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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Ultra-rapid, physics-based development pathway for reactor-relevant RF antenna materials

This paper presents a rapid, atomistically-informed, experimental development pathway for fusion reactor-relevant radio frequency (RF) antenna materials in the Cu-Cr-(Nb,Al,Zr) composition system, with the goal of improving upon GRCop-84. RF antennas in a tokamak fusion reactor will face a unique set of challenges as both structural and functional materials. The desired material must simultaneously achieve and maintain high electrical conductivity, high strength, high thermal conductivity, resist high temperatures, possess low nuclear activation, and incur low damage due to neutron bombardment. The GRCop-84 alloy serves as a starting point for iterative improvement, with the desire to reduce or eliminate Nb from the material to minimize nuclear activation. The rapid development pathway makes use of a multi-target combinatorial thick film sputtering process to produce full ternary phase diagrams on a Si wafer substrate. Transient grating spectroscopy (TGS), a laser-ultrasonic method, will determine spatially-varying thermo-elastic properties, while four terminal electrical conductivity measurements will map out the best per- forming regions of the sample for in-depth study at larger length scales. High energy proton and self-ion irradiation emulates the effects of neutron damage on the thermal/electric properties. With rapid turnaround time (∼days) in terms of mapping radiation damage-induced material property changes in the full ternary system, these techniques allow rapid iteration towards an optimal material, testing hundreds of nearby compositions in the time it took to test one. Focused testing of larger, single composition samples (produced in an arc furnace or by laser sintering) provides data on structural and high power RF properties, and validates our thick-film based workflow.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Defect Equilibria from First Principles: From Widegap Oxides to Topological Semimetals

Materials functionality and performance is rarely determined by the ideal crystal alone but is usually affected by formation of imperfections and the solution of impurities. In some applications, such as solar thermochemical hydrogen generation, defect formation is the fundamentally enabling mechanism of the desired functionality. In other cases, such as Cd3As2 topological semimetals, unintentional self-doping presents an obstacle to the access to the unique electronic properties. In either case, a quantitative understanding of the relevant defect mechanism is essential for developing design strategies. This presentation will touch upon numerous aspects in the computational simulation of defect equilibria, including non-equilibrium design strategies, the coupling of solid state and gas-phase reactions, dopant-defect and defect-defect interactions, both attractive and repulsive, the accuracy of total energy functionals and electronic structure methods, and the role of the shape of the density of states for the charge balance condition and Fermi level position, as well as machine-learning prediction of defect energies (1). Specific materials systems include Ga2O3 (2), Cd3As2 (3), and (Sr,Ce)MnO3 (4). (1) M.D. Witman, A. Goyal, T. Ogitsu, A.H. McDaniel, S. Lany, Nat. Comput. Sci. 3, 675 (2023). (2) A. Goyal, A. Zakutayev, V. Stevanovic, S. Lany, J. Appl. Phys. 129, 245704 (2021). (3) C. Brooks, M. van Schilfgaarde, D. Pashov, J.N. Nelson, K. Alberi, D.S. Dessau, S. Lany, Phys. Rev. B 107, 224110 (2023). (4) A. Goyal, M.D. Sanders, R.P. O'Hayre, S. Lany, PRX Energy 3, 013008 (2024).

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS,M↗
DOE OSTI2024

Machine learning-enhanced design of lead-free halide perovskite materials using density functional theory

The investigation of emerging non-toxic perovskite materials has been undertaken to advance the fabrication of environmentally sustainable lead-free perovskite solar cells. This study introduces a machine learning methodology aimed at predicting innovative halide perovskite materials that hold promise for use in photovoltaic applications. The seven newly predicted materials are as follows: CsMnCl 4 , Rb 3 Mn 2 Cl 9 , Rb 4 MnCl 6 , Rb 3 MnCl 5 , RbMn 2 Cl 7 , RbMn 4 Cl 9 , and CsIn 2 Cl 7 . The predicted compounds are first screened using a machine learning approach, and their validity is subsequently verified through density functional theory calculations. CsMnCl 4 is notable among them, displaying a bandgap of 1.37 eV, falling within the Shockley-Queisser limit, making it suitable for photovoltaic applications. Here, through the integration of machine learning and density functional theory, this study presents a methodology that is more effective and thorough for the discovery and design of materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Direct Ab Initio Simulation of the Synthesis of BaZrO 3 and the Microstructure Impacts on Proton Transport

