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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Ultrafast Optical Nanoscopy of Carrier Dynamics in Silicon Nanowires

Carrier distribution and dynamics in semiconductor materials often govern their physical properties that are critical to functionalities and performance in industrial applications. The continued miniaturization of electronic and photonic devices calls for tools to probe carrier behavior in semiconductors simultaneously at the picosecond time and nanometer length scales. Here, in this paper, we report pump–probe optical nanoscopy in the visible-near-infrared spectral region to characterize the carrier dynamics in silicon nanostructures. By coupling experiments with the point-dipole model, we resolve the size-dependent photoexcited carrier lifetime in individual silicon nanowires. We further demonstrate local carrier decay time mapping in silicon nanostructures with a sub-50 nm spatial resolution. Our study enables the nanoimaging of ultrafast carrier kinetics, which will find promising applications in the future design of a broad range of electronic, photonic, and optoelectronic devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

In-Situ Atomic-Scale Revelation of Amorphous Metallic Iron Formation during Hydrogen-Driven Reduction of Iron Oxides

The transition to hydrogen as a green reductant in metal production is critical for decarbonizing the metallurgical industry, yet atomic-scale mechanisms governing reduction pathways and phase evolution remain unresolved. Using in-situ environmental transmission electron microscopy, we identify a hidden pathway that reveals dynamic formation of amorphous metallic iron (Fe) during the hydrogen-driven reduction of ferrous oxides of Fe 3 O 4 and FeO. Real-time imaging uncovers three coexisting transformation routes: (i) Fe 3 O 4 → FeO, (ii) Fe 3 O 4 → amorphous Fe, and (iii) FeO → amorphous Fe. The resulting amorphous Fe exhibits fluid-like mobility, enabling its rapid aggregation and crystallization into core-shell nanostructures, with a crystalline core enveloped by an amorphous shell. Complementary ab initio molecular dynamics simulations trace the amorphous Fe formation to interfacial strain at the metal/oxide interfaces, where large lattice mismatches destabilize the metal lattice during initial metallization. This interplay between thermodynamics and kinetics governs phase evolution: thermodynamics favors a self-limiting amorphous Fe overlayer, while rapid oxide reduction kinetics drives amorphous overgrowth. Our findings demonstrate that amorphous intermediates bypass rate-limiting crystalline steps, providing mechanistic insights to optimize H 2 -based processes for sustainable steelmaking. In conclusion, these insights bridge the gap between macroscopic process engineering and atomic-scale dynamics, with broader implications for catalysis and nanostructured material synthesis, where oxide reduction pathways critically shape functional phases and microstructures.

36 MATERIALS SCIENCE↗
DOE OSTI2022

van der Waals Semiconductor Empowered Vertical Color Sensor

We report biomimetic artificial vision is receiving significant attention nowadays, particularly for the development of neuromorphic electronic devices, artificial intelligence, and microrobotics. Nevertheless, color recognition, the most critical vision function, is missed in the current research due to the difficulty of downscaling of the prevailing color sensing devices. Conventional color sensors typically adopt a lateral color sensing channel layout and consume a large amount of physical space, whereas compact designs suffer from an unsatisfactory color detection accuracy. In this work, we report a van der Waals semiconductor-empowered vertical color sensing structure with the emphasis on compact device profile and precise color recognition capability. More attractive, we endow color sensor hardware with the function of chromatic aberration correction, which can simplify the design of an optical lens system and, in turn, further downscales the artificial vision systems. Also, the dimension of a multiple pixel prototype device in our study confirms the scalability and practical potentials of our developed device architecture toward the above applications.

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

Improving the Quasi‐Biennial Oscillation via a Surrogate‐Accelerated Multi‐Objective Optimization

Accurate simulation of the quasi-biennial oscillation (QBO) is challenging due to uncertainties in representing convectively generated gravity waves. We develop an end-to-end uncertainty quantification workflow that calibrates these gravity wave processes in E3SM for a realistic QBO. Central to our approach is a domain knowledge-informed, compressed representation of high-dimensional spatio-temporal wind fields. By employing a parsimonious statistical model that learns the fundamental frequency from complex observations, we extract interpretable and physically meaningful quantities capturing key attributes. Building on this, we train a probabilistic surrogate model that approximates the fundamental characteristics of the QBO as functions of critical physics parameters governing gravity wave generation. Leveraging the Karhunen–Loève decomposition, our surrogate efficiently represents these characteristics as a set of orthogonal features, capturing cross-correlations among multiple physics quantities evaluated at different pressure levels and enabling rapid surrogate-based inference at a fraction of the computational cost of full-scale simulations. Finally, we analyze the inverse problem using a multi-objective approach. Our study reveals a tension between amplitude and period that constrains the QBO representation, precluding a single optimal solution. To navigate this, we quantify the bi-criteria trade-off and generate a set of Pareto optimal parameter values that balance the conflicting objectives. This integrated workflow improves the fidelity of QBO simulations and offers a versatile template for uncertainty quantification in complex geophysical models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Depinning transition of a domain wall in ferromagnetic films

