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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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201 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Using scalable computer vision to automate high-throughput semiconductor characterization

Abstract High-throughput materials synthesis methods, crucial for discovering novel functional materials, face a bottleneck in property characterization. These high-throughput synthesis tools produce 10 4 samples per hour using ink-based deposition while most characterization methods are either slow (conventional rates of 10 1 samples per hour) or rigid (e.g., designed for standard thin films), resulting in a bottleneck. To address this, we propose automated characterization (autocharacterization) tools that leverage adaptive computer vision for an 85x faster throughput compared to non-automated workflows. Our tools include a generalizable composition mapping tool and two scalable autocharacterization algorithms that: (1) autonomously compute the band gaps of 200 compositions in 6 minutes, and (2) autonomously compute the environmental stability of 200 compositions in 20 minutes, achieving 98.5% and 96.9% accuracy, respectively, when benchmarked against domain expert manual evaluation. These tools, demonstrated on the formamidinium (FA) and methylammonium (MA) mixed-cation perovskite system FA 1−x MA x PbI 3 , 0 ≤ x ≤ 1, significantly accelerate the characterization process, synchronizing it closer to the rate of high-throughput synthesis.

Science & Technology - Other Topics↗
NASA NTRS2026

Developing a Pyrolysis Gas Thermal Blocking Model for Reentry Demise

In NASA’s Object Reentry Survival Analysis Tool (ORSAT), aerodynamic drag and aerothermal heating coefficients are computed for each of the free-molecular, continuum, and transitional flow regimes using analytical and semi-analytical methods. These heating coefficients were derived for typical metallic materials that melt and do not have a strong gas-phase contribution to the flow in the boundary layer. Modern satellites typically feature fiber-reinforced polymer (FRP) components, such as solar array booms, facesheets of sandwich panels, or overwraps for composite-overwrapped pressure vessels (COPV). These FRP materials do not behave the same as metals in the reentry environment, but instead will pyrolyze and develop significant volumes of gas into the boundary layer. Accurately predicting the reentry demise of FRP components is critical to assessing the reentry casualty risk for modern spacecraft. Research in recent years has shown that this demisability can depend heavily on how the expulsion of gaseous pyrolysis products through the outer surface of the material affects the heat flux at the surface. The ODPO has been developing a reduced-order model of the effect of pyrolysis gas blowing on the heat flux based on correlations between a blowing factor and a non-dimensional heat flux to be incorporated in the upcoming version 7.3 of the Object Reentry Survivability Analysis Tool (ORSAT). This presentation discusses the progress of this development project and the challenges remaining for generalizing the model across families of FRP materials.

Benton Greene↗
DOE OSTI2026

Frontier Job-Centric Telemetry Dataset

Comprehensive analysis of high-performance computing (HPC) systems requires linking workload execution to system behavior. This kind of analysis is vital for diagnosing performance issues, managing capacity, detecting anomalous workloads, and understanding how applications interact with system hardware. This job-centric telemetry dataset unifies scheduler job records with node-level measurements, enabling direct association between workloads and their corresponding power, thermal, and performance characteristics. It contains sanitized, scheduler related metadata for 152,400 individual jobs that ran on the Frontier supercomputer and ended on selected days throughout 2024 and 2025, a subpopulation of ~6.8% of the total number of allocated jobs with non-zero run time on the system over that same period. Each is linked with files that contain telemetry time series records of the power utilization and temperature behavior of its allocated nodes and their processors during the run time of the job. Where available, a portion of the job files also contain network performance time series. Jobs are sampled from select days that reflect normal levels of user activity and possess job size distributions with large numbers of leadership class jobs (>20% of Frontier nodes). Jobs in this dataset attempt to best represent successful user workflows.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Netload Range Cost Curves for Coordinated Transmission-Distribution Planning Under DER Growth Uncertainty

