Search NASA⌕ Search

SEARCH · Search NASA

Results for “Electronic Structure Calculations”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Spin dynamics in the itinerant antiferromagnet SrCr 2 ⁢As 2

SrCr 2 ⁢As 2 is an itinerant antiferromagnet in the same structural family as the SrFe 2 ⁢As 2 high-temperature superconductors. Here, we report our calculations of exchange-coupling parameters 𝐽 𝑖⁢𝑗 for SrCr 2 ⁢As 2 using a static linear-response method based on first-principles electronic-structure calculations. We find that the dominant nearest-neighbor exchange coupling 𝐽 1 >0 is antiferromagnetic whereas the next-nearest-neighbor exchange coupling 𝐽 2 <0 is ferromagnetic with 𝐽 2 /𝐽 1 = −0.68, reinforcing the checkerboard in-plane magnetic structure. Thus, unlike other transition-metal arsenides based on Mn, Fe, or Co, we find no competing magnetic interactions in SrCr 2 ⁢As 2 , which aligns with experimental findings. Moreover, the orbital resolution of exchange interactions shows that 𝐽 1 and 𝐽 2 are dominated by direct exchange mediated by the Cr 𝑑 orbitals. To validate the calculations we conduct inelastic neutron-scattering measurements on powder samples that show steeply dispersive magnetic excitations arising from the magnetic Γ points and persisting up to energies of at least 175 meV. The spin-wave spectra are then modeled using the Heisenberg Hamiltonian with the theoretically calculated exchange couplings. In conclusion, the calculated neutron-scattering spectra are in good agreement with the experimental data.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Pilgrim : A thermal rate constant calculator and a chemical kinetics simulator

Pilgrim is a program written in Python and designed to use direct dynamics in the calculation of thermal rate constants of chemical reactions by the variational transition state theory (VTST), based on electronic structure calculations for the potential energy surface. Pilgrim can also simulate reaction mechanisms using kinetic Monte Carlo (KMC). For reaction processes with many elementary steps, the rate constant of each of these steps can be calculated by means of conventional transition state theory (TST) or by using VTST. In the current version, Pilgrim can evaluate thermal rates using the canonical version of reaction-path VTST, which requires the calculation of the minimum energy path (MEP) associated with each elementary step or transition structure. Multi-dimensional quantum effects can be incorporated through the small-curvature tunneling (SCT) approximation. These methodologies are available both for reactions involving a single structure of the reactants and the transition state and also for reactions involving flexible molecules with multiple conformations of the reactant and/or of the transition state. For systems with many conformers, the program can evaluate each of the elementary reaction rate constants by multipath canonical VTST or multi-structural VTST. Moreover, the reactant can be unimolecular or bimolecular. Torsional anharmonicity can be incorporated through either the MSTor or the Q2DTor programs. Dual-level calculations are also available in Pilgrim: automatic high-level single-point energies can be used to correct the energy of reactants, transition states, products, and MEP points using the interpolated single-point energies (ISPE) algorithm. When the rate constants of all the chemical processes of interest are known, by means of their calculation using Pilgrim or alternatively through analytical fits to the rate constants as functions of temperature, it is possible to simulate a multistep mechanism under specified laboratory conditions using KMC. Finally, this algorithm allows performing a kinetic simulation to monitor the evolution of each chemical species with time and obtain the product yields.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Antiferromagnetic Order and Linear Magnetoresistance in Fe-Substituted Shandite Co 3 In 2 S 2

Co 3 In 2 S 2 is a shandite phase closely related to the ferromagnetic Weyl semimetal Co 3 Sn 2 S 2 and contains Co atoms on an ideal kagome net. Elemental substitutions in Co 3 Sn 2 S 2 have been shown to invariably suppress its magnetism, and it remains a rare example of a shandite phase with magnetic order. Here, we report a new magnetic shandite compound discovered by substituting Fe into Co 3 In 2 S 2 . Single crystals of (Co 1–x Fe x ) 3 In 2 S 2 were grown, and neutron diffraction, ac and dc magnetization, and heat capacity measurements reveal long-range antiferromagnetic order with an interesting noncollinear structure and transition temperatures from 11 to 17 K. Partially substituting Fe for Co was inspired by calculated electronic structures, which suggest that Co 3 In 2 S 2 is near a magnetic instability and shows a peak in the density of states that can be approached by hole doping. While the focus of the present work is primarily on magnetism, there is a nodal ring below the Fermi energy in Co 3 In 2 S 2 that may also provide interest from a topological perspective. Potentially related to this, we find large, linear, nonsaturating magnetoresistance in this compound. Furthermore, this work expands the scope of magnetic topological materials among shandites and motivates similar chemical manipulation studies to reveal hidden magnetic instabilities in this important family and other topological systems.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Machine learning dielectric screening for the simulation of excited state properties of molecules and materials

