on the solvation dynamics is studied using infrared spectroscopies and molecular dynamics simulations. In particular, this study focuses on the dynamical effect of nanoscopic heterogeneities present in deep eutectic solvents (DESs) composed of lauric acid (LA) and N-methylacetamide (NMA). To this end, a molecular probe containing a carbon triple bond is used as an infrared reporter. The results show that the vibrational probe is likely to be located in the NMA polar domains. Furthermore, the probe solvation dynamics derived from the 2DIR spectra presents a slowdown of its timescale with increasing LA concentration in the DES. Kubo modeling of the probe solvation dynamics shows a correlation between the amplitude of its long time component and the presence of molecular heterogeneities in the sample. Semiclassical modeling of the vibrational line shape of the triple bond stretch demonstrates that the heterogeneities affect the whole solvation dynamics of the system through the amplitudes of the frequency fluctuations. Molecular dynamics simulations confirm the experimental results and their interpretation by showing a slowdown of the solvation dynamics when the LA heterogeneities are present. Overall, the study presents a molecular framework to explain the effect of confinement created by nanoscopic LA heterogeneities on the solvation dynamics of the system.

Chemical compounds↗
DOE OSTI2022

Systematic Evaluation of Counterpoise Correction in Density Functional Theory

A widespread belief persists that the Boys–Bernardi function counterpoise (CP) procedure “overcorrects” supramolecular interaction energies for the effects of basis-set superposition error. To the extent that this is true for correlated wave function methods, it is usually an artifact of low-quality basis sets. The question has not been considered systematically in the context of density functional theory, however, where basis-set convergence is generally less problematic. We present a systematic assessment of the CP procedure for a representative set of functionals and basis sets, considering both benchmark data sets of small dimers and larger supramolecular complexes. The latter include layered composite polymers with ~150 atoms and ligand–protein models with ~300 atoms. Provided that CP correction is used, we find that intermolecular interaction energies of nearly complete-basis quality can be obtained using only double-ζ basis sets. Furthermore, this is less expensive as compared to triple-ζ basis sets without CP correction. CP-corrected interaction energies are less sensitive to the presence of diffuse basis functions as compared to uncorrected energies, which is important because diffuse functions are expensive and often numerically problematic for large systems. Our results upend the conventional wisdom that CP “overcorrects” for basis-set incompleteness. In small basis sets, CP correction is mandatory in order to demonstrate that the results do not rest on error cancellation.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Predicting and Understanding Non-Covalent Interactions Using Novel Forms of Symmetry-Adapted Perturbation Theory

Although sometimes derided as “weak” interactions, non-covalent forces play a critical role in ligand binding and crystal packing and in determining the conformational landscape of flexible molecules. Symmetry-adapted perturbation theory (SAPT) provides a framework for accurate ab initio calculation of intermolecular interactions and furnishes a natural decomposition of the interaction energy into physically meaningful components: semiclassical electrostatics (rigorously obtained from monomer charge densities), Pauli or steric repulsion, induction (including both polarization and charge transfer), and dispersion. This decomposition helps to foster deeper understanding of non-covalent interactions and can be used to construct transferable, physics-based force fields. Separability of the SAPT interaction energy also provides the flexibility to construct composite methods, a feature that we exploit to improve the description of dispersion interactions. Furthermore, these are challenging to describe accurately because they arise from nonlocal electron correlation effects that appear for the first time at second order in perturbation theory but are not quantitatively described at that level.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Desorption lifetimes and activation energies influencing gas–surface interactions and multiphase chemical kinetics

