Search NASA⌕ Search

SEARCH · Search NASA

Results for “3D molecular generation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

608 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Carbon in GaN as a nonradiative recombination center

Trap-assisted nonradiative recombination has been shown to limit the efficiency of optoelectronic devices. While substitutional carbon (⁠C N ) has been suggested to be a nonradiative recombination center in GaN devices, a complete recombination cycle including the two charge-state transition levels has not been previously described. In this work, we investigate the trap-assisted recombination process due to C N in GaN, including multiphonon emission, radiative recombination, trap-assisted Auger–Meitner (TAAM) recombination as well as thermal emission of holes. Our study shows the key role of TAAM processes at the high carrier densities relevant for devices. We also reveal the carrier-density regimes where thermal emission and radiative recombination are expected to play an observable role. Our results highlight that carbon concentrations exceeding ~10 17 cm −3 can have a noticeable impact on device efficiency, not just in GaN active layers but also in InGaN and AlGaN. Furthermore, our comprehensive formalism not only offers detailed results for carbon but also provides a general framework for assessing the multiple processes that participate in trap-assisted recombination in semiconductors.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Robustness of inertial fusion energy relevant implosions to low-mode asymmetries

Inertial confinement fusion implosions for power production need to be robust. Degradation sources need to be understood and considered for an economic power plant. In this work, the impact of low-mode asymmetries on yield is studied using 2D radiation hydrodynamics simulations for inertial fusion energy relevant implosions. First, a high-gain indirectly driven capsule design is developed. This design is subsequently degraded with low-mode drive asymmetries. The results show that yield is constant with increasing amounts of asymmetry until a cliff is reached where the yield quickly drops below ignition. Robustness arises because the degraded hotspot still has enough time to get to ignition before capsule decompression. This robustness occurs even though the asymmetry couples less energy to the hotspot and causes decompression to occur sooner. The robustness is linked to the generalized Lawson parameter, χ⁠. The value of χ steadily decreases with increasing asymmetry. Once χ is close to one, the hotspot is no longer able to ignite before the capsule decompresses. A simple piston model is used to predict where the robustness cliff is for any design. The trade-off between yield and robustness is also demonstrated.

Physics - Plasma physics↗
DOE OSTI2026

High-resolution modeling of indoor radon exposure with uncertainty quantification in Utah

Indoor radon accounts for 37% of population-level exposure to ionizing radiation in the United States. However, radon metrics are typically reported at coarse spatial scales, potentially obscuring meaningful local variation. We developed a high-resolution modeling framework to estimate indoor radon concentrations across Utah while explicitly quantifying predictive uncertainty. A total of 19,497 residential radon measurements collected between 2006 and 2017 were combined with environmental and housing characteristics and analyzed using a geospatial neural network that accommodates spatial dependence and nonlinear associations. Predictions were generated on a uniform hexagonal grid at 0.73 km2 resolution (H3 level 8). Out-of-sample predictions aggregated to the H3 level 8 grid showed good agreement with observed concentrations (Pearson r=0.64), while household-level predictions exhibited more moderate agreement (r=0.45). The model produced well-calibrated uncertainty estimates, with 24.1% of held-out observations exceeding the predicted 75th-percentile threshold. Maps of predicted radon concentrations and the probability of exceeding the U.S. EPA action level of 148 Bq/m3 (4 pCi/L) revealed substantial fine-scale spatial heterogeneity that was not apparent in conventional coarse-resolution summaries, with greater local variability observed in densely monitored urban counties than in sparsely sampled regions. High-resolution radon models that explicitly quantify uncertainty provide a useful framework for characterizing the spatial distribution of indoor radon and identifying areas of elevated exceedance risk. These findings highlight the value of fine-scale monitoring data and uncertainty-aware modeling approaches for radon exposure assessment, environmental risk characterization, and radon-related health research.

