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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Analysis of Bis(trifluoromethylsulfonyl)imide Interactions with Metal Cations Through a Chemical Informatics Approach

Nominally weakly coordinating anions are useful for modulating the solubility and chemical properties of metal complexes, but identification and analysis of the systematics of the interactions of anions with cationic metal complexes has not received the attention it deserves. Here, a chemical informatics approach is demonstrated for identifying and quantitatively analyzing the ways that the bis(trifluoromethylsulfonyl)imide anion (TFSI) can interact with metal-containing species. An open access computer program (PyCIFTer) was developed to facilitate large-scale structural analysis of TFSI-containing species by utilization of experimental atomic coordinate data from single-crystal X-ray diffraction (XRD) studies obtained from the Cambridge Structural Database (CSD). PyCIFTer establishes a three-dimensional vector space from the raw atomic coordinates, generating acyclic, undirected graphs that are used to rapidly analyze the structural properties (bond lengths and angles) of TFSI in individual structures in sequential/batch fashion. The structures are sorted by PyCIFTer into groups based on pre-set and chemically sensible criteria, affording a comprehensive and systematic view of TFSI structural chemistry. This approach avoids tedious one-at-a-time interrogation of structures, a prospect unreasonable in this case, and many others of contemporary chemical relevance; there were over 1500 structures in the CSD containing TFSI as of November 2024. The results demonstrate that TFSI only rarely binds to cations in the solid state, favoring the formation of species in which TFSI is found in cations’ outer coordination spheres. The prospect of applying PyCIFTer to other moieties is also discussed. PyCIFTer is also schematically compared to the commercial CSD Python application programming interface (API). Taken together, this work demonstrates the usefulness of modular workflows for sequential/batch analysis of structural data from XRD, an approach that appears poised to accelerate the translation of legacy structural results into new chemical insights and hypotheses.

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

Structural and Thermoelectric Properties of Black Arsenic–Phosphorus

Here, we report the structural and temperature dependent transport properties of As x P 1-x (x = 0, 0.2, 0.5, 0.83, 1) alloys. It is observed that black phosphorous (BP)-related phonon modes in the alloy samples are red-shifted with increasing arsenic concentration, while black arsenic-related modes in these samples are blue-shifted with increasing phosphorus concertation. As the arsenic concentration, x increases from 0 to 1, the 4-probe resistance of the As x P 1-x alloys is found to decrease by more than 3 orders of magnitude. The transport studies reveal that samples with the highest arsenic concentration (x = 1 and 0.83) show metallic behavior in the temperature dependence of resistance with a small thermopower at room temperature with an anomalous temperature dependence. In contrast, the samples with high phosphorus concentration (x = 0, 0.2, and 0.5) show very large thermopower values at room temperature reaching a value as high as 803 μV/k for x = 0.2. The temperature dependence of the thermopower of these samples can be well described by the variable range hopping (VRH) mechanism in two-dimensions (2-d), S ~ T 1/3 . Similarly, their 4-probe resistance (R) values can be fitted with 2-d VRH mechanism, R ~ exp(T -1/3 ).

36 MATERIALS SCIENCE↗
DOE OSTI2026

Integrated machine learning-molecular dynamics framework for electrolyte property prediction

Electrochemical stability windows determine the operating range of battery electrolytes, yet accurate prediction remains challenging because stability emerges from statistical ensembles of local solvation environments rather than single ground-state molecular structures. Traditional density functional theory calculations on energy-minimized clusters cannot capture the thermal variations in local coordination environments and geometries that govern decomposition, while SMILES-based machine learning methods lack explicit representation of three-dimensional solvation structure and ion pairing. Here, we introduce a structure-aware machine learning framework that predicts frontier orbital energies (HOMO and LUMO) directly from molecular dynamics-sampled solvation configurations, achieving sub-0.6 eV accuracy at computational costs 3–4 orders of magnitude lower than first-principles methods. Across twelve representative battery electrolytes, we demonstrate that solvent-separated and contact ion pairs exhibit strong size- and local chemistry dependent electronic stability, with variations in coordination shifts of HOMO or LUMO level by 2–3 eV, and that extended solvation structure and partially desolvated environment further modulate stability by up to 3 eV. By encoding the statistical nature of electrochemical failure through ensemble sampling of explicit solvation geometries, our approach enables high-throughput screening and rational design of next-generation battery electrolytes with mechanistic understanding of structure–property relationships.

Energy - Storage↗
DOE OSTI2025

Molecular Insights Into the Ionic Assembly of Poly-Galacturonic Acid Oligomers - Impact of Charge, Ionic Radius, and Polymer Functionalization

Pectin, a major class of matrix polysaccharides present in plant cell walls (PCW), contains widespread anionic saccharides that cross-link in the presence of cations. It modulates important functions such as cell-cell adhesion and determines the PCW's biomechanical properties. It is known that mono-, di-, and tri-valent cations facilitate cross-linking; however, significant knowledge gaps remain in understanding the structure and mechanism of pectin cross-linking. In this study, replica-exchange molecular dynamics (REMD) simulations were employed to elucidate the role of ionic charge, ionic radii, and functional groups on the cross-linking of homogalacturonan (HG), the most abundant pectin molecule. Our enhanced sampling approach in fully solvated environments suggests more effective cross-linking with higher-valent and smaller ions, and that the "zipper" conformation is more favorable than the prevalent "egg-box" conformation. These findings advance our fundamental understanding of pectin matrix structure in PCWs and provide a solid foundation to probe structure-property relationships in pectic polysaccharides.

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

Solid-state transformations during laser directed energy deposition of Ti-6Al-4V powder hydride-dehydrided from scrap metals

During laser directed energy deposition (DED-LB), thermal cycling and powder chemical composition produce distinct thermal histories, which vary mechanical properties. Using real-time X-ray diffraction, this study investigates solid-state transformations during DED-LB to understand process-structure-property relationships for angular Ti-6Al-4V powder hydride–dehydrided from scrap metals. Results showed that regions near the molten pool experienced high cooling rates, leading to martensitic transformation from the β phase and increased hardness. Regions farther from the molten pool underwent tempering without solid-state transformation and decreased hardness. These findings support alternative feedstocks for metal additive manufacturing for a circular economy and resilient supply chains.

Additive manufacturing (AM)↗
DOE OSTI2023

Machine learning unifies flexibility and efficiency of spinodal structure generation for stochastic biomaterial design

Abstract Porous biomaterials design for bone repair is still largely limited to regular structures (e.g. rod-based lattices), due to their easy parameterization and high controllability. The capability of designing stochastic structure can redefine the boundary of our explorable structure–property space for synthesizing next-generation biomaterials. We hereby propose a convolutional neural network (CNN) approach for efficient generation and design of spinodal structure—an intriguing structure with stochastic yet interconnected, smooth, and constant pore channel conducive to bio-transport. Our CNN-based approach simultaneously possesses the tremendous flexibility of physics-based model in generating various spinodal structures (e.g. periodic, anisotropic, gradient, and arbitrarily large ones) and comparable computational efficiency to mathematical approximation model. We thus successfully design spinodal bone structures with target anisotropic elasticity via high-throughput screening, and directly generate large spinodal orthopedic implants with desired gradient porosity. This work significantly advances stochastic biomaterials development by offering an optimal solution to spinodal structure generation and design.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Structure and dynamical properties of two-dimensional dusty plasmas on one-dimensional periodic substrates

In the presence of the substrate, various structural and dynamical properties of two-dimensional dusty plasma (2DDP) were investigated using Langevin dynamical simulations. This paper reviews a series of results of the structural and dynamical properties of 2DDP modified by one-dimensional periodic substrates (1DPSs) as follows. First, when the depth of the 1DPS increases gradually, it is found that the static structural order of 2DDP along each potential well of the 1DPS increases first, and then decreases gradually. When the width of the 1DPS increases gradually, the particle arrangement in each potential well of the 1DPS changes from one straight row gradually to two rows, including the stable zigzag structure. Second, when there are two rows in each potential well of the 1DPS, the phonon spectra are split into two branches, corresponding to the breathing and sloshing modes, respectively. In addition, due to the pure repulsion between dust particles, from the obtained phonon spectra, the sloshing wave propagates backward at small wave numbers. Third, the calculated mean-square displacement (MSD) shown that, at the intermediate timescale between the initial ballistic and final diffusive motions, the particle motion tends to be more subdiffusive while the depth of the 1DPS increases. While the width of the 1DPS increases gradually, the long-time diffusive motion first increases, then decreases, and finally increases again, exhibiting the oscillation-like diffusion, due to the stable zigzag structure. Finally, when an external direct-current driving force is applied on all particles of 2DDP, three different depinning phases are discovered, which are the pinned, disordered plastic flow, and moving ordered states, respectively, as the driving force increases from zero. In addition, the continuous/discontinuous property of the phase transition between these different depinning states is investigated, showing that the transition property is modulated by the depth of the applied 1DPS

