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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Evaluating Fracture Behavior of Bioinspired Alumina-YSZ Composites through Static and Dynamic Mechanical Testing

Ceramic materials are known for their high hardness and strength but are limited by low toughness and sudden failure. Inspired by the microstructure of dental enamel, which features undulating rods that promote crack deflection and energy absorption, architected specimens were designed and manufactured. A bespoke ball-on-ring (BoR) testing apparatus measured the static biaxial rupture strength of these bioinspired materials. Additionally, impact testing with spherical steel projectiles assessed their behavior under dynamic conditions. Monolithic alumina specimens were compared to architected alumina reinforced with yttria-stabilized zirconia (YSZ) rods produced via direct ink write 3D printing. BoR tests revealed that monolithic alumina had a Weibull modulus of 10.53 and a characteristic strength of 372.3 MPa, while the composite specimens showed a Weibull modulus of 5.46 and a characteristic strength of 213.3 MPa. Although the composite failed at lower stresses and projectile velocities, it exhibited notable crack deflection and fracture resistance, with cracks being effectively interrupted by the rod inclusions. The composite specimens also resulted in fewer and larger fragments upon impact. Finite element simulations confirmed the effectiveness of the rod structures in enhancing fracture resistance.

Bioinspired materials↗
DOE OSTI2022

Metall: A persistent memory allocator for data-centric analytics

Data analytics applications transform raw input data into analytics-specific data structures before performing analytics. Unfortunately, such data ingestion steps are often more expensive than analytics. In addition, various types of NVRAM devices are already used in many HPC systems today. Such devices will be useful for storing and reusing data structures beyond a single process life cycle. We developed Metall, a persistent memory allocator built on top of the memory-mapped file mechanism. Metall enables applications to transparently allocate custom C++ data structures into various types of persistent memories. Metall incorporates a concise and high-performance memory management algorithm inspired by Supermalloc and the rich C++ interface developed by Boost.Interprocess library. On a dynamic graph construction workload, Metall achieved up to 11.7x and 48.3x performance improvements over Boost.Interprocess and memkind (PMEM kind), respectively. We also demonstrate Metall’s high adaptability by integrating Metall into a graph processing framework, GraphBLAS Template Library. Here this study’s outcomes indicate that Metall will be a strong tool for accelerating future large-scale data analytics by allowing applications to leverage persistent memory efficiently.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Accelerating scientific discoveries through data-driven innovations

Developing artificial intelligence (AI) and machine learning (ML) methods that can accelerate scientific discoveries and advance science has become one of the important research directions for the AI/ML research community. It has been gaining increasing attention from researchers in diverse scientific areas, including biomedical science, materials science, climate science, physics, chemistry, and many others. Data-driven AI/ML innovations to enable reliable predictions and optimal decision making for scientific discoveries face several critical challenges, among which are high system complexity, large search space, incomplete knowledge, and small data, all of which demand novel strategies to effectively address them. Meeting these challenges and thereby accelerating scientific discoveries and industrial innovations, calls for research that can take full advantage of the latest advances in AI/ML to integrate data-driven techniques with scientific knowledge and is able to execute them in modern high-performance computing (HPC) environments at scale. This Patterns special collection "Accelerating scientific discoveries through data-driven innovations" features articles that showcase the promising roles of AI/ML and data-driven modeling in accelerating scientific discoveries and may inspire the next wave of data-driven innovations in various scientific domains.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Enhancing molecular design efficiency: Uniting language models and generative networks with genetic algorithms

This study examines the effectiveness of generative models in drug discovery, material science, and polymer science, aiming to overcome constraints associated with traditional inverse design methods relying on heuristic rules. Generative models generate synthetic data resembling real data, enabling deep learning model training without extensive labeled datasets. They prove valuable in creating virtual libraries of molecules for material science and facilitating drug discovery by generating molecules with specific properties. While generative adversarial networks (GANs) are explored for these purposes, mode collapse restricts their efficacy, limiting novel structure variability. To address this, we introduce a masked language model (LM) inspired by natural language processing. Although LMs alone can have inherent limitations, we propose a hybrid architecture combining LMs and GANs to efficiently generate new molecules, demonstrating superior performance over standalone masked LMs, particularly for smaller population sizes. This hybrid LM-GAN architecture enhances efficiency in optimizing properties and generating novel samples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Learning from nature’s plant engineers: Hijacking metabolism and development beyond genetics

