Search NASA⌕ Search

SEARCH · Search NASA

Results for “ATOMIC STRUCTURE”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Toward a Machine Learning Approach to Interpreting X-ray Spectra of Trace Impurities by Converting XANES to EXAFS

The fact that the photoabsorption spectrum of a material contains information about the atomic structure, commonly understood in terms of multiple scattering theory, is the basis of the popular extended X-ray absorption spectroscopy (EXAFS) technique. How much of the same structural information is present in other complementary spectroscopic signals is not obvious. Here we use a machine learning approach to demonstrate that within theoretical models that accurately predict the EXAFS signal, the extended near-edge region does indeed contain the EXAFS-accessible structural information. We do this by exhibiting deep operator neural networks (DeepONets) that have learned the relationship between the extended and near edge portions of the X-ray absorption spectrum to predict the former from the latter. We find that we can accurately predict the EXAFS spectrum between 6 and 14 Å –1 from the first 6 Å –1 (≈100 eV) of the absorption spectrum of Cu 2 + substitutional defects in the Fe 3+ mineral hematite (α-Fe 2 O 3 ). This surprising finding implies that theoretical analyses of X-ray absorption spectra could be implemented that extract the same conclusions as high-quality EXAFS studies from spectra collected over a much smaller range of photon energies. This relaxes a host of experimental limitations related to the X-ray source and measurement sample, including collection time, minimum dopant concentration, source brilliance, and energy range. We describe the theoretical data sets and DeepONet construction and show that the resulting DeepONets produce EXAFS that recovers linear combination fits to experimental data with accuracy approaching the original ab initio calculations. We discuss the implications of our findings for minor constituent characterization and for understanding the information content of spectroscopic data more broadly, including how this approach might be applied to measured experimental spectra. In conclusion, to encourage similar efforts, the simulated X-ray spectra, machine learning, and fitting code are publicly available.

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

X-ray Spectroscopy Fingerprints of Pristine and Functionalized Graphene

In this work, we demonstrate how to identify and characterize the atomic structure of pristine and functionalized graphene materials from a combination of computational simulation of X-ray spectra, on the one hand, and computer-aided interpretation of experimental spectra, on the other. Despite the enormous scientific and industrial interest, the precise structure of these 2D materials remains under debate. As we show in this study, a wide range of model structures from pristine to heavily oxidized graphene can be studied and understood with the same approach. We move systematically from pristine to highly oxidized and defective computational models, and we compare the simulation results with experimental data. Comparison with experiments is valuable also the other way around; this method allows us to verify that the simulated models are close to the real samples, which in turn makes simulated structures amenable to several computational experiments. Our results provide ab initio semiquantitative information and a new platform for extended insight into the structure and chemical composition of graphene-based materials.

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

Local Order in Liquid Gallium–Indium Alloys

Liquid metals such as eutectic Ga–In alloys have low melting points and low toxicity and are used in catalysis and micro-robotics. This study investigates the local atomic structure of liquid gallium-indium alloys by a combination of density measurements, diffraction data, and Monte-Carlo simulation via the empirical potential structure refinement approach. A high-Q shoulder observed in liquid Ga is related to structural rearrangements in the second coordination shell. Structure analysis found coordination environments close to a random distribution for eutectic Ga–In alloy, while electronic effects appear to dominate the mixing enthalpy.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Evaluating Brightness and Stability of Cathodoluminescence from Colloidal Semiconductor Nanocrystals

Cathodoluminescence offers promise as a technique for correlation of atomic structure with electronic structure at the level of individual nanoparticles or even defects, with the ability to analyze complex nanostructures at length-scales far below those typically available to optical spectroscopy. Unlike other forms of electron microscopy, cathodoluminescence offers direct insights into the electronic structure of the visualized sample. Despite reports more than 10 years ago of individual nanoparticle cathodoluminescence, effective cathodoluminescence collection from colloidal semiconductor materials is relatively rare and remains challenging due to the instability of materials under the conditions of electron beam irradiation. In this work, to clarify the roadblocks for cathodoluminescence analysis of colloidal nanocrystals, we attempt a comprehensive study of the cathodoluminescence properties of semiconductor quantum shells, which have a thin concentric CdSe shell surrounding CdS nanoparticles, then surrounded by a further concentric CdS shell. These same materials were recently demonstrated to show promising scintillation performance in radioluminescence measurements, including high brightness (up to 100 ph/keV) and excellent durability. Comparative quantum yield measurements are designed to assess the brightness of semiconductor nanocrystal films, which show that the quantum shells are much less bright under electron irradiation compared to X-ray photons. Instability of CL emission is assigned to charging effects on the samples—and not thermal effects—through a series of voltage, current, dwell time, and atmospheric pressure experiments.

