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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Spatial Study 2021: Sample-Based Surface Water Chemistry and Organic Matter Characterization across Watersheds in the Yakima River Basin, Washington, USA (v3)

This dataset supports a broader study examining the drivers of spatial variability in sediment respiration rates in the Yakima River Basin. The dataset provides geochemistry and organic matter characterization data generated from samples collected during the same two-week period at 47 sites within multiple rivers throughout the Yakima River Basin in Washington, USA. Related sensor data are published at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1892054. This data package was originally published September 2022. It was updated May 2023 (modified files) and November 2024 (new and modified files). See the change history section in the readme for more details. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) dissolved inorganic carbon (DIC), dissolved organic carbon (DOC; reported as non-purgeable organic carbon; NPOC), total nitrogen (TN), total suspended solids (TSS), ions, and benzene polycarboxylic acid (BPCA) concentration and stable isotope data; (5) averaged values from water chemistry data; (6) surface water sampling protocol; (7) sensor protocol (8) readme; (9) methods codes; (10) international generic-sample number (IGSN) mapping file; and (11) folder of high resolution characterization of organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). This folder contains two subfolders, one containing the .xml data files and the other containing instructions for using Formultitude (https://github.com/PNNL-Comp-Mass-Spec/Formultitude) and an R script to process the data based on the user's specific needs. All files are .csv, .pdf, .R, .ref, or .xml. We thank the United States Forest Service, Washington Department of Natural Resources, Washington Department of Fish and Wildlife, Washington State Parks, Confederated Tribes and Bands of the Yakama Nation, and Cowiche Canyon Conservancy for access to field locations where these samples were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

An interactive machine learning platform for analyzing multi-particle coincidence data from cold target recoil ion momentum spectroscopy

We present SCULPT (Supervised Clustering and Uncovering Latent Patterns with Training), a comprehensive software platform for analyzing tabulated high-dimensional multi-particle coincidence data from Cold Target Recoil Ion Momentum Spectroscopy (COLTRIMS) experiments. The software addresses critical challenges in modern momentum spectroscopy by integrating advanced machine learning techniques with physics-informed analysis in an interactive web-based environment. SCULPT implements uniform manifold approximation and projection for non-linear dimensionality reduction to reveal correlations in high-dimensional data. We also discuss potential extensions to deep autoencoders for feature learning and genetic programming for automated discovery of physically meaningful observables. A novel adaptive confidence scoring system provides quantitative reliability assessments by evaluating user-selected clustering quality metrics with predefined weights that reflect each metric’s robustness. The platform features configurable molecular profiles for different experimental systems, interactive visualization with selection tools, and comprehensive data filtering capabilities. Utilizing a subset of SCULPT’s capabilities, we analyze photo-double-ionization data measured using the COLTRIMS method for three-body dissociation of the D 2 O molecule, revealing distinct fragmentation channels and their correlations with physics parameters. The software’s modular architecture and web-based implementation make it accessible to the broader atomic and molecular physics community, significantly reducing the time required for complex multi-dimensional analyses. This opens the door to finding and isolating rare events exhibiting non-linear correlations on the fly during experimental measurements, which can help steer exploration and improve the efficiency of experiments.

Artificial neural networks↗
DOE OSTI2024

Manuscript Workflows from and Processed Organic Matter Composition of Experimentally Burned Open Air and Muffle Furnace Vegetation Chars across Differing Burn Severity and Feedstock Types from Pacific Northwest, USA (v3)

This dataset includes processed organic matter chemistry data from an experimental study designed to compare how the chemical composition of organic matter changes across different burn conditions and vegetation materials representative of major land cover types of the Pacific Northwest, USA. Chars were created in a closed muffle furnace or on an open burn table from four different feedstock species representing vegetation commonly impacted by fire regimes across the Pacific Northwest, USA. Source data and associated metadata (including methods and geospatial information) can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1894135 (Grieger et al. 2022). This dataset provides processing scripts and processed data for both solid and dissolved phase organic matter characterization data from experimentally generated chars. These processed data can be used to compare how different burn conditions may influence resultant organic matter chemistry and help further our understanding of potential biogeochemical impacts on river corridors post-fire. The processed data were subsequently analyzed; and the results and ecological implications of the findings were published in peer-reviewed manuscripts. The scripts and workflows used to develop the manuscripts are also included in this data package.This data package was originally published June 2024. It was updated September 2024 (new and modified files) and in January 2025 (modified files). See the change history section in the readme for more details.This dataset is comprised of one data package readme, one data dictionary (dd), one file level metadata (flmd), and folders containing (A) processed data; (B) general processing scripts; and (C) additional folders with specific manuscript analysis scripts and processed data. Step-by-step instructions to assist the user in recreating the workflow used to generate the results in the manuscripts is also provided. The processed data folder includes (1) a folder of processed Parallel Factor Analysis (PARAFAC) and spectra indices outputs from excitation emissions matrix (EEM) fluorescence and absorbance data; (2) a folder of processed solid state carbon-13 (13-C NMR) integrals; (3) folder of high resolution characterization of organic matter via 21 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) processed data outputs from Formultitude (https://github.com/PNNL-Comp-Mass-Spec/Formultitude), blank corrections and data aggregation, and calculated molecular indices. All files are .pdf, .csv, .html, .Rmd, .R, or .RData.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Theoretical Design of Lithium Chloride Superionic Conductors for All-Solid-State High-Voltage Lithium-Ion Batteries