The increasing penetration of distributed energy resources (DERs) requires better coordination between transmission and distribution (T&D) planning to ensure system security and cost efficiency. However, misaligned planning horizons, computational burdens, and privacy concerns hinder effective coordination, leading to either underutilized resources caused by overinvestments or reliability risks due to underinvestment. To address this challenge, we introduce netload range cost curves (NRCCs), a novel approach for managing long-term DER growth uncertainty through T&D coordination, while preserving existing data-sharing and regulatory structures. NRCCs provide pairs of (i) peak substation netload guarantees and (ii) corresponding distribution upgrade options and costs, enabling their seamless integration into transmission planning workflows. To compute NRCCs efficiently, we develop a transmission-aware distribution network planning (TADNP), which is subsequently integrated to an iterative computation procedure. These NRCCs are then embedded into an NRCC-informed transmission planning model to enable resource-efficient coordination. We illustrate our proposed approach with a case study based on realistic distribution and transmission systems in the San Francisco Bay Area, California. Our results indicate the possibility of dramatic savings in transmission investments by incorporating the proposed NRCC-integrated T&D coordination framework.

Li, Yujia↗
NASA NTRSDate not supplied

Early Progress Toward the Feasibility of the Centrifugal Nuclear Thermal Rocket

The Centrifugal Nuclear Thermal Rocket (CNTR) is a Nuclear Thermal Propulsion (NTP) concept designed to heat propellant directly by the reactor fuel. The primary difference between the CNTR concept and traditional NTP systems is that rather than using traditional solid fuel elements, the CNTR uses liquid fuel with the liquid contained in rotating cylinders by centrifugal force. If the concept can be successfully realized, the CNTR would have a high specific impulse (~1800 seconds) at high thrust, which may enable (i) viable near-term human Mars exploration by reducing round-trip times to 420 days and (ii) direct injection orbits for scientific missions to the Solar System outer planets and potentially Kuiper Belt objects. The CNTR could also use storable propellants such as ammonia, methane, or hydrazine at an Isp of ~900 seconds, enabling long-term in-space storage of a dormant system. Significant engineering challenges must be addressed to establish the technical viability of the CNTR. Research is presently underway to determine resolutions for these engineering challenges. In particular, research has begun on the analytical modeling and simulation of the two-phase heat transfer between the liquid metallic uranium fuel and the gaseous propellant. A paper was presented at the 2021 IAC which described these challenges and the study plan to address them. This paper describes the analytical and experimental progress to date toward resolving these challenges and establishing the engineering feasibility of the CNTR technology.

Nuclear Thermal Propulsion↗
DOE OSTI2024

Resonant Metasurfaces with Van Der Waals Hyperbolic Nanoantennas and Extreme Light Confinement

This work reports on a metasurface based on optical nanoantennas made of van der Waals material hexagonal boron nitride. The optical nanoantenna made of hyperbolic material was shown to support strong localized resonant modes stemming from the propagating high-k waves in the hyperbolic material. An analytical approach was used to determine the mode profile and type of cuboid nanoantenna resonances. An electric quadrupolar mode was demonstrated to be associated with a resonant magnetic response of the nanoantenna, which resembles the induction of resonant magnetic modes in high-refractive-index nanoantennas. The analytical model accurately predicts the modes of cuboid nanoantennas due to the strong boundary reflections of the high-k waves, a capability that does not extend to plasmonic or high-refractive-index nanoantennas, where the imperfect reflection and leakage of the mode from the cavity complicate the analysis. In the reported metasurface, excitations of the multipolar resonant modes are accompanied by directional scattering and a decrease in the metasurface reflectance to zero, which is manifested as the resonant Kerker effect. Van der Waals nanoantennas are envisioned to support localized resonances and can become an important functional element of metasurfaces and transdimensional photonic components. By designing efficient subwavelength scatterers with high-quality-factor resonances, this work demonstrates that this type of nanoantenna made of naturally occurring hyperbolic material is a viable substitute for plasmonic and all-dielectric nanoantennas in developing ultra-compact photonic components.

