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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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1,181 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Low-Temperature Gold Deposition Improves CdTe Back Contacts

Improved back contacts can benefit CdTe photovoltaics (PV). In this work, Cd(Se,Te) PV absorbers are cooled during Au evaporation to thermally quench a chemical reaction occurring between gold and CdTe and the generation of a reaction product that lowers device efficiency. Reducing substrate temperature enhances PV power conversion efficiency via open-circuit voltage and fill factor increases. X-ray photoelectron spectroscopy (XPS) reveals that lower temperature also reduces chemical perturbations of the CdTe, potentially linking back contact formation to a CdTe degradation product that hinders PV performance. Comparing reaction enthalpy and substrate heating energy shows that back contact formation by sputtering elemental metals onto ZnTe may exhibit a degradation pathway analogous to that of CdTe/Au reported here. Degradation-diminishing contact formation processes are therefore of general interest for optoelectronic devices, and the reduced substrate temperature in this study is one example.

14 SOLAR ENERGY↗
DOE OSTI2026

A strong and ductile Super Kovar alloy via fully coherent nanoprecipitates

Emerging high-precision technologies demand materials with exceptional dimensional stability and mechanical robustness, as even microscopic thermomechanical deformation can cause functional failure. However, a fundamental trilemma exists: High strength, ductility, and low thermal expansion are mutually exclusive, as strengthening-induced lattice distortions compromise the spin-lattice coupling, which is essential for low thermal expansion. Here, we overcome this trilemma by designing “Super Kovar,” an Fe-Ni-Co-Al-Ta alloy, featuring fully coherent nanoprecipitates. It unifies a 1.0-gigapascal ultimate tensile strength and ∼39% elongation with a Kovar-grade thermal expansion of 3.81 × 10−6 K−1 (100 to 410 K). The key is a dense dispersion of L12 nanoprecipitates that form an almost strain-free coherent interface with the ferromagnetic matrix. Beyond providing precipitation strengthening, these coherent interfaces suppress intrinsic phonons of nanoprecipitates via elastic coupling while avoiding magnetic domain pinning to preserve the Invar effect of the matrix. This reduces the thermal expansion of the precipitates by 56% and achieves a fourfold enhancement in the strength-ductility product, establishing a paradigm for dimensionally stable, ultrastrong alloys.

Yu, Chengyi [University of Science and Technology ↗
DOE OSTI2024

Factors Influencing Gas Evolution from High‐Nickel Layered Oxide Cathodes in Lithium‐Based Batteries

Abstract Gas evolution from high‐nickel layered oxide cathodes (>90% Ni) remains a major issue for their practical application. Gaseous species, such as CO 2 , O 2 , and CO, that are evolved at high states of charge (SOC) worsen the overall safety of batteries, as pressure build‐up within the cell may lead to cell rupture. Since these gasses are produced during cathode degradation, tracking the formation of gasses is also important in diagnosing cathode failure. Online electrochemical mass spectrometry (OEMS) is a powerful in situ technique to study gas evolution from the cathode during high‐voltage charge. However, the differences in the OEMS experimental setups between different groups make it challenging to compare results between groups. In this perspective, the various factors that influence gas evolution based on the OEMS results collected in this group are presented. The focus is on the conditions that lead to gas release, with a particular emphasis on reactive oxygen formation and subsequent chemical reactions with the electrolyte. Promising strategies, such as electrolytes, compositional tuning, and surface coatings that are effective at suppressing gas evolution from the cathode are highlighted. Critical insights into mitigating cathode degradation and gas evolution are provided to guide the development of safer, high‐energy batteries.

