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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Proteome-scale Structure Prediction Data - Pseudodesulfovibrio mercurii

The number of proteins predicted for Pseudodesulfovibrio mercurii is 3,446, each of which have five predicted structures from an AlphaFold run, as well as structural alignment results using the TMscore-based structural alignment method within the APoc program. Specifically, AlphaFold outputs the atoms and coordinates of the protein model in human-readable PDB files and quantitative prediction metrics in Python PICKLE files. The 5 models have been ranked based on the predicted TM-score (pTMS), a quantitative confidence metric output by AlphaFold that reports on protein model quality. The top ranked model has undergone an energy minimization calculation to relax and remove any potential clashes in the atomic coordinates. Structural alignment results are stored in two files for each protein; the top ranked model (as discussed above) is used for all alignment analyses. Both are compressed gzip files that, once unpacked, are human readable. The first file is the TMalign score results and contains the quantitative metrics for the top alignments between the predicted structure and experimental structures from the PDB70, a curated non-redundant database of about 80,000 experimental structures developed by the Soding lab. Each data point in this file is directly associated with one experimental structure; PDB ID and brief meta-data about the protein taken from the PDB70 file are reported alongside the quantitative metrics. The second results file contains the raw results associated with each alignment reported in the score results file. Specifically, the translation and rotation arrays for each alignment are provided so that the structural alignment can be recreated. Additionally, residue-level scores are reported to quantify the closeness of the aligned residues between the predicted and experimental models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Effect of Thermodynamic and Environmental Factors on Crystallization of DNA‐Origami Superlattices

The directed self‐assembly of nanoscale materials into ordered superlattices presents a powerful strategy for creating next‐generation materials with programmable mechanical, optical, and photonic properties. Deoxyribonucleic acid (DNA) origami has emerged as a versatile scaffold for encoding nanoscale geometry and guiding the crystallization of complex 3D architectures. However, a systematic understanding of the parameters that govern the efficiency and quality of superlattice formation remains limited. In this study, we utilize octahedral DNA nanoscale frames as a model system to investigate the relative influence of key factors, including buffer composition, ionic strength, frame concentration, and thermal annealing protocols, on the size, order, and reproducibility of the resulting superlattices. Our findings provide a quantitative framework to rationally optimize DNA‐based assembly pathways. Structural characterization via small‐angle x‐ray scattering (SAXS), scanning electron microscopy (SEM), and optical microscopy validates the quality and fidelity of the assembled lattices. Moreover, by templating these DNA frameworks into inorganic replicas, we establish general design principles that extend beyond biomolecular systems, providing a foundation for the synthesis of programmable materials in broader nanofabrication contexts.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Effects of Ligand Chemistry on Ion Transport in 2D Hybrid Organic–Inorganic Perovskites

2D hybrid organic–inorganic perovskites are potentially promising materials as passivation layers that can enhance the efficiency and stability of perovskite photovoltaics. The ability to suppress ion transport is proposed as a stabilization mechanism, yet an effective characterization of relevant modes of halide diffusion in 2D perovskites is nascent. In light of this knowledge gap, molecular dynamics simulations with enhanced sampling and experimental validation to systematically characterize how ligand chemistry in seven (R-NH 3 ) 2 PbI 4 systems impacts halide diffusion, particularly in the out-of-plane direction is combined. It is found that increasing stiffness and length of ligands generally inhibits ion transport, while increasing ligand polarization generally enhances it. Structural and energetic analyses of the migration pathways provide quantitative explanations for these trends, which reflect aspects of the disorder of the organic layer. Overall, this mechanistic analysis greatly enhances the current understanding of halide migration in 2D hybrid organic–inorganic perovskites and yields insights that can inform the design of future passivation materials.

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

Variational neural network approach to QFT in the field basis

We present a variational neural network approach for solving quantum field theories in the field basis, focusing on the free Klein-Gordon model formulated in momentum space. While recent studies have explored neural-network-based variational methods for scalar field theory in position space, a systematic benchmark of the analytically solvable Klein-Gordon ground state—particularly in the momentum-space field basis—has been lacking. In this work, we represent the ground-state wavefunctional as a neural network defined on a discretized set of field configurations and train it by minimizing the Hamiltonian expectation value. This framework enables direct comparison to exact analytic results for a range of key observables, including the ground-state energy, two-point correlators, expectation value of the field, and the structure of the learned wavefunctional itself. Our results provide quantitative diagnostics of accuracy and establish a validated foundation for extending neural-network wavefunctional methods to interacting field theories and position-space formulations.

