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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 109 records · Page 6

Rethinking radiation effects in materials science using the plasma-focused ion beam

This work demonstrates the viability of using a plasma-focused ion beam (PFIB) as a new platform to carry out radiation effects studies in solids. While materials subjected to irradiation in either nuclear reactors or energetic particle accelerators experience limitations with respect to inaccuracies in both flux measurements and lack of precise control of irradiation areas, we demonstrate a new irradiation technique that allows the exposure of a single specimen in multiple areas, at multiple doses, and in site-specific dependencies - all with flux variations on the order of only 1%. This versatile technique also allows materials to be exposed to significantly higher irradiation dose rates than conventional accelerators. To validate the new methodology, we selected the classical example of ion-beam-induced amorphization of pure single-crystal Si. By pioneering the use of the PFIB for radiation effects studies in materials science, we were able to exploit, in both micro- and nanometer-sized detail, the differences in electron image contrast arising from crystalline versus amorphous solid-state phases in classical semiconductors subjected to irradiation, thus providing new insights on amorphization mechanisms. This methodology opens new research frontiers at the fringe of materials science with promising applications beyond the scope of materials at extremes such as in nanopatterning, nanodevices and nanoarchitectonics.

36 MATERIALS SCIENCE↗

Advances and opportunities in materials science for scalable quantum computing

We report that by harnessing unique quantum mechanical phenomena, such as superposition and entanglement, quantum computers offer the possibility to drastically outperform classical computers for certain classes of problems. The realization of this potential, however, presents a substantial challenge, because noise and imperfections associated with the materials used to fabricate devices can obscure the delicate quantum mechanical effects that enable quantum computing. Hence, progress in synthesis, characterization, and modeling of materials for quantum computing have driven many exciting advances in recent years and will become increasingly important in the years to come. As progressively more complex, multi-qubit systems come online, and as significant government and industrial investment drives research forward, new challenges and opportunities for materials science continue to emerge. The articles in this issue survey the current state of materials science progress and obstacles for some leading quantum computing platforms; opportunities for deeper involvement by materials scientists abound. Ultimate realization of the full potential of quantum computers will require a multidisciplinary effort spanning many traditional areas of expertise.

36 MATERIALS SCIENCE↗

Commutative Algebra Modeling in Materials Science – A Case Study on Metal–Organic Frameworks (MOFs)

Metal-organic frameworks (MOFs) are a class of important crystalline and highly porous materials whose hierarchical geometry and chemistry hinder interpretable predictions in materials properties. Commutative algebra is a branch of abstract algebra that has been rarely applied in data and material sciences. We introduce the first ever commutative algebra modeling and prediction in materials science. Specifically, category-specific commutative algebra (CSCA) is proposed as a new framework for MOF representation and learning. It integrates element-based categorization with multiscale algebraic invariants to encode both local coordination motifs and global network organization of MOFs. These algebraically consistent, chemically aware representations enable compact, interpretable, and data efficient modeling of MOF properties such as Henry’s constants and uptake capacities for common gases. Compared to traditional geometric and graph-based approaches, CSCA achieves comparable or superior predictive accuracy while substantially improving interpretability and stability across data sets. By aligning commutative algebra with the chemical hierarchy, the CSCA establishes a rigorous and generalizable paradigm for understanding structure and property relationships in porous materials and provides a nonlinear algebra-based framework for data-driven material discovery.

Khaemba, Caleb S.↗

Applications of synchrotron radiation to materials science: Diffraction imaging (topography) and microradiography

Synchrotron radiation sources are now available throughout the world. The use of hard X-ray radiation from these sources for materials science is described with emphasis on diffraction imaging for material characterization. With the availability of synchrotron radiation, real-time in situ measurements of dynamic microstructural phenomena have been started. This is a new area where traditional application of X-rays has been superseded. Examples are chosen from limited areas and are by no means exhaustive. The new emerging information will, no doubt, have great impact on materials science and engineering.

Kuriyama, Masao↗

Quantitative Scanning Transmission Electron Microscopy for Materials Science: Imaging, Diffraction, Spectroscopy, and Tomography

Scanning transmission electron microscopy (STEM) is one of the most powerful characterization tools in materials science research. Due to instrumentation developments such as highly coherent electron sources, aberration correctors, and direct electron detectors, STEM experiments can examine the structure and properties of materials at length scales of functional devices and materials down to single atoms. STEM encompasses a wide array of flexible operating modes, including imaging, diffraction, spectroscopy, and 3D tomography experiments. This review outlines many common STEM experimental methods with a focus on quantitative data analysis and simulation methods, especially those enabled by open source software. The hope is to introduce both classic and new experimental methods to materials scientists and summarize recent progress in STEM characterization. The review also discusses the strengths and weaknesses of the various STEM methodologies and briefly considers promising future directions for quantitative STEM research.

