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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Applications of Nickelate perovskites for neuromorphic computing from electronic structure and Machine Learning

While the limit of Moore's law is presently being reached with current microelectronic technologies, we need to develop new paradigms that overcome this limitation. In that respect, neuromorphic computing is a concept that emulates the neural behavior and response of the human brain, and it has been recognized as a promising alternative approach. In this research project, we will perform multi-fidelity scale bridging to explore the potential use of materials with metal to insulator transition for neuromorphic applications. In particular, rare earth nickelates are promising for such purposes, as the transition in these materials is quite sensitive to a broad set of different external stimuli. Our multi-fidelity approach will bridge the high-fidelity electronic structure calculations with classical potentials. We will bridge dynamical mean field theory with a classical atomistic representation via a deep learning force field. The neural network is trained with energies, charges, and forces obtained by accurate electronic structure theories based on Dynamical Mean Field Theory. The configurational space is generated from known crystal phases, ab initio molecular dynamics with exchange-correlation functionals corrected with the Hubbard model, disordered phases with different concentrations of oxygen vacancies, and nonsymmetrical positions and induced strain by grain interfaces or contact with a substrate. Strategies to train the model with a reduced number of training examples are obtained from active learning methods, and new structures for improving the learning process are generated by using machine learning autoencoders. This classical potential will be validated through a diversity of electronic structure methods and represents an important step to combine the flexibility and accuracy of first-principles with the speed of classical potentials. The generated multi-fidelity surrogate model will be used to understand the role of strain, oxygen vacancies, proton doping, the variation of the crystal phase, substrate effects, vibrational effects as the octahedral rotation, grain boundaries and defect effects on the response of a Metal to Insulator Transition (MIT) in correlated materials. Long time and large-scale simulations will help understand the role of different stimuli to control the hysteresis of the MIT, as it has been experimentally suggested. Selected configurations will be analyzed with higher-level theories to provide an accurate electronic description and to study how the orbitals and charges are rearranged under different conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Bulk and Nanocrystalline Cesium Lead-Halide Perovskites as Seen by Halide Magnetic Resonance

Lead-halide perovskites increasingly mesmerize researchers because they exhibit a high degree of structural defects and dynamics yet nonetheless offer an outstanding (opto)electronic performance on par with the best examples of structurally stable and defect-free semiconductors. This highly unusual feature necessitates the adoption of an experimental and theoretical mindset and the reexamination of techniques that may be uniquely suited to understand these materials. Surprisingly, the suite of methods for the structural characterization of these materials does not commonly include nuclear magnetic resonance (NMR) spectroscopy. The present study showcases both the utility and versatility of halide NMR and NQR (nuclear quadrupole resonance) for probing the structure and structural dynamics of CsPbX 3 (X = Cl, Br, I), in both bulk and nanocrystalline forms. The strong quadrupole couplings, which originate from the interaction between the large quadrupole moments of, e.g., the 35 Cl, 79 Br, and 127 I nuclei, and the local electric-field gradients, are highly sensitive to subtle structural variations, both static and dynamic. The quadrupole interaction can resolve structural changes with accuracies commensurate with synchrotron X-ray diffraction and scattering. It is shown that space-averaged site-disorder is greatly enhanced in the nanocrystals compared to the bulk, while the dynamics of nuclear spin relaxation indicates enhanced structural dynamics in the nanocrystals. The findings from NMR and NQR were corroborated by ab initio molecular dynamics, which point to the role of the surface in causing the radial strain distribution and disorder. These findings showcase a great synergy between solid-state NMR or NQR and molecular dynamics simulations in shedding light on the structure of soft lead-halide semiconductors.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Elucidating the atomistic origin of anharmonicity in tetragonal CH3NH3PbI3 with Raman scattering

Halide perovskite (HP) semiconductors exhibit unique strong coupling between the electronic and structural dynamics. In this work, we use Raman polarization-orientation (PO) measurements and ab initio molecular dynamics (AIMD) to investigate the origin and temperature evolution of the strong structural anharmonicity throughout the tetragonal phase of CH 3 NH 3 PbI 3 . Raman PO measurements reveal a soft modelike spectral feature. This mode shows an unusual continuous increase in damping with temperature which is indicative of an anharmonic potential surface. The analysis of AIMD trajectories identifies two major sources of anharmonicity: the orientational unlocking of the [CH 3 NH 3 ] + ions and large-amplitude octahedral tilting that continuously increases with temperature. Our work suggests that the standard phonon picture cannot describe the structural dynamics of tetragonal CH 3 NH 3 PbI 3 .

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Ab-Initio Study of Stacking Fault Segregation Behavior in Ni-based Superalloys at High Temperatures

Ni-based superalloys demonstrate extraordinary creep properties compared to traditional metallic systems due to the formation of L12 (γ’) precipitates. Despite experimental evidence of alloying element segregation to the stacking faults, prior ab-initio efforts indicated repulsion of Nb from superlattice intrinsic stacking faults (SISFs) . Due to the importance of this element in key strengthening mechanisms, we developed a new technique to account for multi-component segregation behavior at temperature combining ab-initio molecular dynamics (AIMD) and Monte-Carlo (MC) simulations. Using this technique, we replicated experimentally observed segregation behavior of Nb, Co, and Ti to the SISF in L12 (Figure 1). Furthermore, we investigated the co-segregation behaviors of individual pairs of alloying elements to determine the interaction effects which lead to this segregation behavior in the full alloy system. By simulating the reduced-chemistry models using our approach, we reconciled previous ab-initio calculations demonstrating repulsion of Nb from the SISF and the experimentally observed segregation behavior.

Molecular Dynamics↗
DOE OSTI2025

An atomic cluster expansion (ACE) potential for water under extreme conditions

We present a machine learning interatomic potential for water designed to capture its complex multiphase behavior, including both molecular and superionic ice phases. The potential is based on the atomic cluster expansion (ACE) formulation and has been parameterized to enable high-fidelity molecular dynamics simulations of water under extreme conditions, for pressures up to 100 GPa and for temperatures between 500 and 6000 K. A diverse range of configurations was generated through ab initio molecular dynamics (AI-MD) simulations, covering insulating and superionic ice phases, liquid water, and dissociated plasma phase. We demonstrate that the H 2 O ACE potential accurately reproduces experimental and DFT predicted isotherms and Hugoniots. Crucially, the potential is able to capture the intricate phase behavior of water, including the transition from molecular fluid to the appropriate solid ice phases, and the superionic ice phases. This work provides a robust interatomic potential that can be used for large-scale, accurate simulations of water under extreme thermodynamic conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Ab initio lattice thermal conductivity of Mg Si O 3 across the perovskite-postperovskite phase transition

Lattice thermal conductivity (κ lat ) of MgSiO 3 postperovskite (MgPPv) under the Earth's lower mantle high pressure-temperature conditions is studied using the phonon quasiparticle approach by combing ab initio molecular dynamics and lattice dynamics simulations. Phonon lifetimes are extracted from the phonon quasiparticle calculations, and the phonon group velocities are computed from the anharmonic phonon dispersions, which, in principle, capture full anharmonicity. Here, it is found that throughout the lowermost mantle, including the D” region, κ lat of MgPPv is ~25% larger than that of MgSiO 3 perovskite (MgPv), mainly due to MgPPv's higher phonon velocities. Such a difference in phonon velocities between the two phases originates in the MgPPv's relatively smaller primitive cell. Systematic results of temperature and pressure dependences of both MgPPv's and MgPv's κ lat are demonstrated.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Correlated Displacement of Dynamic Elastic Dipoles Produces Nonclassical Electrostriction in Zr-Doped Ceria

By combining experimental data with density functional theory-based ab initio molecular dynamics modeling, this work provides evidence that nonclassical electrostriction in isovalent Zr-doped ceria is due to the correlated anharmonic motion of dynamic elastic dipoles associated with multiple [ZrO 8 ]-local bonding units with a high Zr concentration (Zr 0.1 Ce 0.9 O 2 ). Introduction of 0.5 mol % trivalent or divalent codopants (Sc, Yb, La, or Ca) reduces the longitudinal electrostriction strain coefficient by more than a factor of 10, produces a 3-fold decrease in the relative dielectric permittivity, and increases the elastic modulus. Since these changes depend neither on the radius nor on the valency of the codopant, we conclude that the responsible species are charge-compensating oxygen vacancies (VO). For trivalent dopants (Do 0.005 Zr 0.1 Ce 0.895 O 1.9975 ), oxygen vacancies are present at a concentration ratio 1:40 with respect to Zr, giving, for random distribution, a characteristic interaction distance of ≤2.3 unit cells (1.2 nm). Oxygen vacancies participate in [ZrO 7 -V O ] local bonding units, disrupting the correlated dynamic displacements of the connected [ZrO 8 ]-local bonding units. Finally, such correlated motion of dynamic elastic dipoles may also explain the exponential increase in the longitudinal electrostriction strain coefficient with an increase in Zr concentration to <0.2 mole fraction and must be taken into account for further development of nonclassical electrostrictors based on Zr-doped ceria.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Ab Initio Dynamics of Graphene and Graphyne Electrodes in Vacuum and in the Presence of Electrolytes

Graphene and graphyne electrodes are both relevant for electrochemical energy storage applications due to their unique physical, chemical, and electronic properties. Graphyne has been considered even more attractive than graphene due to its larger specific surface area, greater electronic mobility, and intrinsic band gap. The analyses presented in this work reveal relevant features of graphyne in an interaction with an electrolyte that can be useful for practical applications. Although there is already a considerable volume of work on graphyne, the analysis of its properties taking into account the dynamics of its network and the interaction with the condensed medium has not yet been presented. Here, ab initio molecular dynamics simulations were performed to study the energetic, structural, spectroscopic, and electronic properties of graphene and graphyne electrodes in vacuum and in the presence of an electrolyte (EMIM-BF 4 ). A detailed analysis of the electrode–electrolyte interaction is reported for both systems. Structural features are presented in terms of both radial and spatial distribution functions and angular orientation distributions. Power spectral analyses and molecular orbital maps provided important insights into the intermolecular interactions in graphene and graphyne systems, describing the main differences as well as revealing similarities between them.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Neural network potential for Zr–Rh system by machine learning

Zr–Rh metallic glass has enabled its many applications in vehicle parts, sports equipment and so on due to its outstanding performance in mechanical property, but the knowledge of the microstructure determining the superb mechanical property remains yet insufficient. Here, we develop a deep neural network potential of Zr–Rh system by using machine learning, which breaks the dilemma between the accuracy and efficiency in molecular dynamics simulations, and greatly improves the simulation scale in both space and time. Here, the results show that the structural features obtained from the neural network method are in good agreement with the cases in ab initio molecular dynamics simulations. Furthermore, we build a large model of 5400 atoms to explore the influences of simulated size and cooling rate on the melt-quenching process of Zr 77 Rh 23 . Our study lays a foundation for exploring the complex structures in amorphous Zr 77 Rh 23 , which is of great significance for the design and practical application.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Thermodynamics of monoclinic and tetragonal hafnium dioxide (HfO 2 ) at ambient pressure

Accurate and precise thermodynamic models of oxide compounds and their phases are important for calculating the phase stability of oxide materials. We develop and use a coupled quantum mechanical and molecular dynamics approach to create thermodynamic models of hafnia (HfO2) polymorphs from 0 K to 3000 K at ambient pressure. The approach is based on the quasi-harmonic approximation below the Debye temperature and on ab-initio molecular dynamics calculations above the Debye temperature to predict constant pressure heat capacities (C-p). A Bayesian model provides interpolated values between these regimes. As a case study, we develop thermodynamic models of monoclinic and tetragonal HfO2 polymorphs. The predicted heat capacities are in excellent agreement with experiment, and the predicted temperature of the monoclinic to tetragonal phase transition (2173 K) is in good agreement with the experimental value (2078K). These results provide a comprehensive and accurate thermodynamic model of the monoclinic and tetragonal phases of hafnia on a broad range of temperatures and can serve as input to CALPHAD assessment of multi-component hafnia-based phase diagrams.

36 MATERIALS SCIENCE↗
DOE OSTI2021

In Silico Discovery of Multistep Chemistry Initiated by a Conical Intersection: The Challenging Case of Donor–Acceptor Stenhouse Adducts

Detailed mechanistic understanding of multistep chemical reactions triggered by internal conversion via a conical intersection is a challenging task that emphasizes limitations in theoretical and experimental techniques. We present a discovery-based, hypothesis-free computational approach based on first-principles molecular dynamics to discover and refine the switching mechanism of donor–acceptor Stenhouse adducts (DASAs). We simulate the photochemical experiment in silico, following the “hot” ground state dynamics for 10 ps after photoexcitation. Using state-of-the-art graphical processing units-enabled electronic structure calculations we performed in total ~2 ns of nonadiabatic ab initio molecular dynamics discovering (a) critical intermediates that are involved in the open-to-closed transformation, (b) several competing pathways which lower the overall switching yield, and (c) key elements for future design strategies. Finally, our dynamics describe the natural evolution of both the nuclear and electronic degrees of freedom that govern the interconversion between DASA ground-state intermediates, exposing significant elements for future design strategies of molecular switches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Chemical Bond Covalency in Superionic Halide Solid‐State Electrolytes

