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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Isotope engineering for spin defects in van der Waals materials

Abstract Spin defects in van der Waals materials offer a promising platform for advancing quantum technologies. Here, we propose and demonstrate a powerful technique based on isotope engineering of host materials to significantly enhance the coherence properties of embedded spin defects. Focusing on the recently-discovered negatively charged boron vacancy center ($${{{{{{{{\rm{V}}}}}}}}}_{{{{{{{{\rm{B}}}}}}}}}^{-}$$ V B − ) in hexagonal boron nitride (hBN), we grow isotopically purified h 10 B 15 N crystals. Compared to$${{{{{{{{\rm{V}}}}}}}}}_{{{{{{{{\rm{B}}}}}}}}}^{-}$$ V B − in hBN with the natural distribution of isotopes, we observe substantially narrower and less crowded$${{{{{{{{\rm{V}}}}}}}}}_{{{{{{{{\rm{B}}}}}}}}}^{-}$$ V B − spin transitions as well as extended coherence timeT 2 and relaxation timeT 1 . For quantum sensing,$${{{{{{{{\rm{V}}}}}}}}}_{{{{{{{{\rm{B}}}}}}}}}^{-}$$ V B − centers in our h 10 B 15 N samples exhibit a factor of 4 (2) enhancement in DC (AC) magnetic field sensitivity. For additional quantum resources, the individual addressability of the$${{{{{{{{\rm{V}}}}}}}}}_{{{{{{{{\rm{B}}}}}}}}}^{-}$$ V B − hyperfine levels enables the dynamical polarization and coherent control of the three nearest-neighbor 15 N nuclear spins. Our results demonstrate the power of isotope engineering for enhancing the properties of quantum spin defects in hBN, and can be readily extended to improving spin qubits in a broad family of van der Waals materials.

Science & Technology - Other Topics↗
DOE OSTI2026

Best Practices for Resilience Hub Development and Management

The Carbon League and its community partners in East St. Louis, Illinois, have identified five facilities to serve as resilience hubs. These hubs are intended to support the local community through a range of services and resources during blue-sky (everyday), gray-sky (pre-event), and black-sky (emergency) conditions. Transforming these facilities into fully functional resilience hubs requires a broad operational improvement and programmatic planning roadmap. This memo outlines best practices to guide the development of these resilience hubs in East St. Louis, including recommendations for infrastructure services; safety and physical protection; community services; operational protocols; and a phased implementation strategy aligned with realistic funding and capacity constraints. Infrastructure recommendations include strengthening electric power, communications, water, sanitation, and transportation/logistics capabilities, all of which are essential for hubs that may serve as cooling and warming centers, distribution points, and information hubs during emergencies. Safety recommendations focus on accessibility, emergency action planning, indoor air quality, and secure storage of critical equipment. A phased roadmap provides guidance from immediate, low-cost readiness actions to long-term optimization and community integration. Performance metrics and maintenance protocols ensure continuous improvement and operational readiness. This guidance draws on best practices that can be used to support the development of resilient, community-centered hubs capable of enhancing public safety, health, and well-being during everyday operations and emergencies alike.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Three-dimensional nucleation and growth of deformation twins in magnesium

At two-thirds the weight of aluminum, magnesium alloys have the potential to reduce the fuel consumption of transportation vehicles. These advancements depend on our ability to optimize the desirable versus undesirable effects of deformation twins, which are three-dimensional (3D) microstructural domains that form under mechanical stresses. Previously only characterized through surface or thin-film measurements, we here present 3D in situ characterization of deformation twinning inside an embedded grain over mesoscopic fields of view using dark-field x-ray microscopy supported by crystal plasticity finite element analysis. The results revealed the role of triple junctions on twin nucleation and the sequence and irregularity of twin growth and showed that twin-grain junctions, twin-twin junctions, and twin boundaries were the sites of localized dislocation accumulation.