Here, we report first principle numerical study of domain wall (DW) depinning in two-dimensional magnetic film, which is modeled by 2D random-field Ising system with the dipole-dipole interaction. We observe non-conventional activation-type motion of DW and reveal the fractal structure of DW near the depinning transition. We determine scaling functions describing critical dynamics near the transition and obtain universal exponents establishing connection between thermal softening of pinning potential and critical dynamics. In addition, we observe that tuning the strength of the dipole-dipole interaction switches DW dynamics between two different universality classes, corresponding to two distinct dynamic regimes characterized by non-Arrhenius and conventional Arrhenius-type DW motions.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Topology of tokamak plasma equilibria with toroidal current reversal

Some general principles about scalar functions with critical points are used to rigorously ascertain that magnetic equilibria with both toroidal current reversal and nested magnetic surfaces are atypical solutions and highly unstable to arbitrary perturbations of boundary conditions and other parameters. The cause for such is shown to lie in the condition of nested magnetic surfaces and not in the possibility of current reversal and consequent vanishing of the poloidal field inside the plasma. Rather than supporting the claim that instability against experimentally driven perturbations forbids configurations with toroidal current reversal, it is argued that these can be attained if an axisymmetric island system is allowed for in order to break the condition of nested magnetic surfaces. A number of results previously reported in the literature are discussed and reinterpreted under the proposed framework, providing some physical insight on the nature of equilibria with toroidal current reversal.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Alkaline earth stannates: The next silicon?

Semiconductor materials are being used in an increasingly diverse array of applications, with new device concepts being proposed each year for solar cells, flat-panel displays, sensors, memory, and spin transport. This rapid progress of invention outpaces the development of new semiconductor materials with the required properties and performance. In many applications, high carrier mobility at room temperature is required in addition to specific functional properties critical to the device concept. We review recent developments on high mobility stannate perovskite oxide materials and devices.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Structural and dynamical description of the enzymatic reaction of a phosphohexomutase

Enzymes are known to adopt various conformations at different points along their catalytic cycles. Here, we present a comprehensive analysis of 15 isomorphous, high resolution crystal structures of the enzyme phosphoglucomutase from the bacterium Xanthomonas citri. The protein was captured in distinct states critical to function, including enzyme-substrate, enzyme-product, and enzyme-intermediate complexes. Key residues in ligand recognition and regions undergoing conformational change are identified and correlated with the various steps of the catalytic reaction. In addition, we use principal component analysis to examine various subsets of these structures with two goals: (1) identifying sites of conformational heterogeneity through a comparison of room temperature and cryogenic structures of the apo-enzyme and (2) a priori clustering of the enzyme-ligand complexes into functionally related groups, showing sensitivity of this method to structural features difficult to detect by traditional methods. This study captures, in a single system, the structural basis of diverse substrate recognition, the subtle impact of covalent modification, and the role of ligand-induced conformational change in this representative enzyme of the α-D-phosphohexomutase superfamily.

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

Novel technologies for emission reduction complement conservation agriculture to achieve negative emissions from row-crop production

Plants remove carbon dioxide from the atmosphere through photosynthesis. Because agriculture’s productivity is based on this process, a combination of technologies to reduce emissions and enhance soil carbon storage can allow this sector to achieve net negative emissions while maintaining high productivity. Unfortunately, current row-crop agricultural practice generates about 5% of greenhouse gas emissions in the United States and European Union. Here, to reduce these emissions, significant effort has been focused on changing farm management practices to maximize soil carbon. In contrast, the potential to reduce emissions has largely been neglected. Through a combination of innovations in digital agriculture, crop and microbial genetics, and electrification, we estimate that a 71% (1,744 kg CO 2 e/ha) reduction in greenhouse gas emissions from row crop agriculture is possible within the next 15 y. Importantly, emission reduction can lower the barrier to broad adoption by proceeding through multiple stages with meaningful improvements that gradually facilitate the transition to net negative practices. Emerging voluntary and regulatory ecosystems services markets will incentivize progress along this transition pathway and guide public and private investments toward technology development. In the difficult quest for net negative emissions, all tools, including emission reduction and soil carbon storage, must be developed to allow agriculture to maintain its critical societal function of provisioning society while, at the same time, generating environmental benefits.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

