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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Charge Transport in Solvated Donor–Acceptor Functionalized Peptoids: Molecular Dynamics and Rate Theory

Scalable solar-energy conversion requires photoactive materials that combine the efficiency of natural photosynthetic systems with the stability and processability needed for practical applications. Achieving reliable charge transport in soft, self-assembled organic materials remains challenging, as structural fluctuations and environmental effects strongly influence charge-transfer (CT) rates. Here, we present a broadly applicable computational framework for evaluating CT rates in the condensed phase, combining Fermi’s golden rule rate theory with inputs from all-atom molecular dynamics (MD) simulations and first-principles electronic-structure calculations. The approach does not rely on system-specific parametrization and is applicable to a wide range of soft and disordered materials. We demonstrate the applicability and usefulness of the framework on redox-active peptoids functionalized with iron–porphyrin (Fe–P) complexes, a bioinspired platform with programmable donor–acceptor units and tunable three-dimensional organization. The calculated CT rates exhibit strong sensitivity to molecular conformation, with variations spanning several orders of magnitude. This dependence is shown to arise from the pronounced variation in diabatic electronic coupling with the relative orientations and separations of the Fe–P complexes across the conformational ensemble. The framework provides a consistent route for connecting atomistic structure to CT kinetics in the condensed phase and enables analysis of structure–rate relations in organic semiconducting systems.

Charge transfer↗
DOE OSTI2026

Deciphering the Solvation Structure of Aqueous ZnCl 2 Solutions from X-ray Absorption Spectra Using the Interpretable Graph Neural Network

Machine learning (ML) provides powerful pathways for predicting spectroscopic observables from atomic structures, but its broader impact depends on making model predictions interpretable in terms of physical and chemical principles. Here, we introduce a physics-guided graph neural network (GNN) model that predicts Zn K-edge X-ray spectroscopy (XAS) spectra of aqueous ZnCl 2 solutions. Training data are generated from ab initio XAS calculations on molecular dynamics snapshots obtained using a machine learning interatomic potential. The GNN reproduces experimental spectra across concentrations from dilute (<0.1 m) to highly concentrated (30 m, “water-in-salt”) regimes and scales efficiently to large, disordered liquid systems beyond the reach of conventional ab initio approaches. Gradient-based attribution analysis reveals that the model learns physically meaningful structure-spectrum relationships. Ligand-specific attributions reflect orbital hybridization patterns and the origin of the excitations derived from the density functional theory. Bond-length attributions recover spectral shifts consistent with multiple-scattering theory. Finally, this work bridges data-driven prediction with electronic-structure theory, establishing a general paradigm for interpretable ML that links atomic structure, electronic structure, and spectroscopic observables.

25 ENERGY STORAGE↗
DOE OSTI2025

The Influence of Charge Correlation and Ion Solvation on the Phase Behavior of Single-Ion Conducting Polymer Blend Electrolytes Using SAXS/SANS

Single-ion conducting polymer blends (SICPBs) have demonstrated exceptional electrochemical performance as solid-state battery electrolytes; however, their nanoscale morphology and thermodynamic behavior remain unexplored. In this work, we investigate blends composed of deuterated poly(ethylene oxide) and poly[lithium sulfonyl(trifluoromethane sulfonyl)imide methacrylate], dPEO/P(LiMTFSI), and report the first experimental study of the nanostructures of charge-neutral polymer blends using small-angle neutron scattering (SANS) and small-angle X-ray scattering (SAXS). Despite the macroscopic miscibility indicated by a single glass-transition temperature, SANS and SAXS results reveal disordered, charge-correlated nanostructures that are strongly influenced by blend composition and temperature. At low concentrations of charge polymer, the scattering is dominated by concentration fluctuations, and the random phase approximation is applied to extract values of the Flory–Huggins interaction parameter, χ SC . At higher charged polymer content, concentration fluctuations are suppressed, and a correlation model is used to characterize the nanostructures of the charge correlations. We find that the structures of the charge correlations are highly dependent on blend composition─consistent with predictions from Sing’s self-consistent field theory-liquid state models. Understanding these features is essential for uncovering the ion transport mechanism that leads to improved electrochemical performance previously reported in SICPB systems.

