Search NASA⌕ Search

SEARCH · Search NASA

Results for “deep direct-use”

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.

985 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

NanoPSD: A software for automatic detection of Nano-Particle Shape Distribution in electron microscopy images

Accurate quantification of the size and morphology of nanoparticles from electron microscopy (EM) images is essential to understand growth mechanisms, surface reactivity, and functional behavior in nanoscale materials. Manual analysis remains slow, subjective, and difficult to reproduce in large datasets. We introduce NanoPSD (Nano-Particle Shape Distribution), an open-source and fully automated framework for quantitative particle detection and morphology analysis from EM images. NanoPSD integrates adaptive contrast enhancement, polarity-agnostic scale-bar detection, Optical Character Recognition (OCR)-based calibration, and classical segmentation via Otsu thresholding with morphological refinement. Particle contours are used to extract geometric descriptors, including equivalent circular diameter, aspect ratio, circularity, and solidity, enabling automated classification into spherical, rod-like, and aggregate morphologies. The framework supports both single-image and batch processing, generating publication-quality visualizations, LaTeX-ready tables, and structured comma-separated values (CSV) datasets. As a demonstration, we applied NanoPSD to plasma-synthesized nanoparticle samples diagnosed via transmission electron microscopy (TEM). The code produced statistically robust size and morphology distributions spanning a few to tens of nanometers with minimal user supervision. The pipeline demonstrates high reproducibility and scalability, processing large image collections with consistent calibration and output formatting. Its modular design enables seamless integration of future deep-learning-based segmentation models, providing a pathway toward intelligent, data-driven electron microscopy analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Improving Marine Energy Production Through Commercialization of a Low Cost, Drag-Reducing Slippery Coating (CRADA 679 Abstract)

Marine energy capture systems offer great promise for providing clean energy, but they operate in a challenging and dynamic environment and must be optimized to the highest extent possible. Computational studies predict that drag reduction on marine energy and blue economy systems will result in meaningful improvements in energy efficiency. Based on extensive coating experience, PNNL is proposing to bring to market a new drag-reducing coating called Superhydrophobic Lubricant-Infused Drag-Efficient Coating – SLIDE-Coat. PNNL has a deep knowledge base regarding this class of slippery coatings, and we have a group of enthusiastic industry partners who have committed to partnering, conducting field testing, and providing well over 50% cost share. In addition to validating the technology, the team will create a commercialization roadmap to ensure the commercial success of the technology after the government-sponsored two-year program is complete. The main technical goal is to design, manufacture, and experimentally validate a new coating that can reduce hydrodynamic skin friction drag by 20%. The main commercialization goal is to develop a roadmap that identifies activities needed to complete SLIDE-Coat’s development after the conclusion of this project. Year 1 will focus on adaptation and modification of the existing SLIC coating system to optimize drag reduction and assessment and quantification of drag reduction on relevant materials in a laboratory setting. Year 2 will focus on optimizing and demonstrating drag reduction with preferred coatings. The manufacturability, ease of application, adhesion to relevant surfaces, and consistency will be assessed. Quantification of drag reduction on prototype materials in a relevant marine field setting will be executed.

16 TIDAL AND WAVE POWER↗
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 OSTI2025

CO Adsorption on a Single‐Atom Catalyst Stably Embedded in Graphene

Abstract Confined single metal atoms in graphene‐based materials have proven to be excellent catalysts for several reactions and promising gas sensing systems. However, whether the chemical activity arises from the specific type of metal atom or is a direct consequence of the confinement itself remains unclear.

Chemistry↗
DOE OSTI2026

Distributed Tomographic Reconstruction with Quantization

Conventional tomographic reconstruction typically depends on centralized servers for both data storage and computation, leading to concerns about memory limitations and data privacy. Distributed reconstruction algorithms mitigate these issues by partitioning data across multiple nodes, reducing server load and enhancing privacy. However, these algorithms often encounter challenges related to memory constraints and communication overhead between nodes. In this paper, we introduce a decentralized Alternating Directions Method of Multipliers (ADMM) with configurable quantization. By distributing local objectives across nodes, our approach is highly scalable and can efficiently reconstruct images while adapting to available resources. To overcome communication bottlenecks, we propose two quantization techniques based on K-means clustering and JPEG compression. Numerical experiments with benchmark images illustrate the tradeoffs between communication efficiency, memory use, and reconstruction accuracy.