Controlling and predicting the processing-structure-performance relationship in functional materials is a grand challenge in materials science, with important implications for a wide range of emerging applications; a high fidelity understanding of the performance impact of microstructures formed under synthesis conditions is required to develop advanced materials, such as solid-state fuel cells and electrolyzers. Using the ceramic BaZrO 3 as a case study, we directly simulate the synthesis and investigate how proton transport is dictated by microstructures. We develop a framework that couples density functional theory (DFT), machine-learning interatomic potential (MLIP) driven molecular dynamics, and grand canonical Monte Carlo to perform large-scale, microstructure-resolved, atomistic simulations of proton transport in experimentally representative polycrystalline structures. Our fully ab initio approach, using a MLIP as a proxy for DFT, allows us to quantify the competition between two distinct diffusion mechanisms: one associated with grain-boundary regions and another within grains. When the impacts of grain boundaries are taken into account, proton transport exhibits substantial deviation from the bulk oxide limit. This addresses long-standing discrepancies between theory and experiments. Our integrated approach provides atomistic insight into microstructure-dependent proton pathways in BaZrO 3 and establishes a general protocol for predicting processing-structure-performance relationships.

organic↗
DOE OSTI2018

Plastic Deformation of Materials Under Loading Along Piecewise Smooth Trajectories with Areas of Unloading by the Elastic Law

Within the framework of a version of plasticity theory based on the concept of slip, we propose a method for the determination of plastic strains in materials with regard for the strain anisotropy in the case of loading applied along piecewise smooth trajectories (with areas of unloading according to the elastic law). The material function of plasticity Π used in this theory is determined, for a given function of hardening F , either from the tension–compression tests or from the tests with alternating torsion of thin-walled pipes.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Borophene as a prototype for synthetic 2D materials development

The synthesis of 2D materials with no analogous bulk layered allotropes promises a substantial breadth of physical and chemical properties through the diverse structural options afforded by substrate-dependent epitaxy. However, despite the joint theoretical and experimental efforts to guide materials discovery, successful demonstrations of synthetic 2D materials have been rare. The recent synthesis of 2D boron polymorphs (that is, borophene) provides a notable example of such success. In this Perspective, we discuss recent progress and future opportunities for borophene research. Borophene combines unique mechanical properties with anisotropic metallicity, which complements the canon of conventional 2D materials. The multi-centre characteristics of boron-boron bonding lead to the formation of configurationally varied, vacancy-mediated structural motifs, providing unprecedented diversity in a mono-elemental 2D system with potential for electronic applications, chemical functionalization, materials synthesis and complex heterostructures. As a result, with its foundations in computationally guided synthesis, borophene can serve as a prototype for ongoing efforts to discover and exploit synthetic 2D materials.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Liquid carbon dioxide absorbents, methods of using the same, and related systems

A carbon dioxide absorbent composition is described, including (i) a liquid, nonaqueous silicon-based material, functionalized with one or more groups that either reversibly react with CO.sub.2 or have a high-affinity for CO.sub.2; and (ii) a hydroxy-containing solvent that is capable of dissolving both the silicon-based material and a reaction product of the silicon-based material and CO.sub.2. The absorbent may be utilized in methods to reduce carbon dioxide in an exhaust gas, and finds particular utility in power plants.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Liquid carbon dioxide absorbents, methods of using the same, and related system

A carbon dioxide absorbent composition is described, including (i) a liquid, nonaqueous silicon-based material, functionalized with one or more groups that either reversibly react with CO 2 or have a high-affinity for CO 2 , and (ii) a hydroxy-containing solvent that is capable of dissolving both the silicon-based material and a reaction product of the silicon-based material and CO 2 . The absorbent may be utilized in methods to reduce carbon dioxide in an exhaust gas, and finds particular utility in power plants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A new perspective on lone pair dynamics in halide perovskites

