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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

FAIR Data and Interpretable AI Framework for Architectured Metamaterials

Our interdisciplinary effort successfully generated FAIR (Findable, Accessible, Interoperable, and Reusable) benchmark datasets for mechanical metamaterials while introducing a novel Artificial Intelligence (AI) framework known as Learning Refined Compositional Rules (LRCR). This framework was specifically designed to bridge the gap across varying computational length scales and extract the underlying physical mechanisms that connect a material's structural geometry to its bulk acoustic properties. Historically, the discovery of such structured materials relied heavily on human intuition or opaque, black-box optimization algorithms that were difficult to generalize. By combining interpretable machine learning techniques with rigorous experimental validation, this project established clear, generalizable design guidelines for tuning wave dispersion and controlling vibrations. Ultimately, the public availability of these structured datasets and algorithms will significantly reduce computational costs and accelerate the design of advanced multi-functional acoustic devices, offering broad societal impacts across fields like aerospace engineering, telecommunications, and biomedical implant design.

36 MATERIALS SCIENCE↗
DOE OSTI2025

32 examples of LLM applications in materials science and chemistry: towards automation, assistants, agents, and accelerated scientific discovery

Abstract Large language models (LLMs) are reshaping many aspects of materials science and chemistry research, enabling advances in molecular property prediction, materials design, scientific automation, knowledge extraction, and more. Recent developments demonstrate that the latest class of models are able to integrate structured and unstructured data, assist in hypothesis generation, and streamline research workflows. To explore the frontier of LLM capabilities across the research lifecycle, we review applications of LLMs through 32 total projects developed during the second annual LLM hackathon for applications in materials science and chemistry, a global hybrid event. These projects spanned seven key research areas: (1) molecular and material property prediction, (2) molecular and material design, (3) automation and novel interfaces, (4) scientific communication and education, (5) research data management and automation, (6) hypothesis generation and evaluation, and (7) knowledge extraction and reasoning from the scientific literature. Collectively, these applications illustrate how LLMs serve as versatile predictive models, platforms for rapid prototyping of domain-specific tools, and much more. In particular, improvements in both open source and proprietary LLM performance through the addition of reasoning, additional training data, and new techniques have expanded effectiveness, particularly in low-data environments and interdisciplinary research. As LLMs continue to improve, their integration into scientific workflows presents both new opportunities and new challenges, requiring ongoing exploration, continued refinement, and further research to address reliability, interpretability, and reproducibility.

Computer Science↗
DOE OSTI2024

Biodegradable Temperature & pH Sensors VIASTIMULI-Responsive Polymers

Soil sensors play a key role in agriculture, and for good reason; knowledge about soil conditions enables farmers to make informed decisions about resource expenditure and crop selection for areas of land. On an industrial agriculture scale, though, this is difficult; the average U.S. farm is approximately 500 acres. To put that in perspective, if you’ve driven past Concannon Winery, all that land is only about 200 acres. This is why modern state-of-the-art soil sensors need to be equipped to not only collect precise and accurate data, but also to transmit that data large distances.

36 MATERIALS SCIENCE↗
NASA NTRS2000

Microgravity Research Results and Experiences from the NASA Mir Space Station Program

The Microgravity Research Program Office (MRPO) participated aggressively in Phase I of the International Space Station Program using the Russian Mir Space Station. The Mir Station offered an otherwise unavailable opportunity to explore the advantages and challenges to long duration microgravity space research. Payloads with both NASA and commercial backing were included as well as cooperative research with the Canadian Space Agency (CSA). From this experience, much was learned about dealing with long duration on orbit science utilization and developing new working relationships with our Russian partner to promote efficient planning, operations, and integration to solve complexities associated with a multiple partner program. Microgravity participation in the NASA Mir Program began with the first joint NASA Mir flight to the Mir Space Station. The earliest participation setup acceleration measurement capabilities that were used throughout the Program. Research, conducted by all Microgravity science disciplines, continued on each subsequent increment for the entire three-year duration of the Program. The Phase I Program included the Microgravity participation of over 30 Fluids, Combustion, Materials, and Biotechnology Sciences and numerous commercially sponsored research payloads. In addition to the research gained from Microgravity investigations, long duration operation of facility hardware was tested. Microgravity facilities operated on Mir included the Space Acceleration Measurement System (SAMS), the Microgravity Glovebox (MGBX), the Biotechnology System (BTS) and the Canadian Space Agency sponsored Microgravity Isolation Mount (MIM). The Russian OPTIZONE Furnace was also incorporated into our material science research. All of these efforts yielded significant and useful scientific research data. This paper focuses on the microgravity research conducted onboard the Mir space station. It includes the Program preparation and planning necessary to support this type of cross increment research experience; the payloads which were flown; and summaries of significant microgravity science findings. Most importantly this paper highlights the various disciplines of microgravity research conducted during the International Space Station, Phase 1 Program onboard the Mir Station. A capsulation of significant research and the applicability of our findings are provided. In addition, a brief discussion of how future microgravity science gathering capabilities, hardware development and payload operations techniques have enhanced our ability to conduct long duration microgravity research.