The development of solid electrolytes (SEs) is a promising pathway to improve the energy density and safety of conventional Li ion batteries. Several lithium chloride SEs, Li 3 MCl 6 (M = Y, Er, In, and Sc), have gained popularity due to their high ionic conductivity, wide electrochemical window, and good chemical stability. This study systematically investigated 17 Li 3 MCl 6 SEs to identify novel and promising lithium chloride SEs. Calculation results revealed that 12 Li 3 MCl 6 (M = Bi, Dy, Er, Ho, In, Lu, Sc, Sm, Tb, TI, Tm, and Y) were stable phase with a wide electrochemical stability window and excellent chemical stability against cathode materials and moisture. Li-ion transport properties were examined using bond valence site energy (BVSE) and ab initio molecular dynamics (AIMD) calculation. Li 3 MCl 6 showed the lower migration energy barrier in monoclinic structures, while orthorhombic and trigonal structures exhibited higher energy barriers due to the sluggish diffusion along the two-dimensional path based on the BVSE model. AIMD results confirmed the slower ion migration along the 2D path, exhibiting lower ionic diffusivity and higher activation energy in orthorhombic and trigonal structures. For the further increase of ionic conductivity in monoclinic structures, Li-ion vacancy was formed by the substitution of M 3+ with Zr 4+ . Zr-substituted phase (Li 2.5 M 0.5 Zr 0.5 Cl 6 , M = In, Sc) exhibited up to a fourfold increase in ionic conductivity. This finding suggested that the optimization of Li vacancy in the Li 3 MCl 6 SEs could lead to superionic Li 3 MCl 6 SEs.

25 ENERGY STORAGE↗
DOE OSTI2020

Origin of Unusual Acidity and Li+ Diffusivity in a Series of Water-in-Salt Electrolytes.

Superconcentrated aqueous electrolytes ("water-in-salt" electrolytes, or WiSEs) enable various aqueous battery chemistries beyond the voltage limits imposed by the Pourbaix diagram of water. However, their detailed structural and transport properties remain unexplored and could be better understood through added studies. Here, we report on our observations of strong acidity (pH 2.4) induced by lithium bis(trifluoromethane sulfonyl)imide (LiTFSI) at superconcentration (at 20 mol/kg). Multiple nuclear magnetic resonance (NMR) and pulsed-field gradient (PFG) diffusion NMR experiments, density functional theory (DFT) calculations, and molecular dynamics (MD) simulations reveal that such acidity originates from the formation of nanometric ion-rich structures. The experimental and simulation results indicate the separation of water-rich and ion-rich domains at salt concentrations >= 5 m and the acidity arising therefrom is due to deprotonation of water molecules in the ion-rich domains. As such, the ion-rich domain is composed of hydrophobic -CF3 (of TFSI-) and hydrophilic hydroxyl (OH-) groups. At 20 m concentration, the tortuosity and radius of water diffusion channels are estimated to be similar to 10 and similar to 1 nm, respectively, which are close to values obtained from hydrated Nafion membranes that also have hydrophobic polytetrafluoroethylene (PTFE) backbones and hydrophilic channels consisting of SO3- ion cluster networks providing for the transport of ions and water. Thus, we have discovered the structural similarity between WiSE and hydrated Nafion membranes on the nanometer scale.