Halide perovskites form the foundation of an emerging class of materials for broad application in renewable and sustainable applications, including photocatalysis and solar energy harvesting. These materials exhibit beneficial photophysical properties, including bandgaps suitable for solar energy harvesting and efficient charge screening that underlies efficient charge carrier separation and resistance to defects. For organic–inorganic hybrid perovskites, these benefits are thought to arise, in part, from dipolar molecular cations that can reorient in response to charged particles and defects. In this work, we provide a similar perspective for inorganic metal halide perovskites, which do not contain molecular species with permanent dipoles. We discuss how lone pair electrons lead to dipolar ions that exhibit dynamics in analogy with traditional molecular plastic crystals and hybrid perovskites. We argue that further understanding these electronic plastic crystal motions with first principles simulations and synchrotron scattering can help create a basic understanding of photophysical properties of metal halide perovskites and inform the design of advanced functional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Defect Genome of Cubic Perovskites for Fuel Cell Applications

Heterogeneities such as point defects, inherent to material systems, can profoundly influence material functionalities critical for numerous energy applications. This influence in principle can be identified and quantified through development of large defect data sets which we call the defect genome, employing high-throughput ab initio calculations. However, high-throughput screening of material models with point defects dramatically increases the computational complexity and chemical search space, creating major impediments toward developing a defect genome. In this paper, we overcome these impediments by employing computationally tractable ab initio models driven by highly scalable workflows, to study formation and interaction of various point defects (e.g., O vacancies, H interstitials, and Y substitutional dopant), in over 80 cubic perovskites, for potential proton-conducting ceramic fuel cell (PCFC) applications. The resulting defect data sets identify several promising perovskite compounds that can exhibit high proton conductivity. Furthermore, the data sets also enable us to identify and explain, insightful and novel correlations among defect energies, material identities, and defect-induced local structural distortions. Finally, such defect data sets and resultant correlations are necessary to build statistical machine learning models, which are required to accelerate discovery of new materials.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2015

Crystal and Electronic Structures of Complex Bismuth Iodides A 3 Bi 2 I 9 ( A = K, Rb, Cs) Related to Perovskite: Aiding the Rational Design of Photovoltaics

Ternary bismuth halides form an interesting functional materials class in the context of the closely related Pb halide perovskite photovoltaics, especially given the significantly reduced toxicity of Bi when compared with Pb. The compounds A 3 Bi 2 I 9 (A = K, Rb, Cs) examined here crystallize in two different structure types: the layered defect-perovskite K 3 Bi 2 I 9 type, and the Cs 3 Cr 2 Cl 9 type. The latter structure type features isolated Bi 2 I 9 3– anions. Here, the crystal structures of the ternary iodides are redetermined and a corrected structural model for Rb 3 Bi 2 I 9 , as established by single crystal X-ray diffraction and solid state 87Rb NMR spectroscopy and supported by density functional theory (DFT) calculations is presented. A variety of facile preparation techniques for single crystals, bulk materials, as well as solution-processed thin films are described. The optical properties and electronic structures are investigated experimentally by optical absorption and ultraviolet photoemission spectroscopy and computationally by DFT calculations. Absolute band positions of the valence and conduction bands of these semiconductors, with excellent agreement of experimental and calculated values, are reported, constituting a useful input for the rational interface design of efficient electronic and optoelectronic devices. The different structural connectivity in the two different structure types, somewhat surprisingly, appears to not impact band positions or band gaps in a significant manner. Computed dielectric properties, including the finding of anomalously large Born effective charge tensors on Bi 3+ , suggest proximal structural instabilities arising from the Bi 3+ 6s 2 lone pair. These anomalous Born effective charges are promising for defect screening and effective charge carrier transport. The structural, electronic, and optical properties of the complex bismuth iodides are to some extent similar to the related lead iodide perovskites. In conclusion, the deeper valence band positions in the complex bismuth iodides point to the need for different choices of hole transport materials for Bi-iodide based solar cell architectures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Understanding the Redox Obstacles in High Sulfur-Loading Li–S Batteries and Design of an Advanced Gel Cathode

Lithium-sulfur batteries with a high energy density are being considered a promising candidate for next-generation energy storage. However, realization of Li-S batteries is plagued by poor sulfur utilization due to the shuttle of intermediate lithiation products between electrodes and its dynamic redistribution. To optimize the sulfur utilization, an understanding of its redox behavior is essential. Here in this paper, we report a gel cathode consisting of a polysulfide-impregnated O- and N-doped porous carbon and an independent, continuous, and highly conducting 3-dimensional graphite film as the charge-transfer network. This design decouples the function of electron conduction and polysulfide absorption, which is beneficial for understanding the sulfur redox behavior and identifying the dominant factors leading to cell failure when the cells have high sulfur content and insufficient electrolyte. In conclusion, this design also opens up new prospects of tuning the properties of Li-S batteries via separately designing the material functions of electron conduction and polysulfide absorption.