Abstract. Adsorption and desorption of gases on liquid or solid substrates are involved in multiphase processes and heterogeneous chemical reactions. The desorption energy (Edes0), which depends on the intermolecular forces between adsorbate and substrate, determines the residence time of chemical species at interfaces. We show how Edes0 and temperature influence the net uptake or release of gas species, the rates of surface–bulk exchange and surface or bulk reactions, and the equilibration timescales of gas–particle partitioning. Using literature data, we derive a parameterization to estimate Edes0 for a wide range of chemical species based on the molecular mass, polarizability, and oxygen-to-carbon ratio of the desorbing species independent of substrate-specific properties, which is possible because of the dominant role of the desorbing species' properties. Correlations between Edes0 and the enthalpies of vaporization and solvation are rooted in molecular interactions. The relation between Edes0 and desorption kinetics reflects the key role of interfacial exchange in multiphase processes. For small molecules and semi-volatile organics (VOC, IVOC, SVOC), Edes0 values around 10–100 kJ mol−1 correspond to desorption lifetimes around nanoseconds to days at room temperature. Even higher values up to years are obtained at low temperatures and for low volatile organic compounds (LVOC, ELVOC/ULVOC) relevant for secondary organic aerosols (SOA). Implications are discussed for SOA formation, gas–particle partitioning, organic phase changes, and indoor surface chemistry. We expect these insights to advance the mechanistic and kinetic understanding of multiphase processes in atmospheric and environmental physical chemistry, aerosol science, materials science, and chemical engineering.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

How Accurate Are Simulations and Experiments for the Lattice Energies of Molecular Crystals?

Molecular crystals play a central role in a wide range of scientific fields, including pharmaceuticals and organic semiconductor devices. However, they are challenging systems to model accurately with computational approaches because of a delicate interplay of intermolecular interactions such as hydrogen bonding and Van der Waals dispersion forces. Here, by exploiting recent algorithmic developments, we report the first set of diffusion Monte Carlo lattice energies for all 23 molecular crystals in the popular and widely used X23 dataset. Comparisons with previous state-of-the-art lattice energy predictions (on a subset of the dataset) and a careful analysis of experimental sublimation enthalpies reveals that high-accuracy computational methods are now at least as reliable as (computationally derived) experiments for the lattice energies of molecular crystals. Overall, this work demonstrates the feasibility of high-level explicitly correlated electronic structure methods for broad benchmarking studies in complex condensed phase systems, and signposts a route towards closer agreement between experiment and simulation. Published by the American Physical Society 2024

Physics↗
DOE OSTI2020

Vibrational exciton nanoimaging of phases and domains in porphyrin nanocrystals

Much of the electronic transport, photophysical, or biological functions of molecular materials emerge from intermolecular interactions and associated nanoscale structure and morphology. However, competing phases, defects, and disorder give rise to confinement and many-body localization of the associated wavefunction, disturbing the performance of the material. Here, we employ vibrational excitons as a sensitive local probe of intermolecular coupling in hyperspectral infrared scattering scanning near-field optical microscopy (IR s-SNOM) with complementary small-angle X-ray scattering to map multiscale structure from molecular coupling to long-range order. In the model organic electronic material octaethyl porphyrin ruthenium(II) carbonyl (RuOEP), we observe the evolution of competing ordered and disordered phases, in nucleation, growth, and ripening of porphyrin nanocrystals. From measurement of vibrational exciton delocalization, we identify coexistence of ordered and disordered phases in RuOEP that extend down to the molecular scale. Even when reaching a high degree of macroscopic crystallinity, identify significant local disorder with correlation lengths of only a few nanometers. This minimally invasive approach of vibrational exciton nanospectroscopy and -imaging is generally applicable to provide the molecular-level insight into photoresponse and energy transport in organic photovoltaics, electronics, or proteins.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Voltage-dependent excitation dynamics in UV-absorbing organic photovoltaics with efficient charge transfer exciton emission

