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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

The Science of Detached Bridgman Growth and Solutocapillary Convection in Solid Solution Crystals

Bridgman and Float-zone crystal growth experiments are planned for NASA's First Materials Science Research Rack using the European Space Agency's Materials Science Laboratory with the Low Gradient Furnace (LGF) and Float Zone Furnace with Rotating Magnetic Field (FMF) inserts, respectively. Samples will include germanium and germanium-silicon alloys with up to 10 atomic percent silicon. The Bridgman part of the investigation includes detached growth samples and so there will be a solid-liquid-gas tri-junction in those experiments just as there will be in all float-zone experiments. There are other similarities as well as significant differences between the types of growth that will be discussed. The presentation will call attention to the reasons that experiments in microgravity will provide information unattainable from Earth-based experiments.

Szofran, F. R.↗
NASA NTRS2000

Microgravity Disturbance Characterization of the Quench Module Insert (QMI) Phase Change Device (PCD)

The Materials Science Research Facility (MSRF) is a multi-user, multi-purpose facility for materials science research. One experiment within the MSRF will be the Quench Module Insert (QMI), a high-temperature furnace with unique capabilities for processing different classes of materials. The primary functions of the QMI furnace are to melt, directionally solidify, and quench metallic samples, providing data to aid in understanding the effects of the microgravity environment on the characteristics of these processed metals. The QMI houses sealed individual sample ampoules containing material to be processed. Quenching of the samples in the QMI furnace is accomplished by releasing low-melting-point metallic shoes into contact with the outside of the sample ampoule, dissipating heat and cooling the sample inside. The impact from this method of quench will induce sample vibrations which could be large enough to adversely affect sample quality. Utilizing breadboard hardware, the sample quench sequence, releasing the shoes, was conducted. Data was collected from accelerometers located on the breadboard sample cartridge, indicating the maximum acceleration achieved by the sample. The primary objective of the test described in this presentation was to determine the acceleration imparted on the sample by the shoe contact. From this information, the science community can better assess whether this method of quench will allow them to obtain the data they need.

Gattis, Christy↗
DOE OSTI2026

Freeze It or Leave It? Evaluating the Role of Cryo-Electron Microscopy in Battery Research

Cryogenic electron microscopy (cryo-EM) continues to gain prominence in materials science, particularly in battery research where it has enabled high-resolution, multimodal characterization of electrode materials and interfaces that otherwise degrade quickly under electron beam irradiation. But as anyone who has attempted cryo-EM techniques knows, freezing comes at a cost; cryo-EM experiments are time-consuming, highly sensitive, and carry an increased risk of artifacts due to issues such as frost contamination. Thus, when planning new characterization of battery materials or other beam-sensitive samples, it is critical to consider whether (and which) cryo-EM techniques are appropriate, based on study goals and an understanding of electron beam-sample interactions. Here we review such considerations for battery materials to elucidate the questions of when, why, and how to freeze to achieve high-quality characterization.

25 ENERGY STORAGE↗
DOE OSTI2025

Materials Research at Idaho National Laboratory

I am going to spent 8 mins to introduce materials science related research at INL to the student and early career researchers who attend MRS Falls 2025. I am one of 10 panelists, all of whom are from different national labs.

36 - MATERIALS SCIENCE↗
NASA NTRS1992

NASA-UVA light aerospace alloy and structures technology program (LA2ST)

The NASA-UVa Light Aerospace Alloy and Structure Technology (LAST) Program continues to maintain a high level of activity, with projects being conducted by graduate students and faculty advisors in the Departments of Materials Science and Engineering, Civil Engineering and Applied Mechanics, and Mechanical and Aerospace Engineering at the University of Virginia. This work is funded by the NASA-Langley Research Center under Grant NAG-1-745. Here, we report on progress achieved between January 1 and June 30, 1992. The objectives of the LA2ST Program is to conduct interdisciplinary graduate student research on the performance of the next generation, light weight aerospace alloys, composites and thermal gradient structures in collaboration with Langley researchers. Technical objectives are established for each research project. We aim to produce relevant data and basic understanding of material mechanical response, corrosion behavior, and microstructure; new monolithic and composite alloys; advanced processing methods; new solid and fluid mechanics analyses; measurement advances; and critically, a pool of educated graduate students for aerospace technologies. The accomplishments presented in this report cover topics including: (1) Mechanical and Environmental Degradation Mechanisms in Advance Light Metals and Composites; (2) Aerospace Materials Science; (3) Mechanics of Materials and Composites for Aerospace Structures; and (4) Thermal Gradient Structures.

