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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Structure-Based Discovery and Development of Highly Potent Dihydroorotate Dehydrogenase Inhibitors for Malaria Chemoprevention

Malaria remains a serious global health challenge, yet treatment and control programs are threatened by drug resistance. Dihydroorotate dehydrogenase (DHODH) was clinically validated as a target for treatment and prevention of malaria through human studies with DSM265, but currently no drugs against this target are in clinical use. We used structure-based computational tools including free energy perturbation (FEP+) to discover highly ligand efficient, potent, and selective pyrazolebased Plasmodium DHODH inhibitors through a scaffold hop from a pyrrole-based series. Optimized pyrazole-based compounds were identified with low nM-to-pM Plasmodium falciparum cell potency and oral activity in a humanized SCID mouse malaria infection model. The lead compound DSM1465 is more potent and has improved absorption, distribution, metabolism and excretion/pharmacokinetic (ADME/PK) properties compared to DSM265 that support the potential for once-monthly chemoprevention at a low dose. This compound meets the objective of identifying compounds with potential to be used for monthly chemoprevention in Africa to support malaria elimination efforts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

The STRong lensing Insights into the Dark Energy Survey (STRIDES) 2017/2018 follow-up campaign: discovery of 10 lensed quasars and 10 quasar pairs

Here, we report the results of the STRong lensing Insights into the Dark Energy Survey (STRIDES) follow-up campaign of the late 2017/early 2018 season. We obtained spectra of 65 lensed quasar candidates with ESO Faint Object Spectrograph and Camera 2 on the NTT and Echellette Spectrograph and Imager on Keck, confirming 10 new lensed quasars and 10 quasar pairs. Eight lensed quasars are doubly imaged with source redshifts between 0.99 and 2.90, one is triply imaged (DESJ0345-2545, z = 1.68), and one is quadruply imaged (quad: DESJ0053-2012, z = 3.8). Singular isothermal ellipsoid models for the doubles, based on high-resolution imaging from SAMI on Southern Astrophysical Research Telescope or Near InfraRed Camera 2 on Keck, give total magnifications between 3.2 and 5.6, and Einstein radii between 0.49 and 1.97 arcsec. After spectroscopic follow-up, we extract multi-epoch grizY photometry of confirmed lensed quasars and contaminant quasar + star pairs from DES data using parametric multiband modelling, and compare variability in each system’s components. By measuring the reduced χ 2 associated with fitting all epochs to the same magnitude, we find a simple cut on the less variable component that retains all confirmed lensed quasars, while removing 94 per cent of contaminant systems. Based on our spectroscopic follow-up, this variability information improves selection of lensed quasars and quasar pairs from 34-45 per cent to 51–70 per cent, with most remaining contaminants being star-forming galaxies. Using mock lensed quasar light curves we demonstrate that selection based only on variability will over-represent the quad fraction by 10 per cent over a complete DES magnitude-limited sample, explained by the magnification bias and hence lower luminosity/more variable sources in quads.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Recoil imaging for dark matter, neutrinos, and physics beyond the Standard Model

Recoil imaging entails the detection of spatially resolved ionization tracks generated by particle interactions. This is a highly sought-after capability in many classes of detector, with broad applications across particle and astroparticle physics. However, at low energies, where ionization signatures are small in size, recoil imaging only seems to be a practical goal for micro-pattern gas detectors. This white paper outlines the physics case for recoil imaging, and puts forward a decadal plan to advance towards the directional detection of low-energy recoils with sensitivity and resolution close to fundamental performance limits. The science case covered includes: the discovery of dark matter into the neutrino fog, directional detection of sub-MeV solar neutrinos, the precision study of coherent-elastic neutrino-nucleus scattering, the detection of solar axions, the measurement of the Migdal effect, X-ray polarimetry, and several other applied physics goals. We also outline the R&D programs necessary to test concepts that are crucial to advance detector performance towards their fundamental limit: single primary electron sensitivity with full 3D spatial resolution at the $\sim$100 micron-scale. These advancements include: the use of negative ion drift, electron counting with high-definition electronic readout, time projection chambers with optical readout, and the possibility for nuclear recoil tracking in high-density gases such as argon. We also discuss the readout and electronics systems needed to scale-up such detectors to the ton-scale and beyond.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Near-physiological-temperature serial crystallography reveals conformations of SARS-CoV-2 main protease active site for improved drug repurposing