Chemistry↗
DOE OSTI2025

Exploiting ν-dependence of projected energy correlators in HICs

We extend the recently derived factorization formula for energy-energy correlators to study the analytic structure of general ν-point projected energy correlators in heavy ion collisions. The ν-point projected energy correlators (or, ν-correlators) are an analytically continued family of the integer N-point projected energy correlators, which probe correlations between N final-state particles. By tracking the largest separation (χ) between the N particles, in vacuum, their structure is closely related to the DGLAP splitting functions and exhibits a classical scaling behavior ∼ 1/χ which is modified by resummation through the anomalous dimensions. We show that, in a thermal medium, the ν-correlators display non-trivial angular scaling already at the leading order in perturbation theory. We find that for non-integer values, particularly ν < 1, medium-induced jet function is enhanced compared to ν > 1. This is particularly manifested in the ratios of ν-correlators with respect to the two-point energy correlator, which encodes intrinsic angular information for ν < 1 when compared to large ν values. Moreover, for small-ν values, the ν-correlators appear to saturate at ν = 0.01 . We further confirm our leading-order numerical computations against simulated events from JEWEL for the parton-level production cross-section. Finally, we qualitatively discuss the effect of BFKL resummation for various values of ν.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2026

Assessment of Near-Angle Scatter on Exo-Earth Coronagraphy

Near-Angle Scatter (NAS) of the host star’s light into the coronagraph dark hole may limit the ability of a potential Habitable Worlds Observatory (HWO) to detect and characterize an Earth-like planet around a Sun-like star. This paper summarizes a 5-year investigation of the impact of NAS on high-contrast coronagraphy. Science requirements were flowed down to a draft flux ratio noise ratio (FRN) error budget with allocations for NAS. The modeled sources of NAS include correlated (low and mid-spatial) surface structure, uncorrelated surface microroughness and coating structure, particulate contamination, micrometeoroid impacts and polarization leakage. The paper develops specifications for these sources of scattered light that meet their FRN error budget allocations, distinguishing between scatter that can and cannot be modulated. The development process utilizes an analytical expression that predicts scatter throughput into the dark hole based on BRDF/BSDF. Using this relationship, Photon Engineering performed a FRED® straylight analysis of the HWO EAC-1 (Exploratory Analytical Case #1) coronagraph to parametrically study predicted scattered light contrast in the dark hole. The model revealed that primary mirror microroughness or contamination is not a significant source of scattered light; the most critical surfaces are the smallest and those located closest to the coronagraph focal plane mask. The assessment found that uncorrelated microstructure, contamination, and micrometeoroid impacts require more investigation and potential significant sources of unmodulated scattered light, and highlights that slow thermal wavefront drift is an order of magnitude more impactful than fast mechanical jitter.

coronagraphy↗
NASA NTRS2026

PROTECT: Production and Reuse of Thermally Efficient Ceramic Thermal Protection Systems

PROTECT (Production and Reuse Of Thermally Efficient Ceramic TPS) is a NASA Early Career Initiative focused on developing the next generation of reusable ceramic thermal protection systems (TPS). This project addresses key challenges in TPS design, including temperature capability, thermal stability, and refurbishment time, by integrating novel material development with predictive modeling. Leveraging enhanced capabilities in NASA’s Porous Microstructure Analysis (PuMA) software, PROTECT introduces new modeling tools to predict the thermal and mechanical behavior of fibrous ceramic materials. These tools enable accurate prediction of performance metrics such as thermal conductivity and structural integrity, reducing reliance on costly physical testing. Preliminary advances in these areas will be presented. To support model validation, PROTECT is building a comprehensive database of raw material properties using advanced characterization techniques, including micro computed tomography (CT) scanning in collaboration with the University of Illinois Urbana-Champaign (UIUC). The presentation will detail the sampling workflows and analysis methods used to generate this detailed microstructural data and how it is used to develop improved models in PuMA. This multi-center collaboration, spanning NASA (JSC, ARC, KSC, GRC), Oak Ridge National Laboratory, UIUC, and SpaceX, is developing tailored TPS solutions for LEO, lunar, and Martian missions. By bridging heritage systems with the demands of modern spaceflight, PROTECT contributes to the advancement of reusable TPS technologies for future exploration missions.