cathodoluminescence↗
DOE OSTI2021

Disordered TiO x –SiO x Nanocatalysts Using Bioinspired Synthetic Routes

Metal oxide nanomaterials have increasing significance and broad applications in catalysis, ranging from support materials to active catalysts. Here, we have demonstrated a facile synthetic strategy to create disordered, high-surface-area metal oxide nanomaterials using biomineralization-inspired methods. Using protamine as a protein template, a range of TiO x –SiO x nanomaterials were synthesized and implemented for catalytic CO 2 thermal reduction reactions. The modularity of synthetic options afforded via biomineralization enables increases in surface area, which are ideally suited for subsequent modification to regulate catalytic performance. All materials were thoroughly characterized using a suite of synchrotron scattering and spectroscopic methods. Through these techniques, we have demonstrated that protamine-induced biomineralization results in largely disordered materials with changes in the local atomic structure dependent on the applied synthetic conditions. Protamine removal with treatment under acidic conditions greatly increased material surface area while causing measurable changes in the structure as revealed by X-ray absorption spectroscopy. Upon subsequent hydrogenation, Ti- and Si-based defects were induced in the materials while the disordered nature of the material was still largely retained. Furthermore, we found that the incorporation of Si into TiO x was able to mitigate the known anatase to rutile phase change during the reaction while stabilizing the defect sites. The synthetic strategies described in this work are expected to be translatable to other metal oxide nanomaterial chemical structures, providing a means to control catalytic properties using benign synthetic strategies.

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

Tunable Heteroassembly of a Plant Pseudoenzyme–Enzyme Complex

Pseudoenzymes have emerged as key regulatory elements in all kingdoms of life despite being catalytically nonactive. Yet many factors defining why one protein is active while its homologue is inactive remain uncertain. For pseudoenzyme–enzyme pairs, the similarity of both subunits can often hinder conventional characterization approaches. In plants, a pseudoenzyme, PDX1.2, positively regulates vitamin B 6 production by association with its active catalytic homologues such as PDX1.3 through an unknown assembly mechanism. Here we used an integrative experimental approach to learn that such pseudoenzyme–enzyme pair associations result in heterocomplexes of variable stoichiometry, which are unexpectedly tunable. We also present the atomic structure of the PDX1.2 pseudoenzyme as well as the population averaged PDX1.2–PDX1.3 pseudoenzyme–enzyme pair. Finally, we dissected hetero-dodecamers of each stoichiometry to understand the arrangement of monomers in the heterocomplexes and identified symmetry-imposed preferences in PDX1.2–PDX1.3 interactions. In this work, our results provide a new model of pseudoenzyme–enzyme interactions and their native heterogeneity.

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

Atomistic Origins of Reversible Noncatalytic Gas–Solid Interfacial Reactions

Noncatalytic gas-solid reactions are a large group of heterogeneous reactions that are usually assumed to occur irreversibly because of the strong driving force to favor the forward direction toward the product formation. Using the example of Ni oxidation into NiO with CO 2 , herein we demonstrate the existence of the reverse element that results in the NiO reduction from the countering effect of the gaseous product of CO. Using in-situ electron microscopy observations and atomistic modeling, we show that the oxidation process occurs via preferential CO 2 adsorption along step edges that results in step-flow growth of NiO layers, and the presence of Ni atoms on the flat NiO surface promotes the nucleation of NiO layers. Simultaneously, the NiO reduction happens via preferential step-edge adsorption of CO that leads to the receding motion of atomic steps, and the presence of Ni vacancies in the NiO surface facilitates the CO adsorption induced surface pitting. Based on the in-situ TEM observations, temperature and CO 2 pressure effect maps are constructed to illustrate the spatiotemporal dynamics of the competing NiO redox reactions. We report, these results demonstrate the rich gas-solid surface reaction dynamics induced by the co-existing forward and reverse reaction elements and have practical applicability in manipulating gas-solid reactions via controlling the gas environment or atomic structure of the solid surface to steer the reaction toward the desired direction.

