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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Performance Evaluation of LPBF Manufactured 316H Components

This work represents the continuation of a benchmark study that includes modeling, fabrication and characterization as demonstration to support industry’s adoption of advanced manufacturing processes in a variety of structures. This comprehensive study investigated the feasibility of using additive manufacturing (AM) technologies, specifically Laser Powder Direct Energy Deposition (LP-DED) and Laser Powder Bed Fusion (LPBF), to produce complex nuclear microreactor components using 316H stainless steel. The research focused on manufacturing an expanded elbow pipe component with transitioning sections, which are traditionally difficult and costly to produce through conventional manufacturing methods. The overall study’s primary objectives are therefore demonstrating AM viability for nuclear applications, optimizing process parameters, developing comprehensive material characterization protocols, validating computational modeling approaches, and establishing manufacturing guidelines for complex geometries. Although the initial work included the phased approach of cubical, upscaled cylindrical components, it is to enable to obtain more knowledge for the printing of the expanded elbow structure. The project achieved significant progress in process development by successfully optimizing LP-DED parameters to achieve 99.16-99.97% relative density in 316H stainless steel components. Through systematic evaluation of sixteen cube samples with varied laser powers (400-700W) and scan speeds (600-900 mm/min), optimal processing windows were identified at 500-550W with 600-700 mm/min or 650-700W with 650-900 mm/min scan speeds. The DED manufactured 316H demonstrated mechanical properties comparable or superior to wrought materials, with Young's modulus ranging from 153-208 GPa and controlled microstructural characteristics including greater than 95% face-centered cubic (FCC) phases and engineered cellular structures with sizes between 3.23-6.17 µm.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Synthesis and Characterization of Layered Actinide (U, Np, Pu) Oxide and Hydroxide Phases

Systematic structural comparisons across the early actinides remain limited by the scarcity of well-defined transuranic layered oxide and oxyhydroxide phases. Here, we report the synthesis and single-crystal characterization of new layered actinide compounds spanning U, Np, and Pu obtained under mild hydrothermal conditions in concentrated alkali hydroxide media. These include hydrated oxides α-Cs 2 U 2 O 7 •0.5H 2 O and Rb 2 An 2 O 7 •0.5H 2 O (An = Np, Pu), oxy-hydroxides Rb 6 [(AnO 2 ) 6 O 8 (OH) 2 ]•xH 2 O x = 0, 0.5 (An = U, Np) and Rb 4 [(UO 2 ) 5 O 6 (OH) 2 ]•2H 2 O, as well as nitrate-intercalated compounds Cs 6 [(AnO 2 ) 3 O 4 (OH) 2 ](NO 3 ) 2 (An = Np, Pu). Single-crystal X-ray diffraction studies reveal extended two-dimensional architectures constructed from edge- and vertex-sharing actinyl polyhedra, with systematic evolution in equatorial coordination, hydration, and anionic sheet topology across the U–Np–Pu series. Incorporation of nitrate anions within the interlayer region of Cs 6 [(AnO 2 ) 3 O 4 (OH) 2 ](NO 3 ) 2 establishes a previously unobserved structural motif in layered transuranic oxyhydroxides, demonstrating an additional pathway for anion-mediated framework stabilization. Correlation of crystallographic metrics with single-crystal Raman spectroscopy provides new vibrational benchmarks linking differences in An═O yl bond lengths to the equatorial coordination and the interstitial cations. These findings expand the structural hierarchy of layered actinide materials and address clarifying periodic trends governing topology, bonding, and vibrational signatures in high-valent 5ƒ oxide systems.

actinides↗
DOE OSTI2023

Method for simultaneous characterization and expansion of reference libraries for small molecule identification

A variational autoencoder (VAE) has been developed to learn a continuous numerical, or latent, representation of molecular structure to expand reference libraries for small molecule identification. The VAE has been extended to include a chemical property decoder, trained as a multitask network, to shape the latent representation such that it assembles according to desired chemical properties. The approach is unique in its application to metabolomics and small molecule identification, focused on properties that are obtained from experimental measurements (m/z, CCS) paired with its training paradigm, which involves a cascade of transfer learning iterations. First, molecular representation is learned from a large dataset of structures with m/z labels. Next, in silico property values are used to continue training. Finally, the network is further refined by being trained with the experimental data. The trained network is used to predict chemical properties directly from structure and generate candidate structures with desired chemical properties. The network is extensible to other training data and molecular representations, and for use with other analytical platforms, for both chemical property and feature prediction as well as molecular structure generation.