Propulsion, Refractory, and Coating Materials↗
DOE OSTI2026

Interactions Between Climate Policy and Technology-influenced Travel Behavior: Mitigating Induced Demand from CACC

Advances in vehicle technology have influenced the development of automated vehicle systems, where vehicles that do not require human intervention are already deployed in the roadway networks. While these advances are proved to increase roadway safety and highway capacity, more research is needed to understand the long-term and regional-level impacts on mobility, land use, energy consumption, and emissions. This study proposes a multi-model approach to analyze the effect of vehicle automation and deep decarbonization policies over a period from 2020 to 2040 in Austin, Texas. We use the Global Change Analysis Model (GCAM) to develop internally the scenarios that are then passed to the SMART Mobility modeling workflow, a large-scale simulation framework combining the POLARIS activity-based travel demand model and mesoscopic traffic simulator with the Autonomie vehicle energy consumption model and the UrbanSim land use simulator. Results suggest that the introduction of vehicles with advanced automation could increase fuel consumption when no decarbonization policies are implemented. Also, advances in vehicle technology research and development could lead to a decline in energy use in the long-term. Energy pricing and vehicle electrification incentives could help reduce the impact of vehicle automation. Finally, our analysis indicates the relevance of introducing land use processes in longterm vehicle automation studies.

land use↗
DOE OSTI2026

TRACE Input Modernization

This work presents a Tom’s Obvious Minimal Language (TOML)-based representation of input for the US Nuclear Regulatory Commission’s TRAC/RELAP Advanced Computational Engine (TRACE) thermal hydraulics code. Implemented using the Workbench Analysis Sequence Processor (WASP), the approach maps traditional TRACE input structures to a hierarchical format composed of named parameters, typed values, and native data collections. The resulting representation preserves TRACE’s existing modeling capabilities while providing a modern, structured interface for model development and management. WASP further extends TOML through a file import directive that supports modular model composition and reusable input organization. In addition, WASP provides extended array data entry convenience with various data repeat and interpolation capabilities. Examples of the new TOML syntax are provided for major TRACE input categories, including hydraulic components, heat structures, control systems, and trip logic. The TOML representation establishes a foundation for improved validation, tooling, automation, and model maintainability while remaining compatible with existing TRACE workflows. To facilitate migration to the TOML-based input format, the TRACE executable now supports conversion of native TRACE input into an intermediate JSON representation. A Python utility subsequently transforms the JSON data into an equivalent TOML model. Lastly, the TRACE executable now supports execution using TOML-formatted input.

Lefebvre, Robert A. [Oak Ridge National Laboratory↗
DOE OSTI2025

Carbon Utilization and Storage Partnership of the Western United States

This technical report documents research conducted under DOE Award No. DE-FE0031837 focused on evaluating the feasibility of carbon capture, utilization, and storage (CCUS) systems in the central and western United States. The project integrated geologic characterization, reservoir simulation, infrastructure modeling, and economic analysis to assess CO₂ storage potential near industrial sources and develop strategies for transport and sequestration. The work included subsurface modeling, risk assessment, monitoring and verification (MRV) planning, and evaluation of regulatory pathways such as EPA Underground Injection Control (UIC) Class VI permitting and IRS 45Q tax credit eligibility. Results demonstrate the viability of multiple storage approaches, including saline formations, enhanced coalbed methane recovery, and basalt mineralization, supported by data-driven workflows and regional analyses. The project also produced permitting templates, technology transfer activities, and stakeholder engagement efforts to support deployment readiness. These findings contribute to the development of scalable, economically viable CCUS systems and provide a repeatable framework for future carbon management projects.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

