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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Resolving turbulent magnetohydrodynamics: a hybrid operator-diffusion framework

We present a hybrid machine learning framework that combines physics-informed neural operators (PINOs) with score-based generative diffusion models to simulate the full spatio-temporal evolution of two-dimensional, incompressible, resistive magnetohydrodynamic turbulence across a broad range of Reynolds numbers (Re). The framework leverages the equation-constrained generalization capabilities of PINOs to predict coherent, low-frequency dynamics, while a conditional diffusion model stochastically corrects high-frequency residuals, enabling accurate modeling of fully developed turbulence. Trained on a comprehensive ensemble of high-fidelity simulations with Re ϵ {100, 250, 500, 750, 1000, 3000, 10000}, the approach achieves state-of-the-art accuracy in regimes previously inaccessible to deterministic surrogates. At Re = 1000 and 3000, the model faithfully reconstructs the full spectral energy distributions of both velocity and magnetic fields late into the simulation, capturing non-Gaussian statistics, intermittent structures, and cross-field correlations with high fidelity. At extreme turbulence levels (Re = 10 000), it remains the first surrogate capable of recovering the high-wavenumber evolution of the magnetic field, preserving large-scale morphology and enabling statistically meaningful predictions.

Diffusion-Integrated Neural Operators↗
DOE OSTI2023

Higher-order topological superconductivity in twisted bilayer graphene

In this work, we show that introducing spin-singlet or spin-triplet superconductivity into twisted bilayer graphene induces higher-order topological superconductivity. Multiple copies of C 2z ⁢T-protected Majorana Kramers pairs appear at corners on pairing domain walls. The topology originates from the anomaly analyzed in Song et al.—the absence of a lattice support—of the single-valley band structure of twisted bilayer graphene, which is protected by C 2z ⁢T and approximate particle-hole symmetry $\mathcal{P}$. We prove that any pairing (spin-singlet or spin-triplet) term preserving valley-U(1), spin-SU(2), time-reversal, C 2z ⁢T, and $\mathcal{P}$ must drive the system into a higher-order topological superconductor. Here spin-SU(2) is the global spin-SU(2) for the singlet pairing and is broken to U(1) for the triplet pairing. Using a Dirac Hamiltonian, we derive the corner modes and confirm with numerics. These corner states are stable even if $\mathcal{P}$ is weakly broken, which is true in experimental setups. Finally, we suggest experimental detection via the fractional Josephson effect in a TBG-TSC Josephson junction.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

History of and Aftermath from the Withdrawal of the Intermediate-Range Nuclear Forces Treaty

On February 1, 2019, the United States and Russia withdrew from the three-decades old Intermediate-Range Nuclear Forces (INF) treaty. Events precipitating the withdrawal were allegations by both the United States and Russia of a variety of treaty violations. Until that point, the treaty had been a centerpiece of arms control and a key agreement of the global security architecture. The absence of such a pillar has the potential destabilize the status quo of arms control, creating significant uncertainty in global nuclear stability and security. In this paper, we present a historical review as overture to an analysis on the impacts of this development on force structure. This analysis examines the changes in U.S., Russian, and Chinese nuclear forces which may occur as a result of the treaty's demise. The article concludes with commentary on potential actions to preserve stability in a post-INF world.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Structural basis for IL-12 and IL-23 receptor sharing reveals a gateway for shaping actions on T versus NK cells

Interleukin-12 (IL-12) and IL-23 are heterodimeric cytokines that are produced by antigen-presenting cells to regulate the activation and differentiation of lymphocytes, and they share IL-12Rβ1 as a receptor signaling subunit. In this paper, we present a crystal structure of the quaternary IL-23 (IL-23p19/p40)/IL-23R/IL-12Rβ1 complex, together with cryoelectron microscopy (cryo-EM) maps of the complete IL-12 (IL-12p35/p40)/IL-12Rβ2/IL-12Rβ1 and IL-23 receptor (IL-23R) complexes, which reveal “non-canonical” topologies where IL-12Rβ1 directly engages the common p40 subunit. We targeted the shared IL-12Rβ1/p40 interface to design a panel of IL-12 partial agonists that preserved interferon gamma (IFNγ) induction by CD8+ T cells but impaired cytokine production from natural killer (NK) cells in vitro. These cell-biased properties were recapitulated in vivo, where IL-12 partial agonists elicited anti-tumor immunity to MC-38 murine adenocarcinoma absent the NK-cell-mediated toxicity seen with wild-type IL-12. Thus, the structural mechanism of receptor sharing used by IL-12 family cytokines provides a protein interface blueprint for tuning this cytokine axis for therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Site-Specific Structure at Multiple Length Scales in Kagome Quantum Spin Liquid Candidates

