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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Microwave-photonic control of optically accessible spin defects in diamond

A growing variety of optically accessible spin qubits have emerged in recent years as key components for quantum sensors, computers, and memories. However, the scalability of conventional spin-based quantum architectures remains limited by direct microwave delivery, which introduces thermal noise, electromagnetic crosstalk, and design constraints for cryogenic, high-field, and distributed systems. In this work, we present a unified framework for RF-over-fiber (RFoF) control of spins accessible through optically detected magnetic resonance (ODMR) spectroscopy of nitrogen-vacancy (NV) centers in diamond. The RFoF platform relies on an intensity-modulated 1310 nm laser carrying microwave signals over fiber and a high-speed photodiode for optical-to-electrical conversion to drive NV spin transitions. We report an RFoF power-conversion efficiency of 3.42% for an RF output PRF,out=-5.5 dBm at 2.87 GHz, enabling clear resolution of Zeeman splitting in

Rahman, M Reefaz [ORNL] (ORCID:0000000323541611)↗
DOE OSTI2025

Divertor characterization and access to dissipative divertor conditions in negative triangularity discharges in DIII-D

Reduced radial transport, short midplane-to-target parallel connection lengths, and a strong effect of cross-field drifts were responsible for the high densities required for detachment in strong negative triangularity (NT) configurations in DIII-D. Dissipative divertor conditions were achieved in NT discharges at different triangularity, injected power, plasma current, and toroidal field direction. Differences between negative and positive triangularity (PT) discharges are analyzed in this paper to understand the requirements for access to detached divertor conditions: power balance, geometry, radial transport and effect of cross-field particle drifts. Parametric dependencies of access to detachment on plasma current and power flowing into the scrape-off layer remained similar in negative and PT and impurity seeding was observed to reduce the density needed to detach by up to 30% at the expense of core impurity dilution. The impact of triangularity on core-edge integration was tested varying bottom triangularity at fixed top triangularity. The high density needed to detach was not intrinsic to the NT edge as shapes with positive lower triangularity and negative upper triangularity were able to detach at lower upstream densities while maintaining an ELM-free NT edge. Confinement degradation at deeper detachment levels was however observed in all NT shapes, often associated with radiation instabilities.

detachment↗
DOE OSTI2024

First access to ELM-free negative triangularity at low aspect ratio

A plasma scenario with negative triangularity (NT) shaping is achieved on MAST-U for the first time. While edge localized modes (ELMs) are eventually suppressed as the triangularity is decreased below δ ≲ –0.06, an extended period of H-mode operation with Type-III ELMs is sustained at less negative δ even through access to the second stability region for ideal ballooning modes is closed. This documents a qualitative difference from the ELM-free access conditions documented in NT scenarios on conventional aspect ratio machines. The electron temperature at the pedestal top drops across the transition to ELM-free operation, but a steady rise in core temperature as δ is decreased allows for similar normalized β in the ELM-free NT and H-mode positive triangularity shapes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Machine learning materials properties with accurate predictions, uncertainty estimates, domain guidance, and persistent online accessibility

One compelling vision of the future of materials discovery and design involves the use of machine learning (ML) models to predict materials properties and then rapidly find materials tailored for specific applications. However, realizing this vision requires both providing detailed uncertainty quantification (model prediction errors and domain of applicability) and making models readily usable. At present, it is common practice in the community to assess ML model performance only in terms of prediction accuracy (e.g. mean absolute error), while neglecting detailed uncertainty quantification and robust model accessibility and usability. Here, we demonstrate a practical method for realizing both uncertainty and accessibility features with a large set of models. We develop random forest ML models for 33 materials properties spanning an array of data sources (computational and experimental) and property types (electrical, mechanical, thermodynamic, etc). All models have calibrated ensemble error bars to quantify prediction uncertainty and domain of applicability guidance enabled by kernel-density-estimate-based feature distance measures. All data and models are publicly hosted on the Garden-AI infrastructure, which provides an easy-to-use, persistent interface for model dissemination that permits models to be invoked with only a few lines of Python code. We demonstrate the power of this approach by using our models to conduct a fully ML-based materials discovery exercise to search for new stable, highly active perovskite oxide catalyst materials.

domain of applicability↗
DOE OSTI2025

Accessing the deuteron source with pion-deuteron femtoscopy in Pb-Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV

Femtoscopy of nonidentical particle pairs has been instrumental for precision measurements of both two-particle sources and the final-state interactions in high-energy elementary and heavy-ion collisions. The majority of measurements assessing the source properties are based on identical particle pairs, providing direct access to the characteristics of the single-particle source. The work in this paper demonstrates, via femtoscopy measurements of charged pion-deuteron pairs in Pb-Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV, the feasibility of accessing the characteristics of the single-particle femtoscopic source by using particle pairs with large mass differences such as pions and deuterons. The first experimental results of the measurement of deuteron source sizes in ultrarelativistic heavy-ion collisions are presented. The results show good agreement with the trend derived from other charged hadrons such as pions, kaons, and protons as a function of transverse mass, indicating similar source properties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Accessing the gluon GTMD F 1 , 4 in exclusive π 0 production in e p collisions

We demonstrate that the longitudinal single target-spin asymmetry in exclusive π 0 production in e p collisions can give access to the imaginary part of the gluon generalized transverse momentum distribution (GTMD) F 1 , 4 . Such a longitudinal spin asymmetry that results from the Coulomb-nuclear interference effect, leads to a characteristic azimuthal angular correlation of sin 2 ϕ , where ϕ is the azimuthal angle between the scattered lepton transverse momentum and the recoil proton’s transverse momentum. We also present a numerical estimate of the asymmetry for the kinematics accessible at EIC and EicC. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

County Electric Vehicle Home Charging Access Shares From the 2030 National Charging Network Study

This file contains modeled county-level home electric vehicle charging access shares from the study The 2030 National Charging Network: Estimating U.S. Light-Duty Demand for Electric Vehicle Charging Infrastructure by Wood et al. (2023). These are based on modeling in There's No Place Like Home: Residential Parking, Electrical Access, and Implications for the Future of Electric Vehicle Charging Infrastructure by Ge et al. (2021).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Geospatial analysis of freight accessibility and job attraction: The role of interstate ramps, airports, ports, and rail

The number of jobs within an industry is significantly influenced by geographical location, with transportation infrastructure playing a key role. While previous research has largely focused on how access to jobs affects employment, less attention has been given to how transportation infrastructure impacts business operations and job attraction. Here, this study addresses this gap by examining how the ease of transporting products to key transportation facilities affects job numbers in freight-intensive industries. Using job data from the Longitudinal Employment Household Dynamics dataset at the Census Tract level, we applied a non-parametric model to assess the impact of proximity to interstate ramps, rail intermodals, ports, and airports. Our analysis revealed that closer transportation infrastructure generally has a greater impact on employment. Specifically, interstate ramps are crucial for attracting jobs, particularly in rural areas, while airport proximity is essential for industries dealing with high-value, time-sensitive goods, as seen notably in Massachusetts. The importance of transportation facilities varies considerably across states and industries. The findings and method in this study can be used by transportation agencies for freight planning.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

deadtrees.earth — An open-access and interactive database for centimeter-scale aerial imagery to uncover global tree mortality dynamics

Excessive tree mortality is a global concern and remains poorly understood as it is a complex phenomenon. We lack global and temporally continuous coverage on tree mortality data. Ground-based observations on tree mortality, e.g., derived from national inventories, are very sparse, and may not be standardized or spatially explicit. Earth observation data, combined with supervised machine learning, offer a promising approach to map overstory tree mortality in a consistent manner over space and time. However, global-scale machine learning requires broad training data covering a wide range of environmental settings and forest types. Low altitude observation platforms (e.g., drones or airplanes) provide a cost-effective source of training data by capturing high-resolution orthophotos of overstory tree mortality events at centimeter-scale resolution. Here, we introduce deadtrees.earth, an open-access platform hosting more than two thousand centimeter-resolution orthophotos, covering more than 1,000,000 ha, of which more than 58,000 ha are manually annotated with live/dead tree classifications. This community-sourced and rigorously curated dataset can serve as a comprehensive reference dataset to uncover tree mortality patterns from local to global scales using space-based Earth observation data and machine learning models. This will provide the basis to attribute tree mortality patterns to environmental changes or project tree mortality dynamics to the future. The open nature of deadtrees.earth, together with its curation of high-quality, spatially representative, and ecologically diverse data will continuously increase our capacity to uncover and understand tree mortality dynamics.