Wu, Yunhan [ORNL] (ORCID:0000000178842994)↗
DOE OSTI2026

Two-dimensional non-equilibrium melting of charged colloids

Thermodynamic two-dimensional melting has been extensively studied in experiments and simulations, and is well predicted by theory. For systems in equilibrium, this transition is well described by the Kosterlitz–Thouless–Halperin–Nelson–Young theory, where melting is directly linked to the unbinding of topological defects. For driven, non-equilibrium melting and other non-equilibrium phase transitions, the picture is less clear. Here, in this work, we study the two-dimensional melting of a crystal of charged colloids. By randomly replacing some charged colloids with magnetic colloids, we can melt our system by rotating a fraction of the particles to create non-equilibrium, hydrodynamic random flows and local stresses. We can also melt it thermally by changing the particle number density. We find that an effective temperature approach cannot explain the results of our driven system. Rather, in both experiments and simulations, we observe that plotting the hexatic order parameter and the hexatic correlation’s exponent versus the density of disclinations and dislocations, respectively, yields universal curves. This implies that in our systems, two-dimensional melting depends directly on the density of topological defects and is independent of whether thermal or non-equilibrium forces generate them.

critical phenomena↗
DOE OSTI2023

Hybrid Data‐Driven Discovery of High‐Performance Silver Selenide‐Based Thermoelectric Composites

Optimizing material compositions often enhances thermoelectric performances. However, the large selection of possible base elements and dopants results in a vast composition design space that is too large to systematically search using solely domain knowledge. To address this challenge, a hybrid data-driven strategy that integrates Bayesian optimization (BO) and Gaussian process regression (GPR) is proposed to optimize the composition of five elements (Ag, Se, S, Cu, and Te) in AgSe-based thermoelectric materials. Data is collected from the literature to provide prior knowledge for the initial GPR model, which is updated by actively collected experimental data during the iteration between BO and experiments. Within seven iterations, the optimized AgSe-based materials prepared using a simple high-throughput ink mixing and blade coating method deliver a high power factor of 2100 µW m −1 K −2 , which is a 75% improvement from the baseline composite (nominal composition of Ag 2 Se 1 ). In conclusion, the success of this study provides opportunities to generalize the demonstrated active machine learning technique to accelerate the development and optimization of a wide range of material systems with reduced experimental trials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Specific Bacterial Taxa and Their Metabolite, DHPS, May Be Linked to Gut Dyshomeostasis in Patients with Alzheimer’s Disease, Parkinson’s Disease, and Amyotrophic Lateral Sclerosis

Background: Neurodegenerative diseases (NDDs) are multifactorial disorders frequently associated with gut dysbiosis, oxidative stress, and inflammation; however, the pathophysiological mechanisms remain poorly understood. Methods: Using untargeted mass spectrometry-based metabolomics and 16S sequencing of human stool, we investigated bacterial and metabolic dyshomeostasis in the gut microbiome associated with early disease stages across three NDDs—amyotrophic lateral sclerosis (ALS), Alzheimer’s disease (AD), Parkinson’s disease (PD)—and healthy controls (HC). Results: We discovered a previously unrecognized link between a microbial-derived metabolite with an unknown role in human physiology, 2,3-dihydroxypropane-1-sulfonate (DHPS), and gut dysbiosis in NDDs. DHPS was downregulated in AD, ALS, and PD, while bacteria involved in DHPS metabolism, Eubacterium and Desulfovibrio, were increased in all disease cohorts. Additionally, select taxa within the Clostridia class had strong negative correlations to DHPS, suggesting a potential role in DHPS metabolism. A catabolic product of DHPS is hydrogen sulfide, and when in excess, it is known to promote inflammation, oxidative stress, mitochondrial damage, and gut dysbiosis, known hallmarks of NDDs. Conclusions: These findings suggest that cryptic sulfur metabolism via DHPS is a potential missing link in our current understanding of gut dysbiosis associated with NDD onset and progression. As this was a hypothesis generating study, more work is needed to elucidate the role of DHPS in gut dysbiosis and neurodegenerative diseases.