High-throughput micro-scale bandgap mapping for perovskite-inspired materials with complex composition space

Abstract To realize the full promise of high-throughput experimental workflows, the rate of sample synthesis must be matched by that of characterization. Of growing interest are contactless optical techniques that can rapidly measure material homogeneity and properties. Here, we present a hyperspectral imaging method to measure local optical bandgap distributions within samples, utilizing spatially-resolved reflectance spectra coupled with automated data analysis. We collect approximately one million optical bandgap data across the compositional space of Cs 3 (Bi x Sb 1-x ) 2 (Br y I 1-y ) 9 perovskite-inspired materials. Our results show non-monotonic bandgap variations (i.e., bandgap bowing) along six composition gradient sequences, in addition to identifying samples with multiple bandgaps in statistics. High-throughput transient absorption spectroscopy reveals that within these compositions, the depletion of the ground state carriers to excited states occurred at discrete energy levels with independent carrier dynamics, consistent with the bandgap observation and indicative of phase separation. This work demonstrates the potential for rapid optical measurements to assess material quality and homogeneity in a high-throughput experimental setting, supporting screening and recipe optimization of optoelectronic material candidates with desired carrier dynamics and optical properties.

Science & Technology - Other Topics↗
DOE OSTI2026

Accelerating actinium-225 purification by high-pressure ion chromatography

Actinium-225 (t1/2 = 9.92 days) is an important radioisotope for targeted alpha therapy applications. The limited supply obtained through the decay of thorium-229 has motivated accelerator-based production routes, including irradiation of thorium targets. Irradiated targets can produce useful quantities of actinium-225, but the product requires final purification from chemically similar lanthanide contaminants. This work describes an automated high-pressure ion chromatography method for this final polishing step. The method uses a reusable strong-acid cation-exchange column bearing sulfonic acid functional groups. α-Hydroxyisobutyric acid (α-HIBA), adjusted to pH 4.3 with lithium hydroxide, complexes and elutes lanthanides, a dilute hydrochloric acid matrix-exchange step removes residual α-HIBA, and concentrated hydrochloric acid then elutes retained actinium(III). The protocol purified actinium-225 to >99% radiopurity across tracer-level samples and samples containing >150 µCi (5.6 MBq) of activity. A 10 min, 0.1 M hydrochloric acid matrix exchange substantially reduced organic eluent carryover, and in-line sodium iodide detection enabled real-time monitoring of actinium and lanthanide elution. The developed method can be completed in <1 h and provides a basis for automated purification workflows for accelerator-produced actinium-225.

Gaddis, Kevin [ORNL] (ORCID:0000000183398314)↗
DOE OSTI2025

Large language model-driven database for thermoelectric materials

Thermoelectric materials have the ability to convert waste heat into electricity, offering a valuable solution for energy harvesting. However, their widespread use is hindered by low conversion efficiency, the reliance on expensive rare earth elements, and the environmental and regulatory concerns associated with lead-based materials. A fast and cost-effective way to identify highly efficient thermoelectric materials is through data-driven methods. These approaches rely on robust and comprehensive datasets to train models. Although there are several databases on thermoelectric materials, there is still a need to collect and integrate experimental data from peer-reviewed research articles to capture diverse compositions and properties of materials. Here, in this work, we developed a comprehensive database of 7,123 thermoelectric compounds, containing key information such as chemical composition, structural detail, seebeck coefficient, electrical and thermal conductivity, power factor, and figure of merit (ZT). We used the GPTArticleExtractor workflow, powered by large language models (LLM), to extract and curate data automatically from the scientific literature published in Elsevier journals. This process enabled the creation of a structured database that addresses the challenges of manual data collection. The open access database could stimulate data-driven research and advance thermoelectric material analysis and discovery.