Klein-Gordon model↗
DOE OSTI2022

Vibrational Spectroscopy of Hexahalo Complexes

Halogenated inorganic complexes A x [MHal y ] (A = alkali metal or alkaline earth, M = transition or main group metal, x = 1–3, and y = 2–9) are an archetypal class of compounds that provide entry points to large areas of inorganic and physical chemistry. All of the hexahalo complexes adopt an octahedral, O h , symmetry (or nearly so). Consequently, one of the bending modes is forbidden in both the infrared and Raman spectra. In the solid state, many of the complexes crystallize in the cubic space group Fm3̅m, which preserves the octahedral symmetry. Even for those that are not cubic, the octahedral symmetry of the [MHal 6 ] n- ion is largely retained and, to a good approximation, so are the selection rules. In the present work, we show that by using the additional information provided by neutron vibrational spectroscopy, in combination with conventional optical spectroscopies, we can generate complete and unambiguous assignments for all the modes. Comparison of the experimental and calculated transition energies for the systems where periodic-density functional theory was possible (i.e., those for which the crystal structure is known) shows that the agreement is almost quantitative. We also provide a linear relationship that enables the prediction of the forbidden mode.

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

Grain boundary zirconia-modified garnet solid-state electrolyte

Here, we report a method for promoting electrochemical stability in garnet Li 6.4 La 3 Zr 1.4 Ta 0.6 O 12 solid-state electrolyte based on a composite two-phase oxide–oxide microstructure. Grain boundary precipitation of the controlled distribution of amorphous zirconium oxide microparticles is achieved through the addition of reactive tantalum carbide. During ambient-atmosphere sintering, the carbide decomposes through an in situ reaction, the ‘extra’ Ta substituting for Zr within the Li 6.4 La 3 Zr 1.4 Ta 0.6 O 12 lattice. Density functional theory (DFT) calculations identify a thermodynamically favourable reaction path and show how substituting Ta 5+ at Zr 4+ sites affects the crystal structure as well as bulk ionic and electronic conductivities. Quantitative stereology highlights that zirconia also acts as a sintering aid, reducing compact porosity. Cryogenic focused-ion-beam scanning electron microscopy and fractography analysis of cycled solid-state electrolytes illustrates that near-universally observed intergranular Li-metal dendrite propagation is suppressed by the two-phase microstructure, favouring transgranular dendrites instead. Importantly, DFT demonstrates that compared with the Li 6.4 La 3 Zr 1.4 Ta 0.6 O 12 surface, the zirconium oxide surface per se is less electronically conductive and does not trap excess electrons to reduce Li ions. This is a key reason for the substantial improvement in the electrochemical properties over the single-phase baseline.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Size-dependent chiro-optical properties of CsPbBr 3 nanoparticles

Chiral metal halide perovskites have garnered substantial interest because of their promising properties for application in optoelectronics and spintronics. Understanding the mechanism of chiral imprinting is paramount for optimizing their utility. To elucidate the nature of the underlying chiral imprinting mechanism, we investigated how the circular dichroism (CD) intensity varies with nanoparticle size for quantum confined sizes of colloidal CsPbBr 3 perovskite nanoparticles (NPs) capped by chiral β-methylphenethylammonium bromide ligands. We find that the CD intensity decreases strongly with increasing NP size, which, along with the shape of the CD spectra, points to electronic interactions between ligand and NP as the dominant mechanism of chiral imprinting in smaller NPs. We observe that as the NP size increases and crosses the quantum confinement threshold, the dominant mechanism of chirality transfer switches and is dominated by surfaces effects, e.g., structural distortions. Furthermore, these findings provide a benchmark for quantitative models of chiral imprinting.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Development of a coarse-grained molecular dynamics model for poly(dimethyl- co -diphenyl)siloxane