Miao, Runxuan↗
DOE OSTI2026

Explainable machine learning reveals that local structural motifs encode the thermodynamic state across the CuZr metallic glass-forming range

Metallic glasses derive their properties from the statistics of local atomic motifs rather than from long-range order, yet a quantitative, chemistry-specific link between motif populations and the underlying glassy state has remained elusive. In this work we combine large-scale molecular dynamics, Voronoi tessellation, deep neural networks, and SHapley Additive exPlanations (SHAP) to identify which local structural motifs define the glassy state of Cu—Zr metallic glasses. A dataset of 17,180 atomistic configurations spanning ten compositions (Cu 20 Zr 80 –Cu 80 Zr 20 ) and four quench rates (10 9 –10 12 K/s) is used to train a feed-forward neural network that regresses temperature across the 50–2000 K liquid–supercooled–glass range, achieving a mean absolute error of 19.89 K and R 2 = 0.9974, confirming that the local structural state is faithfully encoded in motif-level structure. SHAP analysis then reveals that a tightly coupled near-icosahedral family of motifs (coordination numbers (CN) 11–13, including the full icosahedron 001200 and its single-atom-perturbation sibling 10930) collectively encodes the thermodynamic state of the system across the full glass-forming range. The CN = 11–13 ordered members carry negative SHAP values at high populations, tracking the most deeply-quenched configurations, while 10930 shows the reversed signature consistent with its role as a soft-spot host whose population shrinks as the icosahedral network deepens. The analysis demonstrates that explainable machine learning can isolate the minimal motif vocabulary defining the glassy state and recovers the near-icosahedral building blocks previously identified by data-driven analyses of Cu—Zr. The approach provides a general, chemistry-specific route for characterizing the structural state of disordered materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Linking Community‐Climate Disequilibrium to Ecosystem Function

Turnover in species composition often lags behind the pace of climate change, resulting in mismatches between climate and communities. However, the impact of these community‐climate disequilibria on ecosystem functions is rarely considered, and current methods for measuring disequilibria assume that species ranges were, until recently, in equilibrium with climate. Here, in this work, we develop a simple theoretical model to address both of these problems by linking community‐climate disequilibrium with ecosystem functioning. We show how disequilibrium can impair functioning in the near‐term even when climate change is expected to enhance functioning in the long‐term. Responses are most likely to change over time in communities where turnover is slow, the impact of disequilibrium counteracts the direct effects of climate on ecosystem function, and pre‐existing disequilibrium is large. These findings emphasise the importance of precise and unbiased estimates of community‐climate disequilibria for improving ecological forecasts. By fitting our model to time series of both climate and ecosystem function from a metacommunity simulation, we show the potential for community‐climate disequilibrium to be inferred without direct knowledge about species' distributions or climatic tolerances. We end by outlining a research agenda to apply dynamic disequilibrium concepts and test novel hypotheses across diverse ecosystems.

climate change↗
DOE OSTI2026

Discovery of magnetic-field-tunable density modulations and spin tilting in a layered altermagnet

Altermagnets recently emerged as a new class of magnetic materials, arising from specific spin crystal symmetries. They exhibit a spin-polarized electronic band structure similar to ferromagnets, yet possess zero net magnetization, promising exotic properties. Here we study a layered triangular lattice altermagnet, cobalt-intercalated NbSe 2 using scanning tunneling microscopy and spectroscopy (STM/S). Spectroscopic-imaging STM and spin-polarized STM reveals emergent 2 a 0 tri-directional charge and spin density modulations on the selenium surface. Density functional theory simulations suggest these modulations reflect the underlying cobalt superstructure. We discover that an out-of-plane magnetic field tunes the modulation amplitudes and the electronic density-of-states in a manner dependent on the field direction and strength. This behavior is attributed to the field-induced tilting of cobalt spins, which can have profound implications on the electronic properties of the altermagnet. Our results provide atomic-scale insights to uncover a magnetic-field tunable altermagnetic band structure, highlight the importance of understanding spin canting in altermagnets.

condensed-matter physics↗
DOE OSTI2026

Single-Nucleon Transfer on Unstable 59 Cu Probes the NiCu Cycle in Astrophysical X-Ray Bursts

