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At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Spectral-partitioned Kohn-Sham density functional theory

Here we introduce a general, variational scheme for systematic approximation of a given Kohn-Sham free-energy functional by partitioning the density matrix into distinct spectral domains, each of which may be spanned by an independent diagonal representation without requirement of mutual orthogonality. It is shown that by generalizing the entropic contribution to the free energy to allow for independent representations in each spectral domain, the free energy becomes an upper bound to the exact (unpartitioned) Kohn-Sham free energy, attaining this limit as the representations approach Kohn-Sham eigenfunctions. A numerical procedure is devised for calculation of the generalized entropy associated with spectral partitioning of the density matrix. The result is a powerful framework for Kohn-Sham calculations of systems whose occupied subspaces span multiple energy regimes. As a case in point, we apply the proposed framework to warm- and hot-dense matter described by finite-temperature density functional theory, where at high energies the density matrix is represented by that of the free-electron gas, while at low energies it is variationally optimized. We derive expressions for the spectral-partitioned Kohn-Sham Hamiltonian, atomic forces, and macroscopic stresses within the projector-augmented wave (PAW) and the norm-conserving pseudopotential methods. It is demonstrated that at high temperatures, spectral partitioning facilitates accurate calculations at dramatically reduced computational cost. Moreover, as temperature is increased, fewer exact Kohn-Sham states are required for a given accuracy, leading to further reductions in computational cost. Finally, it is shown that standard multiprojector expansions of electronic orbitals within atomic spheres in the PAW method lack sufficient completeness at high temperatures. Spectral partitioning provides a systematic solution for this fundamental problem.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Metals and Quantum Materials with Spin-orbit Interactions by Quantum Monte Carlo methods

The key goals of this project were as follows: 1) Analysis and benchmarks of electron correlation effects recovered in the fixed-node approximation that is inherent to quantum Monte Carlo (QMC) method as applied to metallic states; 2) development of new algorithms for electron spin-degrees of freedom to be treated as explicit quantum variables; 3) designing electronic structure QMC algorithm for efficient evaluation of spin-orbit effects in systems with heavy atoms; 4) adapting the algorithm to complex wave functions and developing corresponding fixed-phase approximation; 5) design and testing of algorithm for valence-only non-local spin-orbit operators; 6) analysis of fixed-node vs fixed-phase errors and their comparisons. The key accomplishments: i) We carried out a systematic study of Li systems by the fixed-node diffusion Monte Carlo method. This involved Li atom, molecule, cluster and solid calculated by the full range of QMC methods including fixed-node QMC.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Thermal Performance of Triply Periodic Minimal Surface Lattice Structures in Single-Phase Dielectric Fluid Cooling of Power Electronics

Additive manufacturing has transformed thermal management by enabling the production of complex, optimized geometries that conventional manufacturing methods cannot achieve. This study investigates the single-phase convective heat transfer performance of gyroid triply periodic minimal surface (TPMS) lattice structures with functional porosity. TPMS structures provide high surface area to volume ratios and are amenable to 3D printing. A gyroid numerical model was created and validated against an existing experimental study with a similar feature size to the investigated geometries. The TPMS structure has a periodic width of 1.6 mm, a length of 10 mm, and a height of 4 mm, with a functional porosity ranging from 0.5 to 0.8, decreasing with distance from the heated surface. Three different flow configurations were examined for an inlet fluid temperature of 70 °C. The inlet velocities range from 0.01 to 1.2 m/s, corresponding to a Reynolds number range of 10–900 with a heat flux of 50 W/cm 2 applied at the base. AmpCool ® AC-110 dielectric fluid (Prandtl number 59.5) was used as the coolant. Thermal performance and friction characteristics were studied for the three flow orientations. The parallel flow configuration was identified as the most efficient for heat removal. A detailed analysis of the numerical results highlights the underlying physics behind the thermal performance differences among the flow configurations.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Uniaxial stress effect on the electronic structure of quantum materials