Database↗
DOE OSTI2026

Prime Time for Model-Predictive Control? Assessing the Technical and Market Readiness of Advanced Controls in Buildings

Despite three decades of extensive research and field testing that have consistently validated the benefits of Model Predictive Control (MPC) in building applications, the technology has seen limited market adoption. This paper evaluates the readiness of MPC for widespread deployment, showcases recent demonstrations and field tests across diverse building types, including residential, small commercial, large commercial, and campus settings. Our results demonstrate that MPC can optimize system operations to achieve load shifting, minimize curtailment of on-site generation, and reduce energy costs by up to 80 %, while maintaining or improving occupant comfort. We also show that MPC can effectively control large assets, such as MW-sized thermal storage systems, and respond to dynamic pricing signals. However, achieving scale remains difficult due to labor-intensive workflows, reliance on a “PhD-in-the-loop” for MPC design and maintenance, susceptibility to fragile data infrastructure, and persistent workforce education and acceptance barriers. To bridge this gap, we outline a transition from bespoke, labor intensive prototypes toward streamlined, segment-targeted deployment strategies that leverage model templates, semantic tools, and generative AI. By automating control configuration and reducing engineering effort, these recommendations provide a pathway for transforming successful research demonstrations into scalable, market ready solutions for MPC-based controls.

Pritoni, Marco↗
DOE OSTI2026

Revealing the Hidden Third Dimension of Point Defects in Two-Dimensional MXenes

Point defects govern many important functional properties of two-dimensional (2D) materials. However, resolving the three-dimensional (3D) arrangement of these defects in multi-layer 2D materials remains a fundamental challenge, hindering rational defect engineering. Here, we overcome this limitation using an artificial intelligence-guided electron microscopy workflow to map the 3D topology and clustering of atomic vacancies in Ti3C2TX MXene. Our approach reconstructs the 3D coordinates of vacancies across hundreds of thousands of lattice sites, generating robust statistical insight into their distribution that can be correlated with specific synthesis pathways. This large-scale data enables us to classify a hierarchy of defect structures-from isolated vacancies to nanopores-revealing their preferred formation and interaction mechanisms, as corroborated by molecular dynamics simulations. This work provides a generalizable framework for understanding and ultimately controlling point defects across large volumes, paving the way for the rational design of defect-engineered functional 2D materials.

2D materials↗
NASA NTRS2026

PROTECT: Production and Reuse of Thermally Efficient Ceramic Thermal Protection Systems

PROTECT (Production and Reuse Of Thermally Efficient Ceramic TPS) is a NASA Early Career Initiative focused on developing the next generation of reusable ceramic thermal protection systems (TPS). This project addresses key challenges in TPS design, including temperature capability, thermal stability, and refurbishment time, by integrating novel material development with predictive modeling. Leveraging enhanced capabilities in NASA’s Porous Microstructure Analysis (PuMA) software, PROTECT introduces new modeling tools to predict the thermal and mechanical behavior of fibrous ceramic materials. These tools enable accurate prediction of performance metrics such as thermal conductivity and structural integrity, reducing reliance on costly physical testing. Preliminary advances in these areas will be presented. To support model validation, PROTECT is building a comprehensive database of raw material properties using advanced characterization techniques, including micro computed tomography (CT) scanning in collaboration with the University of Illinois Urbana-Champaign (UIUC). The presentation will detail the sampling workflows and analysis methods used to generate this detailed microstructural data and how it is used to develop improved models in PuMA. This multi-center collaboration, spanning NASA (JSC, ARC, KSC, GRC), Oak Ridge National Laboratory, UIUC, and SpaceX, is developing tailored TPS solutions for LEO, lunar, and Martian missions. By bridging heritage systems with the demands of modern spaceflight, PROTECT contributes to the advancement of reusable TPS technologies for future exploration missions.

Propulsion, Refractory, and Coating Materials↗