Recent models of the rapid proton (𝑟⁢𝑝) capture process indicate that a competition between the 59 Cu⁢(𝑝,𝛾) ⁢60 Zn and 59 Cu⁢(𝑝,𝛼) ⁢56 Ni reactions may result in the formation of a nickel-copper (NiCu) cycle that traps the flux of material between 56 Ni and 60 Zn . Here, in this work, we report the identification of 15 proton-unbound levels in 60 Zn , populated via 59 Cu⁢(𝑑,𝑛) transfer, which govern the rate of the 59 Cu⁢(𝑝,𝛾)⁢ 60 Zn reaction in XRBs. Precise excitation energies for levels in 60 Zn were obtained from observed 𝛾 decays, and spectroscopic factors were determined from angle-integrated cross sections. Incorporating these results into stellar-model calculations, we find that with experimentally constrained uncertainties a NiCu cycle in XRBs is indeed possible, though we limit its branching strength to less than 38%. While modest, such a branching has significant impact on the light curve, motivating further studies of the relevant rates. Our calculations also indicate that a significant NiCu cycle leads to an increase in the amount of odd-𝐴 nuclei in the burst ashes, which may affect Urca cooling processes in neutron star crusts.

direct reactions↗
DOE OSTI2026

Superconductivity in Ruddlesden–Popper nickelates: a review of recent progress, focusing on thin films

The discovery of superconductivity with Tc ∼ 80 K in the nickelate Ruddlesden-Popper bilayer La3Ni2O7 at high pressure has opened a new platform for unconventional superconductivity, followed by the subsequent observation of superconductivity in trilayer La4Ni3O10, also at high pressure. Remarkably, ambient-pressure superconductivity was also observed recently in La3Ni2O7 ultra-thin films when grown on substrates that provide compressive strain. This discovery significantly extends the type of experimental techniques that can be used in nickelates, previously limited due to the high-pressure constraint. Discussing the similarities and differences among these nickel oxides will provide new insights into understanding the mechanism of high-Tc superconductivity in correlated electron systems. In this paper, we review the experimental and theoretical progress on Ruddlesden–Popper nickelates, with emphasis on thin films, and discuss future perspectives and research directions.

Zhang, Yang [ORNL] (ORCID:0000000336235883)↗
DOE OSTI2023

Oxidation Chemistry of Bicarbonate and Peroxybicarbonate: Implications for Carbonate Management in Energy Storage

Carbonate formation presents a major challenge to energy storage applications based on low-temperature CO 2 electrolysis and recyclable metal–air batteries. While direct electrochemical oxidation of (bi)carbonate represents a straightforward route for carbonate management, knowledge of the feasibility and mechanisms of direct oxidation is presently lacking. Herein, we report the isolation and characterization of the bis(triphenylphosphine)iminium salts of bicarbonate and peroxybicarbonate, thus enabling the examination of their oxidation chemistry. Infrared spectroelectrochemistry combined with time-resolved infrared spectroscopy reveals that the photoinduced oxidation of HCO 3 – by an Ir(III) photoreagent results in the generation of the short-lived bicarbonate radical in less than 50 ns. The highly acidic bicarbonate radical undergoes proton transfer with HCO 3 – to furnish the carbonate radical anion and H 2 CO 3 , leading to the eventual release of CO 2 and H 2 O, thus accounting for the appearance of H 2 O and CO 2 in both electrochemical and photochemical oxidation experiments. Here, the back reaction of the carbonate radical subsequently oxidizes the Ir(II) photoreagent, leading to carbonate. In the absence of this back reaction, dimerization of the carbonate radical provides entry into peroxybicarbonate, which we show undergoes facile oxidation to O 2 and CO 2 . Together, the results reported identify tangible pathways for the design of catalysts for the management of carbonate in energy storage applications.

25 ENERGY STORAGE↗
DOE OSTI2026

Noncollinear spin order, field-induced transitions, and short-range correlations in Cu 4 ⁢SO 4 ⁢(OH) 6

We report a comprehensive study of spin-$\frac{1}{2}$ quantum magnet brochantite, Cu 4 ⁢SO 4 ⁢(OH) 6 , combining high-field thermodynamic measurements, polarized neutron diffraction, inelastic neutron scattering, and nuclear magnetic resonance spectroscopy. Using bulk magnetization and specific heat measurements we construct the magnetic 𝐻−𝑇 phase diagram for magnetic fields applied along main crystallographic directions up to 24.1 T. Polarized neutron diffraction reveals a noncollinear magnetic ground state confined to the 𝑎⁢𝑏 plane. A field-induced transition is observed for magnetic fields in the 𝑎⁢𝑏 plane whose critical field and character evolve continuously with field direction in the 𝑎⁢𝑏 plane. While the transition for 𝐻 ∥ 𝑏 might be a spin-flop-like transition, the one for 𝐻 ∥ 𝑎 resembles the short-range correlated state above 𝑇 N , suggesting a magnetic configuration related to the quasi-two-dimensional correlations in the 𝑏⁢𝑐 planes. The experimental results demonstrate that the ground-state and field-induced phases cannot be explained by a simple XXZ model with a single dominant exchange interaction and that weaker interchain and anisotropic interactions have to be taken into account. Our work establishes brochantite as a low-symmetry Cu-based quantum magnet with noncollinear order and complex field-induced behavior.