NTRC regulates CP12 to activate Calvin–Benson cycle during cold acclimation

NADPH-dependent thioredoxin reductase C (NTRC) is a chloroplast redox regulator in algae and plants. Here, we used site-specific mutation analyses of the thioredoxin domain active site of NTRC in the green alga Chlamydomonas reinhardtii to show that NTRC mediates cold tolerance in a redox-dependent manner. By means of coimmunoprecipitation and mass spectrometry, a redox- and cold-dependent binding of the Calvin–Benson Cycle Protein 12 (CP12) to NTRC was identified. NTRC was subsequently demonstrated to directly reduce CP12 of C. reinhardtii as well as that of the vascular plant Arabidopsis thaliana in vitro. As a scaffold protein, CP12 joins the Calvin–Benson cycle enzymes phosphoribulokinase (PRK) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) to form an autoinhibitory supracomplex. Using size-exclusion chromatography, NTRC from both organisms was shown to control the integrity of this complex in vitro and thereby PRK and GAPDH activities in the cold. Thus, NTRC apparently reduces CP12, hence triggering the dissociation of the PRK/CP12/GAPDH complex in the cold. Like the ntrc::aphVIII mutant, CRISPR-based cp12::emx1 mutants also exhibited a redox-dependent cold phenotype. In addition, CP12 deletion resulted in robust decreases in both PRK and GAPDH protein levels implying a protein protection effect of CP12. Both CP12 functions are critical for preparing a repertoire of enzymes for rapid activation in response to environmental changes. This provides a crucial mechanism for cold acclimation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

MICROLENSING DISCOVERY OF A POPULATION OF VERY TIGHT, VERY LOW MASS BINARY BROWN DWARFS

Although many models have been proposed, the physical mechanisms responsible for the formation of low-mass brown dwarfs (BDs) are poorly understood. The multiplicity properties and minimum mass of the BD mass function provide critical empirical diagnostics of these mechanisms. We present the discovery via gravitational microlensing of two very low mass, very tight binary systems. These binaries have directly and precisely measured total system masses of 0.025 M{sub Sun} and 0.034 M{sub Sun }, and projected separations of 0.31 AU and 0.19 AU, making them the lowest-mass and tightest field BD binaries known. The discovery of a population of such binaries indicates that BD binaries can robustly form at least down to masses of {approx}0.02 M{sub Sun }. Future microlensing surveys will measure a mass-selected sample of BD binary systems, which can then be directly compared to similar samples of stellar binaries.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Generalizing the Gurson model using symbolic regression and transfer learning to relax inherent assumptions

Abstract To generate material models with fewer limiting assumptions while maintaining closed-form, interpretable solutions, we propose using genetic programming based symbolic regression (GPSR), a machine learning (ML) approach that describes data using free-form symbolic expressions. To maximize interpretability, we start from an analytical, derived material model, the Gurson model for porous ductile metals, and systematically relax inherent assumptions made in its derivation to understand each assumption’s contribution to the GPSR model forms. We incorporate transfer learning methods into the GPSR training process to increase GPSR efficiency and generate models that abide by known mechanics of the system. The results show that regularizing the GPSR fitness function is critical for generating physically valid models and illustrate how GPSR allows a high level of interpretability compared with other ML approaches. The method of systematic assumption relaxation allows the generation of models that address limiting assumptions found in the Gurson model, and the symbolic forms allow conjecture of decreased material strength due to void interaction and non-symmetric void shapes.

36 MATERIALS SCIENCE↗
DOE OSTI2020

2D-FFTLog: efficient computation of real-space covariance matrices for galaxy clustering and weak lensing

ABSTRACT Accurate covariance matrices for two-point functions are critical for inferring cosmological parameters in likelihood analyses of large-scale structure surveys. Among various approaches to obtaining the covariance, analytic computation is much faster and less noisy than estimation from data or simulations. However, the transform of covariances from Fourier space to real space involves integrals with two Bessel integrals, which are numerically slow and easily affected by numerical uncertainties. Inaccurate covariances may lead to significant errors in the inference of the cosmological parameters. In this paper, we introduce a 2D-FFTLog algorithm for efficient, accurate, and numerically stable computation of non-Gaussian real-space covariances for both 3D and projected statistics. The 2D-FFTLog algorithm is easily extended to perform real-space bin-averaging. We apply the algorithm to the covariances for galaxy clustering and weak lensing for a Dark Energy Survey Year 3-like and a Rubin Observatory’s Legacy Survey of Space and Time Year 1-like survey, and demonstrate that for both surveys, our algorithm can produce numerically stable angular bin-averaged covariances with the flat sky approximation, which are sufficiently accurate for inferring cosmological parameters. The code CosmoCov for computing the real-space covariances with or without the flat-sky approximation is released along with this paper.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Functional form of the superconducting critical temperature from machine learning

