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Results for “Coverage-driven transition”

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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421 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Mechanistic Understanding of Interphase-driven Aging in Silicon Anodes

Conventional solid electrolyte interphases (SEIs) strongly adhere to micro-silicon (µ-Si) and crack under volume changes, causing poor cycling performance. Nano-silicon improves cycling performance but remains costly with limited calendar life. Here potentiostatic ageing tests demonstrate that both calendar and cycle ageing are governed by SEI cracking and dissolution with different relative contributions. When the system is not dominated by SEI dissolution, the relative calendar life of Si anodes could correlates positively with their cycle life. LiF-rich SEI that enables long cycle life in µ-Si is therefore expected to enhance calendar life as well. Using this framework, we screened electrolytes, SEIs and electrodes and validated them with full-cell storage. LiF-rich SEI minimizes cracking and dissolution, enabling μ-Si to achieve excellent calendar life, whereas nano-silicon suffers from SEI dissolution and needs reduced electrolyte–electrode contact for better calendar life. This work clarifies calendar-ageing behaviour and accelerates electrolytes and SEI development for long-life Si anodes.

Johnson, Christopher S.↗
DOE OSTI2025

Robust and tunable oxide nanoscrolls for solar-driven H 2 generation and storage

Hydrogen gas is a promising alternative to fossil fuels due to its high energy output and environmentally safe byproducts. Various morphologies of photocatalytic materials have been explored for high-efficiency H 2 production, for instance, quasi-1D nanoscroll structures that provide a larger surface-to-volume ratio. Recently, we predicted layer-by-layer formation of stable oxide nanoscrolls directly from dichalcogenide precursors, eliminating the need for costly formation of two-dimensional oxides for a roll-up synthesis of nanoscrolls. Here, in this study, we evaluate the suitability of those oxide nanoscroll materials—MoO 3 , WO 3 , PdO 2 , HfO 2 , and GeO 2 —for solar-driven photocatalytic H 2 production and storage. Using excited state theory coupled with Bethe–Salpeter equation simulations, we discern their electronic and optical properties as a function of interlayer scroll spacing and find them to be highly conducive for solar-driven photocatalysis. Additionally, using ab initio molecular dynamics simulations, we show that they are also suitable for H 2 storage as the nanoscrolls exhibit an effective trapping of hydrogen, even in the presence of defects and vacancies in the oxides. This work thus demonstrates the discovery of robust and tunable oxide nanoscrolls as materials for advancing solar-driven hydrogen technologies.

Chemical compounds↗
NASA NTRSDate not supplied

Thermal Data-driven Model Reduction for Enhanced Battery Health Monitoring

Electric aviation faces a major challenge of avoiding potentially catastrophic consequences of the battery’s thermal runaway while keeping the weight of the battery low. Detection of early warning signals of battery failures requires accurate monitoring of the battery’s health throughout its lifespan. However, identifying the parameters of the battery from field data is notoriously difficult. We investigate this problem within the framework of modeling the temperature dynamics of a Li-ion cell during tests simulating loading in electric aircraft flights. It is found that the parameters of a higher-fidelity physics-based thermal model cannot be identified from the simulated flight data. To resolve this issue, we reduce the higher-fidelity thermal model to a model with fewer parameters. The resulting reduced-order model can predict temperature dynamics accurately and is identifiable throughout the cell’s lifespan which allows using the model’s parameters to monitor the state-of-health of the aging cell and detect anomalies in thermal behavior.

Li ion batteries↗
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 OSTI2025

Unique Conductivity Behavior in Water-In-Salt Electrolytes Driven by Ion Clusters

Understanding and predicting ion transport in aqueous electrolytes are crucial for advanced energy storage and biophysics, and many emergent technologies yet remain elusive. Herein, we introduce a unified framework to quantitatively describe and predict electrolyte conductivity that shifts from conventional molar concentration-based metrics to a volume fraction-based approach. Through analyzing a variety of electrolyte solutions via this perspective, we observe a universal conductivity peak at a 37% volume fraction. Small-angle X-ray scattering (SAXS) and molecular dynamics (MD) simulations reveal that nanometer-scale ion clusters drive this general behavior. Moreover, key geometric features of the ion transport pathwayssuch as pore size, tortuosity, and connectivityfollow a consistent dependence with respect to the volume fraction, reinforcing the argument for the universal conductivity trend. This paradigm shift opens new avenues for designing high-performance electrolytes and provides transformative insights for advancing studies in many fields, wherein molecular aggregates dictate transport properties.

Nguyen, Huong T. D.↗
DOE OSTI2026

Operando microscopy for neuromorphic hardware

Microscopy techniques can uncover the physical properties and dynamic behaviours of materials, driving the discovery of emergent phenomena and guiding the design of next-generation computing hardware. As artificial intelligence becomes pervasive, the demand for high-performance materials to support sustainable information technologies is growing. Here, this Review highlights state-of-the-art imaging from electron and X-ray to optical techniques to probe the dynamics of neuromorphic materials, including operando characterization of devices. We examine design principles for neuromorphic materials, along with obstacles that hinder their development. Emphasis is placed on spatially and temporally resolved approaches that capture state changes including phase transitions, ferroic switching and spin-wave propagation that emulate biological components such as neurons, synapses and their connectivity. We discuss challenges in operando characterization and the integration of artificial intelligence-driven analysis for feedback-guided material discovery. Finally, we outline opportunities for real-time imaging of neuromorphic systems, paving the way towards adaptive, brain-inspired hardware.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2026

The Significance of Water Vapor Isotopes in Improving Weather Prediction

Water vapor isotopes carry the integrated history of evaporation, condensation, mixing, and transport. Although previous studies have shown potential to improve forecasts under controlled conditions, real-world applications have been limited by systematic biases in both models and satellite retrievals arising from sparse measurements in the free troposphere. Here we assimilate mid‑tropospheric δD retrievals (peak sensitivity ~4.2 km) from the Infrared Atmospheric Sounding Interferometer into the Isotope‑incorporated Global Spectral Model and evaluate the added value beyond co‑assimilated temperature and specific humidity with identical spatial and temporal coverage. Assimilating δD improves 0–120 h forecasts of wind, temperature, specific humidity, and geopotential height, with the largest gains in the midlatitudes; heavy‑precipitation skill also increases for thresholds >3 mm per 6 h. Demonstrated in a coarse‑resolution configuration with limited observations, the results indicate that isotopic information strengthens transport tracking and hydrological constraints, motivating evaluation in operational high‑resolution forecasting systems.

Hydrology↗
DOE OSTI2026

Comprehensive structural characterization of charged polymers involved in moisture-driven direct air capture

This study provides a comprehensive structural characterization of commercially available alkaline anion-exchange polymers (Fumasep FAA-3 and IRA 900) used in moisture-driven direct air capture (DAC) of carbon dioxide. Using X-ray diffraction, SAXS/WAXS, atomic force microscopy, FIB-SEM, and transmission electron microscopy, the authors identify nanoscale clustering, porosity, swelling behavior, and humidity-dependent structural changes that influence CO₂ adsorption and release. These findings establish structure–function relationships critical for designing more durable and energy-efficient DAC polymer materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Electric‐Field‐Driven Reversal of Ferromagnetism in (110)‐Oriented, Single Phase, Multiferroic Co‐Substituted BiFeO 3 Thin Films

Abstract While multiferroic materials are attractive systems for the promise of ultra‐low‐power‐consumption computational technologies, electric‐field‐induced magnetization reversal is a key challenge for realizing devices at scale. Though significant research efforts have been working toward the realization of a material which couples ferroelectricity and ferromagnetism, there are few, even composite, systems which are practical for device scale applications at room temperature. Co‐substituted multiferroic BiFe 0.9 Co 0.1 O 3 is a promising candidate system, due to coupled ferroelectricity and weak ferromagnetism at room temperature. Here, it is theoretically indicated that the ferroic orders in this material are statically coupled, where an in‐plane 109° ferroelectric switching event can result in the reversal of this out‐of‐plane component of magnetization, and the electric field‐induced magnetization reversal is experimentally observed. Such an in‐plane poling configuration is particularly desirable for device applications.

Chemistry↗
NASA NTRS1982

Transit Thermal Control Design for Galileo Entry Probe for Planet Jupiter

A totally passive design was completed for the thermal control of the Galileo entry probe during its transit to the planet Jupiter. The design utilizes radio isotope heater units, multilayer insulation blankets and a thermal radiator in conjunction with a design conductance support structure to achieve both the required storage and critical initial planet atmosphere entry temperatures. The probe transit thermal design was completed and verified based on thermal vacuum testing of a prototype probe thermal test model.

George C. Haverly↗
NASA NTRS1995

Transitional Flow in Thin Tubes for Space Station Freedom Radiator

A two dimensional finite volume method is used to predict the film coefficients in the transitional flow region (laminar or turbulent) for the radiator panel tubes. The code used to perform this analysis is CAST (Computer Aided Simulation of Turbulent Flows). The information gathered from this code is then used to augment a Sinda85 model that predicts overall performance of the radiator. A final comparison is drawn between the results generated with a Sinda85 model using the Sinda85 provided transition region heat transfer correlations and the Sinda85 model using the CAST generated data.

Patrick Loney↗