The COVID-19 pandemic has resulted in 198 million reported infections and more than 4 million deaths as of July 2021 (covid19.who.int). Research to identify effective therapies for COVID-19 includes: (1) designing a vaccine as future protection; (2) de novo drug discovery; and (3) identifying existing drugs to repurpose them as effective and immediate treatments. To assist in drug repurposing and design, we determine two apo structures of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease at ambient temperature by serial femtosecond X-ray crystallography. We employ detailed molecular simulations of selected known main protease inhibitors with the structures and compare binding modes and energies. The combined structural and molecular modeling studies not only reveal the dynamics of small molecules targeting the main protease but also provide invaluable opportunities for drug repurposing and structure-based drug design strategies against SARS-CoV-2.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Stability Frontiers in the AM 6 X 6 Kagome Metals: The Ln Nb 6 Sn 6 ( Ln :Ce–Lu,Y) Family and Density-Wave Transition in LuNb 6 Sn 6

The kagome motif is a versatile platform for condensed matter physics, hosting rich interactions between magnetic, electronic, and structural degrees of freedom. In recent years, the discovery of a charge density wave (CDW) in the AV 3 Sb 5 superconductors and structurally-derived bond density waves (BDW) in FeGe and ScV 6 Sn 6 have stoked the search for new kagome platforms broadly exhibiting density wave (DW) transitions. Here, in this work, we evaluate the known AM 6 X 6 chemistries and construct a stability diagram that summarizes the structural relationships among the >125 member family. Subsequently, we introduce our discovery of the broader LnNb 6 Sn 6 (Ln:Ce–Nd,Sm,Gd–Tm,Lu,Y) family of kagome metals and an analogous DW transition in LuNb 6 Sn 6 . Our X-ray scattering measurements clearly indicate a (1/3, 1/3, 1/3) ordering wave vector (√$\bar{3}$ x √$\bar{3}$ x $3$ superlattice) and diffuse scattering on half-integer L-planes. Our analysis of the structural data supports the “rattling mode” DW model proposed for ScV 6 Sn 6 and paints a detailed picture of the steric interactions between the rare-earth filler element and the host Nb–Sn kagome scaffolding. We also provide a broad survey of the magnetic properties within the HfFe 6 Ge 6 -type LnNb 6 Sn 6 members, revealing a number of complex antiferromagnetic and metamagnetic transitions throughout the family. This work integrates our new LnNb 6 Sn 6 series of compounds into the broader AM 6 X 6 family, providing new material platforms and forging a new route forward at the frontier of kagome metal research.

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

New proton emitter 188 At implies an interaction unprecedented in heavy nuclei

We report the discovery of a new atomic nucleus 188 At, which is the heaviest proton-emitting isotope known to date. The new activity was observed through the 107 Ag( 84 Sr, 3n) 188 At fusion-evaporation reaction using the focal-plane spectrometer of the gas-filled recoil separator in the Accelerator Laboratory of the University of Jyväskylä, Finland. To fully interpret the experimental data, we have expanded the non-adiabatic quasiparticle model to treat nuclei in the beyond-lead region. The description reproduced the measured decay rate and pointed towards emission from an extremely prolate-deformed state with a dominant s 1/2 proton component in the wave function. The Thomas-Ehrman shift can be enhanced in low angular momentum states, but such effects have not been observed in heavy nuclei. The single-proton separation energy of 188 At deviates from that extrapolated from the systematics, which can be interpreted as the first evidence of this effect in heavy nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Infalling ultra-faint dwarfs as emissaries of the Axiverse

Recent discoveries of ultra-faint dwarf galaxies (UFDs) infalling onto the Milky Way, namely Leo K & M at r ≃ 450 kpc, considerably strengthens the case that UFDs constitute a distinct galaxy class that is inherently smaller and fainter, and metal-poorer than the classical dwarf spheroidals (dSph). This distinction is at odds with the inherent continuity of galaxy halo masses formed under scale-free gravity for any standard dark-matter (DM) model. Here, we show that distinct galaxy classes do evolve in cosmological simulations of multiple light bosons representing the “Axiverse” proposal of string theory, where a discrete mass spectrum of axions is generically predicted to span many decades in mass. In this context, the observed UFD class we show corresponds to a relatively heavy boson of 3 × 10 −21 eV, including Leo K & M, whereas a lighter axion of 10 −22 eV comprises the bulk of DM in all larger galaxies including the dSphs. Although Leo M is larger in size than Leo K, we predict its velocity dispersion to be smaller ( ≃ 1.7 km/s) than that of Leo K ( ≃ 4.5 km/s) because of the inverse de Broglie scale dependence on momentum. This scenario can be definitively tested using millisecond pulsars close to the Galactic center, where the Compton frequencies of the heavy and light bosons imprint monotone timing residuals that may be detected by the Square Kilometre Array (SKA) on timescales of approximately one week and four months, respectively.

