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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 37 records · Page 2

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.

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 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.

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.

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.

Beyond the Hype: Navigating the Promise and Pitfalls of Multi-Modal Models for Materials Science

Multi-modal models offer great potential for accelerating discovery in materials and chemical systems, but their adoption raises crucial questions: What materials science challenges are best addressed by multi-modal approaches? How do we weigh the benefits against the resource investment required for multi-modal data acquisition? And critically, how can we optimize experimental workflows to leverage these models effectively? In this presentation, I will delve into the development of multi-modal characterization and analytics, focusing on their application in the demanding fields of next-generation microelectronics and energy storage materials. I will share challenges encountered in designing these workflows, highlighting lessons learned and posing questions that remain unanswered.

AI

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.

97 MATHEMATICS AND COMPUTING

Status and plans of NASA's Materials Science and Manufacturing in Space /MS-MS/ program.

Following two years of relatively low-level exploratory work, the Materials Science and Manufacturing in Space program is now in a phase of expansion toward higher levels of effort. The main thrust of this effort is toward initiation of a research and development program on the Space Shuttle missions that can prepare the way for possible commercial manufacturing operations on permanently orbiting space stations. Experiment capabilities currently being planned for the Space Shuttle will be based on an inventory of reusable general-purpose equipment that can be configured in many different ways to meet individual experiment requirements. It is expected that this approach can support very large numbers of experiments and make flight opportunities accessible to many potential experimenters who would not be prepared to involve themselves in the development of flight hardware.

Armstrong, W. O.

Annual review of materials science in space

The weightlessness of objects in free fall permits numerous novel manipulations of multiphase systems and suppresses buoyancy and convection in liquids and gases. In the present paper, the prospects for materials science in space are examined on the basis of the materials experiments performed on Skylab, including biological preparations and crystal growth. Plans for technology-oriented research on Spacelab are reviewed.

Bredt, J. H.

Compact acoustic levitation device for studies in fluid dynamics and material science in the laboratory and microgravity

An ultrasonic levitation device operable in both ordinary ground-based as well as in potential space-borne laboratories is described together with its various applications in the fields of fluid dynamics, material science, and light scattering. Some of the phenomena which can be studied by this instrument include surface waves on freely suspended liquids, the variations of the surface tension with temperature and contamination, the deep undercooling of materials with the temperature variations of their density and viscosity, and finally some of the optical diffraction properties of transparent substances.

Trinh, E. H.

Materials sciences research

Research projects involving materials research conducted by various international test facilities are reported. Much of the materials research is classified in the following areas: (1) acousto-optic, acousto-electric, and ultrasonic research, (2) research for elucidating transport phenomena in well characterized oxides, (3) research in semiconductor materials and semiconductor devices, (4) the study of interfaces and interfacial phenomena, and (5) materials research relevant to natural resources. Descriptions of the individual research programs are listed alphabetically by the name of the author and show all personnel involved, resulting publications, and associated meeting speeches.

Source record

The Concept Verification Testing of a materials science payload

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 one-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 (GPL) in December 1974 in order 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. The Principal Investigators (PI) who had proposed experiments were onboard and in a consulting status on the ground. The significant results of the week-long simulation will be discussed.

Griner, C. S.

Multireference Methods for Chemistry and Materials Science: Automated Active Spaces, Efficient Dynamic Correlation, and Extended Systems

While multiconfigurational approaches have long been relegated to expert practitioners working on a case-by-case basis, recent developments have increasingly made these methods more routine and applicable to broader sets of systems. This article outlines the state-of-the-art in multiconfigurational approaches, with an emphasis on moving from delicate hand-selected pathways through configuration space toward more robust and efficient approaches to treating a host of challenging chemical systems accurately. First, we overview recent work in automated active-space selection, which has enabled increasingly large-scale applications of multireference methods to modeling vertical excitations and reactivity. Second, we highlight the increasingly efficient methods for recovering correlation energy beyond the active space, as headlined by extensions of pair-density functional theory and its role in accurate and efficient treatment of excited-state dynamics and its utilization to train machine-learned potentials. Finally, we highlight recent efforts to treat extended systems that until recently have lied beyond the traditional limits of active-space methods, giving center stage to product-form wave functions of the localized active space family of methods that allow for the computation of multiconfigurational band structures. These recent advancements point to a broader use of multireference approaches for high-impact chemical and materials science applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH