Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “electronic structure methods”

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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Benchmarking Quantum Chemistry Computations with Variational, Imaginary Time Evolution, and Krylov Space Solver Algorithms

Quantum chemistry is a key application area for noisy-intermediate scale quantum (NISQ) devices, and therefore serves as an important benchmark for current and future quantum computer performance. Previous benchmarks in this field have focused on variational methods for computing ground and excited states of various molecules, including a benchmarking suite focused on the performance of computing ground states for alkali-hydrides under an array of error mitigation methods. State-of-the-art methods to reach chemical accuracy in hybrid quantum-classical electronic structure calculations of alkali hydride molecules on NISQ devices from IBM are outlined here. Here it is demonstrated how to extend the reach of variational eigensolvers with symmetry preserving Ansätze. Next, it is outlined how to use quantum imaginary time evolution and Lanczos as a complementary method to variational techniques, highlighting the advantages of each approach. Finally, a new error mitigation method is demonstrated which uses systematic error cancellation via hidden inverse gate constructions, improving the performance of typical variational algorithms. These results show that electronic structure calculations have advanced rapidly, to routine chemical accuracy for simple molecules, from their inception on quantum computers a few short years ago, and they point to further rapid progress to larger molecules as the power of NISQ devices grows.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Electron doping of NdNiO 3 thin films using dual chamber CaH 2 annealing

Hydrogen donor doping has been exploited as a strategy to manipulate the electronic structure and electrical properties of functional oxide systems. Especially, the development of synthetic methods to achieve electron doping of perovskite rare-earth nickelate thin films utilizing interstitial hydrogen is highly desirable considering the rich electronic phase diagram hosting several functional properties. Here, in this work, we present the hydrogenation of NdNiO 3 (NNO) thin films using CaH 2 annealing and the resulting giant modulation of electrical resistivity in hydrogenated NNO (H–NNO) thin films. Magnetron sputtering was employed to deposit epitaxial ~60 nm-thin NNO films on single crystal LaAlO 3 (LAO) substrates. The formation of the pristine perovskite NNO phase was realized after annealing the films at 500 °C for 24 h. CaH 2 annealing of NNO thin films for time durations ranging from 1 to 6 h was performed in a vacuumed ampule with two interconnected chambers at 280 °C. The two-chamber design enables a simple and clean approach for hydrogen doping without physical contact between the powder and sample of interest. X-ray diffraction and Raman spectroscopy revealed the formation of NNO in pristine samples, and the subsequent hydrogen incorporation upon CaH 2 annealing without forming any impurity phases. The conversion of the oxidation state of Ni towards +2 upon CaH 2 annealing was probed using X-ray photoelectron spectroscopy and X-ray absorption spectroscopy. Consequently, a substantial increase in the room-temperature resistivity was observed upon CaH 2 annealing indicating the formation of a strongly correlated electronic configuration of Ni in H–NNO due to electron doping. Overall, the findings of this study highlight the versatility of CaH 2 annealing as an electron doping method to tune the electrical properties of correlated oxides at low temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Relativistic Exact Two-Component Theory in the Generalized Pseudospectral Representation

We present a formulation and implementation of exact two-component (X2C) relativistic theory in the generalized pseudospectral representation. When combined with the Hartree-Fock-Slater framework, this approach enables efficient and accurate treatments of scalar-relativistic and spin-orbit effects in atomic electronic structures without the computational overhead of four-component methods. Benchmark calculations across light and heavy elements demonstrate that the our X2C scheme yields substantially more accurate relativistic corrections to core-electron binding energies than perturbational Breit-Pauli treatments while converging more rapidly with respect to basis size. The method provides an improved computational framework for modeling ultrafast x-ray-induced processes in heavy-element systems.