Accurate and efficient calculations of absorption spectra of molecules and materials are essential for the understanding and rational design of broad classes of systems. Solving the Bethe–Salpeter equation (BSE) for electron–hole pairs usually yields accurate predictions of absorption spectra, but it is computationally expensive, especially if thermal averages of spectra computed for multiple configurations are required. We present a method based on machine learning to evaluate a key quantity entering the definition of absorption spectra: the dielectric screening. We show that our approach yields a model for the screening that is transferable between multiple configurations sampled during first principles molecular dynamics simulations; hence it leads to a substantial improvement in the efficiency of calculations of finite temperature spectra. We obtained computational gains of one to two orders of magnitude for systems with 50 to 500 atoms, including liquids, solids, nanostructures, and solid/liquid interfaces. Importantly, the models of dielectric screening derived here may be used not only in the solution of the BSE but also in developing functionals for time-dependent density functional theory (TDDFT) calculations of homogeneous and heterogeneous systems. Overall, our work provides a strategy to combine machine learning with electronic structure calculations to accelerate first principles simulations of excited-state properties.

36 MATERIALS SCIENCE↗
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

Machine learning Frenkel Hamiltonian parameters to accelerate simulations of exciton dynamics

In this manuscript, we develop multiple machine learning (ML) models to accelerate a scheme for parameterizing site-based models of exciton dynamics from all-atom configurations of condensed phase sexithiophene systems. This scheme encodes the details of a system’s specific molecular morphology in the correlated distributions of model parameters through the analysis of many single-molecule excited-state electronic-structure calculations. These calculations yield excitation energies for each molecule in the system and the network of pair-wise intermolecular electronic couplings. In this work, we demonstrate that the excitation energies can be accurately predicted using a kernel ridge regression (KRR) model with Coulomb matrix featurization. We present two ML models for predicting intermolecular couplings. The first one utilizes a deep neural network and bi-molecular featurization to predict the coupling directly, which we find to perform poorly. The second one utilizes a KRR model to predict unimolecular transition densities, which can subsequently be analyzed to compute the coupling. We find that the latter approach performs excellently, indicating that an effective, generalizable strategy for predicting simple bimolecular properties is through the indirect application of ML to predict higher-order unimolecular properties. Such an approach necessitates a much smaller feature space and can incorporate the insight of well-established molecular physics.

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

Using Molecular Structure to Tune Intrachain and Interchain Charge Transport in Indacenodithiophene-Based Copolymers

Here, in this work, we compare two structurally near-amorphous rigid-rod polymers-poly(indacenodithiophene-co-benzothiadiazole), p(IDT-BT), and poly(indacenodithiophene-co-benzopyrollodione), p(IDT-BPD)-with orders of magnitude different mobilities to understand the effect charge carrier intrachain delocalization has on electronic transport. Quantum chemical calculations show that p(IDT-BPD) has a barrier to torsion that is significantly lower than that of p(IDT-BT) and is thus more likely to have reduced conjugation lengths. We utilize absorption and photoluminescence spectroscopy to characterize energetic disorder and show that p(IDT-BPD) has higher energetic disorder. Charge modulation spectroscopy (CMS) and model calculations are used to show that charge carriers are substantially delocalized in p(IDT-BT) and occupy near-uniform energetic environments. We find that mobility activated hopping barriers are similar in these two materials. Electronic structure calculations show that both intrachain and interchain couplings of monomer units are poor enough in p(IDT-BPD) that charge carriers collapse to single IDT units and transport via a through-space tunneling mechanism. This work highlights the remarkable charge transport properties of p(IDT-BT) by showing that high mobilities are achievable on device-relevant length scales with only 1D carrier delocalization.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Harnessing the power of ab initio calculations, distributed computing and machine learning to efficiently locate extreme molecules for use in carbon-based solar cells (Final Technical Report)