Lee, Sangwon [Univ. of Michigan, Ann Arbor, MI (Un↗
DOE OSTI2026

Multiscale and multidimensional modeling of particle acceleration and transport in solar flares

Multi-messenger, multi-viewpoint, and time-resolved observations of solar flares are now providing unprecedented constraints on particle acceleration sites, energy conversion, and energy transport. The interpretation of current observations, including microwave imaging spectroscopy from EOVSA, hard x-ray (HXR) imaging from Solar Orbiter/STIX, gamma-ray diagnostics from Fermi, and in situ measurements from Parker Solar Probe and Solar Orbiter, collectively demands modeling frameworks that go beyond traditional spatially unresolved, one-zone models or single-mechanism descriptions. This review surveys multiscale and multidimensional modeling approaches, including kinetic, magnetohydrodynamic (MHD), and macroscopic particle models, that are being developed to meet the need. Kinetic simulations reveal that three-dimensional (3D) effects, including field-line chaos and self-generated turbulence, are essential for sustained power-law particle acceleration. MHD simulations now capture flux-rope eruptions, plasmoid-unstable current sheets, and turbulent flare regions in realistic magnetic topologies. Macroscopic models coupling MHD with energetic-particle models produce spatially resolved electron distributions and synthetic HXR and microwave emissions for direct comparison with observations. Despite these advances, outstanding challenges remain in bridging kinetic and global scales, improving MHD simulations and macroscopic particle models, and achieving quantitative model-observation closure.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Trust-Based Detection and Mitigation of Cyber Attacks in Distributed Cooperative Control of Islanded AC Microgrids

In this study, we address the challenge of detecting and mitigating cyber attacks in the distributed cooperative control of islanded AC microgrids, with a particular focus on detecting False Data Injection Attacks (FDIAs), a significant threat to the Smart Grid (SG). The SG integrates traditional power systems with communication networks, creating a complex system with numerous vulnerable links, making it a prime target for cyber attacks. These attacks can lead to the disclosure of private data, control network failures, and even blackouts. Unlike machine learning-based approaches that require extensive datasets and mathematical models dependent on accurate system modeling, our method is free from such dependencies. To enhance the microgrid’s resilience against these threats, we propose a resilient control algorithm by introducing a novel trustworthiness parameter into the traditional cooperative control algorithm. Our method evaluates the trustworthiness of distributed energy resources (DERs) based on their voltage measurements and exchanged information, using Kullback-Leibler (KL) divergence to dynamically adjust control actions. We validated our approach through simulations on both the IEEE-34 bus feeder system with eight DERs and a larger microgrid with twenty-two DERs. The results demonstrated a detection accuracy of around 100%, with millisecond range mitigation time, ensuring rapid system recovery. Additionally, our method improved system stability by up to almost 100% under attack scenarios, showcasing its effectiveness in promptly detecting attacks and maintaining system resilience. These findings highlight the potential of our approach to enhance the security and stability of microgrid systems in the face of cyber threats.

Computer Science↗
DOE OSTI2025

A Reductively Stable Electrolyte Realizes Deep Cycling Behavior in Anode‐free Sodium Batteries

For anode‐free sodium batteries to achieve practical consideration, highly reversible chemistries require exceptional ≥99.95% coulombic efficiencies that maintain over prolonged cycling periods. To do so, consumption of this severely limited sodium inventory must be restricted while metal nucleation processes that comprise the in situ formed metal anode are improved. Herein, we describe a fluorine‐free carborane electrolyte that satisfies these criteria by emphasizing reductive stability and weakly coordinating anion behavior as design principles. We find this approach promotes the development of a thin, robust SEI chemistry rich in both organic speciation and boron. The electrolyte described herein exhibits ideal metal nucleation behavior on one‐micron thin carbonaceous current collector surfaces and achieves a metal deposition/stripping efficiency near parity for 400 cycles. This novel anode chemistry is introduced to anode‐free full cell configurations where 87% of the initial discharge capacity is retained after 1000 cycles at 2.0 C. In conclusion, post‐test characterization of deep‐cycled anode‐free cells reveals suppressed capacity fade in these systems is attributed to the chemical stability of the carborane anion.