Colby, Sean M.↗
DOE OSTI2020

Engineering Directionality in Quantum Dot Shell Lasing Using Plasmonic Lattices

In this paper, we report how the direction of quantum dot (QD) lasing can be engineered by exploiting high-symmetry points in plasmonic nanoparticle (NP) lattices. The nanolaser architecture consists of CdSe-CdS core-shell QD layers conformally coated on two-dimensional square arrays of Ag NPs. Using waveguide-surface lattice resonances (W-SLRs) near the Δ point in the Brillouin zone as optical feedback, we achieved lasing from the gain in CdS shells at off-normal emission angles. Changing the periodicity of the plasmonic lattices enables other high-symmetry points (Γ or M) of the lattice to overlap with the QD shell emission, which facilitates tuning of the lasing direction. We also increased the thickness of the QD layer to introduce higher order W-SLR modes with additional avoided crossings in the band structure, which expands the selection of cavity modes for any desired lasing emission angle.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Deep learning to generate in silico chemical property libraries and candidate molecules for small molecule identification in complex samples

Comprehensive and unambiguous identification of small molecules in complex samples will revolutionize our understanding of the role of metabolites in biological systems. Existing and emerging technologies have enabled measurement of chemical properties of molecules in complex mixtures and, in concert, are sensitive enough to resolve even stereoisomers. Despite these experimental advances, small molecule identification is inhibited by (i) chemical reference libraries (e.g. mass spectra, collision cross section, and other measurable property libraries) representing <1% of known molecules, limiting the number of possible identifications, and (ii) the lack of a method to generate candidate matches directly from experimental features (i.e. without a library). To this end, we developed a variational autoencoder (VAE) to learn a continuous numerical, or latent, representation of molecular structure to expand reference libraries for small molecule identification. We extended the VAE to include a chemical property decoder, trained as a multitask network, in order to shape the latent representation such that it assembles according to desired chemical properties. The approach is unique in its application to metabolomics and small molecule identification, with its focus on properties that can be obtained from experimental measurements (m/z, CCS) paired with its training paradigm, which involved a cascade of transfer learning iterations. First, molecular representation is learned from a large dataset of structures with m/z labels. Next, in silico property values are used to continue training, as experimental property data is limited. Finally, the network is further refined by being trained with the experimental data. This allows the network to learn as much as possible at each stage, enabling success with progressively smaller datasets without overfitting. Once trained, the network can be used to predict chemical properties directly from structure, as well as generate candidate structures with desired chemical properties. Our approach is orders of magnitude faster than first-principles simulation for CCS property prediction. Additionally, the ability to generate novel molecules along manifolds, defined by chemical property analogues, positions DarkChem as highly useful in a number of application areas, including metabolomics and small molecule identification, drug discovery and design, chemical forensics, and beyond.

Colby, Sean M.↗
DOE OSTI2022

Controlled Growth and Chemical Engineering of FeSe‐Based Superconducting Films

Abstract Chemical engineering tailors functional materials to meet the demands of physical and chemical properties, accelerating materials discovery and design in a multidisciplinary field. However, stereotyped synthetic paradigms in physical and chemical approaches obstruct the effective integration of multiple advantages of respective materials exploration methods. Solid state reaction is often considered separately with wet chemistry synthesis route, such as film growth using physical vapor deposition and hydrothermal methods. Here, the controlled growth of FeSe thin films by physical deposition techniques followed by the chemical engineering to create heterogenous interface in FeSe films via a solution‐based environment is demonstrated. The two‐step route allows an expanded crystal structure and enhanced superconducting transition temperature from 3.6 to 38 K, providing a new strategy to design functional hybrid materials.