Chemistry↗
DOE OSTI2025

Wide-Bandgap Semiconductor Amplifiers for Fusion Plasma Heating and Control

This paper discusses power electronics developed under the ARPA-E GAMOW program to support nuclear fusion power production. The goal of this project was to develop and assess the potential for wide-bandgap (WBG) semiconductor devices in power electronics to enable high-efficiency and high-voltage solid-state systems for fusion plasma generation, heating, and control. The power electronics use an architecture in which multiple high-power boards can be combined to produce megawatt-level power, where using multiple boards provides high reliability. Two main areas of power electronics boards are developed in this project for fusion plasma heating and control applications: (1) pulse generation and control and (2) radiofrequency generation. The first area is for boards capable of driving high-voltage millisecond pulses at high duty cycles. The envisioned application of these pulses is in plasma control of magnetohydrodynamic instabilities, plasma position, and edge-localized modes. Pulse-width modulation allows for the implementation of a wide variety of linear and nonlinear control systems. The boards developed for this project could actuate control coils based on digital input signals and can be parallelized to provide megawatts of output power. The design of the pulse generator is a low-side load switch. A load switch was designed and constructed that utilized 2-kV-rated field-effect transistor (FET)-based cascodes developed by Qorvo under this project to perform initial testing of these cascodes. The second area is being implemented using class E amplifiers with WBG devices and a reactance steering network to handle inductive or capacitive plasma loads. Applications include ion cyclotron resonance heating (ICRH) and high-harmonic fast-wave (HHFW) heating. A class E reactance steering network is demonstrated in modeling and experiment with a resistive-inductive load that models an inductively-coupled plasma. Power combining of boards with class E reactance steering networks is also simulated and demonstrated experimentally, to enable scaling up to high power. Modeling of high-power-density cooling and remaining useful life is conducted to enable reliable, effectively cooled high-power electronics for fusion applications.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Testing and Validation of Wireless Communication Architecture for Heliostat Fields: SIPS Final Report

This work focuses on the development and testing of a low-cost wireless communication system for heliostat fields, enabling significant capital costs reductions for concentrating solar thermal systems. Outputs of this work include a working demonstration of a multi-node communication system, clear reporting of system performance, and technical documentation of system development and architecture for reproducibility. Through this process, an open-source repository was created for manufacturing hardware at ~$30/heliostat. The system includes software for cybersecurity, achieving sub-second communication latencies and derisking of hardware for eventual scale-up to tens of thousands of heliostats. While the system is not currently off-the-shelf ready, there is now a clearly defined pathway for scaling up and completing the commercial development process.

14 SOLAR ENERGY↗
DOE OSTI2026

Research and Development Related to the Commercialization of Perovskite Radiation Detectors (CRADA Final Report)

This work will focus on the development of perovskite radiation detectors fabricated with nanocrystal, thick polycrystalline films, or single crystal materials. This will harness NREL’s instrumentation and expertise in a variety of research areas including but not limited to metal halide perovskites, device characterization, device packaging, accelerated lifetime testing, and ink chemistry development.

14 SOLAR ENERGY↗
DOE OSTI2025

Cooperative and bifunctional Ga-Ca-Cr 2 O 3 @CaO structured monoliths as versatile platform for reactive capture of CO 2 and its subsequent conversion to ethylene

Cooperative and bifunctional materials (BFMs) that integrate adsorbents and catalysts offer a promising strategy for the reactive capture of CO 2 to produce valuable fuels and chemicals. In this study, we developed structured BFMs via 3D printing that combine CaO as an adsorbent with Ga–Ca–Cr 2 O 3 metal oxides as the catalyst for the reactive capture of CO 2 and its subsequent conversion to C 2 H 4 via the oxidative dehydrogenation of C 2 H 6 (CO 2 -ODHE). Three different Ga–Ca compositions were used to modify the catalyst surface characteristics and enhance C 2 H 4 selectivity. In these formulations, Ga ions stabilize the oxygen lattice of the BFM, while Ca ions interact strongly with Cr to form CaCrO 4 , thereby altering the oxygen species and enhancing the material’s basic properties. Under adsorption–reaction conditions at 600–650 °C, the optimal BFM achieved an excellent C 2 H 4 selectivity of 96.4 %, attributed to a balanced redox process and improved basicity that facilitate efficient C 2 H 6 conversion and rapid desorption of C 2 H 4 without excessive oxidation. Overall, this work provides new insights into the formulation of BFMs monoliths and highlights the critical role of catalytic surface modification in enhancing C 2 H 4 selectivity in the CO 2 -ODHE reactive capture process.