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Structural and thermal properties of Eu 2 Ga 11 Sn 35

Clathrates have been reported to form in a variety of different structure types; however, inorganic clathrate-I materials with a low-cation concentration have yet to be investigated. Furthermore, tin-based compositions have been much less investigated as compared to silicon or germanium analogs. We report the temperature-dependent structural and thermal properties of single-crystal Eu 2 Ga 11 Sn 35 revealing the effect of structure and composition on the thermal properties of this low-cation clathrate-I material. Specifically, low-temperature heat capacity, thermal conductivity, and synchrotron single-crystal x-ray diffraction reveal a departure from Debye-like behavior, a glass-like phonon mean-free path for this crystalline material, and a relatively large Grüneisen parameter due to the dominance of low-frequency Einstein modes. In conclusion, our analyses indicate thermal properties that are a direct result of the structure and composition of this clathrate-I material.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Tailoring additive manufacturing to optimize dynamic properties in 316L stainless steel

With the advent of additive manufacturing, manipulation of typical microstructural elements such as grain size, texture, and defect densities is now possible at a faster time scale. While the processing–structure–property relationship in additive manufactured metals has been well studied over the past decade, little work has been done in understanding how this process affects the dynamic behavior of materials. We postulate that additive manufacturing can be used to alter the material microstructure and used to enhance its dynamic strength. In this work, 316L stainless steel (SS) was manufactured via selected laser melting and its microstructure was altered through changing build parameters like laser power, speed, and hatch spacing systematically. These samples were then subjected to spall recovery experiments to measure the spall strength and quantify the amount of damage as a function of build parameters. By mapping the spall strength as a function of build parameters, this work demonstrated that indeed additive manufacturing can be used to tailor the spall strength of 316L SS. This work also determined the optimum build parameters (laser power=195W; scanning speed=1083mm/s; hatch spacing=0.09mm; layer thickness=0.02mm) to obtain the highest spall strength and the least amount of total damage in 316L SS. Microstructural characterization of the pre- and post-mortem samples revealed that increased grain average misorientation and textural index were the main driving force behind this higher spall strength. This work aims to enhance microstructural engineering techniques to design materials with greater resistance to dynamic shock loading.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Stabilizing Liquids Using Interfacial Supramolecular Assemblies

Abstract Stabilizing liquids based on supramolecular assembly (non‐covalent intermolecular interactions) has attracted significant interest, due to the increasing demand for soft, liquid‐based devices where the shape of the liquid is far from the equilibrium spherical shape. The components comprising these interfacial assemblies must have sufficient binding energies to the interface to prevent their ejection from the interface when the assemblies are compressed. Here, we highlight recent advances in structuring liquids based on non‐covalent intermolecular interactions. We describe some of the progress made that reveals structure–property relationships. In addition to treating advances, we discuss some of the limitations and provide a perspective on future directions to inspire further studies on structured liquids based on supramolecular assembly.

Gu, Peiyang↗
DOE OSTI2023

Stabilizing Liquids Using Interfacial Supramolecular Assemblies

Stabilizing liquids based on supramolecular assembly (non-covalent intermolecular interactions) has attracted significant interest, due to the increasing demand for soft, liquid-based devices where the shape of the liquid is far from the equilibrium spherical shape. The components comprising these interfacial assemblies must have sufficient binding energies to the interface to prevent their ejection from the interface when the assemblies are compressed. In this report we highlight recent advances in structuring liquids based on non-covalent intermolecular interactions. We describe some of the progress made that reveals structure–property relationships. In addition to treating advances, we discuss some of the limitations and provide a perspective on future directions to inspire further studies on structured liquids based on supramolecular assembly.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Structure, folding and flexibility of co-transcriptional RNA origami