25 ENERGY STORAGE↗
DOE OSTI2020

Atomistic Explanation of the Dramatically Improved Oxygen Reduction Reaction of Jagged Platinum Nanowires, 50 Times Better than Pt

Pt is the best catalyst for the oxygen reduction reactions (ORRs), but it is far too slow. Huang and co-workers showed that dealloying 5 nm Ni 7 Pt 3 nanowires (NW) led to 2 nm pure Pt jagged NW (J-PtNW) with ORRs 50 times faster than Pt/C. They suggested that the undercoordinated surface Pt atoms, mechanical strain, and high electrochemically active surface area (ECSA) are the main contributors. We report here multiscale atomic simulations that further explain this remarkably accelerated ORR activity from an atomistic perspective. We used the ReaxFF reactive force field to convert the 5 nm Ni 7 Pt 3 NW to the jagged 2 nm NW. We applied quantum mechanics to find that 14.4% of the surface sites are barrierless for O ads + H 2 O ads → 2OH ads , the rate-determining step (RDS). The reason is that the concave nature of many surface sites pushes the OH bond of the H 2 O ads close to the O ads , leading to a dramatically reduced barrier. We used this observation to predict the performance improvement of the J-PtNW relative to Pt (111). Assuming every surface site reacts independently with this predicted rate leads to a 212-fold enhancement at 298.15 K, compared to 50 times experimentally. The atomic structures of the active sites provide insights for designing high-performance electrocatalysts for ORR.

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

Rooting binder-free tin nanoarrays into copper substrate via tin-copper alloying for robust energy storage

The need for high-energy batteries has driven the development of binder-free electrode architectures. However, the weak bonding between the electrode particles and the current collector cannot withstand the severe volume change of active materials upon battery cycling, which largely limit the large-scale application of such electrodes. Using tin nanoarrays electrochemically deposited on copper substrate as an example, here we demonstrate a strategy of strengthening the connection between electrode and current collector by thermally alloying tin and copper at their interface. The locally formed tin-copper alloys are electron-conductive and meanwhile electrochemically inactive, working as an ideal "glue" robustly bridging tin and copper to survive harsh cycling conditions in sodium ion batteries. The working mechanism of the alloy "glue" is further characterized through a combination of electrochemical impedance spectroscopy, atomic structural analysis and in situ X-ray diffraction, presenting itself as a promising strategy for engineering binder-free electrode with endurable performance. The authors here report a binder-free electrode based on tin nanoarrays deposited on copper substrate. It is found that the locally formed electrochemically inactive tin-copper alloys work as a glue that bridges tin and copper to survive harsh cycling conditions in sodium ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2020

In situ nanoscale imaging of moiré superlattices in twisted van der Waals heterostructures

Abstract Direct visualization of nanometer-scale properties of moiré superlattices in van der Waals heterostructure devices is a critically needed diagnostic tool for study of the electronic and optical phenomena induced by the periodic variation of atomic structure in these complex systems. Conventional imaging methods are destructive and insensitive to the buried device geometries, preventing practical inspection. Here we report a versatile scanning probe microscopy employing infrared light for imaging moiré superlattices of twisted bilayers graphene encapsulated by hexagonal boron nitride. We map the pattern using the scattering dynamics of phonon polaritons launched in hexagonal boron nitride capping layers via its interaction with the buried moiré superlattices. We explore the origin of the double-line features imaged and show the mechanism of the underlying effective phase change of the phonon polariton reflectance at domain walls. The nano-imaging tool developed provides a non-destructive analytical approach to elucidate the complex physics of moiré engineered heterostructures.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Direct detection of coupled proton and electron transfers in human manganese superoxide dismutase