Wang, Xubo↗
DOE OSTI2025

Quick-and-Easy Validation of Protein–Ligand Binding Models Using Fragment-Based Semiempirical Quantum Chemistry

Electronic structure calculations in enzymes converge very slowly with respect to the size of the model region that is described using quantum mechanics (QM), requiring hundreds of atoms to obtain converged results and exhibiting substantial sensitivity (at least in smaller models) to which amino acids are included in the QM region. As such, there is considerable interest in developing automated procedures to construct a QM model region based on well-defined criteria. However, testing such procedures is burdensome due to the cost of large-scale electronic structure calculations. Here, we show that semiempirical methods can be used as alternatives to density functional theory (DFT) to assess convergence in sequences of models generated by various automated protocols. The cost of these convergence tests is reduced even further by means of a many-body expansion. We use this approach to examine convergence (with respect to model size) of protein–ligand binding energies. Fragment-based semiempirical calculations afford well-converged interaction energies in a tiny fraction of the cost required for DFT calculations. Two-body interactions between the ligand and single-residue amino acid fragments afford a low-cost way to construct a “QM-informed” enzyme model of reduced size, furnishing an automatable active-site model-building procedure. This provides a streamlined, user-friendly approach for constructing ligand binding-site models that needs neither a priori information nor manual adjustments. Extension to model-building for thermochemical calculations should be straightforward.

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

Semi-supervised Machine Learning Enables the Robust Detection of Multireference Character at Low Cost

Multireference (MR) diagnostics are common tools for identifying strongly correlated electronic structure that makes single-reference (SR) methods (e.g., density functional theory or DFT) insufficient for accurate property prediction. However, MR diagnostics typically require computationally demanding correlated wave function theory (WFT) calculations, and diagnostics often disagree or fail to predict MR effects on properties. To overcome these challenges, we introduce a semi-supervised machine learning (ML) approach with virtual adversarial training (VAT) of an MR classifier using 15 WFT and DFT MR diagnostics as inputs. In semi-supervised learning, only the most extreme SR or MR points are labeled, and the remaining point labels are learned. The resulting VAT model outperforms the alternatives, as quantified by the distinct property distributions of SR- and MR-classified molecules. Additionally, to reduce the cost of generating inputs to the VAT model, we leverage the VAT model’s robustness to noisy inputs by replacing WFT MR diagnostics with regression predictions in an MR decision engine workflow that preserves excellent performance. We demonstrate the transferability of our approach to larger molecules and those with distinct chemical composition from the training set. This MR decision engine demonstrates promise as a low-cost, high-accuracy approach to the automatic detection of strong correlation for predictive high-throughput screening.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Data-Driven Refinement of Electronic Energies from Two-Electron Reduced-Density-Matrix Theory

The exponential computational cost of describing strongly correlated electrons can be mitigated by adopting a reduced-density-matrix (RDM)-based description of the electronic structure. While variational two-electron RDM (v2RDM) methods can enable large-scale calculations on such systems, the quality of the solution is limited by the fact that only a subset of known necessary N-representability constraints can be applied to the 2RDM in practical calculations. Here, we demonstrate that violations of partial three-particle (T1 and T2) N-representability conditions, which can be evaluated with knowledge of only the 2RDM, can serve as physics-based features in a machine-learning (ML) protocol for improving energies from v2RDM calculations that consider only two-particle (PQG) conditions. Proof-of-principle calculations demonstrate that the model yields substantially improved energies, relative to reference values from configuration-interaction-based calculations.

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

A Uranium(II) Arene Complex That Acts as a Uranium(I) Synthon

We report two-electron reduction of the amidate-supported U(III) mono(arene) complex U(TDA) 3 (2) with KC 8 yields the anionic bis(arene) complex [K[2.2.2]cryptand][U(TDA) 2 ] (3) (TDA = N-(2,6-di-isopropylphenyl)pivalamido). EPR spectroscopy, magnetic susceptibility measurements, and calculations using DFT as well as multireference CASSCF methods all provide strong evidence that the electronic structure of 3 is best represented as a 5f 4 U(II) metal center bound to a monoreduced arene ligand. Reactivity studies show 3 reacts as a U(I) synthon by behaving as a two-electron reductant toward I 2 to form the dinuclear U(III)–U(III) triiodide species [K[2.2.2]cryptand][(UI(TDA) 2 ) 2 (μ-I)] (6) and as a three-electron reductant toward cycloheptatriene (CHT) to form the U(IV) complex [K[2.2.2]cryptand][U(η 7 -C 7 H 7 )(TDA) 2 (THF)] (7). The reaction of 3 with cyclooctatetraene (COT) generates a mixture of the U(III) anion [K[2.2.2]cryptand][U(TDA) 4 ] (1-crypt) and U(COT) 2 , while the addition of COT to complex 2 instead yields the dinuclear U(IV)–U(IV) inverse sandwich complex [U(TDA) 3 ] 2 (μ-η 8 :η 3 -C 8 H 8 ) (8). Two-electron reduction of the homoleptic Th(IV) amidate complex Th(TDA) 4 (4) with KC 8 gives the mono(arene) complex [K[2.2.2]cryptand][Th(TDA) 3 (THF)] (5). The C–C bond lengths and torsion angles in the bound arene of 5 suggest a direduced arene bound to a Th(IV) metal center; this conclusion is supported by DFT calculations.

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

Printed assemblies of ultrathin, microscale inorganic light emitting diodes for deformable and semitransparent displays

Described herein are printable structures and methods for making, assembling and arranging electronic devices. A number of the methods described herein are useful for assembling electronic devices where one or more device components are embedded in a polymer which is patterned during the embedding process with trenches for electrical interconnects between device components. Some methods described herein are useful for assembling electronic devices by printing methods, such as by dry transfer contact printing methods. Also described herein are GaN light emitting diodes and methods for making and arranging GaN light emitting diodes, for example for display or lighting systems.

42 ENGINEERING↗
DOE OSTI2021

Exploring Charged Defects in Ferroelectrics by the Switching Spectroscopy Piezoresponse Force Microscopy

Monitoring the charged defect concentration at the nanoscale is of critical importance for both the fundamental science and applications of ferroelectrics. However, up-to-date, high-resolution study methods for the investigation of structural defects, such as transmission electron microscopy, X-ray tomography, etc., are expensive and demand complicated sample preparation. Here, with an example of the lanthanum-doped bismuth ferrite ceramics, a novel method is proposed based on the switching spectroscopy piezoresponse force microscopy (SSPFM) that allows probing the electric potential from buried subsurface charged defects in the ferroelectric materials with a nanometer-scale spatial resolution. When compared with the composition-sensitive methods, such as neutron diffraction, X-ray photoelectron spectroscopy, and local time-of-flight secondary ion mass spectrometry, the SSPFM sensitivity to the variation of the electric potential from the charged defects is shown to be equivalent to less than 0.3 at% of the defect concentration. Additionally, the possibility to locally evaluate dynamics of the polarization screening caused by the charged defects is demonstrated, which is of significant interest for further understanding defect-mediated processes in ferroelectrics.

42 ENGINEERING↗
DOE OSTI2022

Coarse-Grained Simulations for the Characterization and Optimization of Hybrid Protein–DNA Nanostructures

We present here the combination of experimental and computational modeling tools for the design and characterization of protein–DNA hybrid nanostructures. Our work incorporates several features in the design of these nanostructures: (1) modeling of the protein–DNA linker identity and length; (2) optimizing the design of protein–DNA cages to account for mechanical stresses; (3) probing the incorporation efficiency of protein–DNA conjugates into DNA nanostructures. The modeling tools were experimentally validated using structural characterization methods like cryo-TEM and AFM. Our method can be used for fitting low-resolution electron density maps when structural insights cannot be deciphered from experiments, as well as enable in-silico validation of nanostructured systems before their experimental realization. Finally, these tools will facilitate the design of complex hybrid protein–DNA nanostructures that seamlessly integrate the two different biomolecules.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Correlating Nb-SRF Surface Processing with Evolution of Surface Electronic States