Realizing a quantum spin liquid (QSL) ground state in a real material is a leading issue in condensed matter physics research. In this pursuit, it is crucial to fully characterize the structure and influence of defects, as these can significantly affect the fragile QSL physics. In this work, we perform a variety of cutting-edge synchrotron x-ray scattering and spectroscopy techniques, and we advance new methodologies for site-specific diffraction and L-edge Zn absorption spectroscopy. The experimental results along with our first-principles calculations address outstanding questions about the local and long-range structures of the two leading kagome QSL candidates, Zn-substituted barlowite Cu 3 Zn x Cu 1-x (OH) 6 FBr and herbertsmithite Cu 3 Zn(OH) 6 Cl 2 . On all length scales probed, there is no evidence that Zn substitutes onto the kagome layers, thereby preserving the QSL physics of the kagome lattice. Our calculations show that antisite disorder is not energetically favorable and is even less favorable in Zn-barlowite compared to herbertsmithite. Site-specific x-ray diffraction measurements of Zn-barlowite reveal that Cu 2+ and Zn 2+ selectively occupy distinct interlayer sites, in contrast to herbertsmithite. Using the first measured Zn L-edge inelastic x-ray absorption spectra combined with calculations, we discover a systematic correlation between the loss of inversion symmetry from pseudo-octahedral (herbertsmithite) to trigonal prismatic coordination (Zn-barlowite) with the emergence of a new peak. Overall, our measurements suggest that Zn-barlowite has structural advantages over herbertsmithite that make its magnetic properties closer to an ideal QSL candidate: its kagome layers are highly resistant to nonmagnetic defects while the interlayers can accommodate a higher amount of Zn substitution.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Layered Nano-Mosaic of Niobium Disulfide Heterostructures by Direct Sulfidation of Niobium Carbide MXenes for Hydrogen Evolution

MXene-transition metal dichalcogenide (TMD) heterostructures are synthesized through a one-step heat treatment of Nb 2 C and Nb 4 C 3 . These MXenes are used without delamination or any pre-treatment. Heat treatments accomplish the sacrificial transformation of these MXenes into TMD (NbS 2 ) at 700 and 900 °C under H 2 S. This work investigates, for the first time, the role of starting MXene phase in the derivative morphology. It is shown that while treatment of Nb 2 C at 700 °C leads to the formation of pillar-like structures on the parent MXene, Nb 4 C 3 produces nano-mosaic layered NbS 2 . At 900 °C, both MXene phases, of the same transition metal, fully convert into nanomosaic layered NbS 2 preserving the parent MXene’s layered morphology. When tested as electrodes for hydrogen evolution reaction, Nb 4 C 3 -derived hybrids show better performance than Nb 2 C derivatives. The Nb 4 C 3 -derived heterostructure exhibits a low overpotential of 198 mV at 10 mA cm -2 and a Tafel slope of 122 mV dec -1 , with good cycling stability in an acidic electrolyte