anode-free↗
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 OSTI2026

Adaptation of virtual synchronous generators to dynamic conditions in power grids

Virtual synchronous generators (VSGs) are widely adopted as grid-forming controls for inverter-based resources. However, when grid conditions vary significantly as characterized by changes in short-circuit ratio (SCR) and the reactance-to-resistance (X/R) ratio, fixed-gain designs and the commonly used P–Q decoupling assumption can become inaccurate. Such conditions can degrade transient power performance, leading to oscillations, prolonged settling, and overshoot, particularly in stiff-grid operating points. This paper quantifies how grid strength and impedance-dependent coupling affect the active–reactive power dynamics of a conventional VSG over a broad range of SCR and X/R values. An adaptive VSG tuning framework is then developed by combining (i) a coupling-explicit, impedance-parameterized state-space model to enable systematic controller synthesis, (ii) a full-state-feedback law designed via pole placement to meet prescribed damping and settling-time specifications, and (iii) a physics-informed neural network (PINN)–based online grid-impedance estimator that updates controller gains in real time as grid conditions vary. Offline simulations in MATLAB/Simulink and real-time validation on an OPAL-RT platform show that the proposed method preserves consistent damping and settling behavior with reduced overshoot across wide SCR and X/R ranges, compared with fixed-gain VSG baselines.

Adaptive control↗
DOE OSTI2026

Pivotal role of organic adsorbates for the creation of catalytic sites during dry reforming of methane

Inadvertent factors can sometimes be crucial for synthesis of catalysts. The use of polyalcohols is common in the synthesis of heterogeneous catalysts. Interactions between alcohols and heterogeneous catalysts have been shown to induce surface reconstructions that greatly impact catalytic performance. Thus, traces of these alcohol functionalities on the as-synthesized catalysts, combined with heat treatment, could be critical in the generation of catalytic sites. Here, we show that during the synthesis of a Ni–Mo/MgO catalyst using a polyol process, residual ethylene glycol (EG) on the surface plays a significant role in the generation of catalytic sites for dry reforming of methane (DRM). The as-synthesized catalyst presents dispersed cationic Ni. Under DRM reaction conditions, the presence of EG, and H2 generated in situ, promote the generation of co-localized Ni–Mo nanoparticles (NPs). Greater amount of EG in the as-synthesized catalyst prevented sintering, leading to better catalyst stability and higher rates. If the residual EG remaining post-synthesis is removed through calcination, before conducting DRM, NiO NPs are formed and the material is completely inactive for catalyzing the reaction. When using a different support, denoted MgO*, EG also proved indispensable to generate active sites, although Ni–Mo co-localization was not evident, and a combination of DRM-related species was needed to activate the catalyst, not just H2. This work systematically uncovers how the interactions between organic adsorbates, the supported metals and the catalyst support dictate the creation of catalytic active sites.

Polo Garzon, Felipe [ORNL] (ORCID:0000000265076183↗
DOE OSTI2026

Distributed quantum approximate optimization algorithm on a quantum-centric supercomputing architecture

Quantum approximate optimization algorithm (QAOA) has shown promise in solving combinatorial optimization problems by providing quantum speedup on near-term gate-based quantum computing systems. However, QAOA faces challenges for high-dimensional problems due to the large number of qubits required and the complexity of deep circuits, limiting its scalability for real-world applications. In this study, we present a distributed QAOA (DQAOA), which leverages distributed computing strategies to decompose a large computational workload into smaller tasks that require fewer qubits and shallower circuits than are necessary to solve the original problem. These sub-problems are processed using a combination of high-performance and quantum computing resources. The global solution is iteratively updated by aggregating sub-solutions, allowing convergence toward the optimal solution. We demonstrate that DQAOA can handle considerably large-scale optimization problems (e.g., 1000-bit problem), achieving a high solution quality and short time-to-solution, outperforming existing strategies. Furthermore, we realize DQAOA on a quantum-centric supercomputing architecture, paving the way for practical applications of gate-based quantum computers in real-world optimization tasks. To extend DQAOA’s applicability to materials science, we further develop an active learning algorithm integrated with our DQAOA (AL-DQAOA), which involves machine learning, DQAOA, and active data production in an iterative loop. We successfully optimize photonic structures using AL-DQAOA, indicating that solving real-world optimization problems using gate-based quantum computing is feasible. We expect the proposed DQAOA to be applicable to a wide range of optimization problems and AL-DQAOA to find broader applications in material design.

