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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

In Situ High-Temperature Ultrafast Electron Diffraction through Integrated Furnace and MEMS Platforms

Temperature fundamentally governs phase stability, defect evolution, and transport behavior in materials. Despite its central role, direct measurements of structural evolution at elevated temperatures on ultrafast timescales have remained limited. Here, we report the design, integration, and validation of 2 complementary in situ heating platforms that substantially extend the thermal operating range of ultrafast electron diffraction (UED). A compact furnace-type heating stage enables stable diffraction measurements from room temperature to 800 K with ±0.1 K stability under ultrahigh vacuum, achieved through multi-sensor feedback control, dual air-cooling channels, and a thermally isolated motion stage. In parallel, a microelectromechanical system (MEMS)-based heating platform provides rapid thermal response and access to extreme temperatures ≥1,373 K with ±0.1 K stability over hundreds-micrometer regions while supporting simultaneous electrical biasing for electrothermal coupling studies. Absolute temperature calibration is established using diffraction-based thermometry via aluminum lattice expansion and independently validated through in situ melting of bismuth thin films. UED measurements further reveal pronounced temperature-dependent nonequilibrium lattice dynamics in bismuth, including modifications to electron–phonon coupling and Debye–Waller behavior, as well as enhanced ultrafast diffuse scattering in aluminum at elevated temperatures. Together, these developments establish a practical framework for quantitative, time-resolved studies of temperature-driven kinetics and nonequilibrium structural dynamics under extreme thermal environments.

Bai, Qianqian [Chinese Academy of Sciences (CAS), ↗
DOE OSTI2025

Ultracoherent superconducting cavity-based multiqudit platform with error-resilient control

Superconducting radio-frequency (SRF) cavities offer a promising platform for quantum computing due to their long coherence times, yet integrating nonlinear elements like transmons for control often introduces additional loss. We report a multimode quantum system based on a 2-cell elliptical shaped SRF cavity, comprising two cavity modes weakly coupled to an ancillary transmon circuit, designed to preserve coherence while enabling efficient control of the cavity modes. We mitigate the detrimental effects of the transmon decoherence through careful design optimization that reduces transmon-cavity couplings and participation in the dielectric substrate and lossy interfaces, to achieve single-photon lifetimes of 20.6 ms and 15.6 ms for the two modes, and a pure dephasing time exceeding 40 ms. This marks an order-of-magnitude improvement over prior 3D multimode memories. Leveraging sideband interactions and novel error-resilient protocols, including measurement-based correction and post-selection, we achieve high-fidelity control over quantum states. This enables the preparation of Fock states up to $N = 20$ with fidelities exceeding 95%, the highest reported to date to the authors' knowledge, as well as two-mode entanglement with an estimated coherence-limited fidelities of 99.9% after post-selection. These results establish our platform as a robust foundation for quantum information processing, allowing for future extensions to high-dimensional qudit encodings.

Kim, Taeyoon [Fermilab; Northwestern U.]↗
DOE OSTI2025

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

We present hls4ml, a free and open-source platform that translates machine learning (ML) models from modern deep learning frameworks into high-level synthesis (HLS) code that can be integrated into full designs for field-programmable gate arrays (FPGAs) or application-specific integrated circuits (ASICs). With its flexible and modular design, hls4ml supports a large number of deep learning frameworks and can target HLS compilers from several vendors, including Vitis HLS, Intel oneAPI and Catapult HLS. Together with a wider eco-system for software-hardware co-design, hls4ml has enabled the acceleration of ML inference in a wide range of commercial and scientific applications where low latency, resource usage, and power consumption are critical. In this paper, we describe the structure and functionality of the hls4ml platform. The overarching design considerations for the generated HLS code are discussed, together with selected performance results.

FOS: Computer and information sciences↗
DOE OSTI2024

Gains in operational flexibility, safety margins, and cost efficiencies via integrated Plant Reload Optimization platform

The U.S. Department of Energy Light Water Reactor Sustainability Program Risk-Informed Systems Analysis Pathway Plant Reload Optimization Project aims to develop an integrated, comprehensive framework offering an all-in-one solution for reload evaluations with a special focus on optimizing core design. Optimizing the fuel loading pattern is one of the most important considerations in reducing the amount of new fuel used in the core. Due to thousands of possible core configuration options, finding optimal solutions is an unachievable task for a human. The Plant ReLoad Optimization platform, which supports artificial-intelligence-based reactor core designing, is now fully capable of handling realistic problems. The Plant ReLoad Optimization platform development project aims to build a reactor core design tool that includes reactor safety and fuel performance analyses and uses artificial intelligence to support the optimization of core design solutions. The NSGA-II (Non-dominated Sorting Genetic Algorithm II) optimizer was developed and tested within RAVEN (Risk Analysis and Virtual ENvironment) to handle many constraints by using an augmented objectives methodology. The demonstration was performed with constrained multiobjective optimization of a 17 × 17 pressurized-water reactor core loading patterns to minimize fuel cost and maximize fuel cycle length.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

SEED Platform for Building Performance Standards Implementation Guide (Spanish Translation)

This guide provides an overview of the Standard Energy Efficiency Data (SEED) Platform. The SEED Platform developed by the U.S. Department of Energy (DOE) to provide a low-cost, user-friendly tool for jurisdictions to launch and manage energy benchmarking and Building Performance Standard (BPS) programs. It has been translated into Spanish. This is the Spanish translation of NREL/FS-5500-90691.

benchmarking↗
DOE OSTI2024

SEED Platform for Building Performance Standards Implementation Guide (French Translation)

This guide provides an overview of the Standard Energy Efficiency Data (SEED) Platform. The SEED Platform developed by the U.S. Department of Energy (DOE) to provide a low-cost, user-friendly tool for jurisdictions to launch and manage energy benchmarking and Building Performance Standard (BPS) programs. It has been translated into Spanish. This is the French translation of NREL/FS-5500-90691.

benchmarking↗
DOE OSTI2024

SEED Platform for Building Performance Standards Implementation Guide (Arabic Translation)

This guide provides an overview of the Standard Energy Efficiency Data (SEED) Platform. The SEED Platform developed by the U.S. Department of Energy (DOE) to provide a low-cost, user-friendly tool for jurisdictions to launch and manage energy benchmarking and Building Performance Standard (BPS) programs. It has been translated into Spanish. This is the Arabic translation of NREL/FS-5500-90691.

benchmarking↗
DOE OSTI2024

SEED Platform for Building Performance Standards Implementation Guide (Mandarin Translation)

This guide provides an overview of the Standard Energy Efficiency Data (SEED) Platform. The SEED Platform developed by the U.S. Department of Energy (DOE) to provide a low-cost, user-friendly tool for jurisdictions to launch and manage energy benchmarking and Building Performance Standard (BPS) programs. It has been translated into Spanish. This is the Mandarin translation of NREL/FS-5500-90691.

benchmarking↗
DOE OSTI2025

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

We present hls4ml, a free and open-source platform that translates machine learning (ML) models from modern deep learning frameworks into high-level synthesis (HLS) code that can be integrated into full designs for field-programmable gate arrays (FPGAs) or application-specific integrated circuits (ASICs). With its flexible and modular design, hls4ml supports a large number of deep learning frameworks and can target HLS compilers from several vendors, including Vitis HLS, Intel oneAPI and Catapult HLS. Together with a wider eco-system for software-hardware co-design, hls4ml has enabled the acceleration of ML inference in a wide range of commercial and scientific applications where low latency, resource usage, and power consumption are critical. In this paper, we describe the structure and functionality of the hls4ml platform. The overarching design considerations for the generated HLS code are discussed, together with selected performance results.

Schulte, Jan-Frederik [Purdue U.] (ORCID:000000034↗
DOE OSTI2026

Toward the Neutrino Discovery Platform: An Auditable, Uncertainty-Bearing Toolchain for MINERvA Open-Data Cross-Section Analysis

The Neutrino Discovery Platform (NDP) aims to accelerate DUNE-era science by making the neutrino program's existing datasets analyzable through fast, reproducible, and auditable workflows. We report a working version of two of its layers, data curation and agentic orchestration, built and tested end to end on MINERvA open data. The guiding lesson throughout is that a cross section is a measurement, and not just a plotted shape, only if it carries a defensible systematic-uncertainty budget, a trustworthy unfolding, and a reproducible record. Using a single medium-energy playlist pair from the MINERvA open-data release (about $2.05\times10^{17}$ protons on target of data), we first reproduced the shapes of two published charged-current inclusive $\nu_\mu$ measurements through a complete extraction ladder: selection, background subtraction, D'Agostini unfolding, efficiency correction, and flux normalization. These shape-level reproductions ran and tracked the published results, but they lacked the systematic-uncertainty machinery that defines a MINERvA cross section. To supply it, we vendored and built the MINERvA Analysis Toolkit and developed a many-universe systematic-uncertainty tool that produces a portable covariance artifact, a parallel event-loop runner, and a per-run auditability harness. Validated against a published covariance release, the toolchain reproduces the released statistical, flux, and muon-energy-scale terms and shows that they account for roughly 63\% of the total variance, with the remainder unreleased. Using this same infrastructure, we then performed a measurement of our own design, the hadronic recoil-energy distribution of low-energy ($E_\nu<2.5$~GeV) charged-current inclusive events, and found data/simulation shape agreement of $\chi^2/\mathrm{ndf}=1.26$. Together these results show that the platform supports original physics and not only reproductions.