Plant metabolism underpins the food, fiber, and fuel that support our economy, driving strong interest in new strategies to rewire plant metabolism for emerging applications. While most synthetic biology efforts are reliant on genetic engineering, plants can be manipulated in many other ways that remain comparatively underexplored. Across nature, diverse organisms, including bacteria, fungi, and insects, have evolved sophisticated mechanisms to exploit plant metabolic richness, reshaping it for purposes that span from basic nutrition to the construction of complex, novel structures for shelters. These interspecies interactions and non-model systems represent unique manners in which plants can be reprogrammed or hijacked by other organisms, offering inspiration for novel approaches to engineering plant metabolism. By better understanding the basis of how organisms induce these remarkable transformations in plants, we can expand the conceptual boundaries of synthetic biology and reveal alternative routes to manipulating plants for the production of a diverse array of valuable compounds and materials. Deeper insight into these mechanisms will yield novel blueprints for rethinking the scope and breadth in which we can redesign plant metabolism across many applications.

Sarkiss, Anthony E. [University of California, Ber↗
DOE OSTI2023

$f$ 0 (980) production in inelastic pp collisions at s = 5.02 TeV

The measurement of the production of f 0 (980) in inelastic pp collisions at $\sqrt{s}$ = 5.02 TeV is presented. This is the first reported measurement of inclusive f 0 (980) yield at LHC energies. The production is measured at midrapidity, |y| < 0.5, in a wide transverse momentum range, 0 < p T < 16 GeV/c, by reconstructing the resonance in the f 0 (980) → π + π - hadronic decay channel using the ALICE detector. The p T -differential yields are compared to those of pions, protons and $φ$ mesons as well as to predictions from the HERWIG 7.2 QCD-inspired Monte Carlo event generator and calculations from a coalescence model that uses the AMPT model as an input. The ratio of the p T -integrated yield of f 0 (980) relative to pions is compared to measurements in e + e - and pp collisions at lower energies and predictions from statistical hadronisation models and HERWIG 7.2. A mild collision energy dependence of the f 0 (980) to pion production is observed in pp collisions from SPS to LHC energies. All considered models underpredict the p T -integrated 2f 0 (980)/(π + +π - ) ratio. The prediction from the canonical statistical hadronisation model assuming a zero total strangeness content of f 0 (980) is consistent with the data within 1.9σ and is the closest to the data. The results provide an essential reference for future measurements of the particle yield and nuclear modification in p–Pb and Pb–Pb collisions, which have been proposed to be instrumental to probe the elusive nature and quark composition of the f 0 (980) scalar meson.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Precision tests of fundamental physics with η and η ' mesons

Decays of the neutral and long-lived $\eta$ and $\eta'$ mesons provide a unique, flavor-conserving laboratory to test low-energy Quantum Chromodynamics and search for new physics beyond the Standard Model. They have drawn world-wide attention in recent years and have inspired broad experimental programs in different high-intensity-frontier centers. Additionally, new experimental data will offer critical inputs to precisely determine the light quark mass ratios, $\eta$-$\eta'$ mixing parameters, and hadronic contributions to the anomalous magnetic moment of the muon. At the same time, it will provide a sensitive probe to test potential new physics. This includes searches for hidden photons, light Higgs scalars, and axion-like particles that are complementary to worldwide efforts to detect new light particles below the GeV mass scale, as well as tests of discrete symmetry violation. In this review, we give an update on theoretical developments, discuss the experimental opportunities, and identify future research needed in this field.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Toward autonomous laboratories: Convergence of artificial intelligence and experimental automation

The ever-increasing demand for novel materials with superior properties inspires retrofitting traditional research paradigms in the era of artificial intelligence and automation. An autonomous experimental platform (AEP) has emerged as an exciting research frontier that achieves full autonomy via integrating data-driven algorithms such as machine learning (ML) with experimental automation in the material development loop from synthesis, characterization, and analysis, to decision making. In this review, we started with a primer to describe how to develop data-driven algorithms for solving material problems. Then, we systematically summarized recent progress on automated material synthesis, ML-enabled data analysis, and decision-making. Finally, we discussed the challenges and opportunities in an endeavor to develop the next-generation AEP for ultimately realizing an autonomous or self-driving laboratory. In conclusion, this review will provide insights for researchers aiming to learn the frontier of ML in materials science and deploy AEP in their labs for accelerating material development.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Recent progress in low energy neutrino scattering physics and its implications for the standard and beyond the standard model physics