Intermolecular charge-transfer excitons play a central role in determining the performance of organic solar cells as their voltage-dependent formation, dissociation, and recombination dynamics contribute to photocurrent generation, radiative/nonradiative voltage losses, and photovoltaic fill factor. Here, we explore the properties of brightly-emitting wide energy gap (>2 eV) charge transfer excitons by measuring the voltage-dependent photoluminescence, photocurrent, and ultrafast pump–probe transient absorption spectra of organic solar cells employing five UV-absorbing donor molecules that differ only by the length of the oligophenylene or acene group at their core. We find that organic solar cells with a strong correlation between their voltage-dependent photocurrent and charge-transfer exciton photoluminescence have low photovoltaic fill factors as they require voltage to facilitate efficient charge-transfer exciton dissociation. In contrast, solar cells that are efficient can readily generate charges without an applied field and have a separate population of tightly-bound charge-transfer excitons that are responsible for emission. Furthermore, considering that the sum of all excitation loss rates (i.e., recombination and charge extraction) must be equal to the excitation generation rate in the steady state, these voltage-dependent data allow us to solve for the voltage-dependent fate of all excitations in the solar cells and estimate upper and lower bounds for geminate and non-geminate recombination, respectively.

14 SOLAR ENERGY↗
DOE OSTI2022

Gaussian approximation of dispersion potentials for efficient featurization and machine-learning predictions of metal–organic frameworks

Energy-related descriptors in machine learning are a promising strategy to predict adsorption properties of metal–organic frameworks (MOFs) in the low-pressure regime. Interactions between hosts and guests in these systems are typically expressed as a sum of dispersion and electrostatic potentials. The energy landscape of dispersion potentials plays a crucial role in defining Henry’s constants for simple probe molecules in MOFs. To incorporate more information about this energy landscape, we introduce the Gaussian-approximated Lennard-Jones (GALJ) potential, which fits pairwise Lennard-Jones potentials with multiple Gaussians by varying their heights and widths. The GALJ approach is capable of replicating information that can be obtained from the original LJ potentials and enables efficient development of Gaussian integral (GI) descriptors that account for spatial correlations in the dispersion energy environment. GI descriptors would be computationally inconvenient to compute using the usual direct evaluation of the dispersion potential energy surface. Here, we show that these new GI descriptors lead to improvement in ML predictions of Henry’s constants for a diverse set of adsorbates in MOFs compared to previous approaches to this task.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Structure of Gas Phase Monohydrated Nicotine: Implications for Nicotine’s Native Structure in the Acetylcholine Binding Protein

In this work, we report a joint experimental–theoretical study of the never reported before structure and infrared spectra of gas phase monohydrated nicotine (NIC) and nornicotine (NOR) and use them to assign their protonation sites. NIC’s biological activity is strongly affected by its protonation site, namely, the pyrrolidine (Pyrro-NICH + , anticipated active form) and pyridine (Pyri-NICH + ) forms; however, these have yet to be directly experimentally determined in either the nicotinic acetylcholine receptor (nAChR, no water present) or the acetylcholine-binding protein (AChBP, a single water molecule is present) but can only be inferred to be Pyrro-NICH + from the intermolecular distance to the neighboring residues (i.e., tryptophan). Our temperature-controlled double ion trap infrared spectroscopic experiments assisted by the collisional stripping method and high-level theoretical calculations yield the protonation ratio of Pyri:Pyrro = 8:2 at 240 K for the gas phase NICH + ···(H 2 O) complex, which resembles the molecular cluster present in the AChBP. Therefore, a single water molecule in the gas phase enhances this ratio in NICH + relative to the 3:2 for the nonhydrated gas phase NICH + in a trend that contrasts with the almost exclusive presence of Pyrro-NICH + in aqueous solution. In contrast, the Pyri-NORH + protomer is exclusively observed, a fact that may correlate with its weaker biological activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Elucidation of Active Sites in Aldol Condensation of Acetone over Single-Facet Dominant Anatase TiO 2 (101) and (001) Catalysts