Nutrition & Dietetics↗
DOE OSTI2026

MARVEL Reactor Digital Engineering Developments

The MARVEL reactor project has served to introduce a new generation of engineers to the processes required to transform a reactor design from simply an idea on paper into what will be an approved, constructed, and operational nuclear power system. Much as there have been advances in materials, analysis, and evaluation methodologies over the 50 years since the last reactor was built at INL, so too has the technology for managing the engineering process itself advanced. Digital Engineering tools and methods provide improved coordination between previously siloed engineering disciplines, reduced burdens of non-value-added data transcription processes and bring forward insights and improvements that might otherwise fall later in the design stage, where changes are much more costly. While the tools and techniques to support the full digital engineering vision are not yet complete, the MARVEL design processes provide valuable demonstrations and validations of key aspects and illuminate further areas for implementation by subsequent projects.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2026

Collapse of magnetized white dwarfs as site of heavy-element formation and kilonova signal

We present the first end-to-end calculation connecting the accretion-induced collapse (AIC) of a magnetized, rapidly rotating white dwarf to observable kilonova signatures, combining two-dimensional (2D) general-relativistic neutrino-magnetohydrodynamic simulations, followed by radiation hydrodynamics with in-situ nuclear network and 2D Monte Carlo radiative transfer with spatially resolved heating rates. Unlike all previous unmagnetized AIC models – which predicted proton-rich, $^{56}$Ni-dominated ejecta – strong magnetic fields eject ${\approx }\, 0.2\, \mathrm{ M}_\odot$ of neutron-rich material ($\langle Y_e \rangle \sim 0.24$) on dynamical time-scales, before neutrino irradiation can raise the electron fraction, enabling strong r-process nucleosynthesis up to and beyond the third peak. The resulting kilonova is lanthanide-rich ($X_{\rm lan} \approx 8~{{\ \rm per\ cent}}$) and dominated by near-infrared emission. We compute synthetic light curves in the Large Synoptic Survey Telescope and J ames Webb Space Telescope bands and find striking agreement, without parameter tuning, between the observations of AT 2023vfi/GRB 230307A and our broadband light curves for polar viewing angles. These results establish magnetized AIC as a viable channel for heavy r-process element production and a compelling progenitor candidate for long-duration gamma-ray bursts with kilonova signatures.

MHD↗
DOE OSTI2023

Host galaxies of ultra-strong Mg ii absorbers at z ∼ 0.7

ABSTRACT We report spectroscopic identification of the host galaxies of 18 ultra-strong Mg ii systems (USMg ii) at 0.6 ≤ z ≤ 0.8. We created the largest sample by merging these with 20 host galaxies from our previous survey within 0.4 ≤ z ≤ 0.6. Using this sample, we confirm that the measured impact parameters ($\rm 6.3\leqslant D[kpc] \leqslant 120$ with a median of 19 kpc) are much larger than expected, and the USMg ii host galaxies do not follow the canonical $\rm {\it W}_{2796}-{\it D}$ anticorrelation. We show that the presence and significance of this anticorrelation may depend on the sample selection. The $\rm {\it W}_{2796}-{\it D}$ anticorrelation seen for the general Mg ii absorbers show a mild evolution at low $\rm W_{2796}$ end over the redshift range 0.4 ≤ z ≤ 1.5 with an increase of the impact parameters. Compared to the host galaxies of normal Mg ii absorbers, USMg ii host galaxies are brighter and more massive for a given impact parameter. While the USMg ii systems preferentially pick star-forming galaxies, they exhibit slightly lower ongoing star-forming rates compared to main sequence galaxies with the same stellar mass, suggesting a transition from star-forming to quiescent states. For a limiting magnitude of mr < 23.6, at least 29 per cent of the USMg ii host galaxies are isolated, and the width of the Mg ii absorption in these cases may originate from gas flows (infall/outflow) in isolated haloes of massive star forming but not starbursting galaxies. We associate more than one galaxy with the absorber in $\ge 21~{{\ \rm per\ cent}}$ cases, where interactions may cause wide velocity spread.