36 MATERIALS SCIENCE↗
DOE OSTI2025

Polysulfamates as “Macroisosteres” of Polyurethanes with Improved Degradability

Abstract Addressing the environmental persistence of plastics requires the development of next‐generation polymers that combine high performance with enhanced degradability. Progress toward this grand challenge has been impeded, in part, by the absence of a general blueprint for the macromolecular design of such materials. Herein, we introduce a “macroisostere” design strategy, where the carbonyl group (–CO–) in polyurethanes (PUs) is replaced with a sulfonyl group (–SO 2 –), resulting in a virtually unknown family of polymers called polysulfamates. This approach, inspired by the use of bioisosteres in drug discovery, aims to preserve key interchain interactions that contribute to thermomechanical performance while enhancing the hydrolytic lability of the polymer backbone. The optimization of a Sulfur(VI) Fluoride Exchange (SuFEx) polymerization allowed the synthesis of ten polysulfamates structurally analogous to common PUs. Comparative analysis of one PU and its polysulfamate analog showed that this isosteric substitution increases thermal stability, slightly lowers the glass transition temperature, and retains similar hardness and reduced Young's modulus. Notably, the S(VI)‐based polysulfamate demonstrated significantly enhanced hydrolytic degradability. These results highlight the potential of the “macroisostere” approach as a generalizable strategy for designing high‐performance, degradable alternatives to traditional plastics.

Chemistry↗
DOE OSTI2024

Microscopy modality transfer of steel microstructures: Inferring scanning electron micrographs from optical microscopy using generative AI

Scanning electron microscopy (SEM) is resource intensive, which limits its throughput in some applications. As an alternative, we propose applying computer vision and machine learning to generate high-quality synthetic SEM micrographs from micrographs obtained using light optical microscopy (LOM). Working with a correlated LOM/SEM dataset of dual-phase steel images, we test generative models of various architectures, including encoder-decoder networks, generative adversarial networks (GANs), and diffusion-based models. We find that the diffusion models significantly outperform other methods on both qualitative and quantitative assessments, while preserving key metallurgical meaning. This work establishes diffusion as the state-of-the-art for microscopy modality transfer and demonstrates the potential of AI-powered microscopy to enhance LOM with micron scale structural recreation.

Computer vision↗
DOE OSTI2024

Linkages Between Mineral Element Composition of Soils and Sediments With Hyporheic Zone Dissolved Organic Matter Chemistry Across the Contiguous United States

The hyporheic zone is a hotspot for biogeochemical cycling where interactions with mineral metals preserve the release and biodegradation of organic matter (OM). A small fraction of OM can still be exchanged between localized sediments and the overlying water column, and recent evidence suggests there exists a longitudinal structuring in sediment dissolved OM (DOM) chemistry across the continental United States (CONUS). In this study, we tested a hypothesis that water extractable sediment DOM chemistry could be explained by sediment metal contents and integrative watershed scale features at the CONUS scale. Crowdsourced samples were characterized for high resolution mass spectrometry and coupled with sediment metals determined via x-ray fluorescence as well as with land cover and soil elemental information obtained from national databases. Our results highlight weak relationships between DOM chemistry and elemental composition at the CONUS scale indicating limited transferability of organo-metal linkages into multi-scale hydrobiogeochemical models.

58 GEOSCIENCES↗
DOE OSTI2026

Optical interference for the guidance of cryogenic focused ion beam milling beyond the axial diffraction limit

Cryogenic focused ion beam (Cryo-FIB) milling has become a standard step in the cryogenic electron tomography (Cryo-ET) workflow and is required to thin cells to electron-semitransparency. However, this destructive process removes the vast majority of the cellular material and raises a critical question: what thin section should be preserved for Cryo-ET analysis? Using a tri-coincident cryogenic FIB-SEM-LM system, we identify an interferometric optical response that can be used for targeting lamella production to fluorescently labeled structures with accuracy beyond the diffraction limit. Here we demonstrate this approach using synthetic samples of fluorescent beads embedded in micron-scale droplets of amorphous ice. We then apply the approach to capture virions inside host cells. Successful targeting is confirmed by Cryo-ET revealing clusters of virions in intracellular vesicles. The method does not require any fluorescent fiducials or axial registration and can be performed on any fluorescently labeled structure that is visible in widefield fluorescence microscopy.