Huang, Yulong↗
DOE OSTI2025

Comparative experimental study of heat transfer processes in accumulation energy recovery exchangers

In this study, an experimental comparison between three different energy accumulating ceramic heat exchangers for energy recovery in ventilation systems was presented. The units were selected to represent three different approaches on the energy recovery process: honeycomb structure with more accumulation mass (more energy can be stored in one unit)- Unit 1.1, honeycomb structure with lower accumulation mass- Unit 1.2, and a rectangular structure with expanded heat transfer surface- Unit 1.3. The achieved results are useful for the future application of such units in ventilation systems. It was established that all evaluated units demonstrated an acceptable effectiveness of thermal energy recovery from the exhaust air. Their average energy recovery efficiency ranged between 70 % and 80 %, aligning with expected performance benchmarks for regenerative heat exchangers employed in contemporary mechanical ventilation systems. It was also established that the factor which has the highest impact on thermal effectiveness is the heat transfer surface available in the tested heat exchangers. Units with the highest number of channels (i.e., with the highest amount of single channel walls, which can be used for heat transfer) achieve the highest thermal effectiveness. However, higher thermal effectiveness can negatively affect the ventilation potential of the units. Unit 1.3, which was characterized by the highest thermal efficiency, was also characterized by the lowest achievable flow rate. It was also found that the important technical aspect that should be taken into account when analyzing accumulation energy recovery units is also the fluctuation of the supply air temperature. The ability to ensure minimal temperature fluctuations is a significant operational advantage, as it ensures a higher level of safety at lower outside temperatures.

Energy recovery↗
DOE OSTI2025

Recent trends in all-organic polymer dielectrics for high-temperature electrostatic energy storage capacitors

Electrostatic energy storage (EES) capacitors are critical for renewable energy and high-power systems, driving the search for dielectric materials that combine superior electrical insulation, mechanical flexibility, low density, cost-effectiveness, and processability. Polymer-based dielectrics have emerged as leading candidates, particularly for high electric field applications. However, conventional polymers often fail to meet the demands of high-temperature environments due to increased electrical conductivity and reduced discharged energy density at elevated temperatures, resulting in energy loss and reduced performance. High glass transition temperature (T g) polymers show promise but require further optimization to enhance their energy storage capabilities under thermal and electrical stress. This review provides a comprehensive update on recent advancements in high-T g polymer-based dielectrics for EES capacitors, focusing on both intrinsic polymers and all-organic composites. It outlines key design principles, critical performance parameters, and innovative strategies—such as nanofiller doping, layered architectures, physical blending, and chemical crosslinking—to improve electrical, thermal, and mechanical properties. The review also highlights emerging trends, including the integration of machine learning algorithms to explore novel polymer structures and expand the chemical design space. By bridging the gap between academic research and industrial application, this review aims to accelerate the development of next-generation dielectric materials capable of balancing multiple performance metrics for high-temperature EES capacitors.

Xie, Zongliang↗
DOE OSTI2024

Tuning Optical and Electrical Properties of Vanadium Oxide with Topochemical Reduction and Substitutional Tin