The few nanometers of the surface exposed to RF field plays a major role in defining the RF performance of superconducting cavities. Over the past two decades, several pioneering surface treatment and processing methods have emerged, enabling remarkable improvements in cavity performance by simultaneously achieving high Q with increasing Eacc. These processing methods include: thermal treatment under ultra-high vacuum (UHV) conditions across lo¬¬¬¬¬¬¬w-, mid-, and high-temperature ranges and high temperature treatments under controlled N2 atmosphere. These processes also produce distinct surface oxide configurations with different valence states, thicknesses, and uniformity, as well as different oxygen concentration profiles in bulk Nb. In this work, we are trying to understand how do surface-processing methods and the resulting oxide/oxygen profiles affect the electronic structure of surface and the mechanism of superconductivity? With the help of Fermilab’s in-house X-ray photoemission facility and, in collaboration with the synchrotron-based angle-resolved photoemission (ARPES) facility at Argonne National Laboratory, we are investigating how the valence band structure and density of states (DoS) near the Fermi level modify with different surface treatments. Our observations show that different surface-processing methods lead to distinct evolutions of the valence-band states near the Fermi level during the superconducting transition. This behavior suggests variations in Nb-O orbital hybridizations and points towards the possibility of different underlying mechanisms of superconductivity governed by the surface chemistry and oxide configuration. We also correlate these distinct superconducting mechanisms with RF cavity performance, specifically focusing on measured surface resistance, the nature of the Q-slope, and quench fields observed in SRF measurements. These results will enable us to identify the potential limiting factors and relevant controllable parameters that can be further optimized to improve the performance of SRF cavities.

Tripathi, Malvika [Fermilab]↗
DOE OSTI2021

Cryo-EM structure determination of small proteins by nanobody-binding scaffolds (Legobodies)

We describe a general method that allows structure determination of small proteins by single-particle cryo-electron microscopy (cryo-EM). The method is based on the availability of a target-binding nanobody, which is then rigidly attached to two scaffolds: 1) a Fab fragment of an antibody directed against the nanobody and 2) a nanobody-binding protein A fragment fused to maltose binding protein and Fab-binding domains. The overall ensemble of ~120 kDa, called Legobody, does not perturb the nanobody–target interaction, is easily recognizable in EM images due to its unique shape, and facilitates particle alignment in cryo-EM image processing. The utility of the method is demonstrated for the KDEL receptor, a 23-kDa membrane protein, resulting in a map at 3.2-Å overall resolution with density sufficient for de novo model building, and for the 22-kDa receptor-binding domain (RBD) of SARS-CoV-2 spike protein, resulting in a map at 3.6-Å resolution that allows analysis of the binding interface to the nanobody. The Legobody approach thus overcomes the current size limitations of cryo-EM analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Atom-in-jellium predictions of the shear modulus at high pressure

Atom-in-jellium calculations of the Einstein frequency in condensed matter and of the equation of state were used to predict the variation of shear modulus from zero pressure to ~10 7 g/cm 3 , for several elements relevant to white dwarf stars and other self-gravitating systems. This is by far the widest range reported electronic structure calculation of shear modulus, spanning from ambient through the one-component plasma to extreme relativistic conditions. The predictions were based on a relationship between the Debye temperature and shear modulus, which we assess to be accurate at the o(10%) level, and is the first known use of atom-in-jellium theory to calculate a shear modulus. Finally, we assessed the overall accuracy of the method by comparing with experimental measurements and more detailed electronic structure calculations at lower pressures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

AlphaFold -assisted structure determination of a bacterial protein of unknown function using X-ray and electron crystallography

Macromolecular crystallography generally requires the recovery of missing phase information from diffraction data to reconstruct an electron-density map of the crystallized molecule. Most recent structures have been solved using molecular replacement as a phasing method, requiring an a priori structure that is closely related to the target protein to serve as a search model; when no such search model exists, molecular replacement is not possible. New advances in computational machine-learning methods, however, have resulted in major advances in protein structure predictions from sequence information. Methods that generate predicted structural models of sufficient accuracy provide a powerful approach to molecular replacement. Taking advantage of these advances, AlphaFold predictions were applied to enable structure determination of a bacterial protein of unknown function (UniProtKB Q63NT7, NCBI locus BPSS0212) based on diffraction data that had evaded phasing attempts using MIR and anomalous scattering methods. Using both X-ray and micro-electron (microED) diffraction data, it was possible to solve the structure of the main fragment of the protein using a predicted model of that domain as a starting point. The use of predicted structural models importantly expands the promise of electron diffraction, where structure determination relies critically on molecular replacement.