Human manganese superoxide dismutase is a critical oxidoreductase found in the mitochondrial matrix. Concerted proton and electron transfers are used by the enzyme to rid the mitochondria of O 2 •– . The mechanisms of concerted transfer enzymes are typically unknown due to the difficulties in detecting the protonation states of specific residues and solvent molecules at particular redox states. Here, neutron diffraction of two redox-controlled manganese superoxide dismutase crystals reveal the all-atom structures of Mn 3+ and Mn 2+ enzyme forms. The structures deliver direct data on protonation changes between oxidation states of the metal. Observations include glutamine deprotonation, the involvement of tyrosine and histidine with altered pK a s, and four unusual strong-short hydrogen bonds, including a low barrier hydrogen bond. We report a concerted proton and electron transfer mechanism for human manganese superoxide dismutase from the direct visualization of active site protons in Mn 3+ and Mn 2+ redox states.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

AF2Complex predicts direct physical interactions in multimeric proteins with deep learning

Abstract Accurate descriptions of protein-protein interactions are essential for understanding biological systems. Remarkably accurate atomic structures have been recently computed for individual proteins by AlphaFold2 (AF2). Here, we demonstrate that the same neural network models from AF2 developed for single protein sequences can be adapted to predict the structures of multimeric protein complexes without retraining. In contrast to common approaches, our method, AF2Complex, does not require paired multiple sequence alignments. It achieves higher accuracy than some complex protein-protein docking strategies and provides a significant improvement over AF-Multimer, a development of AlphaFold for multimeric proteins. Moreover, we introduce metrics for predicting direct protein-protein interactions between arbitrary protein pairs and validate AF2Complex on some challenging benchmark sets and the E. coli proteome. Lastly, using the cytochrome c biogenesis system I as an example, we present high-confidence models of three sought-after assemblies formed by eight members of this system.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Low complexity domains of the nucleocapsid protein of SARS-CoV-2 form amyloid fibrils

The self-assembly of the Nucleocapsid protein (NCAP) of SARS-CoV-2 is crucial for its function. Computational analysis of the amino acid sequence of NCAP reveals low-complexity domains (LCDs) akin to LCDs in other proteins known to self-assemble as phase separation droplets and amyloid fibrils. Previous reports have described NCAP’s propensity to phase-separate. Here we show that the central LCD of NCAP is capable of both, phase separation and amyloid formation. Within this central LCD we identified three adhesive segments and determined the atomic structure of the fibrils formed by each. Those structures guided the design of G12, a peptide that interferes with the self-assembly of NCAP and demonstrates antiviral activity in SARS-CoV-2 infected cells. Our work, therefore, demonstrates the amyloid form of the central LCD of NCAP and suggests that amyloidogenic segments of NCAP could be targeted for drug development.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Complexions at the iron-magnetite interface

Synthesizing distinct phases and controlling crystalline defects are key concepts in materials design. These approaches are often decoupled, with the former grounded in equilibrium thermodynamics and the latter in nonequilibrium kinetics. By unifying them through defect phase diagrams, we can apply phase equilibrium models to thermodynamically evaluate defects—including dislocations, grain boundaries, and phase boundaries—establishing a theoretical framework linking material imperfections to properties. Using scanning transmission electron microscopy (STEM) with differential phase contrast (DPC) imaging, we achieve the simultaneous imaging of heavy Fe and light O atoms, precisely mapping the atomic structure and chemical composition at the iron-magnetite (Fe/Fe 3 O 4 ) interface. We identify a well-ordered two-layer interface-stabilized phase state (referred to as complexion) at the Fe[001]/Fe 3 O 4 [001] interface. Using density-functional theory (DFT), we explain the observed complexion and map out various interface-stabilized phases as a function of the O chemical potential. The formation of complexions increases interface adhesion by 20% and alters charge transfer between adjacent materials, impacting transport properties. Our findings highlight the potential of tunable defect-stabilized phase states as a degree of freedom in materials design, enabling optimized corrosion protection, catalysis, and redox-driven phase transitions, with applications in materials sustainability, efficient energy conversion, and green steel production.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Materials Graph Library (MatGL), an open-source graph deep learning library for materials science and chemistry