RNA origami is a method for designing RNA nanostructures that can self-assemble through co-transcriptional folding with applications in nanomedicine and synthetic biology. However, to advance the method further, an improved understanding of RNA structural properties and folding principles is required. Here we use cryogenic electron microscopy to study RNA origami sheets and bundles at sub-nanometre resolution revealing structural parameters of kissing-loop and crossover motifs, which are used to improve designs. In RNA bundle designs, we discover a kinetic folding trap that forms during folding and is only released after 10 h. Furthermore, exploration of the conformational landscape of several RNA designs reveal the flexibility of helices and structural motifs. Finally, sheets and bundles are combined to construct a multidomain satellite shape, which is characterized by individual-particle cryo-electron tomography to reveal the domain flexibility. Together, the study provides a structural basis for future improvements to the design cycle of genetically encoded RNA nanodevices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Valorization of bamboo biomass using combinatorial pretreatments

Current studies concerning liquid hot water pretreatment (LHWP) usually focus on cellulose saccharification or hemicellulose conversion, while the appropriate extraction and utilization of LHWP-induced lignin have not been addressed. To valorize whole biomass, here, in this study, a series of LHWP-based combinatorial pretreatments are proposed using advanced solvent systems. The first LHWP stage removed 73.74% of xylan at the optimized pretreatment severity (~4.0), at the same time preserving almost all the cellulose and lignin. As a result, 9.04 g L –1 xylo-oligosaccharides (XOSs) were obtained in the prehydrolyzate, representing 63.31% of the degraded xylan. The LHWP also caused the migration and partial degradation of the lignin which benefits the delignification in the second stage of pretreatment utilizing NaOH, deep eutectic solvent (DES) and 1,4-butanediol (BDO) under relatively mild conditions. The proposed combinatorial pretreatment significantly enhanced glucan conversion. The physiochemical structural properties of the untreated and pretreated substrates were investigated with XRD, FTIR, GPC, SEM, and Simons’ staining to understand the mechanisms of different combinatorial pretreatments for overcoming biomass recalcitrance and facilitating integrated biomass valorization. Finally, the physical and chemical properties of the regenerated lignins were analyzed. The results revealed that lignins from LHWP–NaOH pretreatment preserved most of the native β-O-4 structure (37.1%). Thus it could be used as an ideal method for the catalytic production of aromatic monomers. On the other hand, LHWP–DES pretreatment generated lignins with low molecular weight and high phenolic OH content, which is promising for synthesizing resins and antioxidants. In conclusion, the proposed combinatorial pretreatment established a reliable sequential pretreatment methodology for maximizing the output of bamboo biomass and may fit into different biorefinery configurations for various value-added products.

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

Lowering of Tc in Van Der Waals Layered Materials Under In-Plane Strain

The dependence of electromechanical behavior on strain in ferroelectric materials can be leveraged as parameter to tune ferroelectric properties such as the Curie temperature. For van der Waals materials, a unique opportunity arises because of wrinkling, bubbling, and Moiré phenomena accessible due to structural properties inherent to the van der Waals gap. Here, we use piezoresponse force microscopy and unsupervised machine learning methods to gain insight into the ferroelectric properties of layered CuInP2S6 where local areas are strained in-plane due to a partial delamination, resulting in a topographic bubble feature. We observe significant differences between strained and unstrained areas in piezoresponse images as well as voltage spectroscopy, during which strained areas show a sigmoid-shaped response usually associated with the response measured around the Curie temperature, indicating a lowering of the Curie temperature under tensile strain. These results suggest that strain engineering might be used to further increase the functionality of CuInP2S6 through locally modifying ferroelectric properties on the micro- and nanoscale.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A Combined Machine Learning and High-Energy X-ray Diffraction Approach to Understanding Liquid and Amorphous Metal Oxides