25 ENERGY STORAGE↗
DOE OSTI2024

Solvation Environment and Interface Dynamics of Li 2 B 12 H 12 and Li 2 B 12 F 12 Electrolytes Uncovered by Theory and Operando Optical and FTIR Spectroelectrochemistry

In this work, we evaluated two closo-borate salts (Li 2 B 12 H 12 and Li 2 B 12 F 12 ) in propylene carbonate from theoretical and experimental perspectives to understand how the coordination environment influences their spectroscopic and electrochemical properties. The coordination environments of the closo-borate salts were modeled via density functional theory (DFT) and molecular dynamics (MD). Vibrational spectra calculated from the predicted coordination environments are in agreement with experimentally measured steady-state FTIR data. This theoretical investigation also suggested that Li 2 B 12 F 12 would possess a higher ionic conductivity than Li 2 B 12 H 12 , which was corroborated experimentally. Additionally, an electrochemical cell was designed and fabricated that enabled operando optical and FTIR spectroelectrochemical (OP-IR-SEC) measurements. This allowed for the simultaneous measurement of the relative changes of species at a lithium electrode-liquid electrolyte interface and the visualization of lithium plating at the electrode surface. This technique could provide new chemical insights and potentially link optical changes at the electrode–electrolyte interface to specific chemical species in similar electrochemical systems. The Li 2 B 12 F 12 electrolyte was found to have a higher thermal stability, which may find utility in applications for batteries that are subject to high-temperature conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Solvation and oxidation effects on the crystal structure and morphology of tetraoxolene-based materials

Owing to their rich redox behavior and strong metal chelating ability, tetraoxolene ligands have been established as one of the foundational building blocks for multifunctional metal–organic materials. Here, we show how simple and often overlooked synthetic parameters can be used to control the structures of transition metal and lanthanide-based metal–tetraoxolene materials across multiple length scales. Through the synthesis of twelve new compounds, we provide a comprehensive survey detailing how the choice of solvent, initial ligand redox state, and in situ oxidant impact the local coordination geometry and chain architecture, as well as the crystal size and shape (e.g., rods vs. platelets). This work represents an important step towards the synthesis of new metal–tetraoxolene materials with predictable architectures and, therefore, targeted functionality.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

2D nanoconfinement distorts the solvation structure of hydroxide but not of hydronium

Understanding ion-specific behavior in nanoconfined water is essential for controlling charge transport and selectivity in two-dimensional membranes. Motivated by recent experiments revealing anomalous dielectric and transport behavior of water confined between hBN sheets, we use machine-learning-accelerated first-principles molecular dynamics to investigate the interfacial propensities of hydronium and hydroxide ions under similar confinement. We find that hydronium remains interfacial across all confinement regimes, whereas hydroxide shifts toward the interior as the environment becomes more bulk-like. This contrasting behavior reflects the combined influence of hydrogen bonding, interfacial water layering, and the polarization of hBN, which collectively stabilize hydronium at the surface while making hydroxide slightly more favorable within the structured interior. These findings expose an asymmetry in ion-surface coupling and establish a microscopic origin for hydronium’s enhanced interfacial affinity. The results provide mechanistic insight into ion partitioning in two-dimensional channels and highlight the collective structuring of confined water as a key determinant of interfacial ion thermodynamics.

organic↗
DOE OSTI2024

Toward a quantitative description of solvation structure: a framework for differential solution scattering measurements

Appreciating that the role of the solute–solvent and other outer-sphere interactions is essential for understanding chemistry and chemical dynamics in solution, experimental approaches are needed to address the structural consequences of these interactions, complementing condensed-matter simulations and coarse-grained theories. High-energy X-ray scattering (HEXS) combined with pair distribution function analysis presents the opportunity to probe these structures directly and to develop quantitative, atomistic models of molecular systems in situ in the solution phase. However, at concentrations relevant to solution-phase chemistry, the total scattering signal is dominated by the bulk solvent, prompting researchers to adopt a differential approach to eliminate this unwanted background. Though similar approaches are well established in quantitative structural studies of macromolecules in solution by small- and wide-angle X-ray scattering (SAXS/WAXS), analogous studies in the HEXS regime—where sub-ångström spatial resolution is achieved—remain underdeveloped, in part due to the lack of a rigorous theoretical description of the experiment. To address this, herein we develop a framework for differential solution scattering experiments conducted at high energies, which includes concepts of the solvent-excluded volume introduced to describe SAXS/WAXS data, as well as concepts from the time-resolved X-ray scattering community. Our theory is supported by numerical simulations and experiment and paves the way for establishing quantitative methods to determine the atomic structures of small molecules in solution with resolution approaching that of crystallography.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Catalytic Activation of Pyran Ethers in Self-Solvating Saccharides with Alkaline Earth Metals (Final Report)