The use of high-throughput virtual screening (HTVS) tools is a powerful tool to expedite the materials discovery of commercially relevant materials. In previous years, our group has developed a molecular discovery platform to generate libraries in order to obtain suitable candidates for different applications, starting from the Harvard Clean Energy Project. This platform is suitable to test in-silico on traditional supercomputing clusters and shared resources, for example, in the IBM World Community Grid. In this project, we used the molecular discovery platform to create and screen a library of candidates of organic photovoltaic (OPVs) molecules. Based on a set of candidates created with combinations of molecular moieties, we were able to filter, by conformation stability, the energy of electronic orbitals and approximated power conversion efficiencies (PCE). To improve the predictions of orbital energies calculated and the PCEs, we used Gaussian Process regression and two sets of molecules. These sets correspond to electronic structure calculations of a higher level of theory and experimental PCE values, respectively. Finally, we selected a subset of the best candidates (molecules with a PCE higher than 10%) to understand its absorbance properties with TD-DFT. This project has demonstrated the capabilities of our molecular discovery platform for HTVS. Finally, machine learning can help us to introduce more complex effects included in bulk conditions and computational intensive calculations on models.

14 SOLAR ENERGY↗
DOE OSTI2021

Mechanisms of O 2 Activation by Mononuclear Non-Heme Iron Enzymes

We report two major subclasses of mononuclear non-heme ferrous enzymes use two electron-donating organic cofactors (α-ketoglutarate or pterin) to activate O2 to form Fe IV =O intermediates that further react with their substrates through hydrogen atom abstraction or electrophilic aromatic substitution. New spectroscopic methodologies have been developed, enabling the study of the active sites in these enzymes and their oxygen intermediates. Coupled to electronic structure calculations, the results of these spectroscopies provide fundamental insight into mechanism. This Perspective summarizes the results of these studies in elucidating the mechanism of dioxygen activation to form the Fe IV =O intermediate and the geometric and electronic structure of this intermediate that enables its high reactivity and selectivity in product formation.

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

OH Roaming during the Ozonolysis of α-Pinene: A New Route to Highly Oxygenated Molecules?

The formation of low-volatility organic compounds in the ozonolysis of α-pinene, the dominant atmospheric monoterpene, provides an important route to aerosol formation. Here, in this work, we consider a previously unexplored set of pathways for the formation of highly oxygenated molecules in α-pinene ozonolysis. Pioneering, direct experimental observations of Lester and co-workers have demonstrated a significant production of hydroxycarbonyl products in the dissociation of Criegee intermediates. Theoretical analyses indicate that this production arises from OH roaming-induced pathways during the OO fission of the vinylhydroperoxides (VHPs), which in turn come from internal H transfers in the Criegee intermediates. Ab initio kinetics computations are used here to explore the OH roaming-induced channels that arise from the ozonolysis of α-pinene. For computational reasons, the calculations consider a surrogate for α-pinene, where two spectator methyl groups are replaced with H atoms. Multireference electronic structure calculations are used to illustrate a variety of energetically accessible OH roaming pathways for the four VHPs arising from the ozonolysis of this α-pinene surrogate. Ab initio transition-state theory-based master equation calculations indicate that for the dissociation of stabilized VHPs, these OH roaming pathways are kinetically significant with a branching that generally increases from ~20% at room temperature up to ~70% at lower temperatures representative of the troposphere. For one of the VHPs, this branching already exceeds 60% at room temperature. For the overall ozonolysis process, these branching ratios would be greatly reduced by a limited branching to the stabilized VHP, although there would also be some modest roaming fraction for the nonthermal VHP dissociation process. The strong exothermicities of the roaming-induced isomerizations/additions and abstractions suggest new routes to fission of the cyclobutane rings. Such ring fissions would facilitate further autoxidation reactions, thereby providing a new route for producing highly oxygenated nonvolatile precursors to aerosol formation.

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

Soft and transferable pseudopotentials from multi-objective optimization

Ab initio pseudopotentials are a linchpin of modern molecular and condensed matter electronic structure calculations. In this work, we employ multi-objective optimization to maximize pseudopotential softness while maintaining high accuracy and transferability. To accomplish this, we develop a formulation in which softness and accuracy are simultaneously maximized, with accuracy determined by the ability to reproduce all-electron energy differences between Bravais lattice structures, whereupon the resulting Pareto frontier is scanned for the softest pseudopotential that provides the desired accuracy in established transferability tests. We employ an evolutionary algorithm to solve the multi-objective optimization problem and apply it to generate a comprehensive table of optimized norm-conserving Vanderbilt (ONCV) pseudopotentials (https://github.com/SPARC-X/SPMS-psps). Here, we show that the resulting table is softer than existing tables of comparable accuracy, while more accurate than tables of comparable softness. The potentials thus afford the possibility to speed up calculations in a broad range of applications areas while maintaining high accuracy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Giant Magnetic and Optical Anisotropy in Cerium-Substituted M-Type Strontium Hexaferrite Driven by $4f$ Electrons

By performing density-functional calculations, we find a giant magnetocrystalline anisotropy (MCA) constant in abundant element cerium $\mathrm{Ce}$ substituted M-type hexaferrite, in the energetically favorable strontium site, assisted by a quantum confined electron transfer from $\mathrm{Ce}$ to a specific iron $\mathrm{2a}$ site. Remarkably, the calculated electronic structure shows that the electron transfer leads to the formation of $\mathrm{Ce}^{3+}$ and $\mathrm{Fe}^{2+}$ at the $\mathrm{2a}$ site producing an occupied $\mathrm{Ce}$$(4f^1)$ state below the Fermi level that adds a significant contribution to MCA and magnetic moment. A half $\mathrm{Ce}$ substitution forms a metallic state, while a full substitution retains the semiconducting state of the strontium hexaferrite (host). In the latter, the band gap is reduced due to the formation of charge-transferred states in the gap region of the host. The optical absorption coefficient shows an enhanced anisotropy between light polarization in parallel and perpendicular directions. Calculated formation energies, including the analysis of probable competing phases, and elastic constants confirm that both compositions are chemically and mechanically stable. With successful synthesis, the $\mathrm{Ce}$ hexaferrite can be an alternative high-performing critical-element-free permanent magnet material adapted for use in devices such as automotive traction drive motors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

The solution structures and relative stability constants of lanthanide–EDTA complexes predicted from computation

Ligand selectivity to specific lanthanide (Ln) ions is key to the separation of rare earth elements from each other. Ligand selectivity can be quantified with relative stability constants (measured experimentally) or relative binding energies (calculated computationally). The relative stability constants of EDTA (ethylenediaminetetraacetic acid) with La 3+ , Eu 3+ , Gd 3+ , and Lu 3+ were predicted from relative binding energies, which were quantified using electronic structure calculations with relativistic effects and based on the molecular structures of Ln–EDTA complexes in solution from density functional theory molecular dynamics simulations. The protonation state of an EDTA amine group was varied to study pH ~7 and ~11 conditions. Further, simulations at 25 °C and 90 °C were performed to elucidate how structures of Ln–EDTA complexes varying with temperature are related to complex stabilities at different pH conditions. Relative stability trends are predicted from computation for varying Ln 3+ ions (La, Eu, Gd, Lu) with a single ligand (EDTA at pH ~11), as well as for a single Ln 3+ ion (La) with varying ligands (EDTA at pH ~7 and ~11). Changing the protonation state of an EDTA amine site significantly changes the solution structure of the Ln–EDTA complex resulting in a reduction of the complex stability. As a result, increased Ln–ligand complex stability is correlated to reduced structural variations in solution upon an increase in temperature.

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

Ab initio molecular dynamics on quantum computers

Ab initio molecular dynamics (AIMD) is a valuable technique for studying molecules and materials at finite temperatures where the nuclei evolve on potential energy surfaces obtained from accurate electronic structure calculations. In this work, we present an approach to running AIMD simulations on noisy intermediate-scale quantum (NISQ)-era quantum computers. The electronic energies are calculated on a quantum computer using the variational quantum eigensolver (VQE) method. Algorithms for computation of analytical gradients entirely on a quantum computer require quantum fault-tolerant hardware, which is beyond NISQ-era. Therefore, we compute the energy gradients numerically using finite differences, the Hellmann-Feynman theorem, and a correlated sampling technique. This method only requires additional classical calculations of electron integrals for each degree of freedom without any additional computations on a quantum computer beyond the initial VQE run. As a proof of concept, AIMD simulations are demonstrated for the H-2 molecule on IBM quantum devices. In addition, we demonstrate the validity of the method for larger molecules using full configuration interaction wave functions. As quantum hardware and noise mitigation techniques continue to improve, the method can be utilized for studying larger molecular systems.

