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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Compressing Hamiltonians with ab initio downfolding for simulating strongly-correlated materials on quantum computers

The accurate first-principles description of strongly correlated materials is an important and challenging problem in condensed matter physics. Ab initio downfolding has emerged as a way of deriving compressed many-body Hamiltonians that maintain the essential physics of strongly correlated materials. The solution of these material-specific models is still exponentially difficult to generate on classical computers, but quantum algorithms allow for a significant speed-up in obtaining the ground states of these compressed Hamiltonians. Here, we demonstrate that using quantum algorithms to obtain the properties of downfolded Hamiltonians can indeed yield high-fidelity solutions. By combining ab initio downfolding and variational quantum eigensolvers, we correctly predict the antiferromagnetic state of one-dimensional cuprate Ca 2 Cu O 3 , the excitonic ground state of monolayer W Te 2 , and the charge-ordered state of correlated metal Sr VO 3 . Numerical simulations using a classical tensor network implementation of variational quantum eigensolvers allow us to simulate large models with up to 54 qubits and encompassing up to four bands in the correlated subspace, which is indicative of the complexity that our framework can address. Through these methods we demonstrate the potential of classical preoptimization and downfolding techniques for enabling efficient materials simulation using quantum algorithms.

Alvertis, Antonios M. [NASA, Ames; LBNL, Berkeley]↗
DOE OSTI2025

Ab initio calculations of overlap integrals for μ → e conversion in nuclei

The rate for μ → e conversion in nuclei is set to provide the most stringent test of lepton-flavor symmetry and a window into physics beyond the Standard Model. However, to disentangle new lepton-flavor-violating interactions, in combination with information from μ → ey and μ → 3e, it is critical that uncertainties at each step of the analysis be controlled and fully quantified. In this regard, nuclear response functions related to the coupling to neutrons are notoriously problematic, since they are not directly constrained by experiment. We address these shortcomings by combining ab initio calculations with a recently improved determination of charge distributions from electron scattering by exploiting strong correlations among charge, point-proton, and point-neutron radii and densities. We present overlap integrals for 27 Al, 48 Ca, and 48 Ti including full covariance matrices, allowing, for the first time, for a comprehensive consideration of nuclear structure uncertainties in the interpretation of μ → e experiments.

ab initio calculations↗
DOE OSTI2023

Development of an interatomic potential for the W–Ta system

A physics-inspired, data-driven interatomic potential framework for multi-element system is presented. This potential is based on the generalization of the embedded atom method potential and systematically incorporates two-, three- and many-body effects. Different atomic environments are described by atom-centered Gaussian basis sets which provides sufficient flexibility to capture diverse atomic environments and allows for easy optimization of the free parameters. An interatomic potential model for the tungsten–tantalum (W–Ta) system is developed using this framework by training on data from ab initio density functional theory (DFT) calculations. The potential is thoroughly tested at various compositions by comparing bulk and defect properties from experimental and DFT data. It is shown that the potential predicts the elastic constants, defect properties, such as vacancy and interstitial formation energies, core structures of dislocations, and melting points for both pure and tantalum and tungsten with an accuracy comparable to other single element machine learning based potentials. In conclusion, the potential model is used to investigate the formation energies of ordered alloys and vacancy formation energies for chemically random W–Ta alloys.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Polarizable Water Potential Derived from a Model Electron Density

A new empirical potential for efficient, large scale molecular dynamics simulation of water is presented. The HIPPO (Hydrogen-like Intermolecular Polarizable POtential) force field is based upon the model electron density of a hydrogen-like atom. This framework is used to derive and parametrize individual terms describing charge penetration damped permanent electrostatics, damped polarization, charge transfer, anisotropic Pauli repulsion, and damped dispersion interactions. Initial parameter values were fit to Symmetry Adapted Perturbation Theory (SAPT) energy components for ten water dimer configurations, as well as the radial and angular dependence of the canonical dimer. The SAPT-based parameters were then systematically refined to extend the treatment to water bulk phases. The final HIPPO water model provides a balanced representation of a wide variety of properties of gas phase clusters, liquid water, and ice polymorphs, across a range of temperatures and pressures. This water potential yields a rationalization of water structure, dynamics, and thermodynamics explicitly correlated with an ab initio energy decomposition, while providing a level of accuracy comparable or superior to previous polarizable atomic multipole force fields. The HIPPO water model serves as a cornerstone around which similarly detailed physics-based models can be developed for additional molecular species.