Breaux, Auto [Tulane U. (main)]↗
DOE OSTI2024

Equitable Energy Metrics for Integration into Building Performance Standard Tracking Platforms: Preprint

Building Performance Standards (BPS) are being adopted globally and in the United States of America, where 14 different states and jurisdictions have a policy in place and many others are under development (Department of Energy (DOE) 2023). Accurate and equitable data sources are essential to make informed decisions about focusing investment on upgrading buildings to meet jurisdictional goals. There have been multiple new tools developed related to Energy Equity and Environmental Justice (EEEJ) and the resulting datasets need to be integrated into large building port-folios for quick access and better scalability. Integrating EEEJ data in a user-friendly format can help decision makers more quickly assess impacts and analyze the multitude of potentially significant metrics for which there is not yet consensus. In the U.S. and Canada, many BPS ordinances rely primarily on ENERGY STAR Portfolio Manager (ESPM) to capture building characteristics and energy and water consumption data. These datasets can then be imported into city-specific building tracking tools like the Standard Energy Efficiency Data Platform (SEED). Crucially, BPS decision makers require an efficient means of identifying buildings in priority communities to effectively allocate resources and funding. This process must integrate seamlessly with existing jurisdictional toolsets for optimal utility. This paper will demonstrate, for the case of Washington D.C.'s (the District) data, a workflow that provides actionable data for building upgrade investment prioritization in disadvantaged communities.

BPS↗
DOE OSTI2025

Freestanding BaTiO 3 ‐Au Vertically Aligned Nanocomposite toward Flexible Multi‐Sensing Platform

Abstract Flexible and wearable sensors show enormous potential for personalized healthcare devices by real‐time monitoring of an individual's health. Typically, a single functional material is selected for one sensor to sense a particular physical signal while multiple materials will be selected for multi‐mode sensing. Vertically aligned nanocomposites (VANs) have recently demonstrated various material combinations and novel coupled multifunctionalities that are hard to achieve in any single‐phase material alone, including multiphase multiferroics, magneto‐optic coupling, and strong magnetic and optical anisotropy. Integrating these novel VANs into wearable sensors shows enormous potential in multi‐mode sensing owing to their multifunctional nature. In this work, the transfer of VANs onto polydimethylsiloxane as a novel flexible chemical and pressure sensor is demonstrated. For this demonstration, the classical BaTiO 3 ‐Au VAN with combined plasmonic and piezoelectric properties is used to demonstrate a multi‐sensing mechanism. A thin water‐soluble buffer of Sr 3 Al 2 O 6 serves as a buffer layer for the epitaxial growth and transfer process. The electrical output based on the piezoelectric responses and identifying 4‐mercaptobenzoic acid by surface‐enhanced Raman spectroscopy reveal great potential for free‐standing VANs in a wearable multifunctional sensing platform.

Tsai, Benson Kunhung [School of Materials Engineer↗
DOE OSTI2026

Highly Anisotropic Quasi‐Direct Organic Metal Halide Hybrids: A Platform for Polarization‐Sensitive Optoelectronics