36 MATERIALS SCIENCE↗

Materials science on parabolic aircraft: The FY 1987-1989 KC-135 microgravity test program

This document covers research results from the KC-135 Materials Science Program managed by MSFC for the period FY87 through FY89. It follows the previous NASA Technical Memorandum for FY84-86 published in August 1988. This volume contains over 30 reports grouped into eight subject areas covering acceleration levels, space flight hardware, transport and interfacial studies, thermodynamics, containerless processing, welding, melt/crucible interactions, and directional solidification. The KC-135 materials science experiments during FY87-89 accomplished direct science, preparation for space flight experiments, and justification for new experiments in orbit.

Curreri, Peter A.↗

Preparation for microgravity: The role of the microgravity materials science laboratory

A laboratory dedicated to ground based materials processing in preparation for space flight was established at the NASA Lewis Research Center. Experiments are performed to delineate the effects of gravity on processes of both scientific and commercial interest. Processes are modeled physically and mathematically. Transport model systems are used where possible to visually track convection, settling, crystal growth, phase separation, agglomeration, vapor transport, diffusive flow, and polymers reactions. The laboratory contains apparatus which functionally duplicates apparatus available for flight experiments and other pieces instrumented specifically to allow process characterization. Materials addressed include metals, alloys, salts, glasses, ceramics, and polymers. The Microgravity Materials Science Laboratory is staffed by engineers and technicians from a variety of disciplines and is open to users from industry and academia as well as the government. Examples will be given of the laboratory apparatus typical experiments and results.

Johnston, J. Christopher↗

Seeing is Believing: Autonomous Microscopy and the Data Revolution in Materials Science

This presentation explores the transformative potential of autonomous electron microscopy and artificial intelligence (AI) in accelerating materials science discovery, particularly for energy applications and materials operating in extreme environments. We discuss pioneering self-driving laboratories at NREL designed to intelligently probe material synthesis and degradation across multiple scales, aiming to rapidly bridge the gap between atomic-level understanding and the development of high-performance, reliable materials. Utilizing advanced machine learning techniques, such as few-shot learning and multimodal analysis integrating imaging and spectroscopy, we demonstrate methods to extract actionable descriptors for material behavior, quantify complex microstructural evolution, and statistically link synthesis parameters to defect populations. This AI-driven approach promises to accelerate the creation of predictive materials tailored for specific missions, enabling faster development cycles and enhanced material assurance.

36 MATERIALS SCIENCE↗

Fault-tolerant operation and materials science with neutral atom logical qubits

We report on the fault-tolerant operation of logical qubits on a neutral atom quantum computer, with logical performance surpassing physical performance for multiple circuits including Bell state preparation (12x error reduction), random circuits (15x), and a prototype Anderson Impurity Model ground state solver for materials science applications (up to 6x, non-fault-tolerantly). The logical qubits are implemented via the [[4, 2, 2]] code (C 4 ). Our work constitutes the first complete realization of the benchmarking protocol proposed by Gottesman 2016 demonstrating results consistent with fault tolerance. In light of recent advances on applying concatenated C 4 /C 6 detection codes to achieve error correction with high code rates and thresholds, our work can be regarded as a building block towards a practical scheme for fault tolerant quantum computation. Our demonstration of a materials science application with logical qubits particularly demonstrates the immediate value of these techniques on current experiments.

36 MATERIALS SCIENCE↗

Materials Science Laboratory - Columnar-to-Equiaxed Transition in Solidification Processing and Microstructure Formation in Casting of Technical Alloys under Diffusive and Magnetically Controlled Convective Conditions

The Materials Science Laboratory - Columnar-to-Equiaxed Transition in Solidification Processing and Microstructure Formation in Casting of Technical Alloys under Diffusive and Magnetically Controlled Convective Conditions (MSL-CETSOL and MICAST) are two investigations which supports research into metallurgical solidification, semiconductor crystal growth (Bridgman and zone melting), and measurement of thermo-physical properties of materials. This is a cooperative investigation with the European Space Agency (ESA) and National Aeronautics and Space Administration (NASA) for accommodation and operation aboard the International Space Station (ISS). Research Summary: Materials Science Laboratory - Columnar-to-Equiaxed Transition in Solidification Processing (CETSOL) and Microstructure Formation in Casting of Technical Alloys under Diffusive and Magnetically Controlled Convective Conditions (MICAST) are two complementary investigations which will examine different growth patterns and evolution of microstructures during crystallization of metallic alloys in microgravity. The aim of these experiments is to deepen the quantitative understanding of the physical principles that govern solidification processes in cast alloys by directional solidification.