Astronomy & Astrophysics↗
DOE OSTI2026

Progress and Perspectives: Zirconium Electrodeposition from Different Electrolytes

Zirconium (Zr) possesses outstanding properties, including exceptional chemical resistance and a high melting point, and is therefore desirable for use in a wide variety of challenging environments, such as in nuclear reactors and the chemical processing industry. To minimize the amount of Zr required for any given application, developing methods for generating metallic Zr coatings is highly advantageous. Owing to Zr’s highly negative reduction potential, electrodeposition in traditional solvents at near ambient temperatures remains challenging and thus not well understood. Due to the extreme conditions required to deposit this metal, extensive work has been conducted in molten salt electrolytes, however the broad applicability of this methodology is limited due to its corrosivity. The primary focus of this article is to present an overview of Zr’s electrochemical behavior and to consolidate the efforts of researchers in exploring electrodeposition techniques for Zr involving aqueous, organic, ionic liquid, deep eutectic, and molten salt solvents. With this information, we highlight trends across solvent systems and opportunities for future research.

42 ENGINEERING↗
DOE OSTI2026

Knowledge-guided learning with curated prior genetic biomarkers for robust model interpretation

Abstract Motivation Knowledge-guided learning offers effective and robust model training strategies in data-scarce settings by incorporating established domain knowledge, thereby enhancing generalization, robustness, and interpretability. By contrast, conventional deep learning approaches rely purely on data-driven learning, which can limit robust model interpretability, particularly in high-dimensional settings with limited size samples. In computational biology, knowledge-guided learning has primarily leveraged network- and structural-based knowledge, leading to biologically interpretable representations and enhanced predictive performance compared to conventional approaches. However, curated biomarkers, one of the most accessible forms of biological knowledge, remain largely unexplored within knowledge-guided paradigms. Results In this study, we propose a model-agnostic training paradigm, Biomarker-driven Explainable Prior-guided Learning (BioExPL), that can be applied to any neural networks that incorporates curated prior knowledge. BioExPL enforces neural networks to reflect curated biomarker priors in their latent representations through a novel knowledge-alignment loss. BioExPL consistently demonstrated significantly improved predictive performance and enhanced model interpretability with minimized computational overhead in simulation studies and intensive experiments on multiple cancer datasets. BioExPL not only integrates prior curated knowledge into the model but also accurately identifies unknown associated signals additionally. BioExPL is model-agnostic and domain-independent, enabling its integration into diverse neural network architectures. Availability and implementation The open-source is publicly available at: https://github.com/datax-lab/BioExPL.

Baek, Beomsu [Department of Computer Science, Univ↗
DOE OSTI2026

Anode-less Solid-State Li–S Batteries Enabled by Fe-Stabilized Polysulfides

Anode-less solid-state lithium-sulfur batteries (SSLSBs) with lithium sulfide (Li 2 S) as the cathode promise a high energy density and ease of manufacturing. However, Li 2 S is plagued by poor conductivity, sluggish activation kinetics, and a poor cycle life. Here, in this study, we report an FeCl 3 -activated Li 2 S (FLS) cathode with solid-state polysulfide intermediates generated through a redox reaction between FeCl 3 and Li 2 S. This strategy is shown to boost the electrical conductivity of Li 2 S by 7 orders of magnitude and lower the activation barrier. During cycling, Fe plays a significant role in stabilizing the highly active polysulfide species, contributing to the exceptional electrochemical performance. The FLS cathode achieves 80% capacity retention over 500 cycles with >99% Li 2 S utilization. Furthermore, a Li-metal-free (anode-less) full cell retained over 80% of its initial capacity after 240 cycles. This work underscores the promise of leveraging Fe-stabilized polysulfides in enabling high-energy, long-lasting, solid-state Li-S batteries.