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

Ground-state properties of the Hubbard model in one and two dimensions from the Gutzwiller conjugate gradient minimization theory

We introduce Gutzwiller conjugate gradient minimization (GCGM) theory, an ab initio quantum many-body theory for computing the ground-state properties of infinite systems. GCGM uses the Gutzwiller wave function but does not use the commonly adopted Gutzwiller approximation (GA), which is a major source of inaccuracy. Instead, the theory uses an approximation that is based on the occupation probability of the on-site configurations, rather than approximations that decouple the site-site correlations as used in the GA. We test the theory in the one-dimensional and two-dimensional Hubbard models at various electron densities and find that GCGM reproduces energies and double occupancies in reasonable agreement with benchmark data at a very small computational cost.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Neural network representation of electronic structure from ab initio molecular dynamics

Despite their rich information content, electronic structure data amassed at high volumes in ab initio molecular dynamics simulations are generally under-utilized. Here we introduce a transferable high-fidelity neural network representation of such data in the form of tight-binding Hamiltonians for crystalline materials. This predictive representation of ab initio electronic structure, combined with machine-learning boosted molecular dynamics, enables efficient and accurate electronic evolution and sampling. When it is applied to a one-dimension charge-density wave material, carbyne, we are able to compute the spectral function and optical conductivity in the canonical ensemble. The spectral functions evaluated during soliton-antisoliton pair annihilation process reveal significant renormalization of low-energy edge modes due to retarded electron-lattice coupling beyond the Born–Oppenheimer limit. The availability of an efficient and reusable surrogate model for the electronic structure dynamical system will enable calculating many interesting physical properties, paving the way to previously inaccessible or challenging avenues in materials modeling.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Spin wave Hamiltonian and anomalous scattering in NiPS 3

Here, we report a comprehensive spin wave analysis of the semiconducting honeycomb van der Waal antiferromagnet NiPS 3 . Using single-crystal inelastic neutron scattering, we map out the full Brillouin zone and fit the observed modes to a spin wave model with rigorously defined uncertainty. We find that the third-nearest-neighbor exchange J 3 dominates the Hamiltonian, a feature which we fully account for by ab initio density functional theory calculations. We also quantify the degree to which the threefold rotation symmetry is broken and account for the Q = 0 excitations observed in other measurements, yielding a spin exchange model which is consistent across multiple experimental probes. We also identify a strongly reduced static ordered moment and reduced low-energy intensity relative to the linear spin wave calculations, signaling unexplained features in the magnetism which requires going beyond the linear spin wave approximation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Efficient Multiscale Optoelectronic Prediction for Conjugated Polymers

Conjugated polymers represent a high-potential material class due to the tunability of their optoelectronic properties via straightforward processing protocols. However, to in silico tailor these optoelectronic properties, one must compute the conformationally dependent electronic structure over mesoscopic length and time scales. This task represents a challenging multiscale computational problem in which quantum chemistry and atomistic or coarse-grained molecular dynamics must be integrated. Recently, we introduced a methodology, called electronic coarse graining (ECG), that utilizes artificial neural networks to compute ab initio quality electronic structures using only the reduced degrees of freedom of coarse-grained models. Here, we adapt ECG to variable-molecular weight conjugated oligomers by casting the problem in the framework of sequence detection. A machine-learning (ML) architecture employing one-dimensional convolutional neural networks and long short-term memory networks is utilized to compute ground-state orbital energies, charge density distributions, and optical spectra solely from the coarse-grained model's configurational degrees of freedom. Robust molecular weight transferability for ECG is established via a A-ML approach that leverages model electronic Hamiltonians for ground and excited-state property determination. The accuracy and transferability of the ECG methodology opens the door for scalable optoelectronic property prediction in conjugated polymers directly from coarse-grained degrees of freedom.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Can electric fields drive chemistry for an aqueous microdroplet?

