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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Energy Materials Chemistry Integrating Theory, Experiment and Data Science (Final Report)

The Energy Materials Chemistry Integrating Theory, Experiment and Data Science (EM-CITED) project is a multidisciplinary research effort focused on accelerating discovery of scientific knowledge via incorporation of data science and artificial intelligence in materials chemistry research. The project aims to advance materials chemistry-aware data science to unify theory and experiment knowledge streams. The work resulted in foundational AI frameworks for materials chemistry – Deep Reasoning Networks (DRNets), Hierarchical Correlation Learning for Multi-property Prediction (H-CLMP), and Material-to-Spectrum (Mat2Spec) prediction – as well as a host of strategies for accelerated scientific discoveries through principled incorporation of data science in computational and experimental research.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A foundation model for atomistic materials chemistry

Atomistic simulations of matter, especially those that leverage first-principles (ab initio) electronic structure theory, provide a microscopic view of the world, underpinning much of our understanding of chemistry and materials science. Over the last decade or so, machine-learned force fields have transformed atomistic modeling by enabling simulations of ab initio quality over unprecedented time and length scales. However, early machine-learning (ML) force fields have largely been limited by (i) the substantial computational and human effort required to develop and validate potentials for each particular system of interest and (ii) a general lack of transferability from one chemical system to the next. Here, we show that it is possible to create a general-purpose atomistic ML model, trained on a public dataset of moderate size, that is capable of running stable molecular dynamics for a wide range of molecules and materials. We demonstrate the power of the MACE-MP-0 model-and its qualitative and at times quantitative accuracy-on a diverse set of problems in the physical sciences, including properties of solids, liquids, gases, chemical reactions, interfaces, and even the dynamics of a small protein. The model can be applied out of the box as a starting or "foundation" model for any atomistic system of interest and, when desired, can be fine-tuned on just a handful of application-specific data points to reach ab initio accuracy. Establishing that a stable force-field model can cover almost all materials changes atomistic modeling in a fundamental way: experienced users obtain reliable results much faster, and beginners face a lower barrier to entry. Foundation models thus represent a step toward democratizing the revolution in atomic-scale modeling that has been brought about by ML force fields.

Batatia, Ilyes↗
NASA NTRS1994

The Materials Chemistry of Atomic Oxygen with Applications to Anisotropic Etching of Submicron Structures in Microelectronics and the Surface Chemistry Engineering of Porous Solids

Neutral atomic oxygen is the most abundant component of the ionospheric plasma in the low Earth orbit environment (LEO; 200 to 700 kilometers altitude) and can produce significant degradation of some spacecraft materials. In order to produce a more complete understanding of the materials chemistry of atomic oxygen, the chemistry and physics of O-atom interactions with materials were determined in three radically different environments: (1) The Space Shuttle cargo bay in low Earth orbit (the EOIM-3 space flight experiment), (2) a high-velocity neutral atom beam system (HVAB) at Los Alamos National Laboratory (LANL), and (3) a microwave-plasma flowing-discharge system at JSC. The Space Shuttle and the high velocity atom beam systems produce atom-surface collision energies ranging from 0.1 to 7 eV (hyperthermal atoms) under high-vacuum conditions, while the flowing discharge system produces a 0.065 eV surface collision energy at a total pressure of 2 Torr. Data obtained in the three different O-atom environments referred to above show that the rate of O-atom reaction with polymeric materials is strongly dependent on atom kinetic energy, obeying a reactive scattering law which suggests that atom kinetic energy is directly available for overcoming activation barriers in the reaction. General relationships between polymer reactivity with O atoms and polymer composition and molecular structure have been determined. In addition, vacuum ultraviolet photochemical effects have been shown to dominate the reaction of O atoms with fluorocarbon polymers. Finally, studies of the materials chemistry of O atoms have produced results which may be of interest to technologists outside the aerospace industry. Atomic oxygen 'spin-off' or 'dual use' technologies in the areas of anisotropic etching in microelectronic materials and device processing, as well as surface chemistry engineering of porous solid materials are described.

Koontz, Steve L.↗
DOE OSTI2026

Cellulose-MOFs hybrid materials: Chemistry and mechanism of applications in biomedical - A review

Rising costs and performance limits of modern biomedical materials motivate the search for advanced, biocompatible alternatives. Cellulose-based metal-organic frameworks (cellulose-MOFs) emerge as distinctive hybrids combining renewable polymer chemistry with tunable porous architectures, enabling uncommon structure–function relationships. Their large surface area, controllable pore size, adaptable functional groups, and efficient host–guest interactions underpin diverse biomedical functions. Till now, no comprehensive, application-focused review has systematically summarized cellulose-MOFs synthesis for biomedical applications. This review critically analyzes cellulose-MOFs, emphasizing mechanistic links between chemistry, synthesis routes, interfacial interactions, and biomedical performance, rather than cataloging applications alone. Antibacterial action, targeted drug delivery, and sensing/biosensing are discussed through comparative insights. The article identifies unresolved challenges and proposes future research pathways to rationally design next-generation cellulose-MOFs systems, guiding researchers and clinicians alike.