25 ENERGY STORAGE↗
DOE OSTI2026

Direct Measurement of Cl − Activity in Metal Chloride Molten Salts using a Cl 2 /Cl − Electrode

Molten metal chloride salts are promising candidates for advanced heat transfer fluids in generation IV nuclear reactors and beyond. The activity of the chloride ion in the salt has a large influence on the redox characteristics of the corresponding molten salt. There exists a knowledge gap for the direct measurement of chlorobasicity (Lewis basicity) in molten-salt mixtures. Here, the focus of this work was to develop a Cl 2 /Cl − electrode for the direct measurement of chloride activity in molten metal-chloride salt mixtures. The LiCl–KCl eutectic system was utilized as the reference melt to determine the change in chloride ion activity as increasing concentrations of MgCl 2 are added to the LiCl–KCl eutectic working electrode. The results of the measurements indicated a reduction in chloride ion activity as the concentration of magnesium chloride increased, consistent with the complexation of free chlorides by Lewis acidic magnesium cationic species. The Temkin model was used to estimate the thermodynamic properties of MgCl 4 2− complex.

Chloride↗
DOE OSTI2026

Joint scheduling of energy, fast and primary frequency response reserves in integrated transmission–distribution networks

Inverter-based distributed energy resources (DERs) connected to distribution networks (DNs) can provide fast frequency support, but their reserve deliverability depends on feeder constraints and differs from synchronous primary frequency response (PFR). Existing transmission–distribution coordination studies usually treat reserve generically or neglect feeder-level feasibility, while frequency-security scheduling studies rarely represent distribution feeders explicitly. This paper develops a bi-level day-ahead scheduling framework for integrated transmission–distribution networks that jointly clears energy, transmission-side PFR, and distribution-side fast frequency response (FFR) under exogenous hourly inertia and largest-loss inputs from an external unit commitment (UC) schedule. The transmission problem is modeled with DC-optimal power flow (OPF) and closed-form second-order cone (SOC) frequency-security constraints, whereas each DN is represented by a reserve-aware branch-flow AC-OPF so that scheduled fast reserves remain deliverable during activation. The bi-level problem is reformulated through Karush–Kuhn–Tucker (KKT) conditions into a mixed-integer SOC program, and a penalty term is used to tighten the distribution-network relaxation. In the reduced test system, lower exogenous inertia increased the required primary response from 179.64 MW to 191.08 MW, distribution-side fast response reduced total frequency-response procurement by up to 4.9%, and neglecting distribution constraints overstated the combined distribution-side energy and reserve award by up to 18%. In the expanded study, the largest case was solved in 2.02 s with a 0.00% optimality gap. Time-domain simulations kept the frequency nadir above 59.0 Hz in all tested hours. These results demonstrate the value of fast-response modeling and distribution-feasible reserve delivery in coordinated market clearing.

Noh, Seung-Gil↗
DOE OSTI2025

Electrochemical Behavior of Cerium at an Indium Tin-Doped Oxide Electrode in Acidic Media

The redox behavior and speciation of cerium at mesoporous thin films composed of nanoparticles of indium tin-doped oxide (nITO) electrodes were characterized in pH 4.8, 0.1 M acetate buffer and both 0.1 and 1 M HNO 3 using electrochemical techniques and X-ray photoelectron spectroscopy. Anodic deposition of ceria species from Ce(III) to the nITO electrode was achieved under all solvent conditions via spontaneous condensation of electrochemically generated ceric hydroxide species. In 1 M nitric acid, the rate of CeO 2 dissolution is on the same order as CeO 2 deposition, resulting in negligible amounts of CeO 2 electrodeposited at the nITO surface. The cathodic stripping of CeO 2 from the nITO substrate deposited in 0.1 M nitric acid or pH 4.8 acetate buffer follows a 2-step process where Ce(IV)-oxide is initially reduced to an unstable Ce(III)-oxide species that rapidly undergoes acid catalyzed dissolution to yield soluble Ce(III) (aq) . These findings provide a foundation for the pH and anodic potential controlled deposition of CeO 2 thin films to ITO substrates, which can aid in the development of materials composed of ceria. As a result, they can also be used to infer likely analogous actinide redox behavior and speciation at these electrodes.