Abstract Reaction rates of common organic reactions have been reported to increase by one to six orders of magnitude in aqueous microdroplets compared to bulk solution, but the reasons for the rate acceleration are poorly understood. Using a coarse-grained electron model that describes structural organization and electron densities for water droplets without the expense of ab initio methods, we investigate the electric field distributions at the air-water interface to understand the origin of surface reactivity. We find that electric field alignments along free O–H bonds at the surface are ~16 MV/cm larger on average than that found for O–H bonds in the interior of the water droplet. Furthermore, electric field distributions can be an order of magnitude larger than the average due to non-linear coupling of intramolecular solvent polarization with intermolecular solvent modes which may contribute to even greater surface reactivity for weakening or breaking chemical bonds at the droplet surface.

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

Observation of a mixed close-packed structure in superionic water

The study of superionic (SI) water has been a highly active research area since its theoretical prediction. Despite significant experimental and computational efforts, its melting curve and the stability of different oxygen lattices remain debated, impacting our understanding of SI ice’s peculiar transport properties. Experimental results at lower pressures show disagreement, whereas data at higher pressures are scarce due to the extreme challenges of such experiments. In this work, we present ultrafast X-ray diffraction results of water compressed by multiple shocks to pressures up to ~ 180 GPa. At pressures exceeding 150 GPa and temperatures around 2500 K, our diffraction patterns challenge the pure FCC-SI phase model, providing experimental evidence of the mixed close-packed superionic phase predicted by advanced ab initio calculations. At lower pressures, we observe simultaneous signatures of BCC and FCC structures within a pressure-temperature range consistent with some static-compression experiments, helping to resolve contradictory results in literature. These insights offer new constraints on the stability domains of SI phases and reveal detailed structural features, such as stacking faults. Our results advance the structural understanding of high-pressure SI ice to a level approaching that of ice I polymorphs, with potential implications for water-rich interiors of giant planets.

Andriambariarijaona, Leon [Centre National de la R↗
DOE OSTI2023

Tunable electron–flexural phonon interaction in graphene heterostructures

Peculiar electron-phonon interaction characteristics underpin the ultrahigh mobility, electron hydrodynamics, superconductivity, and superfluidity observed in graphene heterostructures. Here, the Lorenz ratio (L) between the electronic thermal conductivity and the product of the electrical conductivity and temperature provides unique insight into electron-phonon interactions that is inaccessible to past graphene measurements. Here we show an unusual L peak in degenerate graphene near 60 Kelvin and decreased peak magnitude with increased mobility. When combined with ab initio calculations of the many-body electron-phonon self-energy and analytical models, this experimental observation reveals that broken reflection symmetry in graphene heterostructures can relax a restrictive selection rule to allow quasielastic electron coupling with an odd number of flexural phonons, contributing to the increase of L toward the Sommerfeld limit at an intermediate temperature sandwiched between the low-temperature hydrodynamic regime and the inelastic electron-phonon scattering regime above 120 Kelvin. In contrast to past practices of neglecting flexural phonon contributions to transport in two-dimensional materials, this work suggests that tunable electron-flexural phonon coupling can provide a handle to control quantum matter at the atomic scale, such as magic angle twisted bilayer graphene where low-energy excitations may mediate Cooper pairing of flat-band electrons.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Role of morphology in defect formation and photo-induced carrier instabilities in amorphous indium oxide

Ab initio molecular dynamics liquid-quench simulations and hybrid density functional calculations are performed to model the effects of room-temperature atomic fluctuations and photo-illumination on the structural and electronic properties of amorphous sub-stoichiometric In 2 O 2.96 . A large configurational ensemble is employed to reliably predict the distribution of localized defects as well as their response to the thermal and light activation. The results reveal that the illumination effects on the carrier concentration are greater in amorphous configurations with shorter In–O bond length and reduced polyhedral sharing as compared to the structures with a more uniform morphology. Further, the obtained correlation between the photo-induced carrier density and the reduction in the number of fully coordinated In-atoms implies that metal oxides with a significant fraction of crystalline/amorphous interfaces would show a more pronounced response to illumination. Photo-excitation also produces In–O 2 –In defects that have not been previously found in sub-stoichiometric amorphous oxides; these defects are responsible for carrier instabilities due to overdoping.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Improving the reliability of machine learned potentials for modeling inhomogeneous liquids