Low-dimensional organic–inorganic metal halide hybrids (OMHHs) exhibit remarkable optical properties and enhanced environmental stability. We investigate a 1D OMHH with formula C 4 N 2 H 14 PbBr 4 , consisting of Pb–Br chains separated by organic cations, which shows a large Stokes shift (0.83 eV) and broadband emission. Through first-principles calculations and polarized Raman spectroscopy, we characterize the material's vibrational properties and identify the specific phonon modes that drive exciton self-trapping. Our novel GW/Bethe-Salpeter equation force formalism reveals that low-frequency phonons (∼ 100 cm −1 , primarily involving Pb–Br motions) couple strongly with excitons, with a remarkably high Huang-Rhys factor of 137 ± 4, and gives a pathway for ultrafast structural analysis during the absorption process. This phonon-exciton coupling mechanism explains the material's broadband emission and provides a pathway for controlling optical properties through vibrations and for tuning vibrations through optical excitations. The material also exhibits highly anisotropic optical properties and electronic transport, with bands that are dispersive along the Pb–Br chains but nearly flat in perpendicular directions, resulting in direction-dependent electrical conductivity that is calculated to be an order of magnitude higher along the chain direction and consistent with measurements. These combined properties make this system an excellent platform for polarization-sensitive optoelectronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A Chemoselective and Stereodivergent Platform of Heme‐Nitrene Transferases to Access Chiral Aryl‐β‐Amino Esters and An Investigation of the Sequence‐Activity Landscape

Engineered biocatalysts can utilize nitrene precursors to access enantioenriched amination products, yet they have not been applied to produce valuable, enantiomerically enriched noncanonical β-amino esters. Current approaches to synthesizing β-amino acids rely on pre-oxidized precursors and multistep synthetic approaches involving various protecting groups. We engineered a platform of heme enzymes for stereoselective C–H bond amination of readily available carboxylic ester derivatives to install primary amines. A directed evolution campaign coupled with sequencing of over 1000 variants enabled us to develop engineered variants that use either O-pivaloylhydroxylamine triflic acid (PONT) or hydroxylamine hydrochloride (H 2 NOH∙HCl) as aminating reagents. An analysis of the resulting sequence–activity dataset revealed additional improvements that could be made to the final variant, highlighting the utility of sequencing data to guide future steps in directed evolution campaigns. Furthermore, the evolved nitrene transferases expand the scope of accessible chiral β-amino acid building blocks for peptidomimetic applications and provide new starting points for the design and synthesis of enantioenriched β-amino acid motifs.

amino ester building blocks↗
DOE OSTI2026

Latent Catalysis as a Platform for Accessing Diverse Material Properties in Vat Photopolymerization 3D Printing

Vat photopolymerization (VP) 3D printing is an attractive strategy to manufacture customized polymer parts. The properties of printed materials are limited by the need to employ a low viscosity liquid resin and achieve rapid polymerization kinetics. To circumvent this limitation, dual‐cure methods have been developed using reagents embedded in the liquid resin formulation; however, the reagent‐based approach requires the discovery and optimization of new chemistry for each desired material. Here, in this work, we demonstrate a catalytic, dual‐cure platform that enables access to both Nylon‐6 and polyester interpenetrating networks through VP 3D printing under a universal approach. Structure–reactivity relationships of the latent NHC catalysts led to the identification of a magnesium chloride–NHC adduct as a latent catalyst that is orthogonal to radical polymerization and can be unmasked at elevated temperatures post‐printing to initiate ring‐opening polymerization of lactones and lactams. This strategy results in access to semicrystalline materials, which are a challenging morphology to access via VP 3D printing, that have attractive mechanical properties and can be printed at high resolution. This work represents the first photochemical‐based 3D printing of Nylon‐based materials and demonstrates the value of catalytic approaches to access new material properties in VP 3D printing.

Colliver, Cali N. [University of North Carolina, C↗
DOE OSTI2026

A Circular and Tacticity‐Independent Crystalline Mono‐Substituted Nylon‐6 Platform: Unexpected Large Positional Effects on Crystallizability and Performance

Seeking recyclable, more sustainable alternatives to nylon 6 has drawn much attention, but achieving its variants with both crystallinity and enhanced recyclability still remains a challenge. Here, by utilizing bio-derivable mono-substituted racemic lactam monomers, we reveal surprisingly large effects of methyl substitution positions on the nylon-6 backbone on crystallizability, thermomechanical performance, and recyclability of the resulting atactic nylon-6 variants. While γ-methyl substitution gives an amorphous nylon, all other four methyl-substitution positions (α, β, δ, and ε) afford, unexpectedly, crystalline nylons with melting temperatures ranging from 145°C to 200°C and tunable mechanical performance from being stiff and strong (α, ε) to ductile (β, δ). Investigations reveal that the crystallinity of atactic nylons arises independently of stereoregularity, which is driven by the amide backbone with robust hydrogen-bonding interactions and countered by the chain flexibility regulated by the substitution position. These nylons can be chemically recycled back to their parent monomers with high isolated yields up to 92%, enabling a circular, tacticity-independent crystalline nylon platform.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