C2H4 production↗
DOE OSTI2026

Advancing Building Performance: Field Results of Thin-Glass Triple-Pane Window Demonstrations

To meet California and the nation's ambitious energy targets, energy use in the building sector must drop dramatically. Windows continue to be the lowest thermally performing envelope system in the nation's buildings, resulting in poor overall envelope performance and potential impacts to human health and comfort. Current best practice new window performance is typically met by double-pane low-solar-gain glazing. Thin-glass triple-pane windows are a highly promising next step forward in performance and have been deployed in two California multi-family sites to quantify field performance and building energy savings. The technology assessed offers the performance benefits of traditional triple-pane but with little increase in weight or cost, enabling incremental costs competitive with alternative energy reduction solutions for the building envelope. This paper covers a detailed investigation into the demonstration project and measured performance benefits of the windows after a full year of data collection.

Hart, Robert↗
NASA NTRS1971

Battery simulation program

Computer program calculates spacecraft battery energy at specific times dictated by input sequence of recharge, discharge, and no activity phases. Recharge phases are assumed during times not specified, unless batteries are fully charged. Warnings are printed when energy falls below specified level. Program assumes two identical batteries.

Abreu, A.↗
DOE OSTI2021

DEPRECATED AI-Batt-OS (Autonomous Identification of Battery Life Models - Open Source) [SWR 21-17]

DEPRECATED. This repository was archived by the owner on Jun 30, 2026. It is now read-only. Open source implementation of some of the methods utilized by AI-Batt, a battery lifetime modeling and analysis toolkit provided by the National Laboratory of the Rockies (NLR). This software demonstrates the use of bi-level optimization and symbolic regression techniques to semi-autonomously identify algebraic models predicting the capacity fade of lithium-ion batteries during calendar aging. Modeling the degradation of batteries is a complex task, due to the difficulty in separating the time-dependent and time-independent factors impacting cell level degradation, across multiple data series with different numbers of measurements and/or data quality. Bi-level optimization enables model parameters to be optimized to either the entire data set or to individual data series, allowing statistical disambiguation of global behaviors (data series independent) and local behaviors (data series dependent). Symbolic regression is used to automatically search for optimal low-dimesional models predicting the variation of locally optimized parameters versus time-independent experimental variables from millions of possible models, resulting in a more accurate and repeatable model identification process than is possible by a manual search. The provided tools also implement cross-validation and bootstrap resampling schemes, empowering statistical model comparison/selection and quantification of model uncertainties. An example script replicates the results from the manuscript "Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning", submitted to ECS. All code is written in MATLAB. Requires the Statistics and Machine Learning Toolbox. Contact Dr. Paul Gasper at Paul.Gasper@nlr.gov for any questions.

Gasper, Paul [National Renewable Energy Lab. (NREL↗
DOE OSTI2025

Revealing the evolution of order in materials microstructures using multi-modal computer vision

The development of high-performance materials for microelectronics, energy storage, and extreme environments depends on our ability to describe and direct property-defining microstructural order. Our present understanding is typically derived from laborious manual analysis of imaging and spectroscopy data, which is difficult to scale, challenging to reproduce, and lacks the ability to reveal latent associations needed for mechanistic models. Here, we demonstrate a multi-modal machine learning (ML) approach to describe order from electron microscopy analysis of the complex oxide La 1−x Sr x FeO 3 . We construct a hybrid pipeline based on fully and semi-supervised classification, allowing us to evaluate both the characteristics of each data modality and the value each modality adds to the ensemble. We observe distinct differences in the performance of uni- and multi-modal models, from which we draw general lessons in describing crystal order using computer vision.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Tracing U.S. fuel life-cycle greenhouse gas emissions in a multi-sector dynamics model using LC-GCAM

Model-based analysis of fuel pathways is essential for informing energy and environmental policy. Two major model types are typically used: multi-sector dynamics models, which capture the broader energy-economy, such as GCAM (Global Change Analysis Model), and life cycle assessment models, such as GREET (Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation). Each has distinct strengths and limitations, and recent studies increasingly adopt hybrid approaches to harness the advantages of both. However, such integration is often time-consuming and complicated by inconsistencies in system boundaries and technology definitions. We present LC-GCAM, a new tool that enables estimation of life-cycle greenhouse gas emissions and primary energy use for any fuel pathway represented in GCAM. We apply LC-GCAM to 300 scenarios designed to explore key uncertainties affecting the life-cycle performance of future fuel options in the U.S. freight sector. To evaluate LC-GCAM, we compare its results with those from GREET for nine fuel types in a 2030 reference scenario. When input assumptions are modestly aligned, LC-GCAM and GREET estimates typically agree within 10% (absolute sum-based mean absolute percentage error). LC-GCAM offers a flexible and efficient approach to generating life-cycle metrics within an integrated modeling framework, supporting robust policy analysis across a wide range of interacting energy system uncertainties.