Gangloff, Richard P.↗
DOE OSTI2025

Keeping LAMMPS cutting edge

Since its inception 30 years ago, LAMMPS has grown to be a world-class molecular dynamics code and a cornerstone of computational materials science research. This project aimed to keep LAMMPS at the forefront of molecular dynamics simulations by adapting LAMMPS to the latest developments in machine learning technology and hardware. Initially, the project set out to provide a unified implementation of active learning for efficient training data generation in LAMMPS, but the research trajectory pivoted to address more immediate and impactful opportunities. On the hardware side, recent record-breaking molecular dynamics simulations were developed on the Cerebras wafer-scale AI chip, and this project has developed an interface between LAMMPS and the hardware-specific molecular dynamics code to accelerate and simplify development and user adoption. On the software side, PyTorch’s Ahead-of-Time (AOT) compilation features promised increased performance for state-of-the-art equivariant neural network potentials, and this project laid the groundwork for their adoption in LAMMPS, resulting in a nearly 20x acceleration in extreme cases. Combined with a comprehensive benchmark study of LAMMPS across all current exascale systems, this project has reinforced LAMMPS’s role as a versatile, high-performance tool for current and future materials science applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Uncertainty-Driven Rapid Thermodynamic Assessment of Nb-Ta-Zr System and Effects of C impurities (L25GF9298S): Annual Progress Report

An integrated computational materials engineering (ICME) method is in development for rapid thermodynamic experimental investigation and high-fidelity computational modeling of refractory multi-principal element alloys (RMPEAs). These ultra-high-temperature (UHT) alloys are of interest for structural applications in extreme environments, but deficiency of reliable data, especially melting temperatures, impedes the prediction of alloys with favorable properties. The method leverages UHT capabilities and computational expertise of LLNL’s Materials Science Division and the McCormack Lab’s UHT conical nozzle levitation (CNL) system to iteratively map the Nb-Ta-Zr phase space, with focus on the liquidus surface, through targeted experiments selected by quantifying uncertainty in the thermodynamic model fitting parameters. This method will reduce the time to map uncharted RMPEA phase space and thereby accelerate discovery and development of advanced materials for applications in extreme environments.

36 MATERIALS SCIENCE↗
NASA NTRS2018

Composite Bonded Joint: Repair Development

This report documents the details of my work as a NASA KSC intern for the Fall Session from August 27th to December 14th, 2018. My efforts and contributions were with the Materials Science Branch, a staffed organization within the Laboratories, Development, & Testing (NE-L) Division of the Engineering Directorate. The principle responsibilities of the Materials Science group are to support the design, development, and operations activities for materials and processes with the purpose of providing unique solutions for flight hardware, ground support equipment, and customer requests. My role as an intern focused on assisting engineers in developing repair processes to mature bonded joint technology in support of SLS ? scale hardware. My primary goals for this internship were to become more familiar with composite materials and learn more about processes I was unfamiliar with, such as prepregs and out-of-autoclave processing. This project allowed me to learn new skills such as scarfing and curing composites. Additional goals I had were to learn more about NASA's laboratories and projects under development. This internship not only provided me with those experiences, but also allowed me to build relationships with inspiring engineers; a takeaway I will never forget.

Composite Materials↗
NASA NTRS1988

Containerless science for materials processing

Containerless materials processing in space to restrict specimen deformation from hydrostatic pressure of contact with the container is discussed. Several containerless science studies are reviewed, including the study of drop dynamics, nucleation studies, metastable solid phases experiments, glass research, biological materials research, and protein crystal growth. The development of technologies for materials research in space are examined, including acoustic containerless systems, and electrostatic and electromagnetic containerless processing.

Wang, T. G.↗
DOE OSTI2024

Reactive Carbon Capture: Cooperative and Bifunctional Adsorbent-Catalyst Materials and Process Integration for a New Carbon Economy