molecular replacement↗
DOE OSTI2025

Nanoscale Structure and Interfacial Electrochemical Reactivity of Moiré-Engineered Atomic Layers

Here, the electronic properties of atomically thin van der Waals (vdW) materials can be precisely manipulated by vertically stacking them with a controlled offset (for example, a rotational offset─i.e., twist─between the layers, or a small difference in lattice constant) to generate moiré superlattices. In recent years, the application of this “twistronics” concept to interfacial electrochemistry has unveiled unique pathways for tailoring the electrochemical reactivity. Furthermore, this Account provides an overview of our work that leveraged a suite of structural characterization methods, such as interferometric four-dimensional scanning transmission electron microscopy, dark-field transmission electron microscopy, and scanning tunneling microscopy, along with nanoscale electrochemical measurement techniques, namely, scanning electrochemical cell microscopy (SECCM), to uncover and dissect the profound impact of electrode electronic structure, controlled by interlayer twist, on interfacial electron transfer kinetics.

Charge transfer↗
DOE OSTI2022

Simulations of x-ray absorption spectra for CO desorbing from Ru(0001) with transition-potential and time-dependent density functional theory approaches

The desorption of a carbon monoxide molecule from a Ru(0001) surface was studied by means of X-ray Absorption Spectra (XAS) computed with Transition Potential (TP-DFT) and Time Dependent (TD-DFT) DFT methods. By unraveling the evolution of the CO electronic structure upon desorption, we observed that at 2.3 Å from the surface, the CO molecule has already predominantly gas-phase character. While C 1s XAS is quite insensitive to changes in the C–O bond length, the O 1s excitation is very sensitive with the π* coming down in energy upon CO bond stretching, which competes with the increase in orbital energy due to the repulsive interaction with the metallic surface. We show in a systematic way that the TP-DFT method can describe the XAS rather well at the endpoints (chemisorbed and gas phase) but is affected by artificial charge transfer and/or incorrect spin treatment in the transition region in cases like CO, where there are low-lying π* orbitals and large exchange interactions between the core 1s and valence-acceptor π* orbitals. As an alternative, we demonstrate by comparing with experimental data that a linear response approach using TD-DFT employing common exchange-correlation functionals and finite-size clusters can yield a good description of the spectral evolution of the 1s → π* transition with correct spin and gas-to-chemisorbed chemical shifts in good agreement with experiment.

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

Evolution of standardization and dissemination of cryo-EM structures and data jointly by the community, PDB, and EMDB

Cryogenic electron microscopy (cryo-EM) methods began to be used in the mid-1970s to study thin and periodic arrays of proteins. Following a half-century of development in cryo-specimen preparation, instrumentation, data collection, data processing and modeling software, cryo-EM has become a routine method for solving structures from large biological assemblies to small biomolecules at near to true atomic resolution. This review explores the critical roles played by the Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDB) in partnership with the community to develop the necessary infrastructure to archive cryo-EM maps and associated models. Public access to cryo-EM structure data has in turn facilitated better understanding of structure-function relationships and advancement of image processing and modeling tool development. The partnership between the global cryo-EM community and PDB and EMDB leadership has synergistically shaped the standards for metadata, one-stop deposition of maps and models, and validation metrics to assess the quality of cryo-EM structures. The advent of cryo-electron tomography (cryo-ET) for in situ molecular cell structures at a broad resolution range and their correlations with other imaging data introduces new data archival challenges in terms of data size and complexity in the years to come.

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

Ground State Energy Functional with Hartree–Fock Efficiency and Chemical Accuracy

We introduce the deep post Hartree–Fock (DeePHF) method, a machine learning-based scheme for constructing accurate and transferable models for the ground-state energy of electronic structure problems. DeePHF predicts the energy difference between results of highly accurate models such as the coupled cluster method and low accuracy models such as the Hartree–Fock (HF) method, using the ground-state electronic orbitals as the input. It preserves all the symmetries of the original high accuracy model. The added computational cost is less than that of the reference HF or DFT and scales linearly with respect to system size. We examine the performance of DeePHF on organic molecular systems using publicly available data sets and obtain the state-of-art performance, particularly on large data sets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