Wolfram, Paul↗
NASA NTRS2009

Data Base and Guidelines Document Developed for Lithium-Ion Battery

Lithium-Ion (Li-Ion) batteries are fast becoming the battery chemistry of choice for aerospace applications requiring (rechargeable) power supplies. These batteries offer high-energy density and high-specific energy combined with excellent rate capability and cycle potential. The increased energy content and operational characteristics of this system require defined safety and handling procedures to ensure the safe implementation. Standardized approaches to defining, determining, and addressing safety, handling, and qualification for Li-Ion batteries have been developed and published as an NESC-sponsored Li-Ion Battery Guidelines Document. A data base was established cataloging cells and batteries that have been considered for aerospace applications.

Data Base and Guidelines↗
DOE OSTI2026

ClassNMSW- a real-time classification approach for non-recycled municipal solid waste using hyperspectral imaging

Real-time classification of non-recycled municipal solid waste (NMSW) is essential for efficient valorization. This study introduces ClassNMSW, a comprehensive framework for classifying 22 NMSW subclasses under industrial constraints by using hyperspectral imaging (HSI). A primary innovation of this work is the development of a variance-controlled spectral extraction algorithm. Unlike traditional methods that rely on simple averaging, this approach systematically investigates the extent of pixel extraction to minimize the loss of critical chemical information while maximizing data reduction thus ensuring high spectral fidelity with low computational cost. The approach developed in this work integrates automated, computer-vision-based background removal, eliminating the need for the manual thresholding common in current literature. To resolve ambiguities among chemically similar subclasses, a tiered classification and multi-camera fusion strategy (NIR17 and NIR22) is implemented. Results demonstrate that ClassNMSW achieves an object-wise weighted accuracy of 98.70% for single-sensor configurations and 100% under sensor fusion. A novel rolling-window strategy satisfies desired end-to-end latency of <2 s, satisfying the strict deterministic requirements of high-speed industrial sorting environments. The ClassNMSW framework provides a scalable foundation for advancing circularity and resource recovery in large-scale waste valorization operations.

99 - GENERAL AND MISCELLANEOUS↗
NASA NTRS2026

Space Mission Options for Reconnaissance and Mitigation of Asteroid 2024 YR4

Near-Earth asteroid 2024 YR 4 was discovered on 2024-12-27 and its probability of Earth impact in December 2032 peaked at about 3% on 2025-02-18. Additional observations ruled out Earth impact by 2025-02-23. However, the probability of lunar impact in December 2032 then rose, reaching about 4% by the end of the apparition in May 2025. James Webb Space Telescope (JWST) observations on 2025-03-26 estimated the asteroid's diameter at 60 +/- 7 m. Studies of 2024 YR 4 's potential lunar impact effects suggest lunar ejecta could increase micrometeoroid debris flux in low Earth orbit up to 1000 times above background levels over just a few days, possibly threatening astronauts and spacecraft. In this work, we present options for space missions to 2024 YR 4 that could be utilized if lunar impact is confirmed. We cover flyby & rendezvous reconnaissance, deflection, and robust disruption of the asteroid. We examine both rapid-response and delayed launch options through 2032. We evaluate chemical and solar electric propulsion, various launch vehicles, optimized deep space maneuvers, and gravity assists. Re-tasking extant spacecraft and using built spacecraft not yet launched are also considered. The best reconnaissance mission options launch in late 2028, leaving only approximately three years for development at the time of this writing in August 2025. Deflection missions were assessed and appear impractical. However, kinetic robust disruption missions are available with launches between April 2030 and April 2032. Nuclear robust disruption missions are also available with launches between late 2029 and late 2031. Finally, even if lunar impact is ruled out there is significant potential utility in deploying a reconnaissance mission to characterize the asteroid.