To say the least, releasing CO 2 into the atmosphere is reaping undue environmental consequences given the ever-present increase in severe global weather events over the past five years. However, it can be argued that–at least in the confines of current technological capabilities–the atmospheric release of CO 2 is somewhat unavoidable given that even shifting toward clean energy sources–such as solar, nuclear, wind, battery, or H 2 power–incurs an initial carbon requirement by way of manufacturing the very production abilities through which “clean” energy is generated. Even years from now, experts agree that energy production will be diversified and–as the global population continues to drive the growth of global energy consumption–thermal power derived from carbon combustion is likely to remain one intrinsic energetic source, of which CO 2 will always be a byproduct. In this context, it is the responsibility of the scientific community to devise improved pathways of carbon management such that (i) the consequences of combustion on the global environment are reduced and (ii) carbon fuels can be leveraged in a sustainable fashion. In this Account, we discuss a pivotal perspective shift on CO 2 emissions derived from a considerable breakthrough in material science from our work on shape engineering of nanoporous adsorbents and catalysts. This account details the development of materials which no longer vilify CO 2 emissions as a valueless combustion byproduct, instead providing a path for them to become a potential feedstock. In more specific terms, this work details the development of structured, cooperative “bifunctional” materials (BFMs) comprised of (i) a high-temperature adsorbent and (ii) a heterogeneous catalyst that enable single-bed CO 2 capture and utilization in oxidative ethane dehydrogenation (ODHE), oxidative propane dehydrogenation (ODHP), and dry methane reforming (DMR) processes. This Account begins with the conceptual development of the BFMs in the powdered state, followed by detailing the first-ever reports of structuring the materials into facile honeycomb contactors by 3D printing. The Account then summarizes the impressive performance of the 3D-printed BFMs, specifically focusing on how their catalysts (metal oxides and perovskites) influence their reactive CO 2 capture performances in ODHE, ODHP, and DMR processes. Such promise of CO 2 -as-fuel offers a glimpse into the future of a diversified energy economy, in which CO 2 /fuel looping can play an important role. A major factor in achieving this future is, of course, developing an appropriately active catalyst; an account of whose first breakthroughs in material science are detailed herein.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2012

Overview of NASA's Microgravity Materials Research Program

The NASA microgravity materials program is dedicated to conducting microgravity experiments and related modeling efforts that will help us understand the processes associated with the formation of materials. This knowledge will help improve ground based industrial production of such materials. The currently funded investigations include research on the distribution of dopants and formation of defects in semiconductors, transitions between columnar and dendritic grain morphology, coarsening of phase boundaries, competition between thermally and kinetically favored phases, and the formation of glassy vs. crystalline material. NASA microgravity materials science investigators are selected for funding either through a proposal in response to a NASA Research Announcement or by participation in a team proposing to a foreign agency research announcement. In the latter case, a US investigator participating in a successful proposal to a foreign agency can then apply to NASA for funding of an unsolicited proposal. The program relies on cooperation with other aerospace partners from around the world. The ISS facilities used for these investigations are provided primarily by partnering with foreign agencies and in most cases the US investigators are working as a part of a larger team studying a specific area of materials science. The following facilities are to be utilized for the initial investigations. The ESA provided Low Gradient Facility and the Solidification and Quench Inserts to the Materials Research Rack/Materials Science Laboratory are to be used primarily for creating bulk samples that are directionally solidified or quenched from a high temperature melt. The CNES provided DECLIC facility is used to observe morphological development in transparent materials. The ESA provided Electro-Magnetic Levitator (EML) is designed to levitate, melt and then cool samples in order to study nucleation behavior. The facility provides conditions in which nucleation of the solid is not triggered from the wall and in which fluid flows in the sample can be controlled and manipulated. These conditions allow scientists ideal conditions for understanding the relative amounts and distribution of different phases that form in the solid. Finally, the Coarsening of Solid Liquid Melts hardware allows quenching of low temperature samples in the Microgravity Science Glovebox.