Neutrinos continue to provide a testing ground for the structure of the standard model of particle physics as well as hints towards the physics beyond the standard model. Neutrinos of energies spanning over several orders of magnitude, originating in many terrestrial and astrophysical processes, have been detected via various decay and interaction mechanisms. At MeV scales, there has been one elusive process, until a few years ago, known as coherent elastic neutrino-nucleus scattering (CEvNS) that was theoretically predicted over five decades ago but was never observed experimentally. The recent experimental observation of the CEvNS process by the COHERENT collaboration at a stopped pion neutrino source has inspired physicists across many subfields. This has vital implications for nuclear physics, high-energy physics, astrophysics, and beyond. CEvNS, being a low-energy process, provides a natural window to study light, weakly-coupled, new physics in the neutrino sector. In this review, we intend to provide the current status of low energy neutrino scattering physics and its implications for the standard and beyond the standard model physics. We discuss the general formalism of calculating the tree-level CEvNS cross section and present estimated theoretical uncertainties on the CEvNS cross section stemming from different sources. We also discuss the inelastic scattering of tens of MeV neutrinos that have implications for supernova detection in future neutrino experiments. We discuss how the CEvNS experiments can be used as a testing ground for the Standard Model (SM) weak physics as well as in searching for the Beyond the Standard Model (BSM) physics signals. Any deviation from the SM predicted event rate either with a change in the total event rate or with a change in the shape of the recoil spectrum, could indicate new contributions to the interaction cross-section. The SM implications include the study of weak nuclear form factor and weak mixing angle. The BSM studies include non-standard interactions, neutrino electromagnetic properties, and sterile neutrino searches. In conclusion, stopped pion facilities are also a copious source of neutral and changed mesons that allow study of several dark sector physics scenarios such as vector portal models, leptophobic dark matter as well as axion-like particle searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Polysulfide regulation by defect-modulated Ta 3 N 5- x electrocatalyst toward superior room-temperature sodium-sulfur batteries

Resolving low sulfur reaction activity and severe polysulfide dissolution remains challenging in metal-sulfur batteries. Motivated by a theoretical prediction, herein, we strategically propose nitrogen-vacancy tantalum nitride (Ta 3 N 5-x ) impregnated inside the interconnected nanopores of nitrogen-decorated carbon matrix as a new electrocatalyst for regulating sulfur redox reactions in room-temperature sodium-sulfur batteries. Through a pore-constriction mechanism, the nitrogen vacancies are controllably constructed during the nucleation of Ta 3 N 5-x . Further, the defect manipulation on the local environment enables well-regulated Ta 5d-orbital energy level, not only modulating band structure toward enhanced intrinsic conductivity of Ta-based materials, but also promoting polysulfide stabilization and achieving bifunctional catalytic capability toward completely reversible polysulfide conversion. Moreover, the interconnected continuous Ta 3 N 5-x -in-pore structure facilitates electron and sodium-ion transport and accommodates volume expansion of sulfur species while suppressing their shuttle behavior. Due to these attributes, the as-developed Ta 3 N 5-x -based electrode achieves superior rate capability of 730 mAh g -1 at 3.35 A g -1 , long-term cycling stability over 2000 cycles, and high areal capacity over 6 mAh cm -2 under high sulfur loading of 6.2mgcm -2 . This work not only presents a new sulfur electrocatalyst candidate for metal-sulfur batteries, but also sheds light on the controllable material design of defect structure in hopes of inspiring new ideas and directions for future research.