Kim, Seongmin [ORNL] (ORCID:0000000159063004)↗
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 OSTI2026

Expanding the horizon of bio-naphtha beyond gasoline blend: property characterization and conversion opportunity assessment through technoeconomic and life-cycle analyses

Bio-naphtha, a common by-product of biorefineries, is expected to experience substantial growth in supply due to increasing demands for renewable diesel and synthetic aviation fuel (SAF). However, demand for bio-naphtha itself as a gasoline blendstock is limited because of the electrification of light-duty vehicles. This work investigated valorization opportunities for bio-naphtha from catalytic fast pyrolysis, hydrothermal liquefaction, Fischer–Tropsch synthesis, and hydrotreated esters and fatty acids pathways. These opportunities include producing polymer-grade olefin via steam cracking, SAF via steam cracking followed by olefin oligomerization, and renewable aromatics benzene, toluene, and xylene (BTX) and hydrogen via catalytic reforming. Process models were developed in Aspen Plus V14 and Aspen HYSYS V14 to calculate the mass and energy balances for each conversion step. Technoeconomic assessment and life-cycle analysis were conducted to evaluate the minimum fuel/product selling price, conversion cost, and life-cycle CO2 equivalent (CO2e) emission reduction. Technoeconomic assessment results suggest a minimum fuel/product selling price as low as $1.9/kg of olefins, $6.30/gal of gasoline-equivalent SAF, and $1.2/kg of BTX without any incentives. For all pathways, these prices are dominated by bio-naphtha feedstock costs, which account for at least 76% of the total cost. Compared with petroleum baselines, bio-naphtha-derived SAF, olefins, and BTX can achieve significant CO2e emission reductions from the use of renewable carbon resources. The results of life-cycle analysis and subsequent technoeconomic assessment, incorporating carbon credits, indicate the economic viability of using bio-naphtha for polymer-grade olefin and BTX production, with product costs comparable to market prices.

Xu, Shuang↗
DOE OSTI2021

Design and Realization of Ohmic and Schottky Interfaces for Oxide Electronics

Understanding band alignment and charge transfer at complex oxide interfaces is critical to tailoring and utilizing their diverse functionality. Toward this goal, both Ohmic- and Schottky-like charge transfers at oxide/oxide semiconductor/metal interfaces are designed and experimentally validated. A method for predicting band alignment and charge transfer in ABO 3 perovskites is utilized, where previously established rules for simple semiconductors fail. The prototypical systems chosen are the rare class of oxide metals, SrBO 3 with B = V–Ta, when interfaced with the multifaceted semiconducting oxide, SrTiO 3 . For B = Nb and Ta, it is confirmed that a large accumulation of charge occurs in SrTiO 3 due to the higher energy Nb and Ta states relative to Ti. Furthermore, this gives rise to a high mobility metallic interface, which is an ideal epitaxial oxide/oxide Ohmic contact. On the contrary, for B = V, there is no charge transfer into the SrTiO 3 interface, which serves as a highly conductive epitaxial gate metal. Going beyond these specific cases, this work opens the door to integrating the vast phenomena of ABO 3 perovskites into a wide range of practical devices.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Enhanced Catalytic Dechlorination of Polyvinyl Chloride (PVC) and H2 Production Enabled by Synergistic Gaδ+/Ga0 Active Sites in Liquid Metal Particles