Cryoelectron microscopy↗
DOE OSTI2026

Evaluating Supply Prioritization Strategies for Risk-Informed Decision Making in an Arbitrary Gas Network

Supply disruptions and infrastructure failures in natural gas networks present critical challenges to energy reliability and risk-informed planning. This study evaluates two supply prioritization strategies, Maximum Delivery Prioritization (MDP) and Demand-Based Prioritization (DBP), within an arbitrary natural gas network under conditions of supply shortage. Model performance under both strategies is assessed in response to node and edge failure using demand satisfaction metrics, system-wide and localized dependency scores, and geographic information system (GIS)-based spatial analysis. Results show that DBP better preserves supply for high-demand nodes, while MDP offers broader coverage. The underlying network topology plays a critical role in shaping prioritization outcomes. Integrated GIS visualization enhances the interpretability of vulnerability assessments, revealing structurally critical components and localized vulnerabilities. The proposed framework supports scalable, data-driven decision-making for infrastructure planners and engineers, enabling improved disruption recovery and efficiency in constrained natural gas networks. These insights contribute to the development of more robust energy systems capable of withstanding stress and disruptions.

Peterson, Steven [ORNL] (ORCID:0000000287672998)↗
DOE OSTI2025

Mic-hackathon 2024: hackathon on machine learning for electron and scanning probe microscopy

Microscopy is one of the primary sources of information on materials structure and functionality at the nanometer and atomic scales. The data generated through microscopy is often contained in well-structured datasets, enriched with extensive metadata and sample histories, although not always with the same level of detail or storage format. The broad incorporation of data management plans by major funding agencies ensures the preservation and accessibility of this data. However, deriving insights from these rich datasets remains challenging due to the lack of established code ecosystems, standardized benchmarks, and integration strategies. Correspondingly, the efficiency of data usage is very low, and time expenditures at the analysis stage are enormous. In addition to post-acquisition data analysis, the emergence of application programming interfaces by major microscope manufacturers now creates opportunities for real-time ML-based data analytics to enable automated decision making, and particularly ML-agent controlled real-time microscope operation. Despite these opportunities, there is a significant gap in integrating the ML community with the broader microscopy community, limiting the value that these methods bring to physics and materials discovery and materials optimization. Hackathons address these challenges by fostering collaboration between ML experts and microscopy professionals, encouraging the development of innovative solutions that leverage ML for microscopy and preparing the workforce of the future both for microscopy-intensive domains areas, instrument manufacturers, and ML scientists interested in real world applications for fundamental research, materials optimization, and manufacturing. The hackathon generated benchmark datasets and digital twins of microscopes that further contribute to the development of the field and establish data analysis ecosystems. All the codes can be found at GitHub(https://github.com/KalininGroup/Mic-hackathon-2024-codes-publication/tree/1.0.0.1) and Zenodo (https://zenodo.org/records/15579940).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Modeling Protein–Protein and Protein–Ligand Interactions by the ClusPro Team in CASP16

ABSTRACT In the CASP16 experiment, our team employed hybrid computational strategies to predict both protein–protein and protein–ligand complex structures. For protein–protein docking, we combined physics‐based sampling—using ClusPro FFT docking and molecular dynamics—with AlphaFold (AF)‐based sampling, followed by AF‐based refinement. Our method produced numerous high‐accuracy complex models, including cases where AF alone failed, underscoring the critical role of physics‐based sampling alongside deep learning‐based refinement. For protein–ligand docking, we integrated the ClusPro LigTBM template‐based approach with a machine learning‐based confidence model for rescoring. The method preserves conserved interaction fragments derived from homologous complexes, followed by local resampling using physics‐based sampling and a diffusion model. Our template‐based strategy achieved a mean lDDT‐PLI of 0.69 across 233 targets, which was highly competitive. These results demonstrate that combining physics‐based modeling with AI‐driven refinement can significantly enhance the accuracy of both protein–protein and protein–ligand structure predictions.