Schagheck, R. A.↗
NASA NTRS2008

The Mars Climate Sounder In-Flight Positioning Anomaly

The paper discusses the Mars Climate Sounder (MCS) instrument s in-flight positioning errors and presents background material about it. A short overview of the instrument s science objectives and data acquisition techniques is provided. The brief mechanical description familiarizes the reader with the MCS instrument. Several key items of the flight qualification program, which had a rigorous joint drive test program but some limitations in overall system testing, are discussed. Implications this might have had for the flight anomaly, which began after several months of flawless space operation, are mentioned. The detection, interpretation, and instrument response to the errors is discussed. The anomaly prompted engineering reviews, renewed ground, and some in-flight testing. A summary of these events, including a timeline, is included. Several items of concern were uncovered during the anomaly investigation, the root cause, however, was never found. The instrument is now used with two operational constraints that work around the anomaly. It continues science gathering at an only slightly diminished pace that will yield approximately 90% of the originally intended science.

Jau, Bruno M.↗
NASA NTRS2001

NASA Tech Briefs, November 2001

Topics include: special coverage section on data acquisition, and sections on electronic components and systems, software, materials, machinery/automation, physical sciences, book and reports, and a special section of Photonics Tech Briefs.

Source record↗
NASA NTRS2008

The Mars climate sounder in-flight positioning anomaly

The paper discusses the Mars Climate Sounder (MCS) instrument’s in-flight positioning errors and presents background material about it. A short overview of the instrument’s science objectives and data acquisition techniques is provided. The brief mechanical description familiarizes the reader with the MCS instrument. Several key items of the flight qualification program, which had a rigorous joint drive test program but some limitations in overall system testing, are discussed. Implications this might have had for the flight anomaly, which began after several months of flawless space operation, are mentioned. The detection, interpretation, and instrument response to the errors is discussed. The anomaly prompted engineering reviews, renewed ground, and some in-flight testing. A summary of these events, including a timeline, is included. Several items of concern were uncovered during the anomaly investigation, the root cause, however, was never found. The instrument is now used with two operational constraints that work around the anomaly. It continues science gathering at an only slightly diminished pace that will yield approximately 90% of the originally intended science.

Kass, David↗
DOE OSTI2024

Wilkins: HPC in situ workflows made easy

In situ approaches can accelerate the pace of scientific discoveries by allowing scientists to perform data analysis at simulation time. Current in situ workflow systems, however, face challenges in handling the growing complexity and diverse computational requirements of scientific tasks. In this work, we present Wilkins, an in situ workflow system that is designed for ease-of-use while providing scalable and efficient execution of workflow tasks. Wilkins provides a flexible workflow description interface, employs a high-performance data transport layer based on HDF5, and supports tasks with disparate data rates by providing a flow control mechanism. Wilkins seamlessly couples scientific tasks that already use HDF5, without requiring task code modifications. We demonstrate the above features using both synthetic benchmarks and two science use cases in materials science and cosmology.