Vanadium oxides are widely tunable materials, with many thermodynamically stable phases suitable for applications spanning catalysis to neuromorphic computing. The stability of vanadium in a range of oxidation states enables mixed-valence polymorphs of kinetically accessible metastable materials. Low-temperature synthetic routes to, and the properties of, these metastable materials are poorly understood and may unlock new optoelectronic and magnetic functionalities for expanded applications. In this work, we demonstrate topochemical reduction of α-V 2 O 5 to produce metastable vanadium oxide phases with tunable oxygen vacancies (>6%) and simultaneous substitutional tin incorporation (>3.5%). The chemistry is carried out at low temperature (65 °C) with solution-phase SnCl 2 , where Sn 2+ is oxidized to Sn 4+ as V 5+ sites are reduced to V 4+ during oxygen vacancy formation. Despite high oxygen vacancy and tin concentrations, the transformations are topochemical in that the symmetry of the parent crystal remains intact, although the unit cell expands. Band structure calculations show that these vacancies contribute electrons to the lattice, whereas substitutional tin contributes holes, yielding a compensation doping effect and control over the electronic properties. The SnCl 2 redox chemistry is effective on both solution-processed V 2 O 5 nanoparticle inks and mesoporous films cast from untreated inks, enabling versatile routes toward functional films with tunable optical and electronic properties. The electrical conductance rises concomitantly with the SnCl 2 concentration and treatment time, indicating a net increase in density of free electrons in the host lattice. This work provides a valuable demonstration of kinetic tailoring of electronic properties of vanadium–oxygen systems through top-down chemical manipulation from known thermodynamic phases.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Accessing One-Dimensional Chains of Halogenoindates(III) in Organic–Inorganic Hybrids

Organic-inorganic hybrids of halogenoindates(III) are typically represented by one of the zero-dimensional units: InX 4 – , InX 5 2– , InX 6 3– , or In 2 X 11 5– . Higher dimensional anionic forms, although not forbidden, have remained almost elusive. Here, in this study, we report for the first time In 3+ -based organic–inorganic hybrids, (C 4 H 5 N 2 S) 2 InCl 5 and (C 4 H 5 N 2 S) 2 InBr 5 , with 1D anionic chains of trans-halide-bridged InX 6 octahedra whose formation is guided by 2-mercaptopyrimidinium cations (C 4 H 5 N 2 S + ). The chains are characterized by the significant ease of deformation, which is reflected in the elongation of the bridging bonds or the displacement of In 3+ ions. The materials show a robust band gap predominantly governed by C 4 H 5 N 2 S + cations. Dielectric relaxation processes in (C 4 H 5 N 2 S) 2 InBr 5 arise from the cations’ dynamics and suggest the ability of the brominated system to accommodate even larger cations. Our work represents a successful attempt to expand the structural diversity of halogenoindates(III) and opens a pathway to reach multifunctional 1D In 3+ -based hybrids.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Accurate simulation of surfaces and interfaces of ten FCC metals and steel using Lennard–Jones potentials

Abstract The earlier integration of validated Lennard–Jones (LJ) potentials for 8 fcc metals into materials and biomolecular force fields has advanced multiple research fields, for example, metal–electrolyte interfaces, recognition of biomolecules, colloidal assembly of metal nanostructures, alloys, and catalysis. Here we introduce 12-6 and 9-6 LJ parameters for classical all-atom simulations of 10 further fcc metals (Ac, Ca (α), Ce (γ), Es (β), Fe (γ), Ir, Rh, Sr (α), Th (α), Yb (β)) and stainless steel. The parameters reproduce lattice constants, surface energies, water interfacial energies, and interactions with (bio)organic molecules in 0.1 to 5% agreement with experiment, as well as qualitative mechanical properties under standard conditions. Deviations are reduced up to a factor of one hundred in comparison to earlier Lennard–Jones parameters, embedded atom models, and density functional theory. We also explain a quantitative correlation between atomization energies from experiments and surface energies that supports parameter development. The models are computationally very efficient and applicable to an exponential space of alloys. Compatibility with a wide range of force fields such as the Interface force field (IFF), AMBER, CHARMM, COMPASS, CVFF, DREIDING, OPLS-AA, and PCFF enables reliable simulations of nanostructures up to millions of atoms and microsecond time scales. User-friendly model building and input generation are available in the CHARMM-GUI Nanomaterial Modeler. As a limitation, deviations in mechanical properties vary and are comparable to DFT methods. We discuss the incorporation of reactivity and features of the electronic structure to expand the range of applications and further increase the accuracy.