Citizen science↗
DOE OSTI2025

An open-access simulated earthquake ground-motion database for an M7 Hayward Fault earthquake in the San Francisco Bay Region

Comprehensive understanding of earthquake ground motions, particularly in the near-fault region of large-magnitude events, is limited by gaps in strong-motion data. This challenge is prominent in areas with high seismic hazard but infrequent large earthquakes where data is sparse and difficult to interpret. These data limitations lead to uncertainties in the development of site-specific ground motions, which are crucial for engineering risk assessments. To address these challenges, physics-based regional-scale ground-motion simulations have been developed. With the emergence of exaflop-scale computing ecosystems, it is now possible to simulate regional earthquake processes at unprecedented fidelity and generate the large number of fault rupture realizations necessary to characterize both intra- and inter-event ground-motion variability. This article introduces a new database of simulated earthquake ground motions, created for applications in earthquake engineering, earthquake planning, and emergency response. The inaugural version of the database features simulated ground motions for a magnitude 7 Hayward Fault earthquake in the San Francisco Bay Region (SFBR), using the EarthQuake SIMulation (EQSIM) simulation framework and the Graves–Pitarka kinematic rupture model. The aim is to provide high-fidelity, spatially dense, three-component motions generated on the Department of Energy’s (DOE) newest generation of graphics processing unit (GPU)-accelerated supercomputers. These motions are being made openly available to the engineering, scientific, and disaster planning communities. In addition, this work develops protocols for the efficient dissemination of these large data sets and emphasizes community engagement to build confidence in their application. This article discusses the methodology behind the data, underlying software verification and validation, scalable data management, and a user interface for data access. The goal is to facilitate widespread use and elicit expert feedback to maximize the utility and exploitation of simulated motions. While the initial focus is on the San Francisco Region, simulations for additional regions will be added as the DOE program progresses.

Simulated ground-motion database↗
DOE OSTI2024

Facile Access to Organostibines via Selective Organic Superbase Catalyzed Antimony‐Carbon Protonolysis

Abstract The selective formation of antimony‐carbon bonds via organic superbase catalysis under metal‐ and salt‐free conditions is reported. This novel approach utilizes electron‐deficient stibine, Sb(C 6 F 5 ) 3 , to give upon base‐catalyzed reactions with weakly acidic aromatic and heteroaromatic hydrocarbons access to a range of new aromatic and heteroaromatic stibines, respectively, with loss of C 6 HF 5 . Also, the significantly less electron‐deficient stibines, Ph 2 SbC 6 F 5 and PhSb(C 6 F 5 ) 2 smoothly underwent base‐catalyzed exchange reactions with a range of terminal alkynes to generate the stibines of formulae PhSb(C≡CPh) 2 , and Ph 2 SbC≡CR [R=C 6 H 5 , C 6 H 4 ‐NO 2 , COOEt, CH 2 Cl, CH 2 NEt 2 , CH 2 OSiMe 3 , Sb(C 6 H 5 ) 2 ], respectively. These formal substitution reactions proceed with high selectivity as only the C 6 F 5 groups serve as a leaving group to be liberated as C 6 HF 5 upon formal proton transfer from the alkyne. Kinetic studies of the base‐catalyzed reaction of Ph 2 SbC 6 F 5 with phenyl acetylene to form Ph 2 SbC≡CPh and C 6 HF 5 suggested the empirical rate law to exhibit a first‐order dependence with respect to the base catalyst, alkyne and stibine. DFT calculations support a pathway proceeding via a concerted σ‐bond metathesis transition state, where the base catalyst activates the Sb‐C 6 F 5 bond sequence through secondary bond interactions.

Culvyhouse, Jacob↗
DOE OSTI2024

Facile Access to Organostibines via Selective Organic Superbase Catalyzed Antimony‐Carbon Protonolysis