Han, Kee Sung↗
DOE OSTI2025

Recombination of Autodissociated Water Ions in a Nanoscale Pure Water Droplet

The recombination of water ions has diverse scientific and practical implications, ranging from acid-base chemistry and biological systems to planetary environments and applications in fuel cell and carbon conversion technologies. While spatial confinement affects the physicochemical properties of water dynamics, its impact on the recombination process has rarely been studied. In this work, we investigate the dynamics of water, the water ion distribution, and the ion recombination process in water droplets as a function of droplet size through molecular dynamics simulations and adaptive quantum mechanical/molecular mechanical calculations. We compare the dynamics of recombination in water droplet sizes ranging from 100 to 18 000 waters, both in their interiors and on their surfaces. We found that the self-diffusion of water dramatically decreases in droplets with a diameter below 2.2 nm. Using a classical RexPoN force-field, we found that the ions in 1000 H2O's spend almost 50% of the time on the surface and 0.5 nm beneath it with a slight preference for OH- ion to reside longer on the surface. We estimate that, on average, recombination in these drops occurs at 400 ps in 1000 H2O's and 1 ns in 3000 H2O's. We also found that recombination is not limited by the local structure of the surface or the size of the droplet but can be influenced by the geometry of the water wire connecting the ions as they approach each other, which can often prevent recombination. Our results provide insights to the reaction microenvironments presented by nanoscopic water droplets.

Kwon, Soonho↗
DOE OSTI2020

Data-Driven Many-Body Models for Molecular Fluids: CO 2 /H 2 O Mixtures as a Case Study

In this study, we extend the scope of the many-body TTM-nrg and MB-nrg potential energy functions (PEFs), originally introduced for halide ion–water and alkali-metal ion–water interactions, to the modeling of carbon dioxide (CO2) and water (H2O) mixtures as prototypical examples of molecular fluids. Both TTM-nrg and MB-nrg PEFs are derived entirely from electronic structure data obtained at the coupled cluster level of theory and are, by construction, compatible with MB-pol, a many-body PEF that has been shown to accurately reproduce the properties of water. Although both TTM-nrg and MB-nrg PEFs adopt the same functional forms for describing permanent electrostatics, polarization, and dispersion, they differ in the representation of short-range contributions, with the TTM-nrg PEFs relying on conventional Born–Mayer expressions and the MB-nrg PEFs employing multidimensional permutationally invariant polynomials. By providing a physically correct description of many-body effects at both short and long ranges, the MB-nrg PEFs are shown to quantitatively represent the global potential energy surfaces of the CO 2 –CO 2 and CO 2 –H 2 O dimers and the energetics of small clusters, as well as to correctly reproduce various properties in both gas and liquid phases. Furthermore, building upon previous studies of aqueous systems, our analysis provides further evidence for the accuracy and efficiency of the MB-nrg framework in representing molecular interactions in fluid mixtures at different temperature and pressure conditions.

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

Capacitance of Carbon Nanotube/Graphene Composite Electrodes with [BMIM + ][BF$_4^–$]/Acetonitrile: Fixed Voltage Molecular Dynamics Simulations

The capacitance of nanoporous carbon electrode materials is dictated by the physical interactions with electrolyte ions and molecules at the accessible interior electrode surface. While significant progress has been made in designing and synthesizing carbon materials with well-defined and relatively homogeneous nanoporosity, the majority of materials remain heterogeneous, and the resulting properties reflect an average over this distribution. In this regard, computer simulations can be a valuable tool to predict or validate structure/property relationships by systematically investigating well-defined, model electrode morphologies. In this work, we utilize fixed-voltage molecular dynamics simulations to predict structure/capacitance relationships for five different model morphologies of carbon nanotube/graphene (CNT/G) composite electrodes with 1-butyl-3-methylimidazolium tetrafluoroborate/acetonitrile electrolyte. The CNT/G electrode models are inspired by experimental “layer-by-layer” syntheses and strike a balance between realism and computational tractability. Comparison between different model electrode architectures elucidates important structure/property relationships. We find that CNT/graphene contact points serve as “hot spots” with significantly enhanced charge separation relative to the rest of the electrode. Furthermore, we demonstrate a specific nanoconfinement motif that provides substantial 3–4$\times$ enhancement of local capacitance, resulting in a ~40% increase of the total electrode differential capacitance. Because the accessible surface area of the model CNT/G electrodes is precisely determined, a comparison of per-area capacitance across systems is unambiguous. Our results thus complement a prior computational demonstration of capacitance enhancement in nanoconfinement while elucidating additional interaction motifs at CNT/G electrochemical interfaces.