25 ENERGY STORAGE↗
DOE OSTI2025

Developing aqueous solubilizing agents as an alternative to solvent extraction

Here, advancing separations science is important for the entire field of chemistry. One partitioning technique that would benefit from improvement is solvent extraction. Despite its effective and widespread use, the method suffers from some problems: generation of flammable organic waste, lengthy process times, and safety concerns associated with contacting organic solvents with acidic aqueous solutions. We developed an alternative separation method inspired by solvent extraction that side-steps those issues. Toward this end, we identified that the functionality of an extractant (an agent used in solvent extraction to pull analytes from the aqueous phase into the organic phase) would change if it was modified for water solubility. In this alternative scenario, the extractant transforms into an “aqueous solubilizing agent.” We discovered that adding this aqueous solubilizing agent alongside a precipitating agent caused the contaminants to precipitate, but not the analyte. This separation concept was demonstrated within the bounds of one of the most difficult partitioning problems, separating minor actinides (Am 3+ ) from lanthanides (Ln 3+ ). We discovered that the (HSO 3 Ph) 4 BTP (aq) aqueous solubilizing agent prevented Am 3+ (aq) from precipitating with Ln 3+ (aq) when f-element precipitating agents (NaF (aq) or HF (aq) ) were added. This separation boasts impressive Am 3+ (aq) recovery yield (90 ± 2 %), near quantitative Ln 3+ (aq) removal, and high separation factors [>3000, Am 3+ (aq) vs. Nd 3+ (aq) ]. It seems likely – given the large number of candidate extractants that could be modified for aqueous solubility and the numerous combinations of existing solubilizing and precipitating agents – that this alternative approach could be used broadly in place of solvent extraction and solve other important separation problems.

(HSO3Ph)4BTP(aq)↗
DOE OSTI2026

Microstructure and Composition of Passivating Interfaces in Silicon Heterojunction Solar Modules Weathered in Different Climates

Sanyo/Panasonic patented silicon heterojunction with intrinsic thin layer (HIT) solar cells in the 1990's, which demonstrated world record photovoltaic (PV) efficiency around 2014 and inspired the newer generations of silicon heterojunction technology (SHJ) as well as the current world record back-contact PV cell designs. The high-quality passivation strategy, utilizing ultra-thin layers of hydrogenated amorphous silicon (a-Si:H), leads to high voltages and long carrier lifetimes, but these qualities may degrade over time as the modules operate outdoors. Here, we investigate local microstructure and composition at the interface layers of cells from HIT modules weathered in a hot, humid climate (Florida, USA) and temperate climate (Colorado, USA) for 10 years. We employ a comprehensive set of high-resolution electron microscopy imaging and spectroscopy to directly resolve structure and composition in these cells down to the nanoscale. We show features such as alignment of the In2O3 transparent conducting oxide and a-Si:H layers on the textured c-Si facets, interfacial oxidation at the a-Si:H/c-Si and In2O3/a-Si:H interfaces, and twinned c-Si resulting from epitaxial growth into the a-Si:H layer. Our results raise potential degradation mechanisms in these outdoor-weathered modules, but the root cause of electrical loss remains uncertain due to the very small changes in aged samples. This study shows that many atomic scale features at the In2O3/a-Si:H/c-Si interfaces are surprisingly robust, and the electrical losses with aging may either be attributed to other pathways or be very sensitive to the subtle chemical and microstructural features observed here.

14 SOLAR ENERGY↗
DOE OSTI2022

Microwave-assisted C–H oxidation of methylpyridylheteroarenes via a Kornblum-Type reaction

Expansion of the operational capacity of soft-Lewis basic complexant scaffolds towards improved physical properties for the chemoselective sequestration of minor actinides from the electronically similar lanthanides necessitates rapid access to synthons for efficient complexant construction for downstream employment in separations assays. Pursuant to the aforementioned, we were interested in exploring the potential utility of advanced, unsymmetric heteroarene constructs for separations which required access to pyridyl carbaldehydes. Limited commercial availability of synthetic precursors inspired our effort to define a chemoselective, microwave assisted, Kornblum-type reaction via C–H functionalization. This efficient reaction sequence uses I 2 as a mild oxidant without acidic or basic additives, in concert with DMSO as the solvent and putative oxygen source to afford a diverse array of heteroaryl products devoid of competitive remote methyl group oxidation, or degradation of the heteroaryl N atom. Finally, method development, substrate scope, and a preliminary mechanistic hypothesis supported by Density Functional Theory are presented herein.