Aldol condensations of carbonyl compounds for C–C bond formation are a very important class of reactions in organic synthesis and upgrading of biomass-derived feedstocks. However, the atomic level understanding of reaction mechanisms and structure-activity correlation on widely used transition metal oxide catalysts are limited due to the high degree of struc-tural heterogeneity of catalysts such as commercial TiO 2 powders. Here, we provide a deep understanding of the reaction mechanisms, kinetics, and structure–function relationships for vapor phase acetone aldol condensation through the con-trolled synthesis of two catalysts with high surface areas and clean, dominant facets, coupled with detailed characterization and kinetic studies that are further assisted by density functional theory (DFT) calculations. Temperature-dependent diffuse reflectance infrared Fourier transform spectroscopy showed the existence of abundant acetone bonded to surface hydroxyl groups (acetone-O s H) and acetone bonded to Lewis acid sites (acetone-Ti 5c ) on surface of both {101} and {001} facet dom-inant TiO 2 . Intermolecular C–C coupling of enolate intermediate from acetone-Ti 5c and a vicinal acetone-O s H is a kinetically relevant step, which is consistent with kinetic and isotopic studies and DFT calculations. The {001} facet showed a lower apparent activation energy (or higher reactivity) than the {101} facet. This is likely caused by the weaker Lewis acid and Brønsted base strengths of the {001} facet which favors the reprotonation–desorption of the coupled intermediate, making the C–C coupling step more exothermic on the {001} facet and resulting in an earlier transition state with a lower activation barrier. It is also possible that the {001} facet has a smoother surface configuration and less steric hindrance during intermo-lecular C–C bond formation than the {101} facet.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Polarizable Water Potential Derived from a Model Electron Density

A new empirical potential for efficient, large scale molecular dynamics simulation of water is presented. The HIPPO (Hydrogen-like Intermolecular Polarizable POtential) force field is based upon the model electron density of a hydrogen-like atom. This framework is used to derive and parametrize individual terms describing charge penetration damped permanent electrostatics, damped polarization, charge transfer, anisotropic Pauli repulsion, and damped dispersion interactions. Initial parameter values were fit to Symmetry Adapted Perturbation Theory (SAPT) energy components for ten water dimer configurations, as well as the radial and angular dependence of the canonical dimer. The SAPT-based parameters were then systematically refined to extend the treatment to water bulk phases. The final HIPPO water model provides a balanced representation of a wide variety of properties of gas phase clusters, liquid water, and ice polymorphs, across a range of temperatures and pressures. This water potential yields a rationalization of water structure, dynamics, and thermodynamics explicitly correlated with an ab initio energy decomposition, while providing a level of accuracy comparable or superior to previous polarizable atomic multipole force fields. The HIPPO water model serves as a cornerstone around which similarly detailed physics-based models can be developed for additional molecular species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Conversion between triplet pair states is controlled by molecular coupling in pentadithiophene thin films

In singlet fission (SF) the initially formed correlated triplet pair state, 1 (TT), may evolve toward independent triplet excitons or higher spin states of the (TT) species. The latter result is often considered undesirable from a light harvesting perspective but may be attractive for quantum information sciences (QIS) applications, as the final exciton pair can be spin-entangled and magnetically active with relatively long room temperature decoherence times. In this study we use ultrafast transient absorption (TA) and time-resolved electron paramagnetic resonance (TR-EPR) spectroscopy to monitor SF and triplet pair evolution in a series of alkyl silyl-functionalized pentadithiophene (PDT) thin films designed with systematically varying pairwise and long-range molecular interactions between PDT chromophores. The lifetime of the (TT) species varies from 40 ns to 1.5 μs, the latter of which is associated with extremely weak intermolecular coupling, sharp optical spectroscopic features, and complex TR-EPR spectra that are composed of a mixture of triplet and quintet-like features. On the other hand, more tightly coupled films produce broader transient optical spectra but simpler TR-EPR spectra consistent with significant population in 5 (TT) 0 . These distinctions are rationalized through the role of exciton diffusion and predictions of TT state mixing with low exchange coupling J versus pure spin substate population with larger J. The connection between population evolution using electronic and spin spectroscopies enables assignments that provide a more detailed picture of triplet pair evolution than previously presented and provides critical guidance for designing molecular QIS systems based on light-induced spin coherence.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Variable domain mutational analysis to probe the molecular mechanisms of high viscosity of an IgG 1 antibody