Abstract Halide solid‐state electrolytes (SSEs) are promising superionic conductors with high oxidative stability and ionic conductivity, making them attractive for all‐solid‐state lithium‐ion batteries. However, most studies have focused on ion‐stacking structures, overlooking the role of bond characteristics in ionic transport. Here, we investigate bond dynamics and the superionic transition (SIT) in bromide electrolyte, Li 3 InBr 6 , using synchrotron X‐ray techniques and ab initio molecular dynamics (AIMD) simulations. We demonstrate that the SIT in halide SSEs is driven by a thermally induced transition in bonding character (ionic to covalent) rather than a change in crystal phase. AIMD simulations further reveal enhanced Li⁺ diffusion and collective anion motion at elevated temperatures. Expanding our study to Li 3 LnBr 6 (Ln = Gd, Tb, Ho, Tm, and Lu), we confirm the widespread occurrence of SIT in this material class, with Li 3 GdBr 6 exhibiting the highest ionic conductivity (5.2 mS cm −1 at 298 K). More importantly, the ionic‐covalent transition is highly tunable through electrolyte modifications, such as cation/anion substitution and synthesis methods. Our findings provide a new perspective on ionic transport, highlighting the critical role of chemical bond characteristics in halide SSEs.

Chemistry↗
DOE OSTI2024

Uncovering fast solid-acid proton conductors based on dynamics of polyanion groups and proton bonding strength

Achieving high proton conductivity in inorganic solids is key for advancing many electrochemical technologies, including low-energy nano-electronics and energy-efficient fuel cells and electrolyzers. A quantitative understanding of the physical traits of a material that regulate proton diffusion is necessary for accelerating the discovery of fast proton conductors. In this work, we have mapped the structural, chemical and dynamic properties of solid acids to the elementary steps of the Grotthuss mechanism of proton diffusion. Our approach combines ab initio molecular dynamics simulations, analysis of phonon spectra and atomic structure calculations. We have identified the donor–hydrogen bond lengths and the acidity of polyanion groups as key descriptors of local proton transfer and the vibrational frequencies of the cation framework as the key descriptor of lattice flexibility. The latter facilitates rotations of polyanion groups and long-range proton migration in solid acid proton conductors. The calculated lattice flexibility also correlates with the experimentally reported superprotonic transition temperatures. Using these descriptors, we have screened the Materials Project database and identified potential solid acid proton conductors with monovalent, divalent and trivalent cations, including Ag + , Sr 2+ , Ba 2+ and Er 3+ cations, which go beyond the traditionally considered monovalent alkali cations (Cs + , Rb + , K + , and NH 4 + ) in solid acids.

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

Thermally frustrated phase transition at high pressure in B 2-ordered FeV

X-ray diffraction measurements of equiatomic B2-ordered FeV were performed in a diamond-anvil cell at room temperature at several pressure points up to 80 GPa that showed the cubic phase to be stable with no indication of structural phase transitions. Density functional theory at 0 K predicts Fermi surface nesting, an electronic topological transition, and a phonon dynamical instability within the experimentally investigated pressure range. Nevertheless, the instability is absent in phonon dispersion curves extracted from ab initio molecular dynamics simulations below the critical volume at temperatures as low as 10 K, indicating that thermal atomic displacements can frustrate the phase transition by renormalizing the phonon dispersion curves. Ferrimagnetism is critical for the stability of the cubic phase at low temperature, but thermal atomic displacements are enough to support the structure at and above the Néel temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Persistent Homology Metrics Reveal Quantum Fluctuations and Reactive Atoms in Path Integral Dynamics