The atomic-scale response of inhomogeneous fluids at interfaces and surrounding solute particles plays a critical role in governing chemical, electrochemical, and biological processes. Classical molecular dynamics simulations have been applied extensively to simulate the response of fluids to inhomogeneities directly, but are limited by the accuracy of the underlying interatomic potentials. Here, we use neural network potentials (NNPs) trained to ab initio simulations to accurately predict the inhomogeneous responses of two distinct fluids: liquid water and molten NaCl. Although NNPs can be readily trained to model complex bulk systems across a range of state points, we show that to appropriately model a fluid's response at an interface, relevant inhomogeneous configurations must be included in the training data. In order to sufficiently sample appropriate configurations of such inhomogeneous fluids, we develop protocols based on molecular dynamics simulations in the presence of external potentials. We demonstrate that NNPs trained on inhomogeneous fluid configurations can more accurately predict several key properties of fluids—including the density response, surface tension and size-dependent cavitation free energies—for liquid water and molten NaCl, compared to both empirical interatomic potentials and NNPs that are not trained on such inhomogeneous configurations. This work therefore provides a first demonstration and framework to extract the response of inhomogeneous fluids from first principles for classical density-functional treatment of fluids free from empirical potentials.

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

Fast and Accurate Machine Learning Strategy for Calculating Partial Atomic Charges in Metal–Organic Frameworks

Computational high-throughput screening using molecular simulations is a powerful tool for identifying top-performing metal–organic frameworks (MOFs) for gas storage and separation applications. Accurate partial atomic charges are often required to model the electrostatic interactions between the MOF and the adsorbate, especially when the adsorption involves molecules with dipole or quadrupole moments such as water and CO 2 . Although ab initio methods can be used to calculate accurate partial atomic charges, these methods are impractical for screening large material databases because of the high computational cost. We developed a random forest machine learning model to predict the partial atomic charges in MOFs using a small yet meaningful set of features that represent both the elemental properties and the local environment of each atom. The model was trained and tested on a collection of about 320 000 density-derived electrostatic and chemical (DDEC) atomic charges calculated on a subset of the Computation-Ready Experimental Metal–Organic Framework (CoRE MOF-2019) database and separately on charge model 5 (CM5) charges. The model predicts accurate atomic charges for MOFs at a fraction of the computational cost of periodic density functional theory (DFT) and is found to be transferable to other porous molecular crystals and zeolites. In conclusion, a strong correlation is observed between the partial atomic charge and the average electronegativity difference between the central atom and its bonded neighbors.

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

Fragment-based determination of a proteinase K structure from MicroED data using ARCIMBOLDO_SHREDDER

Structure determination of novel biological macromolecules by X-ray crystallography can be facilitated by the use of small structural fragments, some of only a few residues in length, as effective search models for molecular replacement to overcome the phase problem. Independence from the need for a complete pre-existing model with sequence similarity to the crystallized molecule is the primary appeal of ARCIMBOLDO , a suite of programs which employs this ab initio algorithm for phase determination. Here, the use of ARCIMBOLDO is investigated to overcome the phase problem with the electron cryomicroscopy (cryoEM) method known as microcrystal electron diffraction (MicroED). The results support the use of the ARCIMBOLDO_SHREDDER pipeline to provide phasing solutions for a structure of proteinase K from 1.6 Å resolution data using model fragments derived from the structures of proteins sharing a sequence identity of as low as 20%. ARCIMBOLDO_SHREDDER identified the most accurate polyalanine fragments from a set of distantly related sequence homologues. Alternatively, such templates were extracted in spherical volumes and given internal degrees of freedom to refine towards the target structure. Both modes relied on the rotation function in Phaser to identify or refine fragment models and its translation function to place them. Model completion from the placed fragments proceeded through phase combination of partial solutions and/or density modification and main-chain autotracing using SHELXE . The combined set of fragments was sufficient to arrive at a solution that resembled that determined by conventional molecular replacement using the known target structure as a search model. This approach obviates the need for a single, complete and highly accurate search model when phasing MicroED data, and permits the evaluation of large fragment libraries for this purpose.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Disentangling the confounding spectroscopy of C 1 molecules: Without symmetry as a guide, everything is allowed