The selective formation of antimony-carbon bonds via organic superbase catalysis under metal- and salt-free conditions is reported. Here, this novel approach utilizes electron-deficient stibine, Sb(C 6 F 5 ) 3 , to give upon base-catalyzed reactions with weakly acidic aromatic and heteroaromatic hydrocarbons access to a range of new aromatic and heteroaromatic stibines, respectively, with loss of C 6 HF 5 . Also, the significantly less electron-deficient stibines, Ph 2 SbC 6 F 5 and PhSb(C 6 F 5 ) 2 smoothly underwent base-catalyzed exchange reactions with a range of terminal alkynes to generate the stibines of formulae PhSb(C≡CPh) 2 , and Ph 2 SbC≡CR [R=C 6 H 5 , C 6 H 4 -NO 2 , COOEt, CH 2 Cl, CH 2 NEt 2 , CH 2 OSiMe 3 , Sb(C 6 H 5 ) 2 ], respectively. These formal substitution reactions proceed with high selectivity as only the C 6 F 5 groups serve as a leaving group to be liberated as C 6 HF 5 upon formal proton transfer from the alkyne. Kinetic studies of the base-catalyzed reaction of Ph 2 SbC 6 F 5 with phenyl acetylene to form Ph 2 SbC≡CPh and C 6 HF 5 suggested the empirical rate law to exhibit a first-order dependence with respect to the base catalyst, alkyne and stibine. DFT calculations support a pathway proceeding via a concerted σ-bond metathesis transition state, where the base catalyst activates the Sb-C 6 F 5 bond sequence through secondary bond interactions.

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

Metal–Organic Frameworks at the Edge of Stability: Mediating Node Distortion to Access Metastable Nanoparticle Polymorphs

Metal-organic frameworks (MOFs) are emerging as unconventional precursors for nanoparticle synthesis, with potential to leverage their tunable structures and chemistry to achieve nanomaterials with structures and compositions inaccessible via traditional synthetic routes. Here we use in situ synchrotron X-ray diffraction and pair distribution function (PDF) measurements to investigate how the dynamic structure of MOFs at the edge of stability influences their transformation into different metastable polymorphs. Our study reveals that the local structural features of metal-oxo MOF nodes at elevated temperatures are linked to the resulting nanoparticle structures formed under mild conditions. Focusing on the titanium-based MOF MIL-125, we demonstrate that manipulating the chemical environment to facilitate transformation of the Ti8 node geometry promotes formation of metastable, nanometer-scale TiO2 brookite rather than the more common anatase and rutile TiO2 polymorphs typically produced through MOF pyrolysis at high temperature. These findings highlight the potential to harness the MOF topology and chemical environment to design and control node distortions and enable access to exotic metastable nanoparticle states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A One‐Pot Biocatalytic Cascade to Access Diverse l ‐Phenylalanine Derivatives from Aldehydes or Carboxylic Acids

Abstract Nonstandard amino acids (nsAAs) that are l ‐phenylalanine derivatives with aryl ring functionalization have long been harnessed in natural product synthesis, therapeutic peptide synthesis, and diverse applications of genetic code expansion. Yet, to date, these chiral molecules have often been the products of poorly enantioselective and environmentally harsh organic synthesis routes. Here, we reveal the broad specificity of multiple natural pyridoxal 5′‐phosphate (PLP)‐dependent enzymes, specifically an l ‐threonine transaldolase, a phenylserine dehydratase, and an aminotransferase, toward substrates that contain aryl side chains with diverse substitutions. We exploit this tolerance to construct a one‐pot biocatalytic cascade that achieves high‐yield synthesis of 18 diverse l ‐phenylalanine derivatives from aldehydes under mild aqueous reaction conditions. We demonstrate the addition of a carboxylic acid reductase module to this cascade to enable the biosynthesis of l ‐phenylalanine derivatives from carboxylic acids that may be less expensive or less reactive than the corresponding aldehydes. Finally, we investigate the scalability of the cascade by developing a lysate‐based route for preparative‐scale synthesis of 4‐formyl‐ l ‐phenylalanine, a nsAA with a bio‐orthogonal handle that is not readily market‐accessible. Overall, this work offers an efficient, versatile, and scalable route with the potential to lower manufacturing costs and democratize synthesis for many valuable nsAAs.

Anderson, Shelby R. [Department of Chemical and Bi↗
DOE OSTI2025

Effect of stress on Laves phase precipitation in creep ruptured Grade 92 ferritic martensitic steel characterized by a novel accessible method