Subcutaneous injection is the preferred route of administration for many antibody therapeutics for reasons that include its speed and convenience. However, the small volume limit (typically ≤2 mL) for subcutaneous delivery often necessitates antibody formulations at high concentrations (commonly ≥100 mg/mL), which may lead to physicochemical problems. For example, antibodies with large hydrophobic or charged patches can be prone to self-interaction giving rise to high viscosity. Here, we combined X-ray crystallography with computational modeling to predict regions of an anti-glucagon receptor (GCGR) IgG 1 antibody prone to self-interaction. An extensive mutational analysis was undertaken of the complementarity-determining region residues residing in hydrophobic surface patches predicted by spatial aggregation propensity, in conjunction with residue-level solvent accessibility, averaged over conformational ensembles from molecular dynamics simulations. Dynamic light scattering (DLS) was used as a medium throughput screen for self-interaction of ~200 anti-GCGR IgG 1 variants. A negative correlation was found between the viscosity determined at high concentration (180 mg/mL) and the DLS interaction parameter measured at low concentration (2–10 mg/mL). Additionally, anti-GCGR variants were readily identified with reduced viscosity and antigen-binding affinity within a few fold of the parent antibody, with no identified impact on overall developability. The methods described here may be useful in the optimization of other antibodies to facilitate their therapeutic administration at high concentration.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Protein Molecular Dynamics Simulations with Approximate QM: What Can We Learn?

Classical force fields are essential for computer simulations of proteins and are typically parameterized to reproduce secondary and tertiary structure of isolated proteins. However, while protein-protein interactions are ubiquitous in nature, they are not considered in parameterization efforts and are far less understood than isolated proteins. A better characterization of intermolecular interactions is widely recognized as a key to revolutionizing drug and therapeutic developments with high-throughput computational screening. Urgently needed is a critical assessment of the performance of modern protein force fields against first-principles electronic structure methods and experiments. In a daring step toward this goal, we here describe a comparison of peptide folding dynamics as predicted by a molecular mechanics force field on the one hand and by an approximate electronic structure quantum mechanical (QM) method based on density-functional tight-binding (DFTB) on the other. We further compare the dynamics from straightforward DFTB simulations with a near-linear scaling version of DFTB for massively parallel computation based on the fragment molecular orbital (FMO-DFTB) method. We illustrate differences between the phenomenology of the folding dynamics from these three methods for a small model peptide, as well as charge polarization and dynamic fluctuations, point out possible correlations and implications for force field developers, and discuss the lessons learned that might become applicable to future predictive high-throughput computer screening for personalized neoantigen cancer therapy.

Irle, Stephan↗
DOE OSTI2026

Quantifying Outer- and Inner-Coordination Sphere Effects Using Uranium Redox Chemistry in Molten Salt Solutions

Defining the relative influence of intramolecular and intermolecular forces is a fundamental problem in chemistry that is difficult to quantify. To address this challenge, we developed a method to evaluate the relative impact of direct chemical bonding in the inner-coordination sphere vs effects from cations in the outer-coordination sphere by comparative analysis of uranium redox reactivity in various molten salts. We observed that outer-coordination sphere cations (M 1+ ) and inner-coordination sphere anions (X 1– ) both affected uranium redox reactivity, with more polarizing M 1+ and larger X 1– favoring uranium in low oxidation states. Changing M 1+ (Li, Na, K) shifted the U IV + e 1– ⇌ U III (U IV/III ) and U III + 3e 1– → U 0 metal potentials by +330 and +240 mV, respectively. Changing X 1– (Cl, Br, I) caused larger shifts of +440 mV for the U IV/III redox potential and +1060 mV for the U 0 metal deposition potential. Using Coulomb’s Law, we correlated these potentials with electrostatic interactions between UIII and the molten salt. This model provided a facile way of predicting redox chemistry within molten salts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