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At least 1,477 records · Page 82

Electronic structure of strongly correlated systems: recent developments in multiconfiguration pair-density functional theory and multiconfiguration nonclassical-energy functional theory

Strong electron correlation plays an important role in transition-metal and heavy-metal chemistry, magnetic molecules, bond breaking, biradicals, excited states, and many functional materials, but it provides a significant challenge for modern electronic structure theory. The treatment of strongly correlated systems usually requires a multireference method to adequately describe spin densities and near-degeneracy correlation. However, quantitative computation of dynamic correlation with multireference wave functions is often difficult or impractical. Multiconfiguration pair-density functional theory (MC-PDFT) provides a way to blend multiconfiguration wave function theory and density functional theory to quantitatively treat both near-degeneracy correlation and dynamic correlation in strongly correlated systems; it is more affordable than multireference perturbation theory, multireference configuration interaction, or multireference coupled cluster theory and more accurate for many properties than Kohn–Sham density functional theory. This perspective article provides a brief introduction to strongly correlated systems and previously reviewed progress on MC-PDFT followed by a discussion of several recent developments and applications of MC-PDFT and related methods, including localized-active-space MC-PDFT, generalized active-space MC-PDFT, density-matrix-renormalization-group MC-PDFT, hybrid MC-PDFT, multistate MC-PDFT, spin–orbit coupling, analytic gradients, and dipole moments. We also review the more recently introduced multiconfiguration nonclassical-energy functional theory (MC-NEFT), which is like MC-PDFT but allows for other ingredients in the nonclassical-energy functional. We discuss two new kinds of MC-NEFT methods, namely multiconfiguration density coherence functional theory and machine-learned functionals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The LQR/LTR procedure for multivariable feedback control design

This paper provides a tutorial overview of the linear quadratic Gaussian with loop transfer recovery (LQG/LTR) design procedure for linear multivariable feedback systems. LQR/LTR is interpreted as the solution of a specific weighted H-squared tradeoff between transfer functions in the frequency domain. Properties of this solution are examined for both minimum-phase and nonminimum-phase systems. This leads to a formal weight augmentation procedure for the minimum-phase case which permits essentially arbitrary specification of system sensitivity functions in terms of the weights. While such arbitrary specifications are not possible for nonminimum-phase problems, a direct relationship between weights and sensitivities is developed for nonminimum-phase SISO and certain nonminimum-phase MIMO cases which guides the weight selection process.

Stein, Gunter↗

Renormalization and scale evolution of the soft-quark soft function

Soft functions defined in terms of matrix elements of soft fields dressed by Wilson lines are central components of factorization theorems for cross sections and decay rates in collider and heavy-quark physics. While in many cases the relevant soft functions are defined in terms of gluon operators, at subleading order in power counting soft functions containing quark fields appear. We present a detailed discussion of the properties of the soft-quark soft function consisting of a quark propagator dressed by two finite-length Wilson lines connecting at one point. This function enters in the factorization theorem for the Higgs-boson decay amplitude of the h → γγ process mediated by light-quark loops. We perform the renormalization of this soft function at one-loop order, present a conjecture for its two-loop anomalous dimension and discuss solutions to its renormalization-group evolution equation in momentum space, in Laplace space and in the “diagonal space”, where the evolution is strictly local in the momentum variable.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Unconventional pressure-induced magnetic transitions and mechanical properties in non-magnetic LaFeSi

Here, this work demonstrates that two consecutive magnetic transitions occur in non-magnetic LaFeSi compound under negative hydrostatic pressure (small volume expansion). Electronic structure properties of LaFeSi were calculated using density functional theory (DFT) to understand the origin of these magnetic transitions. Mechanical properties of LaFeSi, especially elastic properties (shear and Young’s modulus, and Poisson’s ratio), were determined by DFT distortion calculations to elucidate lattice anisotropy and stability. The antiferromagnetic transition at –7.52 GPa, predicted in our work for LaFeSi, is consistent with the reported experimentally observed antiferromagnetic ground states in CeMnSi and LaMnSi compounds having similar crystal geometry. This finding of unexpected magnetic ordering predicts that layered non-magnetic materials, like LaFeSi, may become magnetically active with lattice expansion.