25 ENERGY STORAGE↗
DOE OSTI2018

Flexible Electronics: Stretchable Electrodes and Their Future

Flexible electronics, as an emerging and exciting research field, have brought great interest to the issue of how to make flexible electronic materials that offer both durability and high performance at strained states. With the advent of on-body wearable and implantable electronics, as well as increasing demands for human-friendly intelligent soft robots, enormous effort is being expended on highly flexible functional materials, especially stretchable electrodes, by both the academic and industrial communities. Among different deformation modes, stretchability is the most demanding and challenging. This review focuses on the latest advances in stretchable transparent electrodes based on a new design strategy known as kirigami (the art of paper cutting) and investigates the recent progress on novel applications, including skin-like electronics, implantable biodegradable devices, and bioinspired soft robotics. By comparing the optoelectrical and mechanical properties of different electrode materials, some of the most important outcomes with comments on their merits and demerits are raised. Key design considerations in terms of geometries, substrates, and adhesion are also discussed, offering insights into the universal strategies for engineering stretchable electrodes regardless of the material. Finally, it is suggested that highly stretchable and biocompatible electrodes will greatly boost the development of next-generation intelligent life-like electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Electronic structure of strongly correlated systems: recent developments in multiconfiguration pair-density functional theory and multiconfiguration nonclassical-energy functional theory

Strong electron correlation plays an important role in transition-metal and heavy-metal chemistry, magnetic molecules, bond breaking, biradicals, excited states, and many functional materials, but it provides a significant challenge for modern electronic structure theory. The treatment of strongly correlated systems usually requires a multireference method to adequately describe spin densities and near-degeneracy correlation. However, quantitative computation of dynamic correlation with multireference wave functions is often difficult or impractical. Multiconfiguration pair-density functional theory (MC-PDFT) provides a way to blend multiconfiguration wave function theory and density functional theory to quantitatively treat both near-degeneracy correlation and dynamic correlation in strongly correlated systems; it is more affordable than multireference perturbation theory, multireference configuration interaction, or multireference coupled cluster theory and more accurate for many properties than Kohn–Sham density functional theory. This perspective article provides a brief introduction to strongly correlated systems and previously reviewed progress on MC-PDFT followed by a discussion of several recent developments and applications of MC-PDFT and related methods, including localized-active-space MC-PDFT, generalized active-space MC-PDFT, density-matrix-renormalization-group MC-PDFT, hybrid MC-PDFT, multistate MC-PDFT, spin–orbit coupling, analytic gradients, and dipole moments. We also review the more recently introduced multiconfiguration nonclassical-energy functional theory (MC-NEFT), which is like MC-PDFT but allows for other ingredients in the nonclassical-energy functional. We discuss two new kinds of MC-NEFT methods, namely multiconfiguration density coherence functional theory and machine-learned functionals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Autonomous Output‐Oriented Aerosol Jet Printing Enabled by Hybrid Machine Learning

Additive manufacturing (AM) is rapidly revolutionizing modern manufacturing with recent progress in advanced printing methods and improved properties of printed materials. However, traditional AM methods are limited by their input‐oriented nature, which demands tedious trial‐and‐error tuning of printing parameters to achieve desired output properties. Here, in this work, an output‐oriented artificial intelligence‐integrated AM (AIAM) method is reported that enables an user to specify desired output properties while the printer autonomously discovers the optimal input printing parameters by integrating hybrid machine learning models and in situ measurements. Based on a predictive mapping between the input printing parameters and the output properties of interests established with <20 experiments designed by active learning, inverse design tasks are performed to intelligently generate the printing parameter settings that lead to desired outcomes using reinforcement learning. This method is demonstrated by autonomous aerosol jet printing (AJP) of conductive polymer films and achieving user‐defined electrical resistances with an ultralow error of 3.7%. The AIAM method, with its output‐oriented nature, holds the potential to significantly improve the autonomy, predictability, efficiency, and accessibility of the AM processes, which will unlock new possibilities in the autonomous and intelligent printing of a broad range of functional materials and devices.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Discovery of Energy Storage Molecular Materials Using Quantum Chemistry-Guided Multiobjective Bayesian Optimization