Catalytic activation of cellulose ethers occurs via hydroxyl-stabilized cleavage of inter-monomer glycosidic bonds. Cooperativity between two hydroxyl groups lowers the ether cleavage transition state necessary to break apart long carbohydrate chains to initiate small molecule formation as fuel precursors. Metals existing with lignocellulosic materials including alkaline earth metals (Ca 2+ , Mg 2+ ) or alkali (Na + , K + ) also can catalyze ether scission cooperatively. By bonding with carbohydrate hydroxyl groups, a metal cation disrupt the hydrogen bonding network and free carbohydrate functional groups to react; a second metal cation stabilizes the carbohydrate ether transition state and enhances the rate of polymer scission. In this work, we expanded our initial understanding of metal-catalyzed glycoside ether scission. Within polysaccharides such as cellulose, two ether groups exist: one between monomers (glycosidic linkages) and one within a pyran ring. The hydroxyl-group hydrogen bonding network and bound metal ions form low energy binding states that interact with both ether oxygens simultaneously. Based on this interaction, our primary hypothesis was that the competition between stabilizing the two ether scission transition states determines the extent of the major pathways. Metals that disrupt the hydrogen bonding network of the C6 of sugars and stabilize the glycosidic ether promote transglycosylation to levoglucosan; in contrast, metals that stabilize the pyran ether oxygen promote sugar ring fragmentation to furans such as furfural. Varying characteristics of metal cation catalysts and configurations of bound polysaccharide chains dictate the relative rates of ether scission.

09 BIOMASS FUELS↗
NASA NTRS1971

Solvation agent for disulfide precipitates from inhibited glycol-water solutions

Small additions /0.01 percent or less/ of triethanoloamine sodium sulfite adduct to mercapto benzothiazole inhibited glycol water heat transfer solutions containing disulfide precipitate produce marked reduction in amount of precipitate. Adduct is useful as additive in glycol base antifreezes and coolants.

Taylor, M. F.↗
NASA NTRS2002

Protein Solvation in Membranes and at Water-Membrane Interfaces

Different salvation properties of water and membranes mediate a host of biologically important processes, such as folding, insertion into a lipid bilayer, associations and functions of membrane proteins. These processes will be discussed in several examples involving synthetic and natural peptides. In particular, a mechanism by which a helical peptide becomes inserted into a model membrane will be described. Further, the molecular mechanism of recognition and association of protein helical segments in membranes will be discussed. These processes are crucial for proper functioning of a cell. A membrane-spanning domain of glycophorin A, which exists as a helical dimer, serves as the model system. For this system, the free energy of dissociation of the helices is being determined for both the wild type and a mutant, in which dimerization is disrupted.

Pohorille, Andrew↗
NASA NTRS2005

Structural and energetic consequences of mutations in a solvated hydrophobic cavity

The structural and energetic consequences of modifications to the hydrophobic cavity of interleukin 1-beta (IL-1beta) are described. Previous reports demonstrated that the entirely hydrophobic cavity of IL-1beta contains positionally disordered water. To gain a better understanding of the nature of this cavity and the water therein, a number of mutant proteins were constructed by site-directed mutagenesis, designed to result in altered hydrophobicity of the cavity. These mutations involve the replacement of specific phenylalanine residues, which circumscribe the cavity, with tyrosine, tryptophan, leucine and isoleucine. Using differential scanning calorimetry to determine the relative stabilities of the wild-type and mutant proteins, we found all of the mutants to be destabilizing. X-ray crystallography was used to identify the structural consequences of the mutations. No clear correlation between the hydrophobicities of the specific side-chains introduced and the resulting stabilities was found.

Solvents/chemistry↗
DOE OSTI2025

Prediction of hydration energies of adsorbates at Pt(111) and liquid water interfaces using machine learning

Aqueous phase heterogeneous catalysis is important to various industrial processes, including biomass conversion, Fischer–Tropsch synthesis, and electrocatalysis. Accurate calculation of solvation thermodynamic properties is essential for modeling the performance of catalysts for these processes. Explicit solvation methods employing multiscale modeling, e.g., involving density functional theory and molecular dynamics have emerged for this purpose. Although accurate, these methods are computationally intensive. This study introduces machine learning (ML) models to predict solvation thermodynamics for adsorbates on a Pt(111) surface, aiming to enhance computational efficiency without compromising accuracy. In particular, ML models are developed using a combination of molecular descriptors and fingerprints and trained on previously published water–adsorbate interaction energies, energies of solvation, and free energies of solvation of adsorbates bound to Pt(111). These models achieve root mean square error values of 0.09 eV for interaction energies, 0.04 eV for energies of solvation, and 0.06 eV for free energies of solvation, demonstrating accuracy within the standard error of multiscale modeling. Feature importance analysis reveals that hydrogen bonding, van der Waals interactions, and solvent density, together with the properties of the adsorbate, are critical factors influencing solvation thermodynamics. Furthermore, these findings suggest that ML models can provide rapid and reliable predictions of solvation properties. This approach not only reduces computational costs but also offers insights into the solvation characteristics of adsorbates at Pt(111)–water interfaces.

Adsorption↗