36 MATERIALS SCIENCE↗

Molten Salt Thermal Property Uncertainty Workshop Report

Operation of a molten salt fueled reactor is governed, more so than any other type of reactor, by the thermal properties of the molten salt fuel because it is in a liquid form. The composition of the fuel salt will evolve during use in a reactor, as fission products are generated and corrosion of structural materials release corrosion products into the salt. The recently released NUREG/CR7299 states that fuel qualification for molten salt fuels will be based upon maintaining fuel salt properties within an acceptable range that results in achievement of fundamental safety functions (NUREG/CR-7299). Understanding the dependence of fuel properties on temperature and composition across the anticipated range of operating temperatures, burn-up and anticipated levels of contamination is required to qualify molten salt fuels. Measuring aspects of salt chemistry is appropriately a major thrust of the Molten Salt Reactor (MSR) campaign under the Advanced Reactor Technology program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Secondary structure determines electron transport in peptides

Proteins play a key role in biological electron transport, but the structure–function relationships governing the electronic properties of peptides are not fully understood. Despite recent progress, understanding the link between peptide conformational flexibility, hierarchical structures, and electron transport pathways has been challenging. Here, we use single-molecule experiments, molecular dynamics (MD) simulations, nonequilibrium Green’s function-density functional theory (NEGF-DFT), and unsupervised machine learning to understand the role of secondary structure on electron transport in peptides. Our results reveal a two-state molecular conductance behavior for peptides across several different amino acid sequences. MD simulations and Gaussian mixture modeling are used to show that this two-state molecular conductance behavior arises due to the conformational flexibility of peptide backbones, with a high-conductance state arising due to a more defined secondary structure (beta turn or 3 10 helices) and a low-conductance state occurring for extended peptide structures. These results highlight the importance of helical conformations on electron transport in peptides. Conformer selection for the peptide structures is rationalized using principal component analysis of intramolecular hydrogen bonding distances along peptide backbones. Molecular conformations from MD simulations are used to model charge transport in NEGF-DFT calculations, and the results are in reasonable qualitative agreement with experiments. Projected density of states calculations and molecular orbital visualizations are further used to understand the role of amino acid side chains on transport. Overall, our results show that secondary structure plays a key role in electron transport in peptides, which provides broad avenues for understanding the electronic properties of proteins.

Science & Technology - Other Topics↗

Recent Advances in Vertically Aligned Nanocomposites with Tunable Optical Anisotropy: Fundamentals and Beyond

Developing reliable and tunable metamaterials is fundamental to next-generation optical-based nanodevices and computing schemes. In this review, an overview of recent progress made with a unique group of ceramic-based functional nanocomposites, i.e., vertically aligned nanocomposites (VANs), is presented, with the focus on the tunable anisotropic optical properties. Using a self-assembling bottom-up deposition method, the as-grown VANs present great promise in terms of structural flexibility and property tunability. Such broad tunability of functionalities is achieved through VAN designs, material selection, growth control, and strain coupling. The as-grown multi-phase VAN films also present enormous advantages, including wafer scale integration, epitaxial quality, sharp atomic interface, as well as designable materials and geometries. This review also covers the research directions with practical device potentials, such as multiplex sensing, high-temperature plasmonics, magneto-optical switching, as well as photonic circuits.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multi-reward reinforcement learning based development of inter-atomic potential models for silica

Abstract Silica is an abundant and technologically attractive material. Due to the structural complexities of silica polymorphs coupled with subtle differences in Si–O bonding characteristics, the development of accurate models to predict the structure, energetics and properties of silica polymorphs remain challenging. Current models for silica range from computationally efficient Buckingham formalisms (BKS, CHIK, Soules) to reactive (ReaxFF) and more recent machine-learned potentials that are flexible but computationally costly. Here, we introduce an improved formalism and parameterization of BKS model via a multireward reinforcement learning (RL) using an experimental training dataset. Our model concurrently captures the structure, energetics, density, equation of state, and elastic constants of quartz (equilibrium) as well as 20 other metastable silica polymorphs. We also assess its ability in capturing amorphous properties and highlight the limitations of the BKS-type functional forms in simultaneously capturing crystal and amorphous properties. We demonstrate ways to improve model flexibility and introduce a flexible formalism, machine-learned ML-BKS, that outperforms existing empirical models and is on-par with the recently developed 50 to 100 times more expensive Gaussian approximation potential (GAP) in capturing the experimental structure and properties of silica polymorphs and amorphous silica.

36 MATERIALS SCIENCE↗

PYK-SubstitutionOME: an integrated database containing allosteric coupling, ligand affinity and mutational, structural, pathological, bioinformatic and computational information about pyruvate kinase isozymes

Interpreting changes in patient genomes, understanding how viruses evolve and engineering novel protein function all depend on accurately predicting the functional outcomes that arise from amino acid substitutions. To that end, the development of first-generation prediction algorithms was guided by historic experimental datasets. However, these datasets were heavily biased toward substitutions at positions that have not changed much throughout evolution (i.e. conserved). Although newer datasets include substitutions at positions that span a range of evolutionary conservation scores, these data are largely derived from assays that agglomerate multiple aspects of function. To facilitate predictions from the foundational chemical properties of proteins, large substitution databases with biochemical characterizations of function are needed. We report here a database derived from mutational, biochemical, bioinformatic, structural, pathological and computational studies of a highly studied protein family—pyruvate kinase (PYK). A centerpiece of this database is the biochemical characterization—including quantitative evaluation of allosteric regulation—of the changes that accompany substitutions at positions that sample the full conservation range observed in the PYK family. We have used these data to facilitate critical advances in the foundational studies of allosteric regulation and protein evolution and as rigorous benchmarks for testing protein predictions. We trust that the collected dataset will be useful for the broader scientific community in the further development of prediction algorithms.