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

High-throughput ab initio reaction mechanism exploration in the cloud with automated multi-reference validation

Quantum chemical calculations on atomistic systems have evolved into a standard approach to studying molecular matter. These calculations often involve a significant amount of manual input and expertise, although most of this effort could be automated, which would alleviate the need for expertise in software and hardware accessibility. Here, we present the AutoRXN workflow, an automated workflow for exploratory high-throughput electronic structure calculations of molecular systems, in which (i) density functional theory methods are exploited to deliver minimum and transition-state structures and corresponding energies and properties, (ii) coupled cluster calculations are then launched for optimized structures to provide more accurate energy and property estimates, and (iii) multi-reference diagnostics are evaluated to back check the coupled cluster results and subject them to automated multi-configurational calculations for potential multi-configurational cases. All calculations are carried out in a cloud environment and support massive computational campaigns. Key features of all components of the AutoRXN workflow are autonomy, stability, and minimum operator interference. We highlight the AutoRXN workflow with the example of an autonomous reaction mechanism exploration of the mode of action of a homogeneous catalyst for the asymmetric reduction of ketones.

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

TeraChem: A graphical processing unit-accelerated electronic structure package for large-scale ab initio molecular dynamics

TeraChem was born in 2008 with the goal of providing fast on-the-fly electronic structure calculations to facilitate ab initio molecular dynamics studies of large biochemical systems such as photoswitchable proteins and multichromophoric antenna complexes. Originally developed for videogaming applications, graphics processing units (GPUs) offered a low-cost parallel computer architecture that became more accessible for general-purpose GPU computing with the release of CUDA in 2007. The evaluation of the electron repulsion integrals (ERIs) is a major bottleneck in electronic structure codes and provides an attractive target for acceleration on GPUs. Thus, highly efficient routines for evaluation of and contractions between the ERIs and density matrices were implemented in TeraChem. Here, electronic structure methods were developed and implemented to leverage these integral contraction routines, resulting in the first quantum chemistry package designed from the ground up for GPUs. This GPU acceleration makes TeraChem capable of performing large-scale ground and excited state calculations in the gas and condensed phase. Today, TeraChem's speed forms the basis for a suite of quantum chemistry applications, including optimization and dynamics of proteins, automated and interactive chemical discovery tools, and large-scale nonadiabatic dynamics simulations.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Engineering Electrical Conductivity in Stable Zirconium-Based PCN-222 MOFs with Permanent Mesoporosity

Electrically conductive metal–organic frameworks (MOFs) featuring zirconium-based nodes are of great interest for electrochemical and optoelectronic applications due to their exceptional thermal and chemical stability, although the number of such MOFs remains limited. Here in this paper, we demonstrate that electron deficient molecules such as transition metal(IV) bis(dicarbollide) (TM IV (C 2 B 9 H 11 ) 2 ; TM IV CB for short, where TM = Ni, Pd, and Pt) or C 60 , spatially infiltrated in the microporous channels of the zirconium-based porphyrinic MOFs PCN-222 and PCN-222-Zn, generate highly stable and electrically conductive frameworks in which the mesopores remain accessible to other guests. Solid-state density functional theory (DFT) and ab initio molecular dynamics (AIMD) simulations indicate incorporation of Ni IV CB and C 60 in the MOF micropores is energetically and structurally feasible. Interestingly, in contrast to the free species, strong donor–acceptor interactions between the MOF and Ni IV CB restrain it to a single conformation. Calculated electronic structures and charge-hopping conduction probabilities illustrate that efficient charge-transfer (CT) from photoexcited linkers to the guest molecules facilitates charge hopping in the framework, making the MOFs electrically conductive. The donor–acceptor conjugates also enhance exciton dissociation at their heterojunctions, fostering the formation of long-lived electron-trapped states with potential utility for photo- and electrochemical devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