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

Machine learning reveals key ion selectivity mechanisms in polymeric membranes with subnanometer pores

Designing single-species selective membranes for high-precision separations requires a fundamental understanding of the molecular interactions governing solute transport. Here, we comprehensively assess molecular-level features that influence the separation of 18 different anions by nanoporous cellulose acetate membranes. Our analysis identifies the limitations of bulk solvation characteristics to explain ion transport, highlighted by the poor correlation between hydration energy and the measured permselectivity (R 2 = 0.37). Entropy-enthalpy compensation, spanning 40 kilojoules per mole, leads to a free-energy barrier (ΔG‡) variation of only ~8 kilojoules per mole across all anions. We apply machine learning to elucidate descriptors for energetic barriers from a set of 126 collected features. Notably, electrostatic features account for 75% of the overall features used to describe ΔG‡, despite the relatively uncharged state of cellulose acetate. Our work presents an approach for studying ion transport across nanoporous membranes that could enable the design of ion-selective membranes.

36 MATERIALS SCIENCE↗
DOE OSTI2026

An end-to-end workflow for executing a classically bootstrapped variational quantum algorithm on an academic quantum computer

Academic quantum computing platforms often face unique challenges in executing quantum workloads due to fragmented software environments and limited engineering support. Unlike commercial ecosystems, academic devices typically evolve without full-stack integration in mind, making it difficult to run complex applications—such as variational quantum algorithms (VQA)—reliably and efficiently. Issues such as incompatible software layers and lack of automated job management significantly increase the overhead of theory-experiment collaboration. To address these challenges, we develop a modular, end-to-end workflow that decouples application-layer code from low-level hardware control, automates circuit submission and result collection, and supports fine-grained circuit-level job scheduling and recovery. The architecture employs a dual-end application programming interface (API) design, enabling robust operation across unstable or resource-constrained hardware backends. For practical use, the framework is lightweight and user-friendly, allowing rapid prototyping of full-stack workflows using basic Python tools. We validate this workflow on a high-fidelity trapped-ion quantum computer by demonstrating a variational quantum eigensolver (VQE) experiment with a classically bootstrapped ansatz initialization technique. The system successfully executed over 60,000 circuits across multiple molecular test cases with minimal human intervention, highlighting the framework’s effectiveness in enabling reproducible, resilient quantum experimentation in academic settings.

Clifford↗
DOE OSTI2021

Demystifying the Diffuse Vibrational Spectrum of Aqueous Protons Through Cold Cluster Spectroscopy

The ease with which the pH is routinely determined for aqueous solutions masks the fact that the cationic product of Arrhenius acid dissolution, the hydrated proton, or H + (aq), is a remarkably complex species. Here, we review how results obtained over the past 30 years in the study of H + ·(H 2 O) n cluster ions isolated in the gas phase shed light on the chemical nature of H + (aq). This effort has also revealed molecular-level aspects of the Grotthuss relay mechanism for positive-charge translocation in water. Recently developed methods involving cryogenic cooling in radiofrequency ion traps and the application of two-color, infrared–infrared (IR–IR) double-resonance spectroscopy have established a clear picture of how local hydrogen-bond topology drives the diverse spectral signatures of the excess proton. This information now enables a new generation of cluster studies designed to unravel the microscopic mechanics underlying the ultrafast relaxation dynamics displayed by H + (aq).

Chemistry↗
DOE OSTI2025

Modeling the Behavior of Complex Aqueous Electrolytes Using Machine Learning Interatomic Potentials: The Case of Sodium Sulfate

Understanding the structure and thermodynamics of solvated ions is essential for advancing applications in electrochemistry, water treatment, and energy storage. While ab initio molecular dynamics methods are highly accurate, they are limited by short accessible time and length scales whereas classical force fields struggle with accuracy. Herein, we explore the structure and thermodynamics of complex monovalent-divalent ion pairs using Na 2 SO 4 (aq) as a case study by applying a machine learning interatomic potential (MLIP) trained on density functional theory (DFT) data. Our MLIP-based approach reproduces key bulk properties such as density and radial distribution functions of water. We provide the hydration structure of the sodium and sulfate ions in the 0.1–2 M concentration range and the one-dimensional and two-dimensional potentials of mean force for the sodium–sulfate ion pairing at the low concentration limit (0.1 M), which are inaccessible to DFT. At low concentrations, the sulfate ion is strongly solvated, leading to the stabilization of solvent-separated ion pairs over contact ion pairs. Minimum energy pathway analysis revealed that coordinating two sodium ions with a sulfate ion is a multistep process whereby the sodium ions coordinate to the sulfate ion sequentially. Finally, we demonstrate that MLIPs allow the study of solvated ions beyond simple monovalent pairs with DFT-level accuracy in their low concentration limit (0.1 M) via statistically converged properties from ns-long simulations.