Ashizawa, Ryota [Department of Applied Mathematics↗
DOE OSTI2022

Carrier Mobility Modulation in Cu 2 Se Composites Using Coherent Cu 4 TiSe 4 Inclusions Leads to Enhanced Thermoelectric Performance

Carrier transport engineering in bulk semiconductors using inclusion phases often results in the deterioration of carrier mobility (μ) owing to enhanced carrier scattering at phase boundaries. Here, we show by leveraging the temperature-induced structural transition between the α-Cu 2 Se and β-Cu 2 Se polymorphs that the incorporation of Cu 4 TiSe 4 inclusions within the Cu 2 Se matrix results in a gradual large drop in the carrier mobility at temperatures below 400 K (α-Cu 2 Se), whereas the carrier mobility remains unchanged at higher temperatures, where the β-Cu 2 Se polymorph dominates. The sharp discrepancy in the electronic transport within the α-Cu 2 Se and β-Cu 2 Se matrices is associated with the formation of incoherent α-Cu 2 Se/Cu 4 TiSe 4 interfaces, owing to the difference in their atomic structures and lattice parameters, which results in enhanced carrier scattering. In contrast, the similarity of the Se sublattices between β-Cu 2 Se and Cu 4 TiSe 4 gives rise to coherent phase boundaries and good band alignment, which promote carrier transport across the interfaces. Interestingly, the different cation arrangements in Cu 4 TiSe 4 and β-Cu 2 Se contribute to enhanced phonon scattering at the interfaces, which leads to a reduction in the lattice thermal conductivity. The large reduction in the total thermal conductivity while preserving the high power factor of β-Cu 2 Se in the (1–x)Cu 2 Se/(x)Cu 4 TiSe 4 composites results in an improved ZT of 1.2 at 850 K, with an average ZT of 0.84 (500–850 K) for the composite with x = 0.01. Furthermore, this work highlights the importance of structural similarity between the matrix and inclusions when designing thermoelectric materials with improved energy conversion efficiency.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Evaluation of Building 23-702, Los Alamos Scientific Laboratory H-8 Foil Handling Building, Mercury, Area 23, Nevada National Security Site, Nye County, Nevada

The U.S. Department of Energy (DOE) National Nuclear Security Administration Nevada Field Office (NNSA/NFO) plans to demolish Building 23-702, the Los Alamos Scientific Laboratory (LASL) H-8 Foil Handling Building (Nevada State Historic Preservation Office [SHPO] Resource No. B15278) at the Nevada National Security Site (NNSS) in Nye County, Nevada. The NNSA/NFO is implementing a long-term project to modernize the town of Mercury for future mission needs. The project is considered an undertaking subject to review under Title 54 of United States Code (USC) § 306108, commonly known as Section 106 of the National Historic Preservation Act, Title 54 USC § 300101, et seq., and its implementing regulations, Title 36 of the Code of Federal Regulations (36 CFR) Part 800. In 2018, Desert Research Institute (DRI) completed an architectural survey of the town of Mercury. This effort resulted in the identification, recordation, and evaluation of the Mercury Historic District (MHD, SHPO Resource No. D230), including the identification of its contributing elements (Reno et al. 2018). The MHD was recommended eligible for listing in the National Register of Historic Places (NRHP, National Register) under the Secretary of the Interior’s (SOI) Significance Criteria A and C, as defined in 36 CFR Part 60.4, as a significant concentration of buildings and structures with a direct and important association with Cold War-era nuclear testing from 1951 through 1992. As part of the modernization program for Mercury, the NNSA/NFO and the SHPO executed the 2018 Programmatic Agreement Between the National Nuclear Security Administration Nevada Field Office and the Nevada State Historic Preservation Officer Regarding Modernization and Operational Maintenance of the Nevada National Security Site, at Mercury in Nye County, Nevada (Mercury PA). The Mercury PA includes streamlined Section 106 procedures for undertakings in the MHD based on contributing element categories. Building 23-702 is identified in Appendix C of the Mercury PA as a Category I contributing element, indicating that it might be individually eligible for the NRHP. It is a historic property for the purposes of Section 106 compliance and subject to the stipulations of the Mercury PA. Per Stipulation VI of the Mercury PA, when the Area of Potential Effect (APE) for an undertaking includes Category I elements, the NNSA/NFO must evaluate the Category I elements for individual NRHP eligibility under all of the SOI Significance Criteria prior to initiating any activity that may affect the elements. The purpose of this report is to evaluate Building 23-702 as a potential individually eligible historic property in fulfillment of Stipulation VI of the Mercury PA. The evaluation detailed herein concludes that Building 23-702 is not individually eligible for listing in the NRHP. Although it retains aspects of integrity and continues to contribute to the MHD, it is not individually significant under any of the SOI Significance Criteria.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Simulating Hydrodynamics in Cosmology with CRK-HACC