Kanhaiya, Krishan (ORCID:0000000236222655)↗
DOE OSTI2022

Cryo-EM structure of transmembrane AAA+ protease FtsH in the ADP state

Abstract AAA+ proteases regulate numerous physiological and cellular processes through tightly regulated proteolytic cleavage of protein substrates driven by ATP hydrolysis. FtsH is the only known family of membrane-anchored AAA+ proteases essential for membrane protein quality control. Although a spiral staircase rotation mechanism for substrate translocation across the FtsH pore has been proposed, the detailed conformational changes among various states have not been clear due to absence of FtsH structures in these states. We report here the cryo-EM structure for Thermotoga maritima FtsH ( Tm FtsH) in a fully ADP-bound symmetric state. Comparisons of the ADP-state structure with its apo-state and a substrate-engaged yeast YME1 structure show conformational changes in the ATPase domains, rather than the protease domains. A reconstruction of the full-length Tm FtsH provides structural insights for the dynamic transmembrane and the periplasmic domains. Our structural analyses expand the understanding of conformational switches between different nucleotide states in ATP hydrolysis by FtsH.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A topological kagome magnet in high entropy form

AbstractTopological kagome magnets RMn 6 Sn 6 (R = rare earth element) attract numerous interests due to their non-trivial band topology and room-temperature magnetism. Here, we report a high entropy version of kagome magnet, (Gd 0.38 Tb 0.27 Dy 0.20 Ho 0.15 )Mn 6 Sn 6 . Such a high entropy material exhibits multiple spin reorientation transitions, which is not seen in all the related parent compounds and can be understood in terms of competing magnetic interactions enabled by high entropy. Furthermore, we also observed an intrinsic anomalous Hall effect, indicating that the high entropy phase preserves the non-trivial band topology. These results suggest that high entropy may provide a route to engineer the magnetic structure and expand the horizon of topological materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Localizing resonant magnetic perturbations for edge localized mode control in KSTAR

An external 3D magnetic perturbation typically drives a resonant response at the rational surfaces from the core to the edge of tokamak plasmas, due to strong mode coupling and amplification. In this paper, we present a method to isolate the edge from core resonant fields using the ideal perturbed equilibrium code and to design an edge-localized resonant magnetic perturbation (RMP) for effective edge localized mode (ELM) control. A robust feature of the edge-localized RMP is the curtailed response to the field at the low-field-side (LFS) midplane, as opposed to typical RMPs which strongly resonate with the LFS fields. This emphasizes the importance of off-midplane coils to improve ELM control without provoking a large core response that could lead to devastating instabilities. The conceptual design of new ELM control coils based on the edge-localized RMP in KSTAR shows how this new insight can be utilized to enhance the efficiency of our ELM suppression capabilities. Simple window-pane coils matching the edge-localized resonant mode structure substantially expand in the ELM suppression window beyond the existing coil. Further optimization using the flexible optimized coils using space-curves code leads to additional enhancement in the edge-localized control.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Probing triaxiality beyond the proton drip line: Spectroscopy of Tm 147

Two triaxial states of the proton-decaying nucleus 147 Tm were studied via a comparison of experimental data to results obtained through nonadiabatic quasiparticle calculations. The experimental data were collected in a recoil-decay tagging study using the vacuum-mode recoil separator MARA coupled with the JUROGAM3 $\gamma$-ray spectrometer. The previously proposed level scheme above the triaxial 11/2 - (π⁢ℎ 11/2 ) ground state was confirmed, and the level structure was expanded to cover the states above the weakly populated proton-emitting 5/2 + (πd 5/2 ) isomeric state. Further, it was found that the isomeric state is also triaxial, and possibly more deformed than the ground state.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Predictive Modeling of Electrodeposition in a Single Pore Flow-Through Electrode: From Electronucleation to Coating Thickness Uniformity