59 BASIC BIOLOGICAL SCIENCES↗

Enhanced spectral purity of WSe 2 quantum emitters via conformal organic adlayers

Quantum emitters in solid-state materials are typically embedded in the bulk of their hosts, making their electronic transitions inaccessible to surface modification. In contrast, two-dimensional materials, with their all-surface nature, offer a platform for tuning quantum emitters via chemical functionalization. Because of its semiconducting properties that enable electrical addressability, monolayer WSe 2 is a promising candidate for quantum emission, although the complex interplay between point defects and the localized strain needed to activate quantum emission leads to poor spectral purity. Here, we demonstrate that functionalizing monolayer WSe 2 with conformal adlayers of 3,4,9,10-perylenetetracarboxylic dianhydride (PTCDA) improves quantum emission spectral purity. Optical spectroscopy reveals that PTCDA functionalization lowers defect activation energies by 10 meV and induces a 30 nm redshift in quantum emission wavelength, while preserving the bright and dark exciton energies of monolayer WSe 2 . First-principles calculations corroborate these findings, thus providing molecular-level insight into the underlying mechanism of enhanced spectral purity.

Ananth, Riddhi [Northwestern Univ., Evanston, IL (↗

Insurance in the Operation of Photovoltaic Plants

This paper provides an overview of property and casualty insurance industry functions, insurance terminology descriptions, and special insurance coverage considerations for photovoltaic (PV) system owners, asset managers, operators, PV operation-and-maintenance service providers, utilities, and other parties. The paper includes the results of an analysis of 6 years of property and casualty insurance claims for PV equipment and discusses considerations for purchasing property and casualty insurance for owners and operators of PV systems. PV is a relatively new asset type, and insurance companies are revisiting rates and offerings as actuarial data become available. This paper seeks to inform decisions that optimize the balance of the cost of insurance with enabling benefits to finance, permitting, utility connections, and the operation of PV plants.

14 SOLAR ENERGY↗

Development of procedures for calculating stiffness and damping properties of elastomers. Part 3: The effects of temperature, dissipation level and geometry

Effects of temperature, dissipation level and geometry on the dynamic behavior of elastomer elements were investigated. Force displacement relationships in elastomer elements and the effects of frequency, geometry and temperature upon these relationships are reviewed. Based on this review, methods of reducing stiffness and damping data for shear and compression test elements to material properties (storage and loss moduli) and empirical geometric factors are developed and tested using previously generated experimental data. A prediction method which accounts for large amplitudes of deformation is developed on the assumption that their effect is to increase temperature through the elastomers, thereby modifying the local material properties. Various simple methods of predicting the radial stiffness of ring cartridge elements are developed and compared. Material properties were determined from the shear specimen tests as a function of frequency and temperature. Using these material properties, numerical predictions of stiffness and damping for cartridge and compression specimens were made and compared with corresponding measurements at different temperatures, with encouraging results.

Smalley, A. J.↗

Pressure-induced structural and dielectric changes in liquid water at room temperature

Understanding the pressure-dependent dielectric properties of water is crucial for a wide range of scientific and practical applications. In this study, we employ a deep neural network trained on density functional theory data to investigate the dielectric properties of liquid water at room temperature across a pressure range of 0.1–1000 MPa. We observe a nonlinear increase in the static dielectric constant ɛ 0 with increasing pressure, a trend that is qualitatively consistent with experimental observations. This increase in ɛ 0 is primarily attributed to the increase in water density under compression, which enhances collective dipole fluctuations within the hydrogen-bonding network as well as the dielectric response. Despite the increase in ɛ 0 , our results reveal a decrease in the Kirkwood correlation factor G K with increasing pressure. Furthermore, this decrease in G K is attributed to pressure-induced structural distortions in the hydrogen-bonding network, which weaken dipolar correlations by disrupting the ideal tetrahedral arrangement of water molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Minimal Experimental Bias on the Hydrogen Bond Greatly Improves Ab Initio Molecular Dynamics Simulations of Water