Gandin, Charles-Andre↗

Materials science experiments in space

The criteria for the selection of the experimental areas and individual experiments were that the experiment or area must make a meaningful contribution to the field of material science and that the space environment was either an absolute requirement for the successful execution of the experiment or that the experiment can be more economically or more conveniently performed in space. A number of experimental areas and individual experiments were recommended for further consideration as space experiments. Areas not considered to be fruitful and others needing additional analysis in order to determine their suitability for conduct in space are also listed. Recommendations were made concerning the manner in which these materials science experiments are carried out and the related studies that should be pursued.

Gelles, S. H.↗

Computational techniques in tribology and material science at the atomic level

Computations in tribology and material science at the atomic level present considerable difficulties. Computational techniques ranging from first-principles to semi-empirical and their limitations are discussed. Example calculations of metallic surface energies using semi-empirical techniques are presented. Finally, application of the methods to calculation of adhesion and friction are presented.

Ferrante, J.↗

Lab Manual & Resources for Materials Science, Engineering and Technology on CD-Rom

The National Educators' Workshop (NEW:Update) series of workshops has been in existence since 1986. These annual workshops focus on technical updates and laboratory experiments for materials science, engineering and technology, involving new and traditional content in the field. Scores of educators and industrial and national laboratory personnel have contributed many useful experiments and demonstrations which were then published as NASA Conference Proceedings. This "out poring of riches" creates an ever-expanding shelf of valuable teaching tools for college, university, community college and advanced high school instruction. Now, more than 400 experiments and demonstrations, representing the first thirteen years of NEW:Updates have been selected and published on a CD-ROM, through the collaboration of this national network of materials educators, engineers, and scientists. The CD-ROM examined in this document utilizes the popular Adobe Acrobat Reader format and operates on most popular computer platforms. This presentation provides an overview of the second edition of Experiments in Materials Science, Engineering and Technology (EMSET2) CD-ROM, ISBN 0-13-030534-0.

Jacobs, James A.↗

Materials science

The first Spacelab space processing payload includes the following categories of hardware: (1) multiuser facilities, (2) common-support equipment, and (3) six autonomous experiments. All the hardware, with the exception of two elements (covering three experiments), will be integrated in a Spacelab double rack called the materials science double rack. The payload experimental facilities are intended to perform, during the first Spacelab mission, a number of significant pilot experiments in the fields of crystal growth, fluid physics and metallurgy, and, at the same time, to flight-verify the materials science hardware items developed (e.g., various furnaces, process chambers, etc.).

Huth, U.↗

Microanalytical Efforts in Support of NASA's Materials Science Programs

Following a brief overview of NASA s Microgravity Materials Science programs, specific examples will be given showing electron beam and optical microscopic applications to two-phase glass structures, dendrite tip radii, solid solution semiconductors, undercooled two-phase stainless steels and meteorites.

Gillies, Donald C.↗

The concept verification testing of materials science payloads

The concept Verification Testing (CVT) project at the Marshall Space Flight Center, Alabama, is a developmental activity that supports Shuttle Payload Projects such as Spacelab. It provides an operational 1-g environment for testing NASA and other agency experiment and support systems concepts that may be used in shuttle. A dedicated Materials Science Payload was tested in the General Purpose Laboratory to assess the requirements of a space processing payload on a Spacelab type facility. Physical and functional integration of the experiments into the facility was studied, and the impact of the experiments on the facility (and vice versa) was evaluated. A follow-up test designated CVT Test IVA was also held. The purpose of this test was to repeat Test IV experiments with a crew composed of selected and trained scientists. These personnel were not required to have prior knowledge of the materials science disciplines, but were required to have a basic knowledge of science and the scientific method.

Griner, C. S.↗

Recent advances and applications of deep learning methods in materials science

Deep learning (DL) is one of the fastest-growing topics in materials data science, with rapidly emerging applications spanning atomistic, image-based, spectral, and textual data modalities. DL allows analysis of unstructured data and automated identification of features. The recent development of large materials databases has fueled the application of DL methods in atomistic prediction in particular. In contrast, advances in image and spectral data have largely leveraged synthetic data enabled by high-quality forward models as well as by generative unsupervised DL methods. In this article, we present a high-level overview of deep learning methods followed by a detailed discussion of recent developments of deep learning in atomistic simulation, materials imaging, spectral analysis, and natural language processing. For each modality we discuss applications involving both theoretical and experimental data, typical modeling approaches with their strengths and limitations, and relevant publicly available software and datasets. We conclude the review with a discussion of recent cross-cutting work related to uncertainty quantification in this field and a brief perspective on limitations, challenges, and potential growth areas for DL methods in materials science.

36 MATERIALS SCIENCE↗