dark matter↗
DOE OSTI2025

A convergence metric for counting statistics in time-resolved small angle neutron scattering

Here, this work introduces a model-independent, dimensionless metric for predicting optimal measurement duration in time-resolved small-angle neutron scattering using early-time data. Built on a Gaussian process regression framework, the method reconstructs scattering profiles with quantified uncertainty, even from sparse or noisy measurements. Demonstrated on the EQ-SANS instrument at the Spallation Neutron Source, the approach generalizes to general SANS instruments with a two-dimensional detector. A key result is the discovery of a dimensionless convergence metric revealing a universal power-law scaling in profile evolution across soft matter systems. When time is normalized by a system-specific characteristic time t*, the variation in inferred profiles collapses onto a single curve with an exponent between −2 and −1. This trend emerges within the first ten time steps, enabling early prediction of measurement sufficiency. The method supports real-time experimental optimization and is especially valuable for maximizing efficiency in low-flux environments such as compact accelerator-based neutron sources.

Tung, Chi-Huan [Oak Ridge National Laboratory (ORN↗
DOE OSTI2024

Initial PIP-II Beam Current Monitor Fault Case Analyses & Beam Position Monitor Linearity Studies in CST Studio Suite

The use of non-invasive sensors & systems to measure particle beam characteristics is a crucial part of modern accelerator control systems due to their ability to return real time beam data while minimizing negative effects on beam quality. To ensure that one can be reasonably confident these sensors will behave as desired upon be-ing implemented within the beamline, simulations pre-dicting the performance of these sensors under beamline conditions can be used as a valuable tool for checking sensor functionality without a physical test bench. This paper details the design, testing, and results of two sensor models developed using CST Studio Suite soft-ware designed to mimic two sensors to be implemented within the PIP-III beamline: an elliptical, large-aperture beam position monitor (BPM) for which vertical & hori-zontal position signal linearity was analyzed, and an AC current transformer (ACCT) beam current monitor (BCM) used to search for potential fault cases within the BCM and beam pipe flange gaps. Special focus is given to the discovery of linearity variations within the BPM and the use of frequency domain techniques in the BCM fault case analyses.

Rouzky, A. R.↗
DOE OSTI2024

Systematic discovery of new nano-scale metastable intermetallic eutectic phases in laser rapid solidified Aluminum-Germanium alloy

Laser surface remelting of as-cast Al-Ge eutectic alloy is shown to produce ultrafine lamellar eutectic morphology with interlamellar spacing refined up to ∼60 nm and composed of FCC Al solid solution and unusual Al x Ge y intermetallic phases that do not form during near-equilibrium solidification. The microstructures are characterized and analyzed using a combination of selected area electron diffraction, high-resolution scanning transmission electron microscopy, energy dispersive X-ray spectroscopy to obtain high-resolution elemental maps, and atomistic modeling using density functional theory followed by atomic-scale image simulation. Depending on the local solidification conditions, the crystallography of the Al x Ge y intermetallic phases in the eutectic microstructure is either monoclinic (C 2/c) or monoclinic (P 2 1 ), with high densities of defects in both cases. This is in sharp contrast to the as-cast alloys that showed nominally pure Al and Ge phases with significant solute partitioning and equilibrium FCC and diamond cubic crystal structures, respectively. Corresponding kinetic phase diagrams are proposed to interpret the evolution of nano-lamellar eutectic morphologies with equilibrium Al and metastable Al x Ge y phases, and to explain increased solid solubility in the Al phases manifested by precipitation of ultrafine clusters of Ge. Furthermore, the reasons for the formation of these metastable eutectics under laser rapid solidification are discussed from the perspective of the competitive growth criterion.

Al-Ge eutectic↗
DOE OSTI2023

Autonomous Molecular Structure Imaging with High-Resolution Atomic Force Microscopy for Molecular Mixture Discovery

Due to its single-molecule sensitivity, high-resolution atomic force microscopy (HR-AFM) has proved to be a valuable and uniquely advantageous tool to study complex molecular mixtures, which hold promise for developing clean energy and achieving environmental sustainability. However, significant challenges remain to achieve the full potential of the sophisticated and time-consuming experiments. Automation combined with machine learning (ML) and artificial intelligence (AI) is key to overcoming these challenges. Here we present Auto-HR-AFM, an AI tool to automatically collect HR-AFM images of petroleum-based mixtures. In this study, we trained an instance segmentation model to teach Auto-HR-AFM how to recognize features in HR-AFM images. Auto-HR-AFM then uses that information to optimize the imaging by adjusting the probe-molecule distance for each molecule in the run. Auto-HR-AFM is the initial tool that will lead to fully automated scanning probe microscopy (SPM) experiments, from start to finish. This automation will allow SPM to become a mainstream characterization technique for complex mixtures, an otherwise unattainable target.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Artificial intelligence-driven approaches for materials design and discovery

Materials design is an important component of modern science and technology, yet traditional approaches rely heavily on trial and error and can be inefficient. Computational techniques, enhanced by modern artificial intelligence, have reshaped the landscape of designing new materials. Among these approaches, inverse design has shown great promise in designing materials that meet specific property requirements. Here, in this Review, we present key computational advances in materials design over the past few decades. We follow the evolution of relevant materials design techniques, from high-throughput forward machine learning methods and evolutionary algorithms, to advanced artificial intelligence strategies such as reinforcement learning and deep generative models. We highlight the paradigm shift from conventional screening approaches to inverse generation driven by deep generative models. Finally, we discuss current challenges and future perspectives of materials inverse design. This Review may serve as a brief guide to the approaches, progress and outlook of designing future functional materials with technological relevance.

computational methods↗
DOE OSTI2024

Material Discovery and Design Principles of Perovskite Oxides for Reversible Solid Oxide Cells (R-SOC)

Reversible solid oxide cells (R-SOCs) are highly efficient devices for energy conversion and storage, capable of operating for both hydrogen utilization and production. In fuel cell mode, an R-SOC consumes hydrogen or natural gas to generate electricity, while in electrolysis mode, it produces hydrogen from steam. The discover of new materials with rapid oxygen surface exchange kinetics and enduring stability is crucial for the economically viable commercialization of R-SOCs. To facilitate this pursuit, we conducted extensive Density Functional Theory (DFT) calculations and developed Machine Learning (ML) models to predict critical catalytic properties essential for R-SOCs, such as oxygen surface exchange/diffusivity, and area-specific resistance (ASR). BaCoxFeyZrzO3-d(BFCZ)(x+y+z=1) emerged as a promising family of electrode materials with high activity and stability, validated through systematic experimental study. Moreover, a robust numerical multiphysics model was developed to optimize materials and microstructure parameters, providing the ability to predict the performance of functional R-SOCs.

Liu, Jian↗
DOE OSTI2024

Observation of interlayer plasmon polaron in graphene/WS 2 heterostructures

Harnessing electronic excitations involving coherent coupling to bosonic modes is essential for the design and control of emergent phenomena in quantum materials. In situations where charge carriers induce a lattice distortion due to the electron-phonon interaction, the conducting states get “dressed", which leads to the formation of polaronic quasiparticles. The exploration of polaronic effects on low-energy excitations is in its infancy in two-dimensional materials. Here, we present the discovery of an interlayer plasmon polaron in heterostructures composed of graphene on top of single-layer WS 2 . By using micro-focused angle-resolved photoemission spectroscopy during in situ doping of the top graphene layer, we observe a strong quasiparticle peak accompanied by several carrier density-dependent shake-off replicas around the single-layer WS 2 conduction band minimum. Our results are explained by an effective many-body model in terms of a coupling between single-layer WS 2 conduction electrons and an interlayer plasmon mode. It is important to take into account the presence of such interlayer collective modes, as they have profound consequences for the electronic and optical properties of heterostructures that are routinely explored in many device architectures involving 2D transition metal dichalcogenides.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Huntingtin structure is orchestrated by HAP40 and shows a polyglutamine expansion-specific interaction with exon 1

Huntington’s disease results from expansion of a glutamine-coding CAG tract in the huntingtin (HTT) gene, producing an aberrantly functioning form of HTT. Both wildtype and disease-state HTT form a hetero-dimer with HAP40 of unknown functional relevance. Here, we demonstrate in vivo and in cell models that HTT and HAP40 cellular abundance are coupled. Integrating data from a 2.6 Å cryo-electron microscopy structure, cross-linking mass spectrometry, small-angle X-ray scattering, and modeling, we provide a near-atomic-level view of HTT, its molecular interaction surfaces and compacted domain architecture, orchestrated by HAP40. Native mass spectrometry reveals a remarkably stable hetero-dimer, potentially explaining the cellular inter-dependence of HTT and HAP40. The exon 1 region of HTT is dynamic but shows greater conformational variety in the polyglutamine expanded mutant than wildtype exon 1. Our data provide a foundation for future functional and drug discovery studies targeting Huntington’s disease and illuminate the structural consequences of HTT polyglutamine expansion.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Probing the solidification of quasicrystals via joint experiment and simulation (Final Report)

Quasicrystals (QCs) possess long-range positional order but non-crystallographic orientational order. Their classically ‘forbidden’ symmetry has long attracted the interest of scientists worldwide. Despite their frequent observation in both metal alloys and soft matter structures in the 35 years since their discovery, little is known about how QCs evolve from a liquid, amorphous, or crystalline precursor. In this project, we sought to resolve the enigma of QC self-assembly through a combined experimental and computational program. The Shahani group employed in situ electron and synchrotron X ray imaging to peer into the growth dynamics of QCs in a liquid, covering a broad range of length scales and solidification pathways. Glotzer's team developed new simulation models incorporating phasonic defects — which are unique to quasicrystals — and used this model to investigate two grains growing together, closely mimicking the experimental conditions. While QCs remain exceptional structures, most compounds in the realm of intermetallics adopt non-trivial geometries. In fact, only around 6% of phases are comprised of the simplest sphere packings that researchers so readily associate with metals. State-of-the-art knowledge of phase transformations at the outset of this collaborative project did not encompass the remaining 94% of intermetallic compounds that possess complex and aperiodic structure types. Therefore, we expect that outcomes from this project will have immediate and profound impact on synthesis and processing science: our efforts will be used to not only explain the growth dynamics of QCs but also complex intermetallics more broadly.

36 MATERIALS SCIENCE↗
DOE OSTI2022

End-to-end optimization for battery materials and molecules by combining graph neural networks and reinforcement learning

The National Renewable Energy Laboratory (NREL), together with the Colorado School of Mines (CSM) and Colorado State University (CSU), has developed a machine learning-enhanced approach to design new battery materials. Currently, such materials are designed in part via numerous expensive high-fidelity computational simulations that predict the performance of a given composition. Even with computational screening tools, the vast landscape of possible molecular or crystal structures exceeds current and future computational capacity. Improving the efficiency by which new materials can be optimized will therefore disrupt the cost, risk, and time required to bring new energy solutions to the marketplace. Predicting the properties of an organic molecule or periodic crystalline material given its structure has grown increasingly common. These approaches leverage large-scale computational and experimental databases and ML approaches such as graph neural networks. The inverse design problem of finding a material that possesses desired properties is substantially more challenging, since enumerating all valid material structures is not feasible. In this project, we leveraged recent success in reinforcement learning to efficiently navigate this high-dimensional search space. Just as algorithms can find the optimal chess moves from nearly limitless options, we train an approach to evolve a simple starting structure into a complex structure that possess the desired properties. Our solution has been demonstrated by applying it to two related design application tasks for short- and long-term energy storage, respectively: (1) the design of solid-state ion conductors and (2) the design of organic redox-active materials. The project has resulted an open-source software library for material design, documented examples of applying the library to both organic and inorganic material optimization, and peer-reviewed publications detailing the data, computational models, and resulting candidate materials.

25 ENERGY STORAGE↗
DOE OSTI2021

Out of the Dark and Into the Light: A New View of Phytochrome Photobodies

Light is a critical environmental stimulus for plants, serving as an energy source via photosynthesis and a signal for developmental programming. Plants perceive light through various light-responsive proteins, termed photoreceptors. Phytochromes are red-light photoreceptors that are highly conserved across kingdoms. In the model plant Arabidopsis thaliana , phytochrome B serves as a light and thermal sensor, mediating physiological processes such as seedling germination and establishment, hypocotyl growth, chlorophyll biogenesis, and flowering. In response to red light, phytochromes convert to a biologically active form, translocating from the cytoplasm into the nucleus and further compartmentalizes into subnuclear compartments termed photobodies. PhyB photobodies regulate phytochrome-mediated signaling and physiological outputs. However, photobody function, composition, and biogenesis remain undefined since their discovery. Based on photobody cellular dynamics and the properties of internal components, photobodies have been suggested to undergo liquid-liquid phase separation, a process by which some membraneless compartments form. Here, we explore photobodies as environmental sensors, examine the role of their protein constituents, and outline the biophysical perspective that photobodies may be undergoing liquid-liquid phase separation. Understanding the molecular, cellular, and biophysical processes that shape how plants perceive light will help in engineering improved sunlight capture and fitness of important crops.

54 ENVIRONMENTAL SCIENCES↗