anions↗
DOE OSTI2023

Diffusion in intact secondary cell wall models of plants at different equilibrium moisture content

Secondary plant cell walls are composed of carbohydrate and lignin polymers, and collectively represent a significant renewable resource. Leveraging these resources depends in part on a mechanistic understanding for diffusive processes within plant cell walls. Common wood protection treatments and biomass conversion processes to create biorefinery feedstocks feature ion or solvent diffusion within the cell wall. X-ray fluorescence microscopy experiments have determined that ionic diffusion rates are dependent on cell wall hydration as well as the ionic species through non-linear relationships. In this work, we use classical molecular dynamics simulations to map the diffusion behavior of different plant cell wall components (cellulose, hemicellulose, lignin), ions (Na + , K + , Cu2 + , Cl - ) and water within a model for an intact plant cell wall at various hydration states (3-30 wt% water). From these simulations, we analyze the contacts between different plant cell wall components with each other and their interaction with the ions. Generally, diffusion increases with increasing hydration, with lignin and hemicellulose components increasing diffusion by an order of magnitude over the tested hydration range. Ion diffusion depends on charge. Positively charged cations preferentially interact with hemicellulose components, which include negatively charged carboxylates. As a result, positive ions diffuse more slowly than negatively charged ions. Measured diffusion coefficients are largely observed to best fit piecewise linear trends, with an inflection point between 10 and 15% hydration. These observations shed light onto the molecular mechanisms for diffusive processes within secondary plant cell walls at atomic resolution.

09 BIOMASS FUELS↗
DOE OSTI2024

Insights into the Properties of MXenes and MXene Analogs from Atomistic Simulation

We review the properties that have been predicted for MXenes and MXene analogs from computational simulation with a focus on structural and electronic properties, energy storage, and ion transport. Methods considered range from quantum mechanical approaches to classical molecular dynamics. We conclude by reviewing current limitations and outstanding questions for simulation and MXene properties that have been little explored to-date.

Muraleedharan, Murali Gopal↗
DOE OSTI2021

Engineering the Interlayer Spacing by Pre-Intercalation for High Performance Supercapacitor MXene Electrodes in Room Temperature Ionic Liquid

MXenes exhibit excellent capacitance at high scan rates in sulfuric acid aqueous electrolytes, but the narrow potential window of aqueous electrolytes limits the energy density. Organic electrolytes and room-temperature ionic liquids (RTILs) can provide higher potential windows, leading to higher energy density. The large cation size of RTIL hinders its intercalation in-between the layers of MXene limiting the specific capacitance in comparison to aqueous electrolytes. In this work, different chain lengths alkylammonium (AA) cations are intercalated into Ti 3 C 2 T x , producing variation of MXene interlayer spacings (d-spacing). AA-cation-intercalated Ti 3 C 2 T x (AA-Ti 3 C 2 ), exhibits higher specific capacitances, and cycling stabilities than pristine Ti 3 C 2 T x in 1 m 1-ethly-3-methylimidazolium bis-(trifluoromethylsulfonyl)-imide (EMIMTFSI) in acetonitrile and neat EMIMTFSI RTIL electrolytes. Pre-intercalated MXene with an interlayer spacing of ≈2.2 nm, can deliver a large specific capacitance of 257 F g –1 (1428 mF cm –2 and 492 F cm –3 ) in neat EMIMTFSI electrolyte leading to high energy density. Quasi elastic neutron scattering and electrochemical impedance spectroscopy are used to study the dynamics of confined RTIL in pre-intercalated MXene. Furthermore, molecular dynamics simulations suggest significant differences in the structures of RTIL ions and AA cations inside the Ti 3 C 2 T x interlayer, providing insights into the differences in the observed electrochemical behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Role of Polysulfide Anions in Solid-Electrolyte Interphase Formation at the Lithium Metal Surface in Li–S Batteries

Delineating intricate interactions between highly reactive Li-metal electrodes and the diverse constituents of battery electrolytes has been a long-standing scientific challenge in materials design for advanced energy storage devices. Here, we isolated lithium polysulfide anions (LiS 4 - ) from an electrolyte solution based on their mass-to-charge ratio and deposited them on Li-metal electrodes under clean vacuum conditions using ion soft landing (ISL), a highly controlled interface preparation technique. The molecular level precision in the construction of these model interfaces with ISL, coupled with in situ x-ray photoelectron spectroscopy and ab initio theoretical calculations, allowed us to obtain unprecedented insight into the parasitic reactions of well-defined polysulfides on Li-metal electrodes. Our study reveals that the oxide-rich surface layer, which is amenable to direct electron exchange, drives multielectron sulfur oxidation (S o → S 6+ ) processes. Furthermore, our results have substantial implications for the rational design of future Li-S batteries with improved efficiency and durability.