Prokhnenko, Oleksandr [Helmholtz-Zentrum Berlin (H↗
DOE OSTI2026

Visualizing Millisecond Atomic Dynamics of Nanocrystals in Liquid

Atomic structures of nanomaterials are inherently dynamic and continuously reshaped through interactions with chemical species and external stimuli. Such dynamics are further amplified as the size and dimensionality of nanomaterials decrease. Despite advances in analytical methods, it remains challenging to capture the structural dynamics of nanomaterials in reactive environments with both atomic spatial resolution and commensurate temporal resolution. Here, in this study, we directly visualize atomic-scale dynamics of gold (Au) nanocrystals in reactive liquid environments with millisecond-speed liquid-cell electron microscopy (EM) and deep-learning denoising. We uncover reversible fluctuations in the local crystallinity of Au nanocrystals dependent on the surrounding chemical environment. These transient fluctuations, driven by interactions at nanocrystal–liquid interfaces, critically influence the dissolution kinetics and grain boundary relaxation. By overcoming the spatiotemporal limitations in conventional liquid-cell EM, our findings provide insights into how transient nanoscale structures dictate the stability and reactivity of nanomaterials.

Kang, Sungsu [University of Chicago, IL (United St↗
DOE OSTI2025

Exact block encoding of imaginary time evolution with universal quantum neural networks

We develop a constructive approach to generate quantum neural networks capable of representing the exact thermal states of all many-body qubit Hamiltonians. The Trotter expansion of the imaginary time propagator is implemented through an exact block encoding by means of a unitary, restricted Boltzmann machine architecture. Marginalization over the hidden-layer neurons (auxiliary qubits) creates the nonunitary action on the visible layer. Then, we introduce a unitary deep Boltzmann machine architecture in which the hidden-layer qubits are allowed to couple laterally to other hidden qubits. We prove that this wave-function is closed under the action of the imaginary time propagator and, more generally, can represent the action of a universal set of quantum gate operations. We provide analytic expressions for the coefficients for both architectures, thus enabling exact network representations of thermal states without stochastic optimization of the network parameters. In the limit of large imaginary time, the yields the ground state of the system. The number of qubits grows linearly with the number of interactions and total imaginary time for a fixed interaction order. Both networks can be readily implemented on quantum hardware via midcircuit measurements of auxiliary qubits. If only one auxiliary qubit is measured and reset, the circuit depth scales linearly with imaginary time and number of interactions, while the width is constant. Alternatively, one can employ a number of auxiliary qubits linearly proportional to the number of interactions, and circuit depth grows linearly with imaginary time only. Every midcircuit measurement has a postselection success probability, and the overall success probability is equal to the product of the probabilities of the midcircuit measurements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Understanding Photovoltage Deficits in Electrochemically Grown Tin Sulfide (SnS) Thin-Film Photovoltaic Devices

Tin­(II) sulfide (SnS) is an earth-abundant semiconductor with a direct optical bandgap of ca. 1.1 eV, which makes it a promising absorber material for thin-film photovoltaic (PV) devices. However, existing devices have significant photovoltage deficits, which may be related to the anisotropic structure of the layered Herzenbergite SnS crystal structure. Here, we explore electrochemical deposition as a near room temperature path to oriented SnS crystal films on Mo and FTO substrates and employ vibrating Kelvin probe surface photovoltage (SPV) spectroscopy and J–V measurements to identify conversion losses in them. According to grazing-incidence X-ray diffraction and SEM, the SnS films consist of crystalline microplates with preferred orientation in the [111] and [001] directions. The bare SnS films produce only small and irreversible surface photovoltage signals, due charge trapping and recombination at the SnS surfaces, but addition of a CdS buffer layer lowers the charge recombination rate by 2 orders of magnitude and increases both the photovoltage and its reversibility due to the formation of a p-SnS/n-CdS junction. According to SPV, the FTO/SnS back interface (but not the Mo/SnS interface) forms a detrimental p–n junction that hinders hole transfer. Additional shunting through the relatively open microcrystal SnS layers and a lower conductivity of the FTO substrate explain the low power conversion efficiencies of the final devices (0.18 and 0.10% for the Mo and FTO substrates). Altogether, this work establishes a low-temperature path for the fabrication of crystalline SnS film-based solar cells and identifies the bottlenecks that limit high photoconversion efficiency.