Downey, James Patton↗
DOE OSTI2026

Knowledge gaps for neuromorphic ionic computing

BACKGROUND Neuromorphic computing, inspired by the human brain’s ability to process information efficiently, represents a transformative approach to computation. In this Review, we explore the emerging field of neuromorphic ionic computing, which leverages ionic conduction and coupling to mimic neural processes, and identify critical knowledge gaps that must be addressed to realize its full potential. A central theme of the discussion is energy efficiency, a challenge that is both a limitation and an opportunity for this technology. Although complementary metal-oxide semiconductor (CMOS)–based neuromorphic technologies have made strides in scaling to billions of neurons and are increasingly applied in artificial intelligence and numerical computing, they remain orders of magnitude behind the human brain in terms of connectivity and energy efficiency. Neuromorphic ionic computing promises to overcome these limitations by leveraging the distinct architectural and operational principles of the brain. Our brains achieve this energy efficiency by combining several key features: using the same network elements to store and process information; using an incredibly complex and massively interconnected three-dimensional (3D) network of locally active elements that enables sparsity, robustness in the presence of noise, adaptation, and life-long learning; computing at comparatively low voltage and frequency; and last, taking advantage of a plethora of ions and small molecules as information carriers. Here, we propose that ionic computing systems can take advantage of similar features to achieve substantial gains in energy efficiency. ADVANCES Since the first reports of neuromorphic ionic behavior in nanofluidic channels, we have witnessed an explosion of reports that used ionic devices to produce synaptomimetic behaviors. However, achieving the goals of ionic computing requires not only implementation of much more sophisticated device functionality but also overcoming fundamental barriers in materials science, device architecture, and system integration. Current ionic devices, even those incorporating state-of-the-art materials, still suffer from limited functionality and stability, which restrict their performance and increase energy demands. Developing new materials with enhanced ionic properties is essential to overcome these limitations. Similarly, the design of neuromorphic devices must evolve to leverage the particular advantages of ionic processes. Existing architectures often follow a single-information-carrier logic of conventional electronics or are constructed of mesoscale fluidics, failing to capitalize on the energy-efficient mechanisms inherent to ionic systems or implement the multiple-information-carrier paradigm. Current neuromorphic chips focus on large-scale networks of analog memory elements based on mechanisms such as charge trap (flash), filamentary, phase change, or spin, which are built on top of a network of artificial CMOS neurons. Although such prototype networks have achieved impressive performance, it is difficult to envision how they can implement the key features such as massive connectivity, sophisticated plasticity, adaptability, sparsity, and “multichromatic” computing. Although small-scale devices have demonstrated promising results, integrating them, maintaining energy efficiency, and implementing temperature control as systems grow in complexity and size to computationally relevant scale remain major hurdles. Furthermore, interfacing neuromorphic ionic devices with existing computing technologies presents technical and conceptual challenges that will require innovative approaches that combine insights from neuroscience, materials science, and engineering. OUTLOOK Despite these challenges, the potential impact of neuromorphic ionic computing is profound with potential applications ranging from artificial intelligence to robotics and beyond. We also argue that neuromorphic ionic computing systems should not, at least in the beginning, compete with CMOS technologies but rather should focus on applications that require extreme energy efficiency with chemical and/or biological compatibility, such as biomedical applications (for example, brain-computer interfaces), environmental monitoring, and agricultural and food applications. Ultimately, this Review highlights the crucial role of interdisciplinary collaboration in advancing the field. Neuromorphic ionic computing is not merely a technological innovation; it represents a substantial step toward sustainable computation, aligning with the growing demand for energy-conscious solutions in a world that is increasingly reliant on data and computation.

Neuromorphic↗
DOE OSTI2024

Materials Characterization: A Primer for Solid Phase Processing Applications

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development (LDRD) Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems produced via advanced manufacturing methods, such as solid phase processing, for use in national security and advanced energy applications (Smith 2021). As a two-year LDRD investment requiring focused research, the MCPC project applied only a subset of the wide range of available destructive and nondestructive characterization methods to provide data to the predictive modeling and data analytics tasks. The purpose of this report is to review a wide range of destructive and nondestructive characterization methods that are relevant in solid-phase processing (SPP) applications, but not necessarily applied in the MCPC Project as a guide to the planning of characterization activities in future research. Particular attention is given to measured characteristics that can correlate to other material characteristics, with a particular interest in nondestructive evaluation (NDE) that can be applied to samples obtained in the MCPC Project. Destructive examinations include tensile tests, optical and electron microscopy, micro-hardness, and residual stress tests. NDE tests include surface visual inspection, eddy current examination for cracks, 4-point potential drop, ultrasound, x-ray, and computed tomography.

36 MATERIALS SCIENCE↗
DOE OSTI2025

MS25: Materials Science-Focused Benchmark Data Set for Machine Learning Interatomic Potentials

Here, we present MS25, a benchmark data set for evaluating machine learning interatomic potentials (MLIPs) across diverse materials-relevant systems including MgO surfaces, liquid water, zeolites, a catalytic Pt surface reaction, high-entropy alloys (HEAs), and disordered Zr-oxides. Five MLIP architectures (MACE, NequIP, Allegro, MTP, and Torch-ANI) are trained and tested, focusing not only on traditional metrics (energies, forces, and stresses) but also explicitly validating derived physical observables such as lattice constants, volumes, and reaction barriers. We find that most models reach comparable accuracy on standard error metrics across the simple systems, although equivariant MLIPs offer 1.5–2× improvements over nonequivariant MLIPs in energy and force error for structurally complex or compositionally disordered environments such as HEAs and Zr–O systems. Our analysis highlights that low errors in energy and force predictions do not guarantee reliable observables, emphasizing the necessity of explicit validation. We demonstrate limitations in cross-framework transferability, as models trained on one zeolite framework (CHA) fail to reliably generalize to predictions of structurally distinct frameworks (e.g., MFI). Size-extensive tests show some dependence on system size for MgO, resulting from forced periodicity. The HEA and Zr–O data sets are identified as challenging tests for future benchmarks and MLIP model architecture developments as they show significant differentiation in error between MLIP architectures and are still relatively difficult at 1000 training images. Moving forward, we recommend that benchmarking efforts shift their focus from marginal accuracy improvements in energy and force errors toward identifying and understanding model failure modes, rigorously assessing transferability, and evaluating how their errors affect observable predictions. For researchers looking to choose an MLIP architecture, we suggest selecting equivariant MLIP architectures if the complexity of the system is a challenge. For simple materials problems, auxiliary features such as integration with molecular dynamics engines, trade-offs between computational data set generation cost vs MLIP inference speed, and framework integration may play a more important decision factor than small differences in error metrics that are unlikely to matter for production-level research.