Experiment Directed Simulations (EDS) is a method within a class of techniques seeking to improve molecular simulations by minimally biasing the system Hamiltonian to reproduce certain experimental observables. In a previous application of EDS to ab initio molecular dynamics (AIMD) simulation based on electronic density functional theory (DFT), the AIMD simulations of water were biased to reproduce its experimentally derived solvation structure. In particular, by solely biasing the O-O pair correlation functions, other structural and dynamical properties that were not biased were improved. In this work, the hypothesis is tested that directly biasing the OH pair correlation (and hence the H-O∙∙∙H hydrogen bonding), will provide an even better improvement of DFT-based water properties in AIMD simulations. The logic behind this hypothesis is that for most electronic DFT descriptions of water the hydrogen bonding is known to be deficient due to anomalous charge transfer and over polarization in the DFT. Using recent advances to the EDS learning algorithm, we thus train a minimal bias on AIMD water that reproduces the O-H radial distribution function derived from the highly accurate MB-pol model of water. Finally, it is then confirmed that biasing the O-H pair correlation alone can lead to improved AIMD water properties, with structural and dynamical properties in even closer to experiment than the previous EDS-AIMD model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The MOOSE fluid properties module

The fluid properties module in MOOSE~\cite{lindsay2022moose} serves a variety of fluid simulation applications based on MOOSE, including the MOOSE Navier Stokes module~\cite{moose_ns}, Pronghorn~\cite{pgh}, the MOOSE thermal hydraulics module, SAM~\cite{sam}, RELAP-7~\cite{relap7}, Sockeye~\cite{sockeye}, Pronghorn-subchannel~\cite{subchannel} and the MOOSE porous flow module~\cite{porous}. These applications are used to solve coarse mesh multi-dimensional thermal-hydraulics~\cite{pgh}, 1D systems analysis~\cite{sam,relap7} in nuclear reactor analysis, heat pipe modeling~\cite{sockeye} and porous flow simulations~\cite{porous} for underground gas storage and water seepage. The use of consistent fluid properties across fluid flow applications facilitates coupled flow simulations~\cite{anl_sam_pgh,osti_1889653}. Each application has historically driven the implementation of several fluid properties, which were later extended to be compatible with other applications. The unique diversity of applications of the module, due to its presence in MOOSE, has driven its expansion to new fluids, such as advanced nuclear reactor coolants and, more recently, arbitrary functions or tables-based property definitions, as detailed in section~\ref{content}, as well as numerous thermophysical properties and variable sets, as detailed in subsection~\ref{sec:prop}. The need for different discretizations of flow equations based on the compressibility of the fluid has motivated support for both primitive (pressure- and temperature-based) and conservative (internal energy- and specific volume-based) flow variables in the module. Thermodynamic relations are used to convert between these two formulations, as needed. The module serves a dual purpose of providing fluid properties for direct use in flow simulations and facilitating the implementation of user-specific fluid properties. Contributions of new properties for existing fluids or new fluids are strongly encouraged.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Nonempirical Range-Separated Hybrid Functional with Spatially Dependent Screened Exchange

Electronic structure calculations based on density functional theory (DFT) have successfully predicted numerous ground-state properties of a variety of molecules and materials. However, exchange and correlation functionals currently used in the literature, including semilocal and hybrid functionals, are often inaccurate to describe the electronic properties of heterogeneous solids, especially systems composed of building blocks with large dielectric mismatch. Here, in this study, we present a dielectric-dependent range-separated hybrid functional, screened-exchange range-separated hybrid (SE-RSH), for the investigation of heterogeneous materials. We define a spatially dependent fraction of exact exchange inspired by the static Coulomb-hole and screened-exchange (COHSEX) approximation used in many-body perturbation theory, and we show that the proposed functional accurately predicts the electronic structure of several nonmetallic interfaces, three- and two-dimensional, pristine, and defective solids and nanoparticles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analysis of Ag/FEP Control Blanket Performance from Multiple Satellites

Published data reporting the change in solar absorptance as a function of time on orbit for certain satellites has been re-examined. The optical property change of metallized FEP as a function of total particulate radiation dose received by specific satellites has been estimated. Results tend to follow a common trend and a design curve has been constructed to estimate solar absorptance change as a function of radiation dose for metallized FEP at any altitude. Effects due to apparent contamination on several of the satellites are addressed and taken into account in determining property changes. Data from LDEF, ML-101, NavStar 1-5, NTS-2, the SCATHA experiment, and SOLRAD 11 are used as the basis of the design curve. A similar comparison is made between published atomic oxygen recession data from numerous Space Shuttle flights, a LEO experiment flown by Lockheed, and LDEF results. Variation of atomic oxygen recession rate of FEP as a function of exposure conditions is determined.

Pippin, H. G.↗