1,2,4-triazine↗
DOE OSTI2025

How volatile isoprenoids improve plant thermotolerance

Volatile isoprenoids mainly include isoprene and monoterpenes, which improve the thermotolerance of the emitting plant by lowering reactive oxygen species (ROS) levels, preserving chloroplast membrane ultrastructure, maintaining photosynthesis and primary metabolism, inducing heat shock proteins, and preserving growth and development. Recent data showed that isoprenoids can act as signaling molecules to improve plant thermotolerance by altering related gene expression through Ca 2+ -mediated signaling pathways. Here, to promote further understanding of isoprenoid-mediated thermotolerance mechanisms, we review current understanding of isoprenoid-induced plant thermotolerance, along with new findings describing the corresponding underlying mechanisms and putative signaling pathways. This information is beneficial for the potential utilization of isoprenoids for enhancing crop tolerance to global warming either by enhancing the emission of isoprenoids or by using isoprenoid-inspired anti-high temperature agents.

Ca2+ signal↗
DOE OSTI2020

Homogeneous Gold Redox Chemistry: Organometallics, Catalysis, and Beyond

Gold redox chemistry holds the promise of unique reactivities and selectivities that are different to other transition metals. Recent studies have utilized strain release, ligand design, and photochemistry to promote the otherwise sluggish oxidative addition to Au(I) complexes. More details on the reductive elimination from Au(III) complexes have also been revealed. These discoveries have facilitated the development of gold redox catalysis and will continue to offer mechanistic insight and inspiration for other transition metals. Furthermore, this review highlights how research in organometallic chemistry has led to gold redox catalysis, as well as applications in materials science, bioconjugation, and radiochemical synthesis.

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

Application of Single-Site Catalysts in the Hydrogen Economy

Catalysts development is an evolutionary process. The generation of new single-metal-site catalysts, with isolated metal atoms dispersed on the surface of substrates, offers maximum atom-utilization efficiency, high specific activity, and novel properties. The unique structure of single-site catalysts also enables their potential to bridge the gap between homogeneous and heterogeneous catalysis. This field is at an early stage, characterized by important discoveries and novel demonstrations of catalytic properties associated with the fine structure of single metal sites; however, specific applications, especially catalytic hydrogenation reactions, are still lacking. Here, we focus on applications of single-site catalysts in the hydrogen economy based on our studies of hydrogen generation/storage via single-metal-site catalysts. We hope this work will inspire the development of single-site catalysts for other applications.

08 HYDROGEN↗
DOE OSTI2021

Exploring chemistry with single-molecule and -particle fluorescence microscopy

The evolution of single-molecule and -particle fluorescence microscopy imaging techniques for the investigation of chemical reactions yielded achievements at all fronts, from synthetic organic chemistry to materials science. The removal of ensemble averaging effects uncovers unique, otherwise hidden reaction intermediates, reactivity, and kinetics. Thus, new insights can be obtained even for well-explored chemical reactions and processes. The aim of this article is to serve as a guide and a source of inspiration for scientists who wish to develop single-molecule and -particle fluorescence microscopy to answer questions in chemistry. Here, we describe the current status of technical accomplishments in the field and point out technical and conceptual obstacles for overcoming in the near future, with focus on improvement of bench-scale synthetic reactions.

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

The exit-wave power-cepstrum transform for scanning nanobeam electron diffraction: robust strain mapping at subnanometer resolution and subpicometer precision

Scanning nanobeam electron diffraction (NBED) with fast pixelated detectors is a valuable technique for rapid, spatially resolved mapping of lattice structure over a wide range of length scales. However, intensity variations caused by dynamical diffraction and sample mistilts can hinder the measurement of diffracted disk centers as necessary for quantification. Robust data processing techniques are needed to provide accurate and precise measurements for complex samples and non-ideal conditions. Here we present an approach to address these challenges using a transform, called the exit wave power cepstrum (EWPC), inspired by cepstral analysis in audio signal processing. The EWPC transforms NBED patterns into real-space patterns with sharp peaks corresponding to inter-atomic spacings. We describe a simple analytical model for interpretation of these patterns that cleanly decouples lattice information from the intensity variations in NBED patterns caused by tilt and thickness. With tracking the inter-atomic spacing peaks in EWPC patterns, strain mapping is demonstrated for two practical applications: mapping of ferroelectric domains in epitaxially strained PbTiO 3 films and mapping of strain profiles in arbitrarily oriented core-shell Pt-Co nanoparticle fuel-cell catalysts. The EWPC transform enables lattice structure measurement at sub-pm precision and sub-nm resolution that is robust to small sample mistilts and random orientations.

42 ENGINEERING↗