HPC↗
DOE OSTI2026

Synthetic data-driven deep learning for label-free autonomous atomic force microscopy

Atomic force microscopy (AFM) is a widely used tool for nanoscale characterization across materials science, energy research, and biology. However, its adoption in high-throughput materials discovery and statistically driven studies remains limited by a strong dependence on expert operator input and by the scarcity of annotated experimental AFM datasets needed to enable data-driven automation. Here, we introduce SimuScan, a synthetic-data–driven framework that enables reliable AFM feature identification, segmentation, and targeted imaging without requiring large manually labeled experimental datasets. SimuScan generates tunable, high-fidelity synthetic AFM images of defined morphologies while incorporating realistic experimental artifacts, including tip–sample convolution, noise, flattening distortions, and surface debris. These datasets are shown to support scalable, label-free training of modern deep learning models for AFM analysis. When integrated into data-driven AFM workflows, SimuScan-trained models can locate and analyze nanoscale structures across large datasets and guide targeted follow-up imaging. We validate this approach on nanostructured surfaces, DNA assemblies, and bacterial cells, demonstrating robust generalization across diverse sample types with minimal operator intervention. More broadly, this work establishes a general strategy for generating explicitly conditioned, task-relevant synthetic data to improve the reliability of downstream models in autonomous microscopy.

Millan-Solsona, Ruben [Oak Ridge National Laborato↗
NASA NTRS2006

Aerocapture Technology Development for Planetary Science - Update

Within NASA's Science Mission Directorate is a technological program dedicated to improving the cost, mass, and trip time of future scientific missions throughout the Solar System. The In-Space Propulsion Technology (ISPT) Program, established in 2001, is charged with advancing propulsion systems used in space from Technology Readiness Level (TRL) 3 to TRL6, and with planning activities leading to flight readiness. The program's content has changed considerably since inception, as the program has refocused its priorities. One of the technologies that has remained in the ISPT portfolio through these changes is Aerocapture. Aerocapture is the use of a planetary body's atmosphere to slow a vehicle from hyperbolic velocity to a low-energy orbit suitable for science. Prospective use of this technology has repeatedly shown huge mass savings for missions of interest in planetary exploration, at Titan, Neptune, Venus, and Mars. With launch vehicle costs rising, these savings could be the key to mission viability. This paper provides an update on the current state of the Aerocapture technology development effort, summarizes some recent key findings, and highlights hardware developments that are ready for application to Aerocapture vehicles and entry probes alike. Description of Investments: The Aerocapture technology area within the ISPT program has utilized the expertise around NASA to perform Phase A-level studies of future missions, to identify technology gaps that need to be filled to achieve flight readiness. A 2002 study of the Titan Explorer mission concept showed that the combination of Aerocapture and a Solar Electric Propulsion system could deliver a lander and orbiter to Titan in half the time and on a smaller, less expensive launch vehicle, compared to a mission using chemical propulsion for the interplanetary injection and orbit insertion. The study also identified no component technology breakthroughs necessary to implement Aerocapture on such a mission. Similar studies of Aerocapture applications at Neptune, Venus, and Mars were studied in 2003 through 2005. All showed significant performance improvements for the missions studied. Findings from these studies were used to guide the technology development tasks originally solicited in a 2002 NASA ROSS Research Announcement. The tasks are now in their final year and have provided numerous improvements in modeling and hardware, for use in proposals or new mission starts. Major Accomplishments: Since validation of the Aerocapture maneuver requires a space flight, ground developments have focused on modeling and environment prediction, materials, and sensors. Lockheed Martin has designed and built a 2-meter Carbon-Carbon aeroshell "hot structure." The article utilizes co-cured stiffening ribs and advanced insulation to achieve large scale, and up to a 40% reduction in areal density over the Genesis probe construction. This concept would be an efficient solution for probes that experience heat rates near 800-1000 W/cm(exp 2), such as at Venus and Earth. Applied Research Associates has extensively tested a family of efficient ablative TPS materials that provide solutions for a range of heating conditions. These materials are being applied to high-temperature structures built by ATK Space Systems, led by Langley Research Center. One-meter aeroshells will be thermally tested to validate construction and demonstrate higher bondline temperatures, which can lead to mass savings of up to 30% over traditional heatshields. Ames Research Center has developed aeroshell instrumentation that could measure environmental conditions and material performance during atmospheric entry. Instruments to measure TPS recession, heat flux, and catalycity could be combined with traditional sensors to provide a "plug-and-play" system for minimal mass and power, that would acquire flight data for model improvement and risk reduction on future missions. Improved atmospheric and aerothermodynamic models ha also been a major focus of the program. Next Steps: Aerocapture is one of five technologies in competition for a flight validation opportunity through the New Millennium Program. If selected, a fully autonomous vehicle will perform an Aerocapture at Earth in 2010, and flight data will be used to validate the guidance system and the TPS material for science mission infusion.