Abstract We introduce CRK-HACC, an extension of the Hardware/Hybrid Accelerated Cosmology Code (HACC), to resolve gas hydrodynamics in large-scale structure formation simulations of the universe. The new framework couples the HACC gravitational N -body solver with a modern smoothed-particle hydrodynamics (SPH) approach called conservative reproducing kernel SPH (CRKSPH). CRKSPH utilizes smoothing functions that exactly interpolate linear fields while manifestly preserving conservation laws (momentum, mass, and energy). The CRKSPH method has been incorporated to accurately model baryonic effects in cosmology simulations—an important addition targeting the generation of precise synthetic sky predictions for upcoming observational surveys. CRK-HACC inherits the codesign strategies of the HACC solver and is built to run on modern GPU-accelerated supercomputers. In this work, we summarize the primary solver components and present a number of standard validation tests to demonstrate code accuracy, including idealized hydrodynamic and cosmological setups, as well as self-similarity measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Sulfur-doped graphene anchoring of ultrafine Au 25 nanoclusters for electrocatalysis

The biggest challenge of exploring the catalytic properties of under-coordinated nanoclusters is the issue of stability. We demonstrate herein that chemical dopants on sulfur-doped graphene (S-G) can be utilized to stabilize ultrafine (sub-2 nm) Au 25 (PET)18 clusters to enable stable nitrogen reduction reaction (NRR) without significant structural degradation. The Au 25 @S-G exhibits an ammonia yield rate of 27.5μgNH 3 ∙ mg Au -1 ∙ h -1 at -0.5 V with faradic efficiency of 2.3%. More importantly, the anchored clusters preserve ~ 80% NRR activity after four days of continuous operation, a significant improvement over the 15% remaining ammonia production rate for clusters loaded on undoped graphene tested under the same conditions. Isotope labeling experiments confirmed the ammonia was a direct reaction product of N 2 feeding gas instead of other chemical contaminations. Ex-situ X-ray photoelectron spectroscopy and X-ray absorption near-edge spectroscopy of post-reaction catalysts reveal that the sulfur dopant plays a critical role in stabilizing the chemical state and coordination environment of Au atoms in clusters. Further ReaxFF molecular dynamics (RMD) simulation confirmed the strong interaction between Au nanoclusters (NCs) and S-G. Furthermore, this substrate-anchoring process could serve as an effective strategy to study ultrafine nanoclusters’ electrocatalytic behavior while minimizing the destruction of the under-coordinated surface motif under harsh electrochemical reaction conditions.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

A tailored deep eutectic solvent for high-yield conversion of poplar residues to bio-based building blocks at mild conditions

The generation of condensed compounds in a deep eutectic solvent (DES) pretreatment has become a paramount factor that inhibits the further conversion of pretreated cellulose-rich substrate. Here, this study proposed a novel three-constituent DES system for the value-added utilization of poplar residues by efficiently suppressing hemicellulose derived condensation reactions. The results showed that adding ethanol into the DES system could effectively deconstruct the recalcitrant structure of poplar residues, simultaneously hindering the condensed composition formation. Under optimum ethanol addition (30%), the maximum xylan and lignin removal of 87.94% and 90.99% could be achieved, with more than 90.47% of glucan being preserved. With this, the glucan enzymatic hydrolysis efficiency was remarkably improved to 100% under the pretreatment conditions of 100 °C for 60 min, which was 84.69 times higher than the regular DES-pretreated poplar residues (1.17%). The working mechanism of relieving condensation reactions was characterized by Py-GC–MS, NMR, SEM, FTIR, and others. The results demonstrated that the addition of ethanol could regulate the degradation/conversion pathway of hemicellulose and lignin precipitation, thus inhibit the formation of condensed compounds during the pretreatment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