Predicting the critical temperature $T_c$ of new superconductors is a notoriously difficult task, even for electron-phonon paired superconductors, for which the theory is relatively well understood. Early attempts to obtain a simple $T_c$ formula consistent with strong-coupling theory, by McMillan and by Allen and Dynes, led to closed-form approximate relations between $T_c$ and various measures of the phonon spectrum and the electron-phonon interaction appearing in Eliashberg theory. Here we propose that these approaches can be improved with the use of machine-learning algorithms. As an initial test, we train a model for identifying low-dimensional descriptors using the $T_c$ < 10 K dataset by Allen and Dynes, and show that a simple analytical expression thus obtained improves upon the Allen-Dynes fit. Furthermore, the prediction for the recently discovered high-$T_c$ material H 3 S at high pressure is quite reasonable. Interestingly, $T_c$'s for more recently discovered superconducting systems with a more two-dimensional electron-phonon coupling, which do not follow Allen and Dynes's expression, also do not follow our analytic expression. Thus, this machine-learning approach appears to be a powerful method for highlighting the need for a new descriptor beyond those used by Allen and Dynes to describe their set of isotropic electron-phonon coupled superconductors. Finally, we argue that this machine-learning method, and its implied need for a descriptor characterizing Fermi-surface properties, represents a promising approach to superconductor materials discovery which may eventually replace the serendipitous discovery paradigm begun by Kamerlingh Onnes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Superfluid density in overdoped cuprates: Thin films versus bulk samples

Recent study of overdoped La 2–x Sr x CuO 4 cuprate superconductor thin films by Božovic et al. has revealed several unexpected findings, most notably the violation of the BCS description which was believed to adequately describe overdoped cuprates. In particular, it was found that the superfluid density in La 2–x Sr x CuO 4 films decreases on the overdoped side as a linear function of critical temperature T c , which was taken as evidence for the violation of Homes' law. Here we show explicitly that the law is indeed violated, and as the main reason for violation we find that the superfluid density in Božovic's films is suppressed more strongly than in bulk samples. Based on the existing literature data, we show that the superfluid density in bulk cuprate samples does not decrease with doping, but instead tends to saturate on the overdoped side. The result is also supported by our recent measurement of a heavily overdoped bulk La 2–x Sr x CuO 4 sample. Moreover, this saturation of superfluid density might not be limited to cuprates, as we find evidence for similar behavior in two pnictide superconductor families. We argue that quantum phase fluctuations play an important role in suppressing the superfluid density in thin films.

2-dimensional systems↗
DOE OSTI2025

Crystal structures of 40- and 71-substitution variants of hydroxynitrile lyase from rubber tree

Hydroxynitrile lyase fromHevea brasiliensis(HbHNL) and the esterase SABP2 fromNicotiana tabacumshare the α/β-hydrolase fold, a Ser–His–Asp catalytic triad and 44% sequence identity, yet catalyze different reactions. Prior studies showed that three active-site substitutions inHbHNL conferred weak esterase activity. To investigate how regions beyond the active site influence catalytic efficiency and active-site geometry, we engineeredHbHNL variants with increasing numbers of substitutions to match SABP2. Variant HNL16 has all amino acids within 6.5 Å of the active site identical to SABP2, HNL40 those within 10 Å and HNL71 those within 14 Å. HNL16 exhibited poor esterase activity, whereas both HNL40 and HNL71 showed efficient esterase catalysis, demonstrating that residues beyond the immediate active site are critical for functional conversion. X-ray structures of HNL40 and HNL71 reveal a progressive shift in backbone positions toward those of SABP2, with r.m.s.d. values of 0.51 Å (HNL40) and 0.41 Å (HNL71) over the C α atoms, and even smaller r.m.s.d.s within the active-site region. Both HNL40 and HNL71 show a restored oxyanion hole and an additional tunnel connecting the active site to the protein surface. This work demonstrates the essential role of distant, indirectly acting residues to catalysis in α/β-hydrolase enzymes.

Biochemistry & Molecular Biology↗