Uniaxial stress has proven to be a powerful experimental tuning parameter for effectively controlling lattice, charge, orbital, and spin degrees of freedom in quantum materials. In addition, its ability to manipulate the symmetry of materials has garnered significant attention. Recent technical progress to combine uniaxial stress cells with quantum oscillation and angle-resolved photoemission techniques allowed to study the electronic structure as function of uniaxial stress. This review provides an overview on experimental advancements in methods and examines studies on diverse quantum materials, encompassing the semimetal WTe 2 , the unconventional superconductor Sr 2 RuO 4 , Fe-based superconductors, and topological materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Two-Component Multireference Restricted Active Space Configuration Interaction for the Computation of L-Edge X-ray Absorption Spectra

X-ray absorption spectroscopy is a powerful probe of local electronic and nuclear structure, providing insights into chemical processes. The theoretical prediction and interpretation of metal L-edge X-ray absorption spectra is complicated by both relativistic effects, including spin-orbit coupling, and by the multiconfigurational nature of the states involved. This work details an exact two-component multireference restricted active space configuration interaction (X2C-MRRASCI) scheme that uses an exact two-component state average complete active space self-consistent-field method (X2C-SA-CASSCF), which includes the spin-orbit coupling in a variational manner, for the accurate description of the electronic structure before using a restricted active space configuration interaction method to describe the core excited states of the X-ray spectrum. Benchmark calculations are presented for a series of iron containing complexes, with results showing key features of the spectrum being reproduced, including ligand to metal charge transfer and shake-up excitations.

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

Evolution of the Electronic Gap of Directly Synthesized Versus Mechanically Transferred WS 2 Monolayer to Multilayer Films

The electronic properties of 2D materials play a critical role in determining their potential for device applications. Despite rapid developments in 2D semiconductors, studies of fundamental electronic parameters, including the electronic gap and ionization energy, are limited, with significant discrepancies in reported values. The study focuses on tungsten disulfide (WS₂) and investigates the electronic structure of films comprising an increasing number of layers deposited with two different methods: direct synthesis via metal–organic chemical vapor deposition (MOCVD) and additive mechanical transfer of exfoliated single layers. The films are characterized via Raman, UV–vis, and photoluminescence spectroscopies, as well as ultraviolet photoelectron and inverse photoemission spectroscopies (UPS/IPES). The electronic gap of WS₂ is found to decrease from 2.43 eV for the monolayer to 1.97 eV for the trilayer, indicating a bulk transition at the trilayer thickness. This reduction in the electronic gap is primarily due to the downward shift of the conduction band minimum relative to the valence band maximum. A comparative analysis with MOCVD-grown WS₂ reveals a slightly larger electronic gap for MOCVD-grown samples, attributed to differences in defect densities. The electronic levels evaluated through UPS/IPES highlight the significant influence of preparation methods on the electronic properties of WS₂.

2D materials↗
DOE OSTI2025

Stabilization of [(N 5 ) 2 BX] 2– and [(N 5 ) 2 B 2 X 2 ] 2– (X = H, F, Cl, Br) by Conjugation and Hyperconjugation Effects

The isolation of nucleophilic boron bases has led to a paradigm shift in boron chemistry. Previous studies of the bis(carbene) borylene complexes revealed that these compounds possess strong donor abilities, and their reaction inertness is due to the large steric hindrance between boron reagents and reactant. In the present study, we have theoretically studied the [(N 5 ) 2 BX] 2– and [(N 5 ) 2 B 2 X 2 ] 2– compounds (X = H, F, Cl, Br). Their electronic structures and properties are discussed by using the NBO, LOL, and ELF methods. We found that both π-conjugation and hyperconjugation effects can effectively stabilize the substituted nucleophilic anionic boron compounds [(N 5 ) 2 BX] 2– and [(N 5 ) 2 B 2 X 2 ] 2– . Substituents, especially X = H, stabilize the boron center through highly delocalized π-bonding, involving the formally “empty” in-plane p orbitals of the boron atom. While the halogen substituents have high electron withdrawal ability, leading to systems being less stable, we suggest the borinium anions [(N 5 ) 2 BH] 2– and [(N 5 ) 2 B 2 H 2 ] 2– as possible synthetic targets of novel environmentally friendly catalysts.

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

Denoising atomic resolution 4D scanning transmission electron microscopy data with tensor singular value decomposition

Tensor singular value decomposition (SVD) is a method to find a low-dimensional representation of data with meaningful structure in three or more dimensions. Here, tensor SVD has been applied to denoise atomic-resolution 4D scanning transmission electron microscopy (4D STEM) data. On data simulated from a SrTiO 3 [100] perfect crystal and a Si [110] edge dislocation, tensor SVD achieved an average peak signal-to-noise ratio (PSNR) of ~40 dB, which matches or exceeds the performance of other denoising methods, with processing times at least 100 times shorter. On experimental data from SrTiO 3 [100] and LiZnSb [11 2 ¯ 0]/GaSb [110] samples, tensor SVD denoises multiple GB 4D STEM data sets in ten minutes on a typical personal computer. Denoising with tensor SVD improves both convergent beam electron diffraction patterns and virtual-aperture annular dark field images.

36 MATERIALS SCIENCE↗
DOE OSTI2024

ComDMFT v.2.0: Fully self-consistent ab initio GW+EDMFT for the electronic structure of correlated quantum materials

ComDMFT is a parallel computational package designed to study the electronic structure of correlated quantum materials from first principles. Our approach is based on the combination of first-principles methods and dynamical mean field theories. In version 2.0, we implemented fully-diagrammatic GW+EDMFT from first-principles self-consistently. In this approach, correlated electrons are treated within full GW+EDMFT and the rest are treated within full-GW, seamlessly. Further, this implementation enables the electronic structure calculation of quantum materials with weak, intermediate, and strong electron correlation without prior knowledge of the degree of electron correlation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Predicting solid state material platforms for quantum technologies

Semiconductor materials provide a compelling platform for quantum technologies (QT). However, identifying promising material hosts among the plethora of candidates is a major challenge. Therefore, we have developed a framework for the automated discovery of semiconductor platforms for QT using material informatics and machine learning methods. Different approaches were implemented to label data for training the supervised machine learning (ML) algorithms logistic regression, decision trees, random forests and gradient boosting. We find that an empirical approach relying exclusively on findings from the literature yields a clear separation between predicted suitable and unsuitable candidates. In contrast to expectations from the literature focusing on band gap and ionic character as important properties for QT compatibility, the ML methods highlight features related to symmetry and crystal structure, including bond length, orientation and radial distribution, as influential when predicting a material as suitable for QT.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Interpretable, extensible linear and symbolic regression models for charge density prediction using a hierarchy of many-body correlation descriptors

Here, density functional theory (DFT) is routinely used to make electronic structure predictions for high-throughput screening of materials and molecules for technologically relevant areas, like the identification of better catalysts, electronic materials, and drug discovery. However, the DFT formalism is limited by (a) its poor (quadratic-to-quartic) scaling, and (b) the need to perform repeated eigenvalue computations of the electronic Hamiltonian as part of its self-consistent field (SCF) iteration procedure to obtain the converged ground state electron density, ρ (r). Approaches that directly predict ρ (r) of a structure with high accuracy can accelerate conventional SCF calculations and can also be used in linearly scaling methods such as orbital-free DFT. To this end, we present a procedure to predict the ground state electron density of molecular and periodic three-dimensional systems directly from the atomic structure with a particular emphasis on physical interpretability. In our framework, ρ (r) is modeled using many-body correlation descriptors that accurately capture the effects of local atomic arrangements in the neighborhood of a grid point. Our use of a linear regression scheme to fit to charge density data enables transparent analysis of the relative contributions of various types of local atomic correlations. By systematically including increasingly complex correlations, our model is shown to accurately predict ρ (r) for a variety of chemically and electronically diverse systems — amorphous Ge, Al(001) slab, crystalline Ga 2 O 3 , molecular benzene, and polyethylene. We then demonstrate a symbolic regression-based protocol to construct easily computable, interpretable features from lower-order correlations that significantly improves our electron density predictions with effectively no increase in the computational cost.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Recent Developments in the General Atomic and Molecular Electronic Structure System

A discussion of many of the recently implemented features of GAMESS (General Atomic and Molecular Electronic Structure System) and LibCChem (the C++ CPU/GPU library associated with GAMESS) is presented. These features include fragmentation methods like the fragment molecular orbital, effective fragment potential and effective fragment molecular orbital methods, hybrid MPI/OpenMP approaches to Hartree-Fock and resolution of the identity second order perturbation theory. Many new coupled cluster theory methods have been implemented in GAMESS, as have multiple levels of density functional/tight binding theory. The role of accelerators, especially graphical processing units, is discussed in the context of the new features of LibCChem, as is the associated problem of power consumption as the power of computers increases dramatically. The process by which a complex program suite like GAMESS is maintained and developed is considered. Future developments are briefly summarized.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Predicting Elastic Properties of Materials from Electronic Charge Density Using 3D Deep Convolutional Neural Networks