Graph deep learning models, which incorporate a natural inductive bias for atomic structures, are of immense interest in materials science and chemistry. Here, we introduce the Materials Graph Library (MatGL), an open-source graph deep learning library for materials science and chemistry. Built on top of the popular Deep Graph Library (DGL) and Python Materials Genomics (Pymatgen) packages, MatGL is designed to be an extensible “batteries-included” library for developing advanced model architectures for materials property predictions and interatomic potentials. At present, MatGL has efficient implementations for both invariant and equivariant graph deep learning models, including the Materials 3-body Graph Network (M3GNet), MatErials Graph Network (MEGNet), Crystal Hamiltonian Graph Network (CHGNet), TensorNet and SO3Net architectures. MatGL also provides several pre-trained foundation potentials (FPs) with coverage of the entire periodic table, and property prediction models for out-of-box usage, benchmarking and fine-tuning. Finally, MatGL integrates with PyTorch Lightning to enable efficient model training.

chemistry↗
DOE OSTI2025

Atomically resolved edges and defects in lead halide perovskites

Although edges and defects constitute only a small fraction of crystalline materials, they exert an outsized impact on a material′s properties. Organic–inorganic halide perovskites are promising next-generation semiconductor materials with superior cost effectiveness and interesting optoelectronic properties. However, clear images of their edges have remained challenging to obtain owing to their extreme sensitivity. Using truly high-speed ultralow-dose four-dimensional scanning transmission electron microscopy with dose fractionation, we perform ptychography at, to our knowledge, the lowest-dose atomic resolution to date, revealing not only the detailed atomic structure of the edges of a halide perovskite but also their structural dynamics. Here, a majority methylammonium (MA) and iodine (I) edge termination is observed in methylammonium lead iodide (MAPbI 3 ), and the damage rate of its edges and internal defects is found to depend on the concentration and type of vacancies present, with a preponderance of I vacancies in particular correlating with higher rates of damage.

4D-STEM↗
DOE OSTI2022

Identifying amyloid-related diseases by mapping mutations in low-complexity protein domains to pathologies

Proteins including FUS, hnRNPA2, and TDP-43 reversibly aggregate into amyloid-like fibrils through interactions of their low-complexity domains (LCDs). Mutations in LCDs can promote irreversible amyloid aggregation and disease. We introduce a computational approach to identify mutations in LCDs of disease-associated proteins predicted to increase propensity for amyloid aggregation. We identify several disease-related mutations in the intermediate filament protein keratin-8 (KRT8). Atomic structures of wild-type and mutant KRT8 segments confirm the transition to a pleated strand capable of amyloid formation. Biochemical analysis reveals KRT8 forms amyloid aggregates, and the identified mutations promote aggregation. Aggregated KRT8 is found in Mallory–Denk bodies, observed in hepatocytes of livers with alcoholic steatohepatitis (ASH). We demonstrate that ethanol promotes KRT8 aggregation, and KRT8 amyloids co-crystallize with alcohol. Lastly, KRT8 aggregation can be seeded by liver extract from people with ASH, consistent with the amyloid nature of KRT8 aggregates and the classification of ASH as an amyloid-related condition.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Simulated sulfur K-edge X-ray absorption spectroscopy database of lithium thiophosphate solid electrolytes

X-ray absorption spectroscopy (XAS) is a premier technique for materials characterization, providing key information about the local chemical environment of the absorber atom. In this work, we develop a database of sulfur K-edge XAS spectra of crystalline and amorphous lithium thiophosphate materials based on the atomic structures reported in Chem. Mater., 34, 6702 (2022). The XAS database is based on simulations using the excited electron and core-hole pseudopotential approach implemented in the Vienna Ab initio Simulation Package. Our database contains 2681 S K-edge XAS spectra for 66 crystalline and glassy structure models, making it the largest collection of first-principles computational XAS spectra for glass/ceramic lithium thiophosphates to date. This database can be used to correlate S spectral features with distinct S species based on their local coordination and short-range ordering in sulfide-based solid electrolytes. The data is openly distributed via the Materials Cloud, allowing researchers to access it for free and use it for further analysis, such as spectral fingerprinting, matching with experiments, and developing machine learning models.

36 MATERIALS SCIENCE↗