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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.
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.
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.
Benchmarking graph neural networks for materials chemistry
Graph neural networks (GNNs) have received intense interest as a rapidly expanding class of machine learning models remarkably well-suited for materials applications. To date, a number of successful GNNs have been proposed and demonstrated for systems ranging from crystal stability to electronic property prediction and to surface chemistry and heterogeneous catalysis. However, a consistent benchmark of these models remains lacking, hindering the development and consistent evaluation of new models in the materials field. Here, we present a workflow and testing platform, MatDeepLearn, for quickly and reproducibly assessing and comparing GNNs and other machine learning models. We use this platform to optimize and evaluate a selection of top performing GNNs on several representative datasets in computational materials chemistry. From our investigations we note the importance of hyperparameter selection and find roughly similar performances for the top models once optimized. We identify several strengths in GNNs over conventional models in cases with compositionally diverse datasets and in its overall flexibility with respect to inputs, due to learned rather than defined representations. Meanwhile several weaknesses of GNNs are also observed including high data requirements, and suggestions for further improvement for applications in materials chemistry are discussed.
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.
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.
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.
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.
Enabling Low-Cost Molten Sodium Batteries Through Engineered Catholyte-Separator Materials Chemistry.
Abstract not provided.
Materials Chemistry in Battery Energy Storage: A Key to Unlocking Our ?Potential? Energy Future .
Abstract not provided.
Interdisciplinary materials research including fundamental physics and chemistry of materials, environmental effects and related problems Semiannual progress report, 1 Sep. 1965 - 28 Feb. 1966
Interdisciplinary materials research including fundamental physics and chemistry of materials, environmental effects, and related problems
Interdisciplinary materials research including fundamental physics and chemistry of materials, environmental effects and related problems Semiannual progress report, Mar. 1 - Aug. 31, 1966
Interdisciplinary materials research including fundamental physics and chemistry of materials, environmental effects and related problems
<interdisciplinary materials research including fundamental physics and chemistry of materials, environmental effects and related problems< semi-annual progress report, mar. 1 - aug. 31, 1964
Mechanical properties of polymers, phase particles in dispersion strengthened alloys, molecular structure relation in polymer flow and dispersions, and ceramics research
Interdisciplinary materials research including fundamental physics and chemistry of materials, environmental effects and related problems Semiannual progress report, Mar. 1 - Aug. 31, 1965
Metallurgic, thermodynamic, ultrasonic, polymer, and spectroscopic studies in materials science
Interdisciplinary materials research including fundamental physics and chemistry of materials, environmental effects and related problems Semiannual progress report, Sep. 1, 1967 - Feb. 29, 1968
Interdisciplinary materials research in inorganic nonmetallic materials, metallic solids, polymers, and solid state physics
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.
Coupled Cluster Downfolding Theory: towards universal many-body algorithms for dimensionality reduction of composite quantum systems in chemistry and materials science
Abstract The recently introduced coupled cluster (CC) downfolding techniques for reducing the dimensionality of quantum many-body problems recast the CC formalism in the form of the renormalization procedure allowing, for the construction of effective (or downfolded) Hamiltonians in small-dimensionality sub-space, usually identified with the so-called active space, of the entire Hilbert space. The resulting downfolded Hamiltonians integrate out the external (out-of-active-space) Fermionic degrees of freedom from the internal (in-the-active-space) parameters of the wave function, which can be determined as components of the eigenvectors of the downfolded Hamiltonians in the active space. This paper will discuss the extension of non-Hermitian (associated with standard CC formulations) and Hermitian (associated with the unitary CC approaches) downfolding formulations to composite quantum systems commonly encountered in materials science and chemistry. The non-Hermitian formulation can provide a platform for developing local CC approaches, while the Hermitian one can serve as an ideal foundation for developing various quantum computing applications based on the limited quantum resources. We also discuss the algorithm for extracting the semi-analytical form of the inter-electron interactions in the active spaces.