Polydimethylsiloxane is an important polymeric material with a wide range of applications. However, environmental effects like low temperature can induce crystallization in this material with resulting changes in its structural and dynamic properties. The incorporation of phenyl-siloxane components, e.g., as in a poly(dimethyl-co-diphenyl)siloxane random copolymer, is known to suppress such crystallization. Molecular dynamics (MD) simulations can be a powerful tool to understand such effects in atomistic detail. Unfortunately, all-atomistic molecular dynamics (AAMD) is limited in both spatial dimensions and simulation times it can probe. Here, to overcome such constraints and to extend to more useful length- and time-scales, we systematically develop a coarse-grained molecular dynamics (CGMD) model for the poly(dimethyl-co-diphenyl)siloxane system with bonded and non-bonded interactions determined from all-atomistic simulations by the iterative Boltzmann inversion (IBI) method. Additionally, we propose a lever rule that can be useful to generate non-bonded potentials for such systems without reference to the all-atomistic ground truth. Our model captures the structural and dynamic properties of the copolymer material with quantitative accuracy and is useful to study long-time dynamics of highly-entangled systems, sequence-dependent properties, phase behaviour, etc.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Subsea permafrost carbon stocks and climate change sensitivity estimated by expert assessment

The continental shelves of the Arctic Ocean and surrounding seas contain large stocks of organic matter (OM) and methane (CH4), representing a potential ecosystem feedback to climate change not included in international climate agreements. We performed a structured expert assessment with 25 permafrost researchers to combine quantitative estimates of the stocks and sensitivity of organic carbon in the subsea permafrost domain (i.e. unglaciated portions of the continental shelves exposed during the last glacial period). Experts estimated that the subsea permafrost domain contains ~560 gigatons carbon (GtC; 170–740, 90% confidence interval) in OM and 45 GtC (10–110) in CH 4 . Current fluxes of CH 4 and carbon dioxide (CO 2 ) to the water column were estimated at 18 (2–34) and 38 (13–110) megatons C yr –1 , respectively. Under Representative Concentration Pathway (RCP) RCP8.5, the subsea permafrost domain could release 43 Gt CO 2 – equivalent (CO 2 e) by 2100 (14–110) and 190 Gt CO 2 e by 2300 (45–590), with ~30% fewer emissions under RCP2.6. The range of uncertainty demonstrates a serious knowledge gap but provides initial estimates of the magnitude and timing of the subsea permafrost climate feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Localized 𝑓-electron magnetism in the semimetal Ce 3 ⁢ Bi 4 ⁢ Au 3

Ce 3 ⁢Bi 4 ⁢ Au 3 crystallizes in the same noncentrosymmetric cubic structure as the prototypical Kondo insulator Ce 3 ⁢ Bi 4 ⁢Pt 3 . Here we report the physical properties of Ce 3 ⁢Bi 4 ⁢ Au 3 single crystals using magnetization, thermodynamic, and electrical-transport measurements. Magnetic-susceptibility and heat-capacity data reveal antiferromagnetic order below 𝑇 𝑁 =3.2K. The magnetic entropy 𝑆 mag reaches 𝑅⁢ ln⁡ 2 slightly above 𝑇 𝑁 , which suggests localized 4⁢𝑓 moments in a doublet ground state. Multiple field-induced magnetic transitions are observed at temperatures below 𝑇 𝑁 , which indicate a complex spin structure with competing interactions. Ce 3 ⁢Bi 4 ⁢ Au 3 shows semimetallic behavior in electrical resistivity in contrast to the majority of reported cerium-based 343 compounds which are semiconducting. Electrical-resistivity measurements under hydrostatic pressure reveal a slight enhancement of 𝑇 𝑁 under pressures up to 2.3 GPa, which supports a scenario wherein Ce 3 ⁢Bi 4 ⁢Au 3 belongs to the far left of the Doniach phase diagram dominated by Ruderman-Kittel-Kasuya-Yosida interactions. Using realistic many-body simulations, we confirm the semimetallic electronic structure of Ce 3 ⁢Bi 4 ⁢ Au 3 and quantitatively reproduce its local moment behavior in the paramagnetic state.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Fault Detection on Seismic Structural Images Using a Nested Residual U-Net