The emergence of advanced manufacturing methods capable of producing porous three-dimensional structures has expanded the design space for next-generation functional components. The ability to fabricate ordered 3D foams for use in electrocatalysis reactors has increased the need for controlled deposition of catalytic metals onto porous support materials, such as carbon. However, there is a lack of clear design guidelines for electrodeposition onto 3D substrates, due to the geometric complexity and multi-scale nature of the problem. Furthermore, electro-nucleation phenomena are often overlooked in macro-scale models of current distribution during deposition. Here, a graphite flow-through electrode (FTE) is used as a model system for copper deposition within a single pore. Potential distributions and electro-nucleation phenomena are coupled in a continuum level model by incorporating nucleation size and density as a function of overpotential, determined experimentally using in situ atomic force microscopy (AFM). The model predictions are validated by measuring the coating uniformity in the pore using micro-computed X-ray tomography (μCT). A scaling analysis comprising dimensionless parameters such as the Wagner number is presented. The simplified scaling relationship framework can guide the electrodeposition process and electrode design to optimize plating of porous substrates under fluid flow conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Solid face sheets enable lattice metamaterials to withstand high-amplitude impulsive loading without yielding

Owing to their ability to provide tunable mechanical responses, lattice materials are frequently studied to elucidate their response to static and dynamic loads. However, these roles are typically in opposition: static loads must be supported sufficiently far away from the onset of buckling or yielding, whereas dynamic loads are typically ameliorated by crushing of the lattice, which provides excellent energy-absorption due to the large plastic deformation accompanying densification. In contrast, this work considers the octet truss as an exemplar topology, in a structural role where it must simultaneously support static loads while enduring high-amplitude impulsive loads. This study focuses on the ability to withstand impulsive loads without yielding, an essential prerequisite to enduring dual loading. Computational studies using the ALE3D hydrocode were performed to examine the response of the octet truss under a short temporal width impulse shape associated with laser-driven shocks. A key finding was that covering the lattice with a solid face sheet and treating this face sheet thickness as a design variable allows the Taylor-like pulse to be attenuated prior to entering the weaker lattice, at the cost of added mass up front. Experimental validation was accomplished by laser-driven shock testing, using octet trusses printed out of Ti-5Al-5V-5Mo-3Cr. The results show that for a given quantity of mass, the attenuation is maximized when as much mass as possible is moved into the face sheet, leaving a more slender lattice structure. The effect of placing mass in the face sheet rather than lattice beams dominates the effect of relative density, to the point where a low-mass structure with most of the mass concentrated in the face sheet can outperform a high-mass structure with most of the mass in the lattice. Finally, by further understanding the propagation of short pulse width waves within under-dense structures, this study expand the domain of applicability of such structures, including lattice materials, to challenging dual-loading regimes spanning decades of strain rates.

36 MATERIALS SCIENCE↗
DOE OSTI2024

AlphaFold -assisted structure determination of a bacterial protein of unknown function using X-ray and electron crystallography

Macromolecular crystallography generally requires the recovery of missing phase information from diffraction data to reconstruct an electron-density map of the crystallized molecule. Most recent structures have been solved using molecular replacement as a phasing method, requiring an a priori structure that is closely related to the target protein to serve as a search model; when no such search model exists, molecular replacement is not possible. New advances in computational machine-learning methods, however, have resulted in major advances in protein structure predictions from sequence information. Methods that generate predicted structural models of sufficient accuracy provide a powerful approach to molecular replacement. Taking advantage of these advances, AlphaFold predictions were applied to enable structure determination of a bacterial protein of unknown function (UniProtKB Q63NT7, NCBI locus BPSS0212) based on diffraction data that had evaded phasing attempts using MIR and anomalous scattering methods. Using both X-ray and micro-electron (microED) diffraction data, it was possible to solve the structure of the main fragment of the protein using a predicted model of that domain as a starting point. The use of predicted structural models importantly expands the promise of electron diffraction, where structure determination relies critically on molecular replacement.

molecular replacement↗