Nuclear quantum effects (NQEs) are known to impact a number of features associated with chemical reactivity and physicochemical properties, particularly for light atoms and at low temperatures. In the imaginary time path integral formalism, each atom is mapped onto a “ring polymer” whose spread is related to the quantum mechanical uncertainty in the particle’s position, i.e., its thermal wavelength. A number of metrics have previously been used to investigate and characterize this spread and explain effects arising from quantum delocalization, zero-point energy, and tunneling. Many of these shape metrics consider just the instantaneous structure of the ring polymers. However, given the significant interest in methods such as centroid molecular dynamics and ring polymer molecular dynamics that link the molecular dynamics of these ring polymers to real time properties, there exists significant opportunity to exploit metrics that also allow for the study of the fluctuations of the atom delocalization in time. Here we consider the ring polymer delocalization from the perspective of computational topology, specifically persistent homology, which describes the 3-dimensional arrangement of point cloud data, (i.e. atomic positions). We employ the Betti sequence probability distribution to define the ensemble of shapes adopted by the ring polymer. The Wasserstein distances of Betti sequences adjacent in time are used to characterize fluctuations in shape, where the Fourier transform and associated principal components provides added information differentiating atoms with different NQEs based on their dynamic properties. We demonstrate this methodology on two representative systems, a glassy system consisting of two atom types with dramatically different de Broglie thermal wavelengths, and ab initio molecular dynamics simulation of an aqueous 4 M HCl solution where the H-atoms are differentiated based on their participation in proton transfer reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Machine Learning-Accelerated First-Principles Molecular Dynamics Explains Anomalous Lattice Thermal Expansion in BaZr 0.78 Y 0.22 O 3-δ

Fuel cells are a vital clean energy technology that converts chemical energy directly into electricity with high efficiency, making them a cornerstone of a sustainable energy future. Herein we investigate the thermal and chemical lattice expansion behavior of hydrated BaZr 0.78 Y 0.22 O 3-δ using machine learning-accelerated ab initio molecular dynamics simulations. Here, our results reproduce the experimentally observed non-monotonic and anomalous temperature dependence of lattice expansion, which we attribute to the competing effects of thermal expansion and dehydration—two mechanisms that influence the lattice expansion in opposite directions. The importance of this work lies in its detailed demonstration of how advanced computational techniques can accurately capture complex environmental effects, providing a valuable framework for modeling similar phenomena in a variety of material systems and applications.

Proton conducting fuel cell↗
DOE OSTI2026

Interfacial Hydrogen-Bond Dynamics in Transition Metal Compounds

Understanding how water behaves when confined within atomic layers of active transition-metal carbides, nitrides, and carbonitrides is essential for uncovering the fundamental principles needed to engineer solid–liquid interfaces at the atomic scale. Yet, how lattice element chemistry and surface termination groups collectively regulate the structure and mobility of such interlayer water remains poorly understood. Here, we present a composition-controlled investigation of interlayer water dynamics in layered transition-metal nitride, carbide, and carbonitride systems using a systematic integration of quasi-elastic neutron scattering (QENS), ab initio molecular dynamics (AIMD) simulations, and density functional theory (DFT) calculations. QENS measurements show that nitride-rich systems host mobile, translationally diffusing water with thermally activated self-diffusion coefficients on the order of 10 –10 m 2 s –1 , whereas mixed C/N lattices confine water to localized, nontranslational motion that is insensitive to temperature. AIMD and DFT reveal that lattice C/N chemistry and surface functional group composition reshape the first hydration layer by modulating the surface electronic structure and termination-dependent hydrogen-bond networks, leading to pronounced differences in water ordering and thermal resilience. On the other hand, fully carbide systems exhibit intermediate behavior, highlighting that water mobility is not primarily controlled by the hydration level alone but by the coupling between lattice composition and surface chemistry. Overall, this study establishes how surface chemistry and lattice composition jointly control interfacial hydrogen bond dynamics, offering a mechanistic framework for designing transition-metal layered materials with tailored interfacial transport properties.

Hydration↗
DOE OSTI2023

Quantum Chemical Simulations of CO 2 and N 2 Capture in Reline, a Prototypical Deep Eutectic Solvent

Deep eutectic solvents such as reline are an emerging class of low-cost, environmentally friendly solvents with tunable properties that are potentially applicable for the capture and separation of CO 2 . Experimental measurements showed that a reline-based membrane contactor can capture and separate CO 2 via physisorption through a dissolution process with 96.7% purity from a mixed gas containing CO 2 and N 2 (50:50% molar ratio). Here, we examine the nature of the interaction of CO 2 and N 2 with reline employing quantum chemical methods. We focus on explaining the mechanism by which CO 2 and N 2 bind to reline and the reason for the high selectivity for absorption of CO 2 compared to N 2 . We analyze the dynamics, energetics, and binding motifs for CO 2 and N 2 in reline employing density functional theory, density functional tight binding, and ab initio molecular dynamics. We also investigate the effect of reline on the vibrational spectra of CO 2 and reline. Our simulations indicate that the selective capture of CO 2 from the mixture of CO 2 and N 2 is due to the interplay between attractive electrostatic and charge polarization forces with opposing entropic effects, which shift the energetic balance and make the N 2 absorption unfavorable in reline.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