25 ENERGY STORAGE↗
DOE OSTI2023

Rigorous Oxidation State Assignments for Supported Ga-Containing Catalysts Using Theory-Informed X-ray Absorption Spectroscopy Signatures from Well-Defined Ga(I) and Ga(III) Compounds

Gallium-based heterogeneous catalysts originally developed for commercial use in propane dehydroaromatization have been explored extensively as potential replacements for Pt- and Cr-based catalysts used in propane dehydrogenation for on-demand propylene production. In a large number of experimental and theoretical studies, active sites with a variety of Ga nuclearities, coordination environments, and oxidation states have been proposed. Isolated Ga(I) ions are often invoked, despite the scarcity of well-defined molecular species and their well-documented instability. In this study, we investigate the appearance of a high-intensity, low-energy white line at the Ga K-edge upon reduction of Ga/HZSM-5 by H 2 at a temperature of ca. 500 °C, accompanied by a dramatic reduction in the extended X-ray absorption fine structure (EXAFS) intensity. In contrast, Ga/γ-Al 2 O 3 does not show such behavior. In order to lay a rigorous foundation for characterizing these types of systems and to establish experimental signatures for the elusive Ga(I) oxidation state, we recorded Ga K-edge X-ray absorption spectra [including high-energy-resolution fluorescence detection-X-ray absorption near-edge spectroscopy (HERFD-XANES)] for several well-defined molecular and crystalline Ga(I) compounds. XANES is essential to establishing the presence of Ga(I), despite the overlap in edge energies with organoGa(III) compounds, because Ga(I)-containing oxide materials show very weak EXAFS scattering. Compared to the XANES of trigonal Ga(III)-containing materials, Ga(I) spectra display a significantly more intense white line feature. Theoretical simulations agree well with this experimental observation and reveal that the strong XANES intensity originates from the superposition of transitions to several empty, nearly degenerate p-like states. Finally, these signatures provide compelling evidence for assigning the intense white line and dramatic loss of EXAFS intensity in Ga/HZSM-5 to the near-quantitative reduction of Ga(III) to Ga(I), while the weaker white line and conventional EXAFS signal of Ga/γ-Al 2 O 3 point to, at most, a minor fraction of Ga(I) sites.

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

Molecular Level Differences in Ionic Solvation and Transport Behavior in Ethylene Oxide-Based Homopolymer and Block Copolymer Electrolytes

Block copolymer electrolytes (BCE) such as polystyrene-block-poly(ethylene oxide) (SEO) blended with lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) and composed of mechanically robust insulating and rubbery conducting nanodomains are promising solid-state electrolytes for Li batteries. Here, we compare ionic solvation, association, distribution, and conductivity in SEO-LiTFSI BCEs and their homopolymer PEO-LiTFSI analogs toward a fundamental understanding of the maximum in conductivity and transport mechanisms as a function of salt concentration. Ionic conductivity measurements reveal that SEO-LiTFSI and PEO-LiTFSI exhibit similar behaviors up to a Li/EO ratio of 1/12, where roughly half of the available solvation sites in the system are filled, and conductivity is maximized. As the Li/EO ratios increase to 1/5 the conductivity, of the PEO-LiTFSI drops nearly 3-fold, while the conductivity of SEO-LiTFSI remains constant. FTIR spectroscopy reveals that additional Li cations in the homopolymer electrolyte are complexed by additional EO units when the Li/EO ratio exceeds 1/12, while in the BCE, the proportion of complexed and uncomplexed EO units remains constant; Raman spectroscopy data at the same concentrations show that Li cations in the SEO-LiTFSI samples tend to coordinate more to their counteranions. Atomistic-scale molecular dynamics simulations corroborate these results and further show that associated ions tend to segregate to the SEO-LiTFSI domain interfaces. The opportunity for "excess" salt to be sequestered at BCE interfaces results in the retention of an optimum ratio of uncompleted and complexed PEO solvation sites in the middle of the conductive nanodomains of the BCE and maximized conductivity over a broad range of salt concentrations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