Munk, Michelle M.↗
NASA NTRSDate not supplied

3D Material Response of the MSL Heatshield Using NuSil-Coated PICA

The Mars Science Laboratory (MSL) Entry, Descent and Landing Instrumentation (MEDLI) collected in-flight data largely used by the ablation community to verify and validate physics-based models for the response of the Phenolic Impregnated Carbon Ablator (PICA) material [1-4]. MEDLI data were recently used to guide the development of NASA’s high-fidelity material response models for PICA implemented in the Porous material Analysis Toolbox based on OpenFOAM (PATO) software [5-6]. A follow-up instrumentation suite, MEDLI2, was used for the Mars 2020 mission [7] after the large scientific impact of MEDLI. Recent analyses performed as part of MEDLI2 development drew the attention to significant effects of a protective coating to the aerothermal response of PICA. NuSil, a silicone-based overcoat sprayed onto the MSL heatshield, including the MEDLI plugs, as contamination control, is currently neglected in PICA ablation models. To mitigate the spread of phenolic dust from PICA, NuSil was applied to the entire MSL and Mars 2020 heatshields, including the MEDLI and MEDLI2 plugs. Ground testing of PICA-NuSil (PICA-N) models exhibited surface temperature jumps due to oxide scale formation and subsequent NuSil burn- off. It is therefore critical to include a model for the aerothermal response of the coating in ongoing code development and validation efforts. Figure 1 illustrates the PICA-N model implemented in PATO with a test case that shows a temperature jump and a change of recession rate at the wall after 20 seconds of simulation when the NuSil coating was fully removed.

Aerospace↗
NASA NTRS1989

Research and technology 1989

The Marshall Space Flight Center annual report summarizes their advanced studies, research programs, and technological developments. Areas covered include: transportation systems; space systems such as Gravity Probe-B and Gamma Ray Imaging Telescope; data systems; microgravity science; astronomy and astrophysics; solar, magnetospheric, and atomic physics; aeronomy; propulsion; materials and processes; structures and dynamics; automated systems; space systems; and avionics.

Source record↗
NASA NTRS2002

NASA Tech Briefs, September 2002

Topics include: a technology focus on data acquisition, electronic components and systems, software, materials, mechanics, machinery/automation, bio-medical, physical sciences, book and reports, and a special section of Photonics Tech Briefs.

Source record↗
NASA NTRS1998

NASA Tech Briefs, September 1998

Topics include: special coverage on data acquisition, also, electronic components and circuits, electronic systems, software, materials, mechanics, machinery/automation, physical sciences, information sciences, This issue contains a special sections of Electronics Tech Briefs and Motion Control Tech Briefs.

Source record↗
DOE OSTI2026

FAIR Data and Interpretable AI Framework for Architectured Metamaterials (Final Report)

This research program established a transformative framework for the discovery and design of mechanical metamaterials, which are architected structures engineered to control physical phenomena like sound and vibration in ways natural materials cannot. To overcome the traditional reliance on trial-and-error, the project developed an interpretable Artificial Intelligence (AI) framework that moves beyond "black box" models to reveal the specific geometric patterns—such as "unit-cell templates"—that govern a material’s performance. A major breakthrough was the development of a hierarchical design method, which allows a single material to block vibrations across multiple frequency ranges simultaneously by layering patterns at different scales without them interfering with one another. This was further expanded to include irregular, graph-based designs that use spanning tree algorithms to ensure structural connectivity while allowing for customized, direction-dependent properties like stiffness and acoustic impedance. Beyond design, the project addressed the practicalities of real-world production by developing uncertainty quantification techniques that account for manufacturing defects and material variability, reducing the need for expensive physical testing by orders of magnitude. To speed up the discovery process, the team implemented Gaussian Process Regression and other surrogate models that provide accurate performance predictions at a fraction of the traditional computational cost. The AI-generated designs were successfully validated through fabrication of physical samples and wave propagation experiments, confirming their ability to accurately guide or reflect waves as predicted. By contributing these tools and high-quality FAIR benchmark datasets to the wider scientific community, this work provides a scalable foundation for advancing technologies in aerospace vibration control, medical imaging, and noise reduction.

36 MATERIALS SCIENCE↗