chemical structure↗
NASA NTRS1986

High-resolution Surface Analysis by Microarea Auger Spectroscopy: Computerization and Characterization

A custom scanning Auger electron microscope (SAM) capable of introducing a 3-5 keV electron beam of several nA into a 30 nm diameter sample area was fitted with a sample introduction system and was fully computerized to be used for materials science research. The method of multispectral Auger imaging was devised and implemented. The instrument was applied to various problems in materials science, including the study of the fiber/matrix interface in a SiC reinforced titanium alloy, the study of SiC whiskers in Al alloy 2124 (in cooperation with NASA-Langley), the study of NiCrAl superalloys (in collaboration with NASA-Lewis), the study of zircalloy specimens (in collaboration with Stanford University), and the microstructure of sintered SiC specimens (in collaboration with NASA-Lewis). The report contains a number of manuscripts submitted for publication on these subjects.

Browning, R.↗
DOE OSTI2024

From Chaos to Clarity: Autonomous Materials Discovery for Extreme Environments [Slides]

The pursuit of advanced functional materials for energy applications demands an understanding of their behavior under the most challenging conditions. Extreme environments, characterized by intense radiation, high temperatures, and corrosive chemistries, push materials to their limits, often revealing unexpected behaviors and degradation pathways. Traditional materials research approaches, relying on trial-and-error experimentation, are often slow and resource-intensive, ill-suited to the complexities of extreme environments. This talk will explore the transformative potential of autonomous materials science in revolutionizing our understanding of materials synthesis and degradation in extreme environments. By integrating advanced microscopy techniques, artificial intelligence, and robotic experimentation, we can accelerate the discovery and design of resilient materials for a sustainable future. The presentation will highlight recent breakthroughs in autonomous microscopy, computer vision, and machine learning, showcasing their ability to unravel complex material transformations at the atomic scale. The talk will also delve into the challenges and opportunities associated with deploying autonomous systems to probe extreme environments, emphasizing the importance of robust algorithms, real-time data analysis, and adaptive experimentation. The ultimate goal is to empower scientists with unprecedented capabilities to explore, understand, and engineer materials that can withstand the harshest conditions, paving the way for innovations in energy, aerospace, and beyond.

14 SOLAR ENERGY↗
NASA NTRS1988

Ten past and ten future GAS/MAUS-payloads

MAUS (materials science autonomous experiments) is one out of a series of flight opportunities which the Space Program of West Germany offers to scientists from the disciplines of materials research and processing for performing materials science investigations under microgravity conditions. Up to now, ten MAUS experiments were flown which were dealing with the following scientific topics: decomposition of binary alloys with miscibility gap in the liquid state, interaction of a solidification front with dispersed particles, critical Marangoni number, investigation of the magnetic compound MnBi, shrinkage of gas bubbles in glass melts and slip casting. The ten future experiments are partly reflights with modification of the scientific objectives as well as new experiments in the fields of chemical reactions, heat transfer, glass technology and Ostwald ripening. Looking to ten flown payloads, the peculiarities of instrument technology in GAS-cans and its evolution is discussed with emphasis on structure, electronics and thermal design. A typical modern payload using 100 percent of the resource is presented.

Staniek, S.↗
DOE OSTI2026

Designing and Utilizing Material Acceleration Platforms: Need for Workforce Development

In the quest to accelerate scientific discovery, the materials science field is rapidly moving toward the implementation of robotics and artificial intelligence driven workflows. Our recent summer school “Future Labs: Robotic Synthesis Coupled with Machine Learning for Energy Materials” provided learning opportunities for students, researchers, and educators in the materials science community. We describe this experience and provide our perspective on which new directions could be pursued to enable the future workforce to acquire cross-disciplinary skills.

Educational policy↗