Materials representation plays a key role in machine learning-based prediction of materials properties and new materials discovery. Currently both graph and three-dimensional (3D) voxel representation methods are based on the heterogeneous elements of the crystal structures. Here, we propose to use electronic charge density (ECD) as a generic unified 3D descriptor for materials property prediction with the advantage of possessing close relation with the physical and chemical properties of materials. We developed an ECD-based 3D convolutional neural networks (CNNs) for predicting the elastic properties of materials, in which CNNs can learn effective hierarchical features with multiple convolving and pooling operations. Extensive benchmark experiments over 2170 $Fm\bar3m$ face-centered-cubic materials show that our ECD-based CNNs can achieve good performance for elasticity prediction. Especially, our CNN models based on the fusion of elemental Materials-Agnostic Platform for Informatics and Exploration features and ECD descriptors achieved the best fivefold cross-validation performance. More importantly, we showed that our ECD-based CNN models can achieve significantly better extrapolation performance when evaluated over nonredundant data sets, where there are few neighbor-training samples around test samples. As an additional validation, we evaluated the predictive performance of our models on 329 materials of space group $Fm\bar3m$ by comparing to density functional theory calculated values, which shows a better prediction power of our model for bulk modulus than shear modulus. Because of the unified representation power of ECD, it is expected that our ECD-based CNN approach can also be applied to predict other physical and chemical properties of crystalline materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Single-molecule 3D imaging of HIV cellular entry by liquid-phase electron tomography

Enveloped viruses, including human immunodeficiency virus (HIV) and SARS-CoV-2, target cells through membrane fusion process. The detailed understanding of the process is sought after for vaccine development but remains elusive due to current technique limitations for direct three-dimensional (3D) imaging of an individual virus during its viral entry. Recently, we developed a simple specimen preparation method for real-time imaging of metal dynamic liquid-vaper interface at nanometer resolution by transmission electron microscopy (TEM). Here, we extended this method to study biology sample through snapshot 3D structure of a single HIV (pseudo-typed with the envelope glycoprotein of vesicular stomatitis virus, VSV-G) at its intermediate stage of viral entry to HeLa cells in a liquid-phase environment. By individual-particle electron tomography (IPET), we found the viral surface release excess lipids with unbound viral spike proteins forming ~50-nm nanoparticles instead of merging cell membrane. Moreover, the spherical-shape shell formed by matrix proteins underneath the viral envelope does not disassemble into a cone shape right after fusion. Further, the snapshot 3D imaging of a single virus provides us a direct structure-based understanding of the viral entry mechanism, which can be used to examine other viruses to support the development of vaccines combatting the current ongoing pandemic.

Kong, Lingli↗
DOE OSTI2025

Ultrafast Correlation Energy Estimator

A virtually no-cost method is proposed that can compute the correlation energies of general, covalently bonded, organic, and inorganic molecules (including conjugated π-electron systems) with a well-defined dominant Lewis structure at the accuracy of 99.5% of the near-exact values determined by the coupled-cluster singles, doubles, and perturbative triples [CCSD(T)] in the complete-basis-set (CBS) limit. This Correlation Energy Per Bond (CEPB) method assigns a partial correlation energy to each bond type (characterized by the identities of the two atoms forming the bond and its integer bond order) and to a lone pair, regardless of the bond length, bond angle, sp-hybridization, π-electron conjugation, ionicity, noncovalent interactions, etc. At its current stage, the method is mainly suitable for near-equilibrium geometries. The correlation energies per bond are determined by a fit to the CCSD(T)/CBS benchmarks. It can neither improve the equilibrium structures nor discern conformers or positional isomers, yet its accuracy for reaction energies rivals that of the second-order Møller–Plesset perturbation theory, which is far more expensive. Its promising performance underscores the possibility that surprisingly compact, chemically intuitive molecular fragments exist into which correlation energies can be partitioned, leading to various ultrafast correlation-energy estimators tailored to different purposes.

Binding energy↗