Biomedical↗
DOE OSTI2026

Examination of Replicate Syntheses of Metal Organic Frameworks as a Window into Reproducibility in Materials Chemistry

Replicate experiments are a useful tool in understanding the repeatability of scientific measurements. In 2019, a systematic search for replicate syntheses of a collection of 130 metal–organic frameworks (MOFs) found that 89% of these materials had no reported replicate syntheses apart from the original publications identifying the material (Agrawal, M. Proc. Natl. Acad. Sci. U.S.A. 2020, 117, 877−88210.1073/pnas.1918484117). A potential weakness of that search was that only 5–11 years had elapsed since the original publication of each material. Here, this analysis is extended to all publications 11–17 years after the original publication. Although this extended time period identifies more repeat syntheses, 83% of the materials still have no reported replicate syntheses. We also consider how appropriately selected Density Functional Theory (DFT) calculations can provide corroboration for the experimentally reported crystal structures. By using data from previous high-throughput DFT studies, corroborating evidence from DFT was available for 17% of the 130 structures for which no replicate syntheses are available. In total, approximately 1/3 of the 130 MOFs have data associated with replicate synthesis experiments and/or directly corroborating DFT calculations.

Sholl, David S. [Oak Ridge National Laboratory (OR↗
NASA NTRS2005

Materials Chemistry Issues in the Development of a Single-Crystal Solar/Thermal Refractive Secondary Concentrator

A translucent crystal concentrates and transmits energy to a heat exchanger, which in turn heats a propellant gas, working gas of a dynamic power system, or a thermopile. Materials are the limiting issue in such a system. Central is the durability of the crystal, which must maintain the required chemical, physical/optical, and mechanical properties as it is heated and cooled. This report summarizes available data to date on the materials issues with this system. We focus on the current leading candidate materials, which are sapphire (Al2O3) for higher temperatures and silica (SiO2) for lower temperatures. We use data from thermochemical calculations; laboratory coupon tests with silica and sapphire; and system tests with sapphire. The required chemical properties include low-vapor pressure and interfacial stability with supporting structural materials. Optical properties such as transmittance and index of refraction must be maintained. Thermomechanical stability is a major challenge for a large, single-crystal ceramic and has been discussed in another report. In addition to the crystal, other materials in the proposed system include refractory metals (Nb, Ta, Mo, W, and Re), carbon (C), and high-temperature ceramic insulation. The major issue here is low levels of oxygen, which lead to volatile refractory metal oxides and rapid consumption of the refractory metal. Interfacial reactions between the ceramic crystal and refractory metal are also discussed. Finally, high-temperature ceramic insulating materials are also likely to be used in this system. Outgassing is a major issue for these materials. The products of outgassing are typically reactive with the refractory metals and must be minimized.

Jacobson, Nathan S.↗
DOE OSTI2024

Mechanistically Guided Materials Chemistry: Synthesis of Ternary Nitrides, CaZrN 2 and CaHfN 2

Recent computational studies have predicted many new ternary nitrides, revealing synthetic opportunities in this underexplored phase space. However, synthesizing new ternary nitrides is difficult, in part because intermediate and product phases often have high cohesive energies that inhibit diffusion. Here, we report the synthesis of two new phases, calcium zirconium nitride (CaZrN 2 ) and calcium hafnium nitride (CaHfN 2 ), by solid state metathesis reactions between Ca 3 N2 and MCl 4 (M = Zr, Hf). Although the reaction nominally proceeds to the target phases in a 1:1 ratio of the precursors via Ca 3 N 2 + MCl4 → CaMN 2 + 2 CaCl 2 , reactions prepared this way result in Ca-poor materials (Ca x M 2–x N2, x < 1). A small excess of Ca 3 N 2 (ca. 20 mol %) is needed to yield stoichiometric CaMN 2 , as confirmed by high-resolution synchrotron powder X-ray diffraction. In situ synchrotron X-ray diffraction studies reveal that nominally stoichiometric reactions produce Zr 3+ intermediates early in the reaction pathway, and the excess Ca 3 N 2 is needed to reoxidize Zr 3+ intermediates back to the Zr 4+ oxidation state of CaZrN 2 . Analysis of computationally derived chemical potential diagrams rationalizes this synthetic approach and its contrast from the synthesis of MgZrN 2 . These findings additionally highlight the utility of in situ diffraction studies and computational thermochemistry to provide mechanistic guidance for synthesis.