Polyvinyl chloride (PVC) is ubiquitous yet challenging to recycle due to its tendency to thermally decompose above 250 °C, releasing toxic, corrosive chlorinated compounds, and its inability to melt. Here, we report a catalytic strategy for PVC upcycling at 160 °C using gallium liquid metal particles (Ga-LMP) featuring a dynamic Ga-GaOOH core–shell architecture. These catalysts enable concurrent dechlorination and hydrogen evolution, yielding up to 7% H2 (based on initial hydrogen atoms in PVC) along with a highly dechlorinated (>95%) carbonaceous solid and aqueous HCl. Mechanistic investigations combining X-ray photoelectron spectroscopy, infrared spectroscopy, solid-state NMR, inelastic neutron scattering, and ab initio molecular dynamics reveal a synergistic interplay between Gaδ+ sites in the GaOOH shell and metallic Ga0 in the core. Cationic Ga initiates C–Cl bond activation and HCl formation, while progressive reduction of the shell exposes Ga0 sites that promote C–H activation and H2 evolution. Control experiments with a Ga salt and bulk Ga liquid metal confirmed that neither oxidation state alone can achieve both transformations efficiently. This work establishes a dynamic dual-site paradigm for liquid metal catalysis, in which the in situ evolution and coexistence of oxidized and metallic species enable sequential and cooperative bond activation pathways. These findings provide a general design principle for novel liquid metal catalysts that target challenging polymer transformations under mild conditions.

Zingg, Benjamin [ORNL] (ORCID:0009000914530153)↗
DOE OSTI2025

Evaluation of Howard A. Hanson Dam Juvenile Fish Passage and Survival Study: Downstream Passage and Survival (Acoustic Telemetry) (Task Final Report)

The Downstream Passage and Survival (Acoustic Telemetry) task was one of several tasks for the Evaluation of Howard A. Hanson Dam (HAHD) Juvenile Fish Passage and Survival study. For this task, a juvenile fish passage and survival study was conducted at HAHD from March 10, 2024 through June 27, 2024 for arrays in the HAHD Reservoir and Green River, and through July 9, 2024 for the arrays in the Duwamish River. Fish releases occurred over four times from March through May. Active tag (acoustic telemetry) technology was used to provide biological baseline information for the passage and survival of juvenile Puget Sound (PS) Chinook salmon (Oncorhynchus tshawytscha). Results will be used by biologists, engineers, resource managers, and regional decision-makers to inform the engineering design of the new fish passage facility (FPF) at HAHD. However, hatchery sub-yearling PS Chinook salmon of the appropriate size for tag implantation during the study period (> 95 mm in fork length, Geist et al. 2018) were unavailable. Therefore, yearling Coho salmon (O. kisutch) were used as a surrogate species for this acoustic telemetry study.

13 HYDRO ENERGY↗
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 OSTI2026

Integrated Magnetics for Multiport Inductive and Conductive Power Transfer Architecture for Electric Vehicles

This paper proposes a shared magnetic arrangement for an electric-vehicle charger that supports both conductive and inductive charging while preserving independent power control at the two ports. In the proposed implementation, the high-frequency transformer used for the conductive path and the resonant inductor required by the inductive path are realized in an integrated form. By combining the magnetic structure and primary-side converter hardware, the charger can deliver improved hardware utilization and higher power density without a corresponding increase in cost or implementation complexity. The paper describes the magnetic realization and presents finite-element and circuit-level simulation results to confirm minimal interaction between the two charging paths. The study demonstrates that the proposed charger is a viable option for flexible, high-power EV charging systems.

Mukherjee, Subho [ORNL] (ORCID:0009000672297925)↗
DOE OSTI2026

Predicting Band-Gap of Inorganic Materials Using Neuromorphic Graph Learning

Predicting properties of inorganic materials is a heavily researched topic, with several new prediction approaches emerging as competitors. One such competitor is graph neural networks, which leverage the structure of the graph to aid in the prediction process. In this work, we propose integration of neuromorphic computation into the graph neural network pipeline. We call this approach Neuromorphic Graph Learning (NGL). We utilize the NGL approach to leverage evolutionary algorithms and a novel Spike Pipeline for Raster Analysis (SPIRE) for the prediction of band gap in inorganic materials.

Mulet, Ian [University of Tennessee (UT)]↗