Cerium↗
DOE OSTI2026

Conditional diffusion machine-learning framework for mapping valence electron distribution from convergent beam electron diffraction

Quantitative convergent beam electron diffraction (CBED) enables determination of aspherical valence electron distributions through refinement of low-order structure factors, which are highly sensitive to chemical bonding and charge density variations. However, conventional quantitative CBED (QCBED) requires solving a highly nonlinear inverse problem with many coupled parameters, and computationally intensive dynamical diffraction calculations, making it time-consuming and difficult to apply to complex systems. More broadly, reconstructing charge density and orbital electron distribution from diffraction data has long been a central challenge in both x-ray and electron crystallography. Here, in this study, we introduce an artificial-intelligence (AI)-based framework that replaces traditional refinement with a data-driven inverse solver. Using a large synthetic CBED dataset generated by Bloch-wave simulations, we train a conditional diffusion model to directly infer crystal structural parameters and multipole density formalism parameters, and hence valence electron distributions, from CBED patterns alone. By learning from forward simulations across realistic parameter space, the model effectively solves the inverse problem. Compared with direct regression approaches, the diffusion-based framework provides posterior parameter distributions for rigorous uncertainty quantification while preserving quantitative fidelity and reducing analysis time by orders of magnitude. By eliminating the need for external single-crystal x-ray diffraction data and complex nonlinear refinement, this approach enables practical, high-throughput, and in situ quantitative CBED, enabling real-time mapping of valence electron distributions and their correlation with functional responses in quantum and energy materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Preliminary Evaluation of Joint Electricity-Hydrogen Concept of Operations

An initial thermal power dispatch (TPD) concept of operations was evaluated that couples a nuclear power plant to a nearby hydrogen production plant. GSE Systems’ generic pressurized water reactor full-scope simulator was modified with a TPD model comprised of a thermal power extraction and delivery system. A prototype human-system interface (HSI) was developed to interact with the TPD model and allow participants to execute the basic operating scenarios for normal operations. Four retired operators performed the evaluation, and due to COVID-19 travel restrictions, the original in-person experimental design was restructured to support a remote participator evaluation using a web meeting platform. Data from operator feedback, observations from the research team, and quantitative survey responses revealed that the initial TPD concept of operations is feasible. The operators were comfortable with the engineered system and HSI and could manage it without adverse impacts to reactor power, plant safety, or equipment. Findings are discussed in terms of both the TPD system design and HSI performance.

human factors↗
DOE OSTI2024

Thermally unstable roosts influence winter torpor patterns in a threatened bat species

Abstract Many hibernating bats in thermally stable, subterranean roosts have experienced precipitous declines from white-nose syndrome (WNS). However, some WNS-affected species also use thermally unstable roosts during winter that may impact their torpor patterns and WNS susceptibility. From November to March 2017–19, we used temperature-sensitive transmitters to document winter torpor patterns of tricolored bats (Perimyotis subflavus) using thermally unstable roosts in the upper Coastal Plain of South Carolina. Daily mean roost temperature was 12.9 ± 4.9°C SD in bridges and 11.0 ± 4.6°C in accessible cavities with daily fluctuations of 4.8 ± 2°C in bridges and 4.0 ± 1.9°C in accessible cavities and maximum fluctuations of 13.8 and 10.5°C, respectively. Mean torpor bout duration was 2.7 ± 2.8 days and was negatively related to ambient temperature and positively related to precipitation. Bats maintained non-random arousal patterns focused near dusk and were active on 33.6% of tracked days. Fifty-one percent of arousals contained passive rewarming. Normothermic bout duration, general activity and activity away from the roost were positively related to ambient temperature, and activity away from the roost was negatively related to barometric pressure. Our results suggest ambient weather conditions influence winter torpor patterns of tricolored bats using thermally unstable roosts. Short torpor bout durations and potential nighttime foraging during winter by tricolored bats in thermally unstable roosts contrasts with behaviors of tricolored bats in thermally stable roosts. Therefore, tricolored bat using thermally unstable roosts may be less susceptible to WNS. More broadly, these results highlight the importance of understanding the effect of roost thermal stability on winter torpor patterns and the physiological flexibility of broadly distributed hibernating species.

Biodiversity & Conservation↗