The spectra of C 1 molecules are confounding in that each of the fundamental vibrational modes transform as the same irreducible representation (A) and hence each band consists of a seemingly random distribution of a-, b-, and c-type transitions. This is in contrast to higher symmetry molecules for which band types are readily deduced by simple symmetry rules. Herein, we present a method to simulate the convoluted rotational contours in the gas-phase spectra of C 1 molecules by combining existing ab initio calculations with Colin Western’s PGOPHER rotational contour program. Specifically, ab initio calculations in the NWC HEM suite of programs were employed to predict the components of the dipole moment derivatives along the principal axes of the moments of inertia. This information was then input into PGOPHER to model the fundamental band contours as a sum of a-, b-, and c-type transitions. This method was applied to simulate the rotational contour spectra of a series of representative C 1 molecules which were then compared against both ab initio stick spectra and experimentally measured broadband IR spectra from the Pacific Northwest National Laboratory infrared gas-phase database. In addition to providing further insight beyond what is revealed in a typical stick spectrum, the simulated contours showed good agreement with the measured spectra.

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

Liquid-liquid phase transition of hydrogen and its critical point: Analysis from ab initio simulation and a machine-learned potential

We simulate high-pressure hydrogen in its liquid phase close to molecular dissociation using a machine-learned interatomic potential. The model is trained with density functional theory (DFT) forces and energies, with the Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional. We show that an accurate NequIP model, an E(3)-equivariant neural network potential, accurately reproduces the phase transition present in PBE. Moreover, the computational efficiency of this model allows for substantially longer molecular dynamics trajectories, enabling us to perform a finite-size scaling (FSS) analysis to distinguish between a crossover and a true first-order phase transition. Here, we locate the critical point of this transition, the liquid-liquid phase transition (LLPT), at 1200-1300 K and 155-160 GPa, a temperature lower than most previous estimates and close to the melting transition.

08 HYDROGEN↗
DOE OSTI2023

Theory and Simulation of Ultrafast Multidimensional Nonlinear X-ray Spectroscopy of Molecules (Final Report)

Emerging X-ray free electron laser (XFEL) beam sources offer new types of probes of matter with unprecedented spatial and temporal resolutions. These experimental advances must be met by robust theoretical and computational tools that provide predictive modeling capacity of the underlining electronic and structural dynamics. The latter will be essential for the design of sophisticated multi-pulse experiments and for their interpretation. The proposed research effort will focus on developing cutting- edge simulation tools for nonlinear multidimensional X-ray/optical spectroscopies and aims to address key questions in Priority Research Opportunities 1 (Probing and controlling electron motion within a molecule) and 3 (Capturing rare events and intermediate states in the transformation of matter) as mentioned in the BES Roundtable Report “Opportunities for Basic Research at the Frontiers of XFEL Ultrafast Science”. XFEL multidimensional nonlinear techniques, which combine sequences of X-ray and possibly optical pulses, provide a unique experimental toolbox for probing the dynamics of core and valence electronic excitations, as well as material structure. Predictive modeling of these dynamical processes requires the combination of analytical theory for nonlinear interactions of light and matter, robust quantum-chemical methodologies for the accurate description of electronic structure of various materials, and multiscale ab initio electron and nuclear dynamics techniques operating beyond Born-Oppenheimer approximation. These challenges will be addressed with three research thrusts (i) Develop and implement theoretical apparatus for modeling a broad range of multidimensional spectroscopic techniques enabled by present and upcoming XFEL facilities. This thrust also includes the incorporation of a computational module in the DOE supported open-source NWChem computational chemistry package as well as the development of other open-source codes ready for dissemination across a broad user base; (ii) Propose and design new multi-pulse experiments that make use of the capabilities of the incoming LCLS-II facility; (iii) Perform selected applications to specific molecular systems that can be carried out at LCLS-II and demonstrate how these X-ray sources may be used to study nonadiabatic dynamics through conical interactions, electronic correlations in multi-core excitons, and charge transfer/energy transfer processes. The proposed research will be carried out by a multi-disciplinary four-institution research team which combines academia and national laboratories and spans the broad and necessary expertise in theoretical spectroscopy, nonlinear optics, quantum chemistry, molecular non-adiabatic dynamics and code development. The work will be performed in a highly interactive team environment with junior researchers shared between institutions thus cementing cross- disciplinary interactions. The developed simulation tools will be immediately deployed for XFEL facility users, both experimentalists and theorists, via freely distributed codes and databases. Altogether, this project will facilitate establishing XFEL-based multidimensional spectroscopies as a novel diagnostic tool for monitoring electronic and structural dynamics in molecular materials.

74 ATOMIC AND MOLECULAR PHYSICS↗