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Results for “ab initio modeling”

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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Theoretical approaches to metal chemistry

Theoretical calculations on metals ranging from very accurate ab initio studies of diatomic and triatomic systems to model studies of larger clusters are presented. Recent improvements in the representation of one-particle and n-particle spaces have made possible the prediction that Al2 has a 3Pi(u) ground state, even though the 3Sigma(-)g state lies within 200/cm. Results suggest that cluster geometry varies dramatically with cluster size, and that rather large clusters are required before the bulk structure becomes optimal. Al cluster studies show that three-body terms are needed for quantitative agreement with ab initio calculations.

Bauschlicher, Charles W.↗
DOE OSTI2022

Nuclear spectroscopy with heavy ion nucleon knockout and (p,2p) reactions

Knockout reactions with heavy ion targets in inverse kinematics, as well as “quasifree” (p,2p) and (p,pn) reactions are useful tools for nuclear spectroscopy. We report calculations on ab initio many-body wave functions based on the no-core shell model to study the nucleon removal reactions in light nuclei, including beryllium, carbon, and oxygen isotopic chains, and explore the importance of using an ab initio method. Our study helps to clarify how the extraction of spectroscopic factors from the experiments depend on the details of the many-body wave functions being probed. We show that recent advances with the ab initio method can provide more insights on the spectroscopy information extracted from experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2012

A Group Increment Scheme for Infrared Absorption Intensities of Greenhouse Gases

A molecule's absorption in the atmospheric infrared (IR) window (IRW) is an indicator of its efficiency as a greenhouse gas. A model for estimating the absorption of a fluorinated molecule within the IRW was developed to assess its radiative impact. This model will be useful in comparing different hydrofluorocarbons and hydrofluoroethers contribution to global warming. The absorption of radiation by greenhouse gases, in particular hydrofluoroethers and hydrofluorocarbons, was investigated using ab initio quantum mechanical methods. Least squares regression techniques were used to create a model based on this data. The placement and number of fluorines in the molecule were found to affect the absorption in the IR window and were incorporated into the model. Several group increment models are discussed. An additive model based on one-carbon groups is found to work satisfactorily in predicting the ab initio calculated vibrational intensities.

Kokkila, Sara I.↗
DOE OSTI2026

Deciphering the Solvation Structure of Aqueous ZnCl 2 Solutions from X-ray Absorption Spectra Using the Interpretable Graph Neural Network

Machine learning (ML) provides powerful pathways for predicting spectroscopic observables from atomic structures, but its broader impact depends on making model predictions interpretable in terms of physical and chemical principles. Here, we introduce a physics-guided graph neural network (GNN) model that predicts Zn K-edge X-ray spectroscopy (XAS) spectra of aqueous ZnCl 2 solutions. Training data are generated from ab initio XAS calculations on molecular dynamics snapshots obtained using a machine learning interatomic potential. The GNN reproduces experimental spectra across concentrations from dilute (<0.1 m) to highly concentrated (30 m, “water-in-salt”) regimes and scales efficiently to large, disordered liquid systems beyond the reach of conventional ab initio approaches. Gradient-based attribution analysis reveals that the model learns physically meaningful structure-spectrum relationships. Ligand-specific attributions reflect orbital hybridization patterns and the origin of the excitations derived from the density functional theory. Bond-length attributions recover spectral shifts consistent with multiple-scattering theory. Finally, this work bridges data-driven prediction with electronic-structure theory, establishing a general paradigm for interpretable ML that links atomic structure, electronic structure, and spectroscopic observables.

25 ENERGY STORAGE↗
DOE OSTI2024

Ab Initio-Based Bond Order Potential for Arsenene Polymorphs Developed via Hierarchical Reinforcement Learning