36 MATERIALS SCIENCE↗
NASA NTRS2016

Application of Chemistry in Materials Research at NASA GRC

Overview of NASA GRC Materials Development. New materials enabled by new chemistries offering unique properties and chemical processing techniques. Durability of materials in harsh environments requires understanding and modeling of chemical interaction of materials with the environment.

Chemistry↗
DOE OSTI2024

Self-Driving Laboratories for Chemistry and Materials Science

Self-driving laboratories (SDLs) promise an accelerated application of the scientific method. Through the automation of experimental workflows, along with autonomous experimental planning, SDLs hold the potential to greatly accelerate research in chemistry and materials discovery. This review provides an in-depth analysis of the state-of-the-art in SDL technology, its applications across various scientific disciplines, and the potential implications for research and industry. This review additionally provides an overview of the enabling technologies for SDLs, including their hardware, software, and integration with laboratory infrastructure. Most importantly, this review explores the diverse range of scientific domains where SDLs have made significant contributions, from drug discovery and materials science to genomics and chemistry. We provide a comprehensive review of existing real-world examples of SDLs, their different levels of automation, and the challenges and limitations associated with each domain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Foundation models for atomistic simulation of chemistry and materials

Conventional computational methods for modeling chemical and materials systems are limited by system size and timescale, forcing a trade-off between quantum-mechanical accuracy and the sampling needed for realistic observables. Large language and vision foundation models — pre-trained on massive datasets using transformer architectures — have revolutionized many fields. It is thus interesting to ask whether a foundation model — subject to suitable data, parameter scaling and training — could enable learned simulations of chemistry and materials. Here, in this study, we review the field of machine-learned interatomic potentials (MLIPs) and posit that scaling up large and diverse chemical and materials datasets and highly expressive architectures using advanced training strategies should result in models that are: more efficient, transferable, robust to out-of-distribution scenarios, and easier to fine-tune to a variety of downstream physical observables than models trained from scratch on small datasets corresponding to specific, targeted atomistic simulation tasks. We provide specific criteria for creating such large-scale MLIP foundation models, coordinated strategies for their development, evaluation and deployment, and highlight potential emergent capabilities that could transform predictive simulations in chemistry and materials science and accelerate discovery across multiple technological domains.

Yuan, Eric C.-Y. [University of California, Berkel↗
DOE OSTI2024

Trust Not Verify? The Critical Need for Data Curation Standards in Materials Informatics

The importance of data curation has been recognized in multiple areas of research; however, the discussion of this important issue is only beginning to emerge in materials science. In this Perspective, we highlight the benefits of using the standardized data curation protocols in materials science and discuss current gaps in accurate and reproducible data reporting using case studies drawn from high-impact materials science papers and well-known databases such as the Crystallography Open Database (COD) and the Cambridge Structural Database (CSD). We argue that both experimental and computational materials scientists need to embrace a culture of rigorous data curation as part of modern research data management. We propose a sample data curation pipeline for materials chemistry and illustrate its use by creating two new materials chemistry databases. Here, we hope that this perspective will serve to catalyze further discussion and promote the continuous development of rigorous data curation practices within the materials science research community. We posit that adherence to best practices of data curation will promote and enhance the reliability, reproducibility, and integrity of materials research and enable the development of reliable AI and machine learning models that critically depend on the use of quality data.

Chemical structure↗
DOE OSTI2024

Developing and Running Quantum Algorithms for Chemistry and Materials (QAChMat) (Final Technical Report)

The goal of the project is to design, develop, and execute new computational methods on practical quantum computing platforms to simulate hard problems in chemical and materials sciences. We exploited the two leading quantum computing platforms of trapped atomic ion and superconducting qubits, established in laboratories at Duke University and the University of Maryland, to discover new simulation and computational methods for the study of quantum chemistry and materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Review of low-cost self-driving laboratories in chemistry and materials science: the “frugal twin” concept

This review proposes the concept of a “frugal twin,” similar to a digital twin, but for physical experiments. Frugal twins range from simple toy examples to low-cost surrogates of high-cost research systems. For example, a color-mixing self-driving laboratory (SDL) can serve as a low-cost version of a costly multi-step chemical discovery SDL. Frugal twins already provide hands-on experience for SDLs with low costs and low risks. They can also offer as test beds for software prototyping (e.g., optimization, data infrastructure), and a low barrier to entry for democratizing SDLs. However, there is room for improvement. The true value of frugal twins can be realized in three core areas. Firstly, hardware and software modularity; secondly, purpose-built design (human-inspired vs. hardware-centric vs. human-in-the-loop); and thirdly state-of-the-art (SOTA) software (e.g., multi-fidelity optimization). We also describe the ethical benefits and risks that come with the democratization of science through frugal twins. For future work, we suggest ideas for new frugal twins, SDL educational course outcomes, and a classification scheme for autonomy levels.

36 MATERIALS SCIENCE↗