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DOE OSTI2024

Scalable learning of potentials to predict time-dependent Hartree–Fock dynamics

We propose a framework to learn the time-dependent Hartree–Fock (TDHF) inter-electronic potential of a molecule from its electron density dynamics. Although the entire TDHF Hamiltonian, including the inter-electronic potential, can be computed from first principles, we use this problem as a testbed to develop strategies that can be applied to learn a priori unknown terms that arise in other methods/approaches to quantum dynamics, e.g., emerging problems such as learning exchange–correlation potentials for time-dependent density functional theory. We develop, train, and test three models of the TDHF inter-electronic potential, each parameterized by a four-index tensor of size up to 60 × 60 × 60 × 60. Two of the models preserve Hermitian symmetry, while one model preserves an eight-fold permutation symmetry that implies Hermitian symmetry. Across seven different molecular systems, we find that accounting for the deeper eight-fold symmetry leads to the best-performing model across three metrics: training efficiency, test set predictive power, and direct comparison of true and learned inter-electronic potentials. All three models, when trained on ensembles of field-free trajectories, generate accurate electron dynamics predictions even in a field-on regime that lies outside the training set. To enable our models to scale to large molecular systems, we derive expressions for Jacobian-vector products that enable iterative, matrix-free training.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Machine learning-accelerated path integral molecular dynamics simulations of reactive organic electrolytes

Hydrogen bonded electrolytes that exhibit accelerated proton transport via sequential reactive hops have drawn interest for their promise in clean energy applications. Molecular dynamics simulations of these electrolytes offer the opportunity to uncover microscopic mechanistic details that could be used to design and tune the properties of candidate electrolyte technologies. However, accurately modeling the proton transfer reactions and transport properties that give rise to high charge conductivites in these electrolytes proves computationally challenging because of the need to perform lengthy condensed phase simulations, treating both the electronic and nuclear degrees of freedom quantum mechanically. In this paper, we demonstrate that such a modeling task can be efficiently achieved with the use of density functional theory (DFT)-trained machine learning potentials (MLP) to accelerate path integral molecular dynamics (PIMD) simulations. We highlight the practical utility of this approach by using it to benchmark how closely PIMD simulations employing different DFT exchange–correlation functionals reproduce the composition-dependent densities, diffusion coefficients, and electrical conductivities of mixtures consisting of imidazole and levulinic acid. Even with the speedup afforded by our MLPs, PIMD simulations remain quite expensive. Furthermore, in order to render PIMD more computationally tractable, we introduce and benchmark the accuracy of a ring polymer contraction approach that leverages a computationally efficient short-range MLP to accelerate our PIMD simulations by an additional factor of four.

Chemical bonding↗

DOE OSTI2022

Rotating quantum turbulence in the unitary Fermi gas

Quantized vortices carry the angular momentum in rotating superfluids, and are key to the phenomenon of quantum turbulence. Advances in ultracold-atom technology enable quantum turbulence to be studied in regimes with both experimental and theoretical control, unlike the original contexts of superfluid helium experiments. While much work has been performed with bosonic systems, detailed studies of fermionic quantum turbulence are nascent, despite wide applicability to other contexts such as rotating neutron stars. In this paper, we present a large-scale study of quantum turbulence in rotating fermionic superfluids using an accurate time-dependent density functional theory called the superfluid local density approximation. We identify two different modes of turbulent decay in the dynamical equilibration of a rotating fermionic superfluid, and contrast these results with a computationally simpler description provided by the Gross-Pitaevskii equation, which we find can qualitatively reproduce these decay mechanisms if dissipation is explicitly included. These results demonstrate that dissipation mechanisms intrinsic to fermionic superfluids play a key role in differentiating fermionic from bosonic turbulence, which manifests by enhanced damping of Kelvin waves.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS2026

Diffusion Quantum Monte Carlo Calculation of the Austenite and Martensite Phases of NiTi

NiTi is a promising material for smart and active technologies due to its exhibition of the shape memory effect, superelasticity, and biocompatibility. The shape memory effect is tied to the reversible transition between the austenite and martensite phases. A major research direction is to alloy NiTi with Zr, Hf, Pd, Pt, etc., in order to tune the martensitic transition temperature (MTT). Modeling the MTT from first principles is challenging because the lattice dynamics is complicated by anharmonicity and various low-energy structures. Using density functional theory, the energy difference between the austenite and martensite phases of NiTi varies by up to 100 meV/atom depending on the choice of density functional, which is of the same order of the energy difference itself. Consequently, free energy calculations with different functionals can result in estimates of the MTT that vary by several hundred K. Using diffusion quantum Monte Carlo, we calculated the energy difference between the B2 and B19' structures of NiTi to be 70.9 +- 2.5 meV/atom.

Kevin K Ly↗

DOE OSTI2020

Comparative study of Minnesota functionals performance on ferroelectric BaTiO 3 and PbTiO 3

Density functional theory based simulations are the leading tool for the computational investigation of ferroelectrics and the parametrization of their classical potentials. However, the predictions often depend strongly on the exchange correlation functional. The most popular choices, LDA and GGA, tend to underestimate or overestimate some structural, electric, and energy properties. These impede development of highly accurate classical potentials that extend the reach of first-principles simulations to finite temperatures and realistic sizes. In this work, we investigate the performance of recently developed Minnesota exchange correlation functionals on prototypical ferroelectrics BaTiO 3 , and PbTiO 3 , in comparison with some popular ones. We find that there exists strong correlation between predictions for some properties (tetragonality, phase energy difference, and polarization) by different functionals. Along the correlation line, we find a range of functionals (including some from the Minnesota suite) whose predictions fall in between those of LDA and GGA and, therefore, offer an improvement. A way to relatively rank functional performance with respect to chosen benchmarks is proposed and applied to identify the top performers for BaTiO 3 and PbTiO 3 . Here, the performance is found to be material dependent. Therefore, we propose that the performance assessment carried out in this work is employed to "screen" functionals prior to their use on ferroelectrics. Quick and computationally inexpensive, it is likely to lead to improved descriptions, especially for classical potential parametrization. The Minnesota functional suite is found to be suitable for this task.

36 MATERIALS SCIENCE↗

NASA NTRS1977

Radar backscattering from a sea having an anisotropic large-scale surface, part 2

A two scale scattering model was derived that combines specular reflections from sea waves and Bragg scattering in a manner consistent with energy conservation. The effect of the tilting of the small scale roughness by the large scale roughness was included, which accounted for the reduction of reflected power. The special case of backscattering for which the transmitted polarization equaled the received polarization was considered. An anisotropic large scale surface was used to specify the probability density function of the large scale surface normal. In order to isolate the azimuthal variation of the normalized radar cross section produced by the anisotropic probability density function, an isotropical small scale spectrum was assumed.

Wentz, F. J.↗

DOE OSTI2021

Optical Properties of the Infinite-Layer La 1-x Sr x NiO 2 and Hidden Hund's Physics

We investigate the optical properties of the normal state of the infinite-layer La 1-x Sr x NiO 2 using density functional theory plus dynamical mean-field theory. We find a correlated metal which exhibits substantial transfer of spectral weight to high energies relative to the density functional theory. The correlations are not due to Mott physics, which would suppress the charge fluctuations and the integrated optical spectral weight as we approach a putative insulating state. Instead, we find the unusual situation, that the integrated optical spectral weight decreases with doping and increases with increasing temperature. We contrast this with the coherent component of the optical conductivity, which decreases with increasing temperature as a result of a coherence-incoherence crossover. Our studies reveal that the effective crystal field splitting is dynamical and increases strongly at low frequency. This leads to a picture of a Hund's metallic state, where dynamical orbital fluctuations are visible at intermediate energies, while at low energies a Fermi surface with primarily d x 2 -y 2 character emerges. The infinite-layer nickelates are thus in an intermediate position between the iron based high temperature superconductors where multiorbital Hund's physics dominates and a one-band system such as the cuprates. To capture this physics we propose a low-energy two-band model with atom centered e g states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1973

On minimizing the probability of misclassification for linear feature selection

The use of techniques for feature selection permits treatment of classification problems in spaces of reduced dimensions. A method is considered of linear feature selection for n-dimensional observation vectors which belong to one of two populations, where each population is described by a known multivariate normal density function. More specifically, the problem of finding a 1xn transformation matrix B for which the probability of misclassification with respect to the one-dimensional transformed density functions was minimized was considered. Theoretical results are presented which give rise to a numerically tractable expression for the variation in the probability of misclassification with respect to B. Using this expression a computational procedure is discussed for obtaining a B which minimizes the probability of misclassification. Preliminary numerical results are discussed.

Guseman, L. F., Jr.↗

NASA NTRS2002

Optimization of Systems with Uncertainty: Initial Developments for Performance, Robustness and Reliability Based Designs

This paper presents a study on the optimization of systems with structured uncertainties, whose inputs and outputs can be exhaustively described in the probabilistic sense. By propagating the uncertainty from the input to the output in the space of the probability density functions and the moments, optimization problems that pursue performance, robustness and reliability based designs are studied. Be specifying the desired outputs in terms of desired probability density functions and then in terms of meaningful probabilistic indices, we settle a computationally viable framework for solving practical optimization problems. Applications to static optimization and stability control are used to illustrate the relevance of incorporating uncertainty in the early stages of the design. Several examples that admit a full probabilistic description of the output in terms of the design variables and the uncertain inputs are used to elucidate the main features of the generic problem and its solution. Extensions to problems that do not admit closed form solutions are also evaluated. Concrete evidence of the importance of using a consistent probabilistic formulation of the optimization problem and a meaningful probabilistic description of its solution is provided in the examples. In the stability control problem the analysis shows that standard deterministic approaches lead to designs with high probability of running into instability. The implementation of such designs can indeed have catastrophic consequences.

Crespo, Luis G.↗

NASA NTRS2011

Hypervelocity Impact Test Fragment Modeling: Modifications to the Fragment Rotation Analysis and Lightcurve Code

Hypervelocity impact tests on test satellites are performed by members of the orbital debris scientific community in order to understand and typify the on-orbit collision breakup process. By analysis of these test satellite fragments, the fragment size and mass distributions are derived and incorporated into various orbital debris models. These same fragments are currently being put to new use using emerging technologies. Digital models of these fragments are created using a laser scanner. A group of computer programs referred to as the Fragment Rotation Analysis and Lightcurve code uses these digital representations in a multitude of ways that describe, measure, and model on-orbit fragments and fragment behavior. The Dynamic Rotation subroutine generates all of the possible reflected intensities from a scanned fragment as if it were observed to rotate dynamically while in orbit about the Earth. This calls an additional subroutine that graphically displays the intensities and the resulting frequency of those intensities as a range of solar phase angles in a Probability Density Function plot. This document reports the additions and modifications to the subset of the Fragment Rotation Analysis and Lightcurve concerned with the Dynamic Rotation and Probability Density Function plotting subroutines.

Gouge, Michael F.↗

DOE OSTI2023

Connectivity between Static Field and Continuous Wave Field Effects on Excitation-Induced H 2 Activation

Due to the tremendous applications of the plasmon resonance excitation process, such as improvements in catalytic efficiency due to plasmonic enhancement and/or hot-electron processes, understanding the mechanism behind these processes has become a popular topic in recent years. In this work, we focus on unraveling the mechanism of excitation-induced H 2 activation using a simplified triangular Au 6 /Ag 6 cluster to investigate the effects of the electric field on electron redistribution and bond activation. We applied both static and continuous wave fields to investigate how these fields affect the systems. Geometrical changes (such as bond lengthening), molecular orbital reordering (affecting the relative energies of orbitals corresponding to hot-electron and charge-transfer excited states), and electronic charge redistribution between the cluster and the adsorbate occur upon application of a static electric field. To study H 2 activation, we apply Ehrenfest dynamics with real-time time-dependent density functional theory and examine how different excitation frequencies and polarizations affect bond activation. Moreover, electron-only dynamics are examined with real-time time-dependent density functional theory, and the time-dependent variations in the orbital populations and electronic transitions provide information about the excitation and relaxation processes of hot electrons with applied electric fields. Here, the static field results represent structures that can be accessed during the evolution of the systems when applying continuous wave fields. Through these studies, the effects of static and continuous wave field effects on plasmon-induced H 2 activation can be understood.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Near-Quantitative Predictions of the First-Shell Coordination Structure of Hydrated First-Row Transition Metal Ions Using K-Edge X-ray Absorption Near-Edge Spectroscopy

Understanding the solvation structure of transition metal ions is important due to its broad impact on the kinetics, stability, and reactivity in a variety of applications in geochemistry, biochemistry, energy storage, and environmental chemistry. Using water as the common ligand, we study the X-ray absorption pre-edge and near-edge spectra at the K-edge of a near-complete series of hydrated first-row transition metal ions with d-orbital occupancy ranging from d 2 to d 10 . Starting with optimized structures that were derived from an explicit solvation treatment at the density functional theory (DFT) level, we then compute the pre-edge X-ray absorption spectra at the metal ion K-edge at the time dependent density functional theory (TDDFT) and restricted active-space second-order perturbation theory (RASPT2) levels of theory. TDDFT calculations provide accurate results for spectra that are dominated by single excitations, while significant improvements were obtained with RASPT2 calculations that correctly distinguish between singly and doubly excited states, where relevant, with quantitative accuracy compared with experiment. We analyze and assign the dierent pre-edge features for each metal ion in order to reveal the impact of the variations in the d orbital occupancy on the rst-shell coordination environment. For completeness, we also report the lowest energy ligand-field d-d transitions for all the transition metal aqua ions considered in this study using complete active space second order perturbation theory (CASPT2).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Effect of off-diagonal elements in the Wannier Hamiltonian on DFT + DMFT for low-symmetry materials: Study of Li 2 MnO 3

Here, we study the effect of the off-diagonal elements of the Wannier Hamiltonian on the electronic structure of the low-symmetry material Li 2 MnO 3 ( C2/m ), using dynamical mean field theory calculations with a continuous-time quantum Monte Carlo impurity solver. The presence of significant off-diagonal elements leads to a pronounced suppression of the energy gap. The off-diagonal elements are largest when the Wannier projection is used based on the global coordinate, and they remain substantial even with the projection using the local coordinate close to the direction of Mn-O bonds. We show that the energy gap is enhanced by the diagonalization of the Mn d block in the full p-d Hamiltonian with the application of a unitary rotation matrix. Additionally, the inclusion of small double counting energy is crucial for achieving the experimental gap by reducing p-d hybridization. Furthermore, we establish the efficiency of a low-energy (d-only basis) model for studying the electronic structure of Li 2 MnO 3 , as the Wannier basis represents a hybridized state of Mn d and O p orbitals. These findings suggest an appropriate approach for investigating low-symmetry materials using the density functional theory plus dynamical mean field theory (DFT + DMFT) method. We also find that the antiferromagnetic ground state $\Gamma$ 2u is stable with U ≤ 2 eV within density functional theory+$U$ calculations, which is much smaller than the widely used U = 5 eV.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

First-principles calculation of the configurational energy density of states for a solid-state ion conductor with a variant of the Wang and Landau algorithm

In this work, a variant of the Wang and Landau algorithm for calculation of the configurational energy density of states is proposed. The algorithm was developed for the purpose of using first-principles simulations, such as density functional theory, to calculate the partition function of disordered sublattices in crystal materials. The expensive calculations of first-principles methods make a parallel algorithm necessary for a practical computation of the configurational energy density of states within a supercell approximation of a solid-state material. The algorithm developed in this work is tested with the two-dimensional (2d) Ising model to bench mark the algorithm and to help provide insight for implementation to a materials science application. Tests with the 2d Ising model revealed that the algorithm has good performance compared to the original Wang and Landau algorithm and the 1/$\textit{t}$ algorithm, in particular the short iteration performance. Further, a proof of convergence is presented within an adiabatic assumption, and the analysis is able to correctly predict the time dependence of the modification factor to the density of states. The algorithm was then applied to the lithium and lanthanum sublattice of the solid-state lithium ion conductor Li 0.5 La 0.5 TiO 3 . This was done to help understand the disordered nature of the lithium and lanthanum. The results find, overall, that the algorithm performs very well for the 2d Ising model and that the results for Li 0.5 La 0.5 TiO 3 are consistent with experiment while providing additional insight into the lithium and lanthanum ordering in the material. The primary result is that the lithium and lanthanum become more mixed between layers along the c axis for increasing temperature. In part, the simulation of the disordered Li 0.5 La 0.5 TiO 3 system serves as a benchmark for what size systems are currently and in the near future practical to calculate with density functional theory methods.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS2003

Heats of Segregation of BCC Metals Using Ab Initio and Quantum Approximate Methods

Many multicomponent alloys exhibit surface segregation, in which the composition at or near a surface may be substantially different from that of the bulk. A number of phenomenological explanations for this tendency have been suggested, involving, among other things, differences among the components' surface energies, molar volumes, and heats of solution. From a theoretical standpoint, the complexity of the problem has precluded a simple, unified explanation, thus preventing the development of computational tools that would enable the identification of the driving mechanisms for segregation. In that context, we investigate the problem of surface segregation in a variety of bcc metal alloys by computing dilute-limit heats of segregation using both the quantum-approximate energy method of Bozzolo, Ferrante and Smith (BFS), and all-electron density functional theory. In addition, the composition dependence of the heats of segregation is investigated using a BFS-based Monte Carlo procedure, and, for selected cases of interest, density functional calculations. Results are discussed in the context of a simple picture that describes segregation behavior as the result of a competition between size mismatch and alloying effects

Good, Brian↗

DOE OSTI2024

Effect of XC functionals and dispersion corrections on the DFT‐computed structural and vibrational properties of SrCl 2 –NaCl and ZrF 4 –LiF

Density functional theory (DFT) calculations were performed to examine the impact of exchange–correlation (XC) functionals and van der Waals corrections (specifically the D3 method) on the structural and vibrational properties of the SrCl 2 –NaCl and ZrF 4 –LiF salt systems. Multiple XC functionals, including the local density approximation (LDA), the generalized gradient approximation using the Perdew–Burke–Ernzerhof (PBE) model, and its modified form suitable for solids (PBEsol), the dispersion-corrected PBE-D3 and PBEsol-D3, were considered. Of these functionals, LDA was found to exhibit the highest degree of error, while PBEsol and PBE-D3 displayed the least error. Underestimated lattice parameters compared with experimental values were observed to result in higher force constants, leading to an overprediction of vibrational frequencies. Conversely, an overestimation of lattice parameters was associated with lower vibrational frequencies. The methodology presented in this study yielded results that are in good agreement with experiment, irrespective of the method (finite differences vs. density functional perturbation theory) employed for calculating infrared and Raman spectra. It was further demonstrated that for alkali halides with weak Raman scattering, utilizing a supercell constructed from primitive cells better predicts Raman features than does the use of conventional cells.

Raman↗

DOE OSTI2020

Validating first-principles molecular dynamics calculations of oxide/water interfaces with x-ray reflectivity data

Metal oxide/water interfaces play a crucial role in many electrochemical and photocatalytic processes, such as photoelectrochemical water splitting, the creation of fuel from sunlight, and electrochemical CO 2 reduction. First-principles electronic structure calculations can reveal unique insights into these processes, such as the role of the alignment of the oxide electronic energy levels with those of liquid water. An essential prerequisite for the success of such calculations is the ability to predict accurate structural models of these interfaces, which in turn requires careful experimental validation. Here we report a general, quantitative validation protocol for first-principles molecular dynamics simulations of oxide/aqueous interfaces. The approach makes direct comparisons of interfacial x-ray reflectivity (XR) signals from experimental measurements and those obtained from ab initio simulations with semilocal and van der Waals functionals. The protocol is demonstrated here for the case of the Al 2 O 3 (001)/water interface, one of the simplest oxide/water interfaces. We discuss the technical requirements needed for validation, including the choice of the density functional, the simulation cell size, and the optimal choice of the thermodynamic ensemble. Our results establish a general paradigm for the validation of structural models and interactions at solid/water interfaces derived from first-principles simulations. Furthermore, while there is qualitative agreement between the simulated structures and the experimental best-fit structure, direct comparisons of simulated and measured XR intensities show quantitative discrepancies that derive from both bulk regions (i.e., alumina and water) as well as the interfacial region, highlighting the need for accurate density functionals to properly describe interfacial interactions. Our results show that XR data are sensitive not only to the atomic structure (i.e., the atom locations) but also to the electron-density distributions in both the substrate and at the interface.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Rationalizing Calcium Electrodeposition Behavior by Quantifying Ethereal Solvation Effects on Ca 2+ Coordination in Well-Dissociated Electrolytes

Ca-ion electrochemical systems have been pushed to the forefront of recent multivalent energy storage advances due to their use of earth-abundant redox materials and their high theoretical specific densities in relation to monovalent or even other more widely explored multivalent-charge carriers. However, significant pitfalls in metal plating and stripping arise from electrolyte decomposition and can be related to the coordination environment around Ca 2+ with both the negatively charged anion and the organic–aprotic solvent. Here, we apply multiple spectroscopic techniques in conjunction with density functional theory to evaluate the coordination environment of Ca 2+ across a class of ethereal solvents. Through the combination of X-ray absorption fine structure and time-dependent density functional theory, descriptive measures of the local geometry, coordination, and electronic structure of Ca–ethereal complexes provide distinct structural trends depending on the extent of the Ca 2+ –solvent interaction. Finally, we correlate these findings with electrochemical measurements of calcium tetrakis(hexafluoroisopropoxy)borate (CaBHFIP 2 ) salts dissolved within this class of solvents to provide insight into the preferred structural configuration of Ca 2+ electrolytic solutions for optimized electrochemical plating and stripping.

25 ENERGY STORAGE↗