At high temperature conditions relevant to fossil and nuclear energy plants, Laves phase (Fe 2 X, X=Mo, W) precipitation is observed in common ferritic martensitic (FM) structural steels, with various reported effects on creep behavior. Despite being valuable metrics to correlate with mechanical properties and other precipitate phases, the volume fraction and number density of Laves phase precipitates has been difficult to quantify accurately using common techniques such as transmission electron microscopy (TEM) due to the relatively large size (∼0.25 μm) and low number density (∼10 11 cm −3 ) of Laves precipitates. Here, to address this characterization challenge, we developed and demonstrated a high-throughput and widely accessible method to quantify the volume fraction and number density of the Laves phase based on scanning electron microscope (SEM) images with a backscattered electron signal and the information depth (ID) of backscattered electrons. We applied this new technique in creep ruptured Grade 92 FM steel to study the effect of Laves phase on creep properties and determine the influence of stress on Laves phase precipitation. The quantitative accuracy of the SEM-based volume fraction and number density values was verified using synchrotron high energy X-ray diffraction and serial sectioning tomography. Stress did not significantly affect the Laves phase size or volume fraction during creep testing at 550 – 650°C and stress levels of 90 – 260 MPa (vs. unstressed conditions). Conversely, a moderate but statistically significant stress-enhanced increase in Laves phase number density, corresponding to an increase in nucleation rate, occurred during creep exposure above 110 MPa.

Creep↗
DOE OSTI2024

Bayesian Optimization for Anything (BOA): An open-source framework for accessible, user-friendly Bayesian optimization

We introduce Bayesian Optimization for Anything (BOA), a high-level Bayesian Optimization (BO) framework and model wrapping toolkit, which presents a novel approach to simplifying BO, with the goal of making it more accessible and user-friendly, particularly for those with limited expertise in the field. BOA addresses common barriers in implementing BO, focusing on ease of use, reducing the need for deep domain knowledge, and cutting down on extensive coding requirements. A notable feature of BOA is its language-agnostic architecture, which facilitates broader application in various fields and to a wider audience. We showcase BOA's application through three examples: a high-dimensional optimization with parameters of the SWAT+ watershed model, a highly parallelized optimization of this intrinsically non-parallel model, and a multi-objective optimization of the FETCH Tree-Crown Hydrodynamics model. Furthermore, these test cases illustrate BOA's effectiveness in addressing complex optimization challenges in diverse scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Lowering the barrier to access information-rich transient kinetic data for machine learning methods

Transient kinetic data contain a wealth of information about intrinsic features of a catalyst as well as the reaction mechanism. Currently, high volume transient data is underutilized, and data science methods could both increase the value of information that can be extracted from this data, integrate experimental with theoretical data sources, and accelerate the pace of catalyst technology advancement. Transient kinetic characterizations with simple probe molecules exhibiting reversible adsorption, irreversible adsorption and bulk-surface diffusion are presented as training components for similar experiments with more complex surface reactions. In conclusion, by increasing the availability and accessibility of transient kinetic data through details of its structure and acquisition, we aim to decrease the barrier for data scientists to apply machine learning methods to this valuable data source.

Catalysis↗
DOE OSTI2025

Laser ablation of high-loading Li-ion battery electrodes improves accessible capacity and cycle life for Behind-the-Meter Storage

Adoption of Behind-the-Meter Storage (BTMS) requires design of batteries that enable high safety, long cycle life, and low cost at the system level. Pairing Li 4 Ti 5 O 12 (LTO) with LiMn 2 O 4 (LMO) achieves targets related to safety and cycle life, but these materials' low energy densities contribute to higher cost at the system scale. Increasing electrode loading is a simple approach to improve energy density, but comes with a trade-off in electrode utilization due to long, tortuous Li + diffusion pathways. Here, laser ablation is used to microstructure (pattern) high-loading electrodes to enhance electrode performance through improved Li + diffusion pathways. Four cell types, comprising combinations of standard or patterned anode and cathode, were prepared to evaluate the effects of laser ablation at each electrode. A rate test shows that patterning electrodes enhances active material utilization at ≳1C rates. Patterning the cathode yields the most benefit, as cells with a patterned cathode demonstrate a ~20% higher accessible capacity than those without at 1.4C. Additionally, 1C capacity retention of cells with patterned cathode (91% through 3000 cycles) is significantly improved over cells with only the anode patterned (64%) and non-patterned electrodes (50%). Characterization of post-mortem cells before and after refreshing their electrolyte suggests that 1C capacity retention is improved by mitigation of electrode "dry-out". We hypothesize that the microstructure acts as a reservoir of additional electrolyte, or a path for gas to escape, so that active material remains wetted throughout long-term cycling, and/or the microstructure may reduce localized, gas-forming overpotentials in the high-loading electrode.

25 ENERGY STORAGE↗