Determining the structure-property relations of liquid and amorphous metal oxides is challenging, due to their variable short-range order and polyhedral connectivity. To predict chemically realistic structures, we have developed a Machine Learned, Gaussian Approximation Potential (GAP) for HfO 2 , with a focus on enhanced sampling of the training database and accurate density functional theory calculations. By using training datasets for the GAP model at the level of Density Functional Theory-Strongly Constrained and Appropriately Normed (DFT-SCAN) level of theory, our results show that the topology of both the low viscosity liquid and the amorphous form are dominated by edge-shared chains and small corner-shared rings of polyhedra. This topology is shown to be consistent with the structure of other liquid and amorphous transition metal oxides of variable ion size, such as TiO 2 and ZrO 2 . Current limitations of the ML-GAP modeling method for obtaining glass structures and future perspectives are also discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2022

High-throughput predictions of metal–organic framework electronic properties: theoretical challenges, graph neural networks, and data exploration

Abstract With the goal of accelerating the design and discovery of metal–organic frameworks (MOFs) for electronic, optoelectronic, and energy storage applications, we present a dataset of predicted electronic structure properties for thousands of MOFs carried out using multiple density functional approximations. Compared to more accurate hybrid functionals, we find that the widely used PBE generalized gradient approximation (GGA) functional severely underpredicts MOF band gaps in a largely systematic manner for semi-conductors and insulators without magnetic character. However, an even larger and less predictable disparity in the band gap prediction is present for MOFs with open-shell 3 d transition metal cations. With regards to partial atomic charges, we find that different density functional approximations predict similar charges overall, although hybrid functionals tend to shift electron density away from the metal centers and onto the ligand environments compared to the GGA point of reference. Much more significant differences in partial atomic charges are observed when comparing different charge partitioning schemes. We conclude by using the dataset of computed MOF properties to train machine-learning models that can rapidly predict MOF band gaps for all four density functional approximations considered in this work, paving the way for future high-throughput screening studies. To encourage exploration and reuse of the theoretical calculations presented in this work, the curated data is made publicly available via an interactive and user-friendly web application on the Materials Project.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Reversal of Anomalous Hall Effect and Octahedral Tilting in SrRuO 3 Thin Films via Hydrogen Spillover

Abstract The perovskite SrRuO 3 (SRO) is a strongly correlated oxide whose physical and structural properties are strongly intertwined. Notably, SRO is an itinerant ferromagnet that exhibits a large anomalous Hall effect (AHE) whose sign can be readily modified. Here, a hydrogen spillover method is used to tailor the properties of SRO thin films via hydrogen incorporation. It is found that the magnetization and Curie temperature of the films are strongly reduced and, at the same time, the structure evolves from an orthorhombic to a tetragonal phase as the hydrogen content is increased up to ≈0.9 H per SRO formula unit. The structural phase transition is shown, via in situ crystal truncation rod measurements, to be related to tilting of the RuO 6 octahedral units. The significant changes observed in magnetization are shown, via density functional theory (DFT), to be a consequence of shifts in the Fermi level. The reported findings provide new insights into the physical properties of SRO via tailoring its lattice symmetry and emergent physical phenomena via the hydrogen spillover technique.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Structural and dynamic properties of solvated hydroxide and hydronium ions in water from ab initio modeling

Predicting the asymmetric structure and dynamics of solvated hydroxide and hydronium in water from ab initio molecular dynamics (AIMD) has been a challenging task. The difficulty mainly comes from a lack of accurate and efficient exchange–correlation functional in elucidating the amphiphilic nature and the ubiquitous proton transfer behaviors of the two ions. By adopting the strongly constrained and appropriately normed (SCAN) meta-generalized gradient approximation functional in AIMD simulations, we systematically examine the amphiphilic properties, the solvation structures, the electronic structures, and the dynamic properties of the two water ions. In particular, we compare these results to those predicted by the PBE0-TS functional, which is an accurate yet computationally more expensive exchange–correlation functional. We demonstrate that the general-purpose SCAN functional provides a reliable choice for describing the two water ions. Specifically, in the SCAN picture of water ions, the appearance of the fourth and fifth hydrogen bonds near hydroxide stabilizes the pot-like shape solvation structure and suppresses the structural diffusion, while the hydronium stably donates three hydrogen bonds to its neighbors. We apply a detailed analysis of the proton transfer mechanism of the two ions and find the two ions exhibit substantially different proton transfer patterns. In conclusion, our AIMD simulations indicate that hydroxide diffuses more slowly than hydronium in water, which is consistent with the experimental results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