deposition↗
DOE OSTI2026

Visualization of the surface distribution of photocatalytic activity at the anatase/rutile TiO2 interface using X-ray photoelectron emission microscopy

We applied X-ray photoelectron emission microscopy (XPEEM) to visualize the surface distribution of photocatalytic activity at the anatase/rutile (A/R) interface of titanium dioxide. Acetic acid was adsorbed on the surface, and its decomposition and desorption reactions under ultraviolet light irradiation were monitored by observing C 1s spectra, enabling direct observation of the spatial distribution of photocatalytic activity. Complementary crystal structure information was obtained using spatially resolved low-energy electron diffraction, low-energy electron microscopy, X-ray absorption spectroscopy, and micro-focused Raman spectroscopy. Comparison with these structural data allowed for the evaluation of the photocatalytic activity as a function of the distance from the A/R interface. The activity is enhanced in the vicinity of the interface and gradually decreases toward both the anatase and rutile regions. These results demonstrate that XPEEM is an effective technique for spatially resolved mapping of photocatalytic activity, which has\\r\\npreviously been inaccessible using conventional characterization techniques.

25 ENERGY STORAGE↗
DOE OSTI2025

Internally Catalyzed Hydrogen Atom Transfer (I-CHAT)—A New Class of Reactions in Combustion Chemistry

The current paradigm of low-T combustion and autoignition of hydrocarbons is based on the sequential two-step oxygenation of fuel radicals. The key chain-branching occurs when the second oxygenation adduct (OOQOOH) is isomerized releasing an OH radical and a key ketohydroperoxide (KHP) intermediate. The subsequent homolytic dissociation of relatively weak O–O bonds in KHP generates two more radicals in the oxidation chain leading to ignition. Based on the recently introduced intramolecular “catalytic hydrogen atom transfer” mechanism (J. Phys. Chem. 2024, 128, 2169), abbreviated here as I-CHAT, we have identified a novel unimolecular decomposition channel for KHPs to form their classical isomers—enol hydroperoxides (EHP). The uncertainty in the contribution of enols is typically due to the high computed barriers for conventional (“direct”) keto–enol tautomerization. Remarkably, the I-CHAT dramatically reduces such barriers. The novel mechanism can be regarded as an intramolecular version of the intermolecular relay transfer of H-atoms mediated by an external molecule following the general classification of such processes (Catal. Rev.-Sci. Eng. 2014, 56, 403). Here, we present a detailed mechanistic and kinetic analysis of the I-CHAT-facilitated pathways applied to n-hexane, n-heptane, and n-pentane models as prototype molecules for gasoline, diesel, and hybrid rocket fuels. We particularly examined the formation kinetics and subsequent dissociation of the γ-enol-hydroperoxide isomer of the most abundant pentane-derived isomer γ-C5-KHP observed experimentally. To gain molecular-level insight into the I-CHAT catalysis, we have also explored the role of the internal catalyst moieties using truncated models. All applied models demonstrated a significant reduction in the isomerization barriers, primarily due to the decreased ring strain in transition states. In addition, the longer-range and sequential H-migration processes were also identified and illustrated via a combined double keto–enol conversion of heptane-2,6-diketo-4-hydroperoxide as a potential chain-branching model. To assess the possible impact of the I-CHAT channels on global fuel combustion characteristics, we performed a detailed kinetic analysis of the isomerization and decomposition of γ-C5-KHP comparing I-CHAT with key alternative reactions—direct dissociation and Korcek channels. Calculated rate parameters were implemented into a modified version of the n-pentane kinetic model developed earlier using RMG automated model generation tools (ACS Omega, 2023, 8, 4908). Simulations of ignition delay times revealed the significant effect of the new pathways, suggesting an important role of the I-CHAT pathways in the low-T combustion of large alkanes.

Biochemistry & Molecular Biology↗