Redox flow batteries (RFBs) are a promising technology for stationary energy storage applications due to their flexible design, scalability, and low cost. In RFBs, energy is carried in flowable redoxactive materials (redoxmers) which are stored externally and pumped to the cell during operation. Further improvements in the energy density of RFBs necessitates redoxmer designs with wider redox potential windows and higher solubility. Additionally, designing redoxmers with a fluorescence-enabled self-reporting functionality allows monitoring of the state of health of RFBs. To accelerate the discovery of redoxmers with desired properties, state-of-the- art machine learning ( ML) methods, such as multiobjective Bayesian optimization (MBO), are useful. Here, we first employed density functional theory calculations to generate a database of reduction potentials, solvation free energies, and absorption wavelengths for 1400 redoxmer molecules based on a 2,1,3-benzothiadiazole (BzNSN) core structure. From the computed properties, we identified 22 Pareto-optimal molecules that represent best trade-off among all of the desired properties. We further utilized these data to develop and benchmark an MBO approach to identify candidates quickly and efficiently with multiple targeted properties. With MBO, optimal candidates from the 1400-molecule data set can be identified at least 15 times more efficiently compared to the brute force or random selection approach. Importantly, we utilized this approach for discovering promising redoxmers from an unseen database of 1 million BzNSN-based molecules, where we discovered 16 new Pareto-optimal molecules with significant improvements in properties over the initial 1400 molecules. Furthermore, we anticipate that this active learning technique is general and can be utilized for the discovery of any class of functional materials that satisfies multiple desired property criteria.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Influence of Hydrophobicity on Polyelectrolyte Complexation

Polyelectrolyte complexes are a fascinating class of soft materials that can span the full spectrum of mechanical properties from low-viscosity fluids to glassy solids. This spectrum can be accessed by modulating the extent of electrostatic association in these complexes. However, to realize the full potential of polyelectrolyte complexes as functional materials, their molecular level details need to be clearly correlated with their mechanical response. The present work demonstrates that by making simple amendments to the chain architecture, it is possible to affect the salt responsiveness of polyelectrolyte complexes in a systematic manner. This is achieved by quaternizing poly(4-vinylpyridine) (QVP) with methyl, ethyl, and propyl substituents—thereby increasing the hydrophobicity with increasing side chain length—and complexing them with a common anionic polyelectrolyte, poly(styrenesulfonate). The mechanical behavior of these complexes is compared to the more hydrophilic system of poly(styrenesulfonate) and poly(diallyldimethylammonium) by quantifying the swelling behavior in response to salt stimuli. More hydrophobic complexes are found to be more resistant to doping by salt, yet the mechanical properties of the complex remain contingent on the overall swelling ratio of the complex itself, following near universal swelling–modulus master curves that are quantified in this work. Furthermore, the rheological behaviors of QVP complex coacervates are found to be approximately the same, only requiring higher salt concentrations to overcome strong hydrophobic interactions, demonstrating that hydrophobicity can be used as an important parameter for tuning the stability of polyelectrolyte complexes in general, while still preserving the ability to be processed “saloplastically”.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Strong polaronic effect in a superatomic two-dimensional semiconductor

Crystalline solids assembled from superatomic building blocks are attractive functional materials due to their hierarchical structure, multifunctionality, and tunability. An interesting example is Re 6 Se 8 Cl 2 , in which the Re 6 Se 8 building blocks are covalently linked into two-dimensional (2D) sheets that are stacked into a layered van der Waals solid. It is an indirect gap semiconductor that, when heavily doped, becomes a superconductor at low temperatures. Given the finite electronic bandwidths (300–400 meV), carrier properties in this material are expected to be strongly influenced by coupling to phonons. Here, we apply angle-resolved photoemission spectroscopy to probe the valence band edge (VBE) of Re 6 Se 8 Cl 2 . We find that dispersion of the VBE is a strong function of temperature. The bandwidth is W = 120 ± 30 meV at 70 K and decreases by one order of magnitude to W ~ 10 ± 20 meV as temperature is increased to 300 K. This observation reveals the dominant polaronic effects in Re 6 Se 8 Cl 2 , consistent with the Holstein polaron model commonly used to describe molecular solids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