Automatic identification of faults on seismic structural images is a challenging yet crucial task in quantitative seismic interpretation. Human picking or attribute-based fault detection methods may misidentify faults on noisy, complex seismic images. In this work, we develop a new automatic fault detection method using a nested residual U-shaped convolutional neural network. Each of the encoders and decoders in this neural network is a residual U-Net, leading to a nested architecture. The final fault map results from the fusion of three fault maps with low, medium, and high fault resolutions. We demonstrate the excellent fault-detection capability of our nested neural network using a series of synthetic and field seismic images. We find that our approach produces clearer and more interpretable fault maps than the current state-of-the-art U-Net fault detection method, particularly on noisy seismic images. Our new automatic fault detection method can facilitate reliable quantitative seismic interpretation on field seismic images.

58 GEOSCIENCES↗
DOE OSTI2024

Combined speckle- and propagation-based single shot two-dimensional phase retrieval method

Single-shot two-dimensional (2D) phase retrieval (PR) can recover the phase shift distribution within an object from a single 2D x-ray phase contrast image (XPCI). Two competing XPCI imaging modalities often used for single-shot 2D PR to recover material properties critical for predictive performance capabilities are: speckle-based (SP-XPCI) and propagation-based (PB-XPCI) XPCI imaging. However, PR from SP-XPCI and PB-XPCI images are, respectively, limited to reconstructing accurately slowly and rapidly varying features due to noise and differences in their contrast mechanisms. Herein, we consider a combined speckle- and propagation-based XPCI (SPB-XPCI) image by introducing a mask to generate a reference pattern and imaging in the near-to-holographic regime to induce intensity modulations in the image. We develop a single-shot 2D PR method for SPB-XPCI images of pure phase objects without imposing restrictions such as object support constraints. It is compared against PR methods inspired by those developed for SP-XPCI and PB-XPCI on simulated and experimental images of a thin glass shell before and during shockwave compression. Reconstructed phase maps show improvements in quantitative scores of root-mean-square error and structural similarity index measure using our proposed method.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Machine Learning Thermodynamics And Kinetics of Defects For Accelerated Materials Discovery

Atomistic defects play a pivotal role in functional and structural materials’ performance across a myriad of technology applications. Quantitative prediction of the thermodynamics and kinetics of defect formation and migration, respectively, typically requires accurate but expensive first-principles approaches, such as density functional theory (DFT). Their computational expense limits the throughput needed to perform high-throughput materials discovery/screening exercises or to perform materials modeling tasks relying on extensive sampling techniques. Therefore, in this Sandia National Laboratories Laboratory Directed Research and Development (LDRD) project (Project #229366), we developed a variety of machine learning techniques, trained on density functional theory calculations, to accelerate the discovery and modeling of materials in which vacancy and interstitial defects primarily dictate material performance. These include applications such as metal oxides for water-splitting or mixed ionic-electronic conduction, metal hydrides for hydrogen storage, and transition metal dichalcogenides for electronics, and the approaches developed herein can further be applied to many other domains that similarly depend on materials’ thermodynamic and kinetic defect properties for their desired functionality.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Residual stress and microstructure in IN718-René41 graded superalloy fabricated by laser blown directed energy deposition

Additively printed Ni-based superalloy with a compositionally graded transition from IN718 to René41 was fabricated by laser blown-powder directed energy deposition (DED/LB-M), with the goals of meeting location-specific temperature capability and reducing component cost for hot gas path turbine components. Residual stress distribution in thin wall specimens with three sets of DED build parameters in the as-built and stress-relieved states was measured by neutron diffraction. For calculating residual stress, the calculated d0 method was found to be more appropriate as stress-free reference than using the lattice spacing measured from the stress-relief heat treated specimens. Longer dwell time (lower interpass temperature), higher energy input, smaller layer thickness resulted in a higher magnitude of tensile residual stresses at edges and compressive residual stresses at center of the specimens. The residual stress results did not show a strong dependence on graded compositions, indicating that the residual stress build-up was more geometry and process dependent. Non-destructive neutron imaging based on the attenuation coefficient qualitatively visualized the compositional variation in the bulk and showed good agreement with quantitative Electron Probe Micro-Analysis (EPMA) measurement. Grain structure, texture, and residual plastic strain along the build direction were characterized by Electron Backscatter Diffraction (EBSD). Long columnar grains with (001) preferred grain orientation were dominant along the build direction. Compositional change did not show an obvious effect on the epitaxial growth of dendrites and the continuation of the columnar grains. Residual plastic strain was relatively low in the as-built specimens.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Lithium Metal Battery Quality Control via Transformer–CNN Segmentation

Lithium metal battery (LMB) has the potential to be the next-generation battery system because of its high theoretical energy density. However, defects known as dendrites are formed by heterogeneous lithium (Li) plating, which hinders the development and utilization of LMBs. Non-destructive techniques to observe the dendrite morphology often use X-ray computed tomography (XCT) to provide cross-sectional views. To retrieve three-dimensional structures inside a battery, image segmentation becomes essential to quantitatively analyze XCT images. This work proposes a new semantic segmentation approach using a transformer-based neural network called TransforCNN that is capable of segmenting out dendrites from XCT data. In addition, we compare the performance of the proposed TransforCNN with three other algorithms, U-Net, Y-Net, and E-Net, consisting of an ensemble network model for XCT analysis. Our results show the advantages of using TransforCNN when evaluating over-segmentation metrics, such as mean intersection over union (mIoU) and mean Dice similarity coefficient (mDSC), as well as through several qualitatively comparative visualizations.

Quenum, Jerome (ORCID:0000000271265853)↗
DOE OSTI2022

A Moving Embedded Boundary Approach for the Compressible Navier-Stokes Equations in a Block-Structured Adaptive Refinement Framework

A computational technique has been developed to perform compressible flow simulations involving moving boundaries using an embedded boundary approach within the block-structured adaptive mesh refinement (SAMR) framework of AMReX [1], [91], [92]. We leverage the SAMR capability to obtain quantitatively accurate results whilst using robust, second-order finite volume schemes. A conservative, unsplit, cut-cell approach is utilized and a ghost-cell approach is developed for computing the flux on the moving, embedded boundary faces. A third-order least-squares formulation has been developed to compute the wall velocity gradients, and was found to significantly improve the performance of the solver in terms of the quantitative comparison of surface quantities such as the skin friction coefficient. Various test cases are performed to validate the method, and compared with analytical, experimental, and other numerical results in literature. Inviscid and viscous test cases are performed that span a wide regime of flow speeds - acoustic (harmonically pulsating sphere), smooth flows (expansion fan created by a receding piston) and flows with shocks (shock-cylinder interaction, shock-wedge interaction, pitching NACA 0012 airfoil and shock-cone interaction). A closed system with moving boundaries - an oscillating piston in a cylinder, showed that the percentage error in mass within the system decreases with refinement, demonstrating that the numerical scheme is conservative with grid refinement, but is not discretely conservative. Viscous test cases involve that of a horizontally moving cylinder at Re = 40, an inline oscillating cylinder at Re = 100, and a transversely oscillating cylinder at Re = 185. The judicious use of adaptive mesh refinement with appropriate refinement criteria to capture the regions of interest leads to well-resolved flow features, and good quantitative comparison is observed with the results available in literature.

adaptive refinement↗
DOE OSTI2023

Structures and Mechanisms of a Novel Bacterial Transport System for Fatty Acids

Abstract Bacterial acquisition of metabolites is largely facilitated by transporters with unique substrate scopes. The tripartite ATP‐independent periplasmic (TRAP) transporters comprise a large family of bacterial proteins that facilitate the uptake of a variety of small molecules. It has been reported that some TRAP systems encode a fourth protein, the T component. The T‐component, or TatT, is predicted to be a periplasmic‐facing lipoprotein that enables the uptake of metabolites from the outer membrane. However, no substrates were revealed for any TatT and their functional role(s) remained enigmatic. We recently identified a homolog in Methylococcus capsulatus that binds to sterols, and herein, we report two additional homologs that demonstrate a preference for long‐chain fatty acids. Our bioinformatics, quantitative analyses of protein‐ligand interactions, and high‐resolution crystal structures suggest that TatTs might facilitate the trafficking of hydrophobic or lipophilic substrates and represent a new class of bacterial lipid and fatty acid transporters.

59 BASIC BIOLOGICAL SCIENCES↗