Arsenene, a less-explored two-dimensional material, holds the potential for applications in wearable electronics, memory devices, and quantum systems. This study introduces a bond-order potential model with Tersoff formalism, the ML-Tersoff, which leverages multireward hierarchical reinforcement learning (RL), trained on an ab initio data set. This data set covers a spectrum of properties for arsenene polymorphs, enhancing our understanding of its mechanical and thermal behaviors without the complexities of traditional models requiring multiple parameter sets. Our RL strategy utilizes decision trees coupled with a hierarchical reward strategy to accelerate convergence in high-dimensional continuous search spaces. Unlike the Stillinger-Weber approach, which demands separate formalisms for buckled and puckered forms, the ML-Tersoff model concurrently captures multiple properties of the two polymorphs by effectively representing the local environment, thereby avoiding the need for different atomic types. Here, we apply the ML model to understand the mechanical and thermal properties of the arsenene polymorphs and nanostructures. We observe an inverse relationship between the critical strain and temperature in arsenene. Thermal conductivity calculations in nanosheets show good agreement with ab initio data, reflecting a decrease in thermal conductivity attributable to increased anharmonic effects at higher temperatures. We also apply the model to predict the thermal behavior of arsenene nanotubes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Unraveling small-scale defects in irradiated ThO 2 using kinetic Monte Carlo simulations

Point defects and their clusters generated through irradiation can have significant impact on the physical and mechanical properties of materials. However, direct experimental visualization of these small-scale defects using high-resolution scanning transmission electron microscopy remains a challenging task. In this study, using thorium dioxide (ThO 2 ) with the fluorite structure as a model system, we demonstrate the use of ab initio basin-hopping simulations in synergy with object kinetic Monte Carlo simulations as a powerful tool for identifying small defect complexes in irradiated materials. In addition to providing quantitative insights into defect evolution in ThO 2 under irradiation, our study reveals an unexpected role of bound anti-Schottky defect clusters in mediating defect transport. Remarkably, despite their poor thermal stability against dissociation at high temperatures, the transient formation of bound anti-Schottky defects under irradiation and their subsequent migration provide the dominant mechanism for the growth of large interstitial loops that have been experimentally observed in ThO 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2020

Intercalation of Lithium into Graphite: Insights from First-Principles Simulations

Understanding ion intercalation at electrode–electrolyte interfaces is key to the development of energy storage and water desalination. Here, we investigate Li + kinetics at a prototypical interface between graphite anodes and an organic electrolyte, and we elucidate key factors that determine ion transport, using first-principles methodology coupling ab initio molecular dynamics simulations with a solvation model. We show that surface chemical composition significantly influences the kinetics of ion intercalation from the liquid into graphite. We find that this is partly related to the ion desolvation process, which varies notably for different graphite surface chemical terminations. In addition, interfacial polarization is found to play an important role in determining energy barriers for ion transfer. We also discuss the impact of electrode potentials, which is often neglected in conventional first-principles calculations despite being a key factor in device configurations. Our study provides insights into the coupling of electronic and ionic effects of interfacial chemistry on ion transport at complex electrode–electrolyte interfaces.

25 ENERGY STORAGE↗
DOE OSTI2021

Temperature-Dependent Properties of Molten Li 2 BeF 4 Salt Using Ab Initio Molecular Dynamics

Molten lithium tetrafluoroberyllate (Li 2 BeF 4 ) salt, also known as FLiBe, with a 2:1 mixture of LiF and BeF 2 is being proposed as a coolant and solvent in advanced nuclear reactor designs, such as the molten salt reactor or the fluoride salt cooled high-temperature reactor. We present the results on the structure and properties of FLiBe over a wide range of temperatures, 0–2000 K, from high-throughput ab initio molecular dynamics simulation using a supercell model of 504 atoms. The variations in the local structures of solid and liquid FLiBe with temperature are discussed in terms of a pair distribution function, coordination number, and bond angle distribution. The temperature-dependent electronic structure and optical and mechanical properties of FLiBe are calculated. The optical and mechanical property results are reported for the first time. The results above and below the melting temperature (~732 K) are compared with the experimental data and with data for crystalline FLiBe. The electronic structure and interatomic bonding results are discussed in correlation with the mechanical strength. A novel concept of total bond order density (TBOD), an important quantum mechanical parameter, is used to characterize the internal cohesion and strength in the simulated models. The results show a variation in the rate of change in properties in solid and liquid phases with anomalous behavior across the melting region. The observed trend is the decrease in mechanical strength, band gap, and TBOD in a nonlinear fashion as a function of temperature. The refractive index shows a surprising minimum at 850 K, among the tested temperatures, which lies above the melting point. These findings provide a new platform to understand the interplay between the temperature-dependent structures and properties of FLiBe salt.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Novel fold of rotavirus glycan-binding domain predicted by AlphaFold2 and determined by X-ray crystallography

The VP8* domain of spike protein VP4 in group A and C rotaviruses, which cause epidemic gastroenteritis in children, exhibits a conserved galectin-like fold for recognizing glycans during cell entry. In group B rotavirus, which causes significant diarrheal outbreaks in adults, the VP8* domain (VP8*B) surprisingly lacks sequence similarity with VP8* of group A or group C rotavirus. Here, by using the recently developed AlphaFold2 for ab initio structure prediction and validating the predicted model by determining a 1.3-Å crystal structure, we show that VP8*B exhibits a novel fold distinct from the galectin fold. This fold with a β-sheet clasping an α-helix represents a new fold for glycan recognition based on glycan array screening, which shows that VP8*B recognizes glycans containing N-acetyllactosamine moiety. Although uncommon, our study illustrates how evolution can incorporate structurally distinct folds with similar functionality in a homologous protein within the same virus genus.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The mechanism for acetate formation in electrochemical CO (2) reduction on Cu: selectivity with potential, pH, and nanostructuring

Nanostructured Cu catalysts have increased the selectivities and geometric activities for high value C–C coupled (C 2 ) products (ethylene, ethanol, and acetate) in the electrochemical CO (2) reduction reaction (CO (2) RR). The selectivity among the high-value C 2 products is also altered, where for instance the yield of acetate increases with alkalinity and is dependent on the catalyst morphology. The reaction mechanisms behind the selectivity towards acetate vs. other C 2 products remain controversial. In this work, we elucidate the reaction mechanism for acetate formation by using ab initio simulations, a coupled kinetic-transport model, and loading dependent experiments. We find that trends in acetate selectivity can be rationalized from variations in electrolyte pH and the local mass transport properties of the catalyst and not from changes in Cu's intrinsic activity. The selectivity mechanism originates from the transport of ketene, a stable (closed shell) intermediate, away from the catalyst surface into solution where it reacts to form acetate. While this type of mechanism has not yet been discussed in the CO (2) RR, variants of it may explain similar selectivity fluctuations observed for other stable intermediates like CO and acetaldehyde. Our proposed mechanism suggests that acetate selectivity increases with increasing pH, decreasing catalyst roughness and significantly varies with the applied potential.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Multi-level parallelization of quantum-chemical calculations

Here, strategies for multiple-level parallelizations of quantum-mechanical calculations are discussed, with an emphasis on using groups of workers for performing parallel tasks. These parallel programming models can be used for a variety ab initio quantum chemistry approaches, including the fragment molecular orbital method and replica-exchange molecular dynamics. Strategies for efficient load balancing on problems of increasing granularity are introduced and discussed. A four-level parallelization is developed based on a multi-level hierarchical grouping, and a high parallel efficiency is achieved on the Theta supercomputer using 131 072 OpenMP threads.

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

Chemical information from XPS: Theory and experiment for Ni(OH) 2

For this work, the features and the electronic character of the states for the Ni 2p x-ray photoelectron spectroscopy (XPS) of Ni(OH) 2 were analyzed. This detailed analysis is based on ab initio molecular orbital wavefunctions for a cluster model of Ni(OH) 2 . The theory is validated by comparison with experiment. Then, advanced methods are used to explain and contrast the properties of different groups of ionic states. An important conclusion is that in most cases, the ionic states cannot be described with a single configuration or determinant. Despite this essential many-body character of the XPS, we demonstrate that it is possible to understand the origin of the main and satellite XPS features in terms of their orbital character.

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

Designing a quantum-accurate machine-learning potential to enable large-scale simulations of deuterium under shock

Large-scale molecular dynamics of deuterium under shock can elucidate kinetic processes vital to the target design in inertial confinement fusion and high-energy-density experiments. However, modeling the complex evolution of this material from an insulating molecular state at ambient pressure to an ionized, atomic fluid under strong shock is beyond the capability of simple pair and even bond order potentials. We thus train a quantum-accurate and broadly transferable machine-learning interatomic potential for deuterium using the Chebyshev Interaction Model for Efficient Simulations framework. We show that due to an improved description of the molecular-to-atomic transition, our model is able to better reproduce the ab initio equation of state, radial distribution functions, and principal Hugoniot than bond order potentials. This represents an important step toward large-scale quantum-accurate and nonequilibrium simulations of complicated systems under dynamic changes including phase transitions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Unification of finite symmetries in the simulation of many-body systems on quantum computers

Symmetry is fundamental in the description and simulation of quantum systems. Leveraging symmetries in classical simulations of many-body quantum systems can result in significant overhead due to the exponentially growing size of some symmetry groups as the number of particles increases. Quantum computers hold the promise of achieving exponential speedup in simulating quantum many-body systems; however, a general method for utilizing symmetries in quantum simulations has not yet been established. In this work, we present a unified framework for incorporating symmetry group transforms on quantum computers to simulate many-body systems. The core of our approach lies in the development of efficient quantum circuits for symmetry-adapted projection onto irreducible representations of a group or pairs of commuting groups. We provide resource estimations for common groups, including the cyclic and permutation groups. Our algorithms demonstrate the capability to prepare coherent superpositions of symmetry-adapted states and to perform quantum evolution across a wide range of models in condensed-matter physics and ab initio electronic structure in quantum chemistry. Specifically, we execute a symmetry-adapted quantum subroutine for small molecules in first-quantization on noisy hardware and demonstrate the emulation of symmetry-adapted quantum phase estimation for preparing coherent superpositions of quantum states in various irreducible representations of a symmetry group. In addition, we present a discussion of open problems regarding treating symmetries in digital quantum simulations of many-body systems, paving the way for future systematic investigations into leveraging symmetries quantumly for practical quantum advantage. The broad applicability and rigorous resource estimation for symmetry transformations make our framework appealing for achieving provable quantum advantage on fault-tolerant quantum computers, especially for symmetry-related properties.

quantum algorithms↗
DOE OSTI2020

Direct time-domain determination of electron-phonon coupling strengths in chromium

In this work, we report the results of an ultrafast, direct structural measurement of optically pumped phonons in a Cr thin film using ultrashort x-ray pulses from a free-electron laser. In addition to measuring and confirming the known long-wavelength dispersion relation of Cr along a particular acoustic branch, we are able to determine the relative phase of the phonons as they are generated. The Cr sample exhibits two generation mechanisms for the phonons: the releasing of a preexisting charge density wave at higher frequencies, and the creation of an acoustic strain pulse via laser heating that dominates at lower frequencies. Furthermore, for the latter mechanism, we are able to measure the frequency dependence of the time required to generate the phonons. To explain the observed magnitude and slope of the delays, we perform first-principles simulations in the framework of density functional perturbation theory and ab initio molecular dynamics to fit anharmonic phonon models. In conclusion, these results show that the wave-vector dependence of the electron-phonon coupling is the driving mechanism behind the delay times: Phase-space limitation leads to higher times near the zone center. The absolute magnitudes of the delay times measured are found to be much shorter than the equilibrium electron-phonon coupling times we compute, indicating that the coupling strength is greatly enhanced when the electronic system is out of equilibrium with the lattice, as has been seen in bismuth and other systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

TwoFold: Highly accurate structure and affinity prediction for protein-ligand complexes from sequences

We describe our development of ab initio protein-ligand binding pose prediction models based on transformers and binding affinity prediction models based on the neural tangent kernel (NTK). Folding both protein and ligand, the TwoFold models achieve efficient and quality predictions matching state-of-the-art implementations while additionally reconstructing protein structures. In conclusion, solving NTK models points to a new use case for highly optimized linear solver benchmarking codes on HPC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Halo Nuclei from Ab Initio Nuclear Theory

A realistic description of halo nuclei, characterized by low-lying breakup thresholds, requires a proper treatment of continuum effects. We have developed an ab initio approach, the No-Core Shell Model with Continuum (NCSMC), capable of describing both bound and unbound states in light nuclei in a unified way. With chiral two- and three-nucleon interactions as the only input, we can predict the structure and dynamics of halo and other light nuclei and, by comparing to available experimental data, test the quality of chiral nuclear forces. We review NCSMC calculations of weakly bound states and resonances of the exotic halo nuclei 6He, 8B, 11Be, and 15C. For the latter, we discuss its production in the capture reaction 14C(n,𝛾 )15C. We highlight the challenges of a description of 6He as a Borromean n-n-4He system. Finally, we present our calculations of excited states in 10Be exhibiting a one-neutron halo structure and a large scale No-Core Shell Model investigation of 11Li as a precursor of a full n-n-9Li NCSMC study.

Navrátil, Petr↗