Asteroid Disruption↗
DOE OSTI2026

Solar Heat for Industrial Processes: Integration with Chemical Reactors

The integration of solar thermal systems with chemical reactors has been proposed as part of a larger effort to develop and deploy solar heat for industrial processes (SHIP) technologies. A strong motivation for SHIP processes and technologies is the potential for high thermal efficiency coupled with low-cost thermal energy storage (TES) which can enable commercial deployment of such systems. While there are different ways to categorize SHIP technologies, one important such distinction is between directly irradiated systems and indirect off-sun process driven by a SHIP system. While directly irradiated systems can provide high thermal efficiencies and high fluxes, they usually require complex engineering solutions due to the need for redesigning the established processes and unit operations. In most cases, it is also more challenging to couple such a process to a TES system, losing some of the benefits of SHIP. On the other hand, using a SHIP system to drive an industrial process off-sun can allow better integration with existing process chains, easier TES capabilities, and potential for more applications fitting a specific SHIP technology. However, the integration of SHIP systems with the industrial processes is not fully explored in detail, especially in the case of high-temperature processes such as reforming, cracking, cement manufacturing, and iron/steelmaking. Many of these systems require heating fluxes of >50 kW/m^2, supplied via combustion of hydrocarbons in a fire box and benefitting from radiative heat transfer between the flue gases and the reaction zones. As such, using SHIP systems for such processes is more complex than providing the same thermal input in the form of a heat transfer medium (HTM) entering the reactor, kiln, or furnace. Moreover, in case convective heat transfer using SHIP is envisioned, for example using supercritical CO2 as the HTM from a particle receiver, the thermal integration might be more challenging than initially envisioned: lower heat transfer coefficients and limited approach temperature might require large flow rates, causing a mismatch between the process thermal requirements and the thermal capacity of the SHIP system. In addition, even if the heat exchange between SHIP and reactor is effective, there is still a cold leg HTM at the reaction temperature or slightly below it. Chemical plants usually include a set of heat exchangers, heat recovery steam generators, and even power generation units - in a tightly integrated design - to recover the flue gases which are eventually vented. With SHIP systems mostly operating on a closed HTM loop, bottoming the cold leg is crucial. In this talk, we will present different modeling results for a variety of syngas production reactions, using catalytic and chemical looping processes, and discuss some of the challenges and design considerations for off-sun chemical reactors using SHIP systems.

14 SOLAR ENERGY↗
DOE OSTI2026

Self-Leveling Inks for Printing Ultra-uniform Perovskite Solar Modules by Flexography

The report describes the development of scalable manufacturing methods for high-performance, stable perovskite solar modules using flexographic printing. The project developed self-leveling perovskite inks that exploit Marangoni flows to reduce coating defects and improve large-area film uniformity. Bayesian optimization was integrated with high-throughput photoluminescence mapping and photovoltaic measurements to efficiently optimize ink formulations and printing conditions. The resulting printed perovskite solar cells achieved champion power conversion efficiencies above 21.6%, with median efficiencies exceeding 20% across large device batches. At the module scale, printed devices achieved active-area efficiencies up to approximately 17.3% on 25 cm² substrates. The project also demonstrated improved performance and stability using additively patterned interconnections compared with laser-scribed controls. Overall, the work establishes a data-driven, roll-compatible pathway toward high-throughput, low-capital-cost manufacturing of uniform and stable perovskite photovoltaics.

14 SOLAR ENERGY↗
DOE OSTI2025

Fast lithium ion diffusion in brownmillerite Li x Sr 2 Co 2 O 5

Transition metal oxides not only exhibits novel magnetic properties but also provides outstanding ionic transports. Ionic conductors have great potential for interesting tunable physical properties via ionic liquid gating and novel energy storage applications such as all-solid-state lithium batteries. In particular, low migration barriers and high hopping attempt frequency are the keys to achieve fast ion diffusion in solids. Taking advantage of the oxygen-vacancy channel in Li x Sr 2 Co 2 O 5 , we show that migration barriers of lithium ion are as small as 0.28–0.17 eV depending on the lithium concentration rates. Our first-principles calculation also investigated hopping attempt frequency and concluded the room temperature ionic diffusivity and ion conductivity are high as 10 −7 –10 −6 cm 2 s −1 and 10 −3 –10 −2 Scm −1 , respectively, which outperform most of perovskite-type, garnet-type, and sulfide Li-ion solid-state electrolytes. This work proves Li x Sr 2 Co 2 O 5 as a promising super-ionic conductor.

Crystallographic defects↗