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At least 271 records · Page 15

Origin of surface and subband states at the InAs(111)A surface

The atomic structure of surfaces and interfaces plays a vital role in the electronic quality and properties of quantum devices. The interplay between the surface and confined bulk subband states in terms of their susceptibility has been investigated in relation to crystal defects on an InAs(111)A-(2×2) reconstructed surface, using low-temperature scanning tunneling microscopy and spectroscopy. We measure the two-dimensional quantized subband states arising from the confined potential imposed by downward bending of the conduction band edge. Furthermore, we show evidence of the existence of surface Bloch states within the confined bulk band gap projected on the surface spectrum which have originated from the surface reconstruction. As expected, larger confined bulk band gaps at the surface and conduction band offset are measured to be 0.58 and 0.31 eV, respectively. Here we further show the scattering of these quantum states at different surface defects and demonstrate that surface states are more susceptible to the defect potential when compared with the corresponding subband states. This apparent contrast follows from the length scale at which these defect potentials actively interact on or near the surface. Our observed experimental results are supported by empirical tight-binding simulations for the subband states and first-principles density functional theory simulations for the surface states present on the surface.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

High Performance Parallel Methods for Space Weather Simulations

This is the final report of our NASA AISRP grant entitled 'High Performance Parallel Methods for Space Weather Simulations'. The main thrust of the proposal was to achieve significant progress towards new high-performance methods which would greatly accelerate global MHD simulations and eventually make it possible to develop first-principles based space weather simulations which run much faster than real time. We are pleased to report that with the help of this award we made major progress in this direction and developed the first parallel implicit global MHD code with adaptive mesh refinement. The main limitation of all earlier global space physics MHD codes was the explicit time stepping algorithm. Explicit time steps are limited by the Courant-Friedrichs-Lewy (CFL) condition, which essentially ensures that no information travels more than a cell size during a time step. This condition represents a non-linear penalty for highly resolved calculations, since finer grid resolution (and consequently smaller computational cells) not only results in more computational cells, but also in smaller time steps.

Hunter, Paul↗

First-Principles Approach to Extracting Chemical Information from X-ray Absorption Near-Edge Spectra of Ga-Containing Materials

The X-ray absorption near-edge structure (XANES) can provide uniquely detailed information on the coordination environments of important Ga-containing materials with unknown structures, including catalytically active materials. In this work, the Ga K-edge XANES was simulated using first-principles-based methods for seven molecular Ga complexes as well β-Ga 2 O 3 , in order to explore the chemical origins of the experimentally observed features. The theoretical spectra were computed using FEFF, CASTEP, and StoBe, to assess the sensitivity of the results to the computational approach. While the XANES features depend on the Ga coordination environment, they are also sensitive to the electronegativity of the ligands and the symmetry at Ga. The white line position responds to changes in both the core state (due to differential screening) and the valence “p” states (arising from differences in ligand coordination).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational Fermi Level Engineering and Doping-Type Conversion of Ga2O3 Via Three-Step Processing

Ga2O3 is being actively explored for power electronics, deep-ultraviolet optoelectronics, and other applications due to its ultra-wide bandgap and low projected fabrication cost of large-size and high-quality crystals. N-type doping of Ga2O3 can be achieved and tuned, but p-type doping faces fundamental obstacles due to deep character of acceptor levels and polaron transport of resulting holes. However, successful engineering of Ga2O3 based devices requires critical control of doping density, Fermi level position, and free carrier concentration, providing opportunities for predictive process simulation. We use first-principles defect theory and defect equilibrium calculations to simulate a 3-step growth-annealing-quench protocol for hydrogen assisted Mg doping in Ga2O3, taking into account the hydrogen-oxygen-water gas phase equilibrium. We predict type conversion to a net p-type regime following O-rich annealing after growth under reducing conditions in the presence of H2. This process is similar to the Mg acceptor activation by H removal in GaN. We show that there is an optimal temperature that maximizes the net acceptor density during the equilibrium annealing step for a given Mg doping level. Quenching of non-equilibrium annealed samples then results in a Fermi level EF below mid-gap down to about EV +1.5 eV, creating a significant number of uncompensated neutral MgGa0 acceptors. The resulting free hole concentration in quenched samples is very low (109 – 1012 cm-3) due to deep energy level of these Mg acceptors, but this type converted Ga2O3 material can create a significant built-in field in a p-n junction with an adjoining n-type material. Additionally, the electron concentration is greatly suppressed in such acceptor-doped Ga2O3, which could enable the use as a current blocking layer to fabricate normally-off (enhancement-mode) vertical Ga2O3 based metal-oxide-semiconductor field effect transistors (MOSFETs), and as a guard ring for edge termination in MOSFETs and Schottky barrier diodes (SBDs) with increased breakdown voltage.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS,M↗

Early Career: First-Principles Tools for Nonadiabatic Attosecond Dynamics in Materials

The overarching goal of this project was to develop computer tools for predicting how electrons move in molecules and solids at the attosecond (billionth-of-a-billionth of a second) time scale, during and after interaction with intense and/or high energy laser light. An associated goal was to also determine how X-ray spectroscopy could be used as a probe of these dynamics. The project resulted in multiple methodology developments that allow for these processes to be simulated from first-principles, most notably the use of small bulk-mimicking clusters to model solids and fixes for a deficiency in a commonly used method (time-dependent density functional theory). Additionally, the simulations showed that X-ray absorption peaks can be directly related to the electron density above the absorbing atom, and can thus be used as an intuitive probe of "where the electrons are" at a given time in the system. Collectively, these tools and results expected to be valuable for predicting and interpreting future attosecond experiments, especially for X-ray pump/probe studies at free-electron laser facilities.

74 ATOMIC AND MOLECULAR PHYSICS↗

Density Functional Tight-Binding Models for Band Structures of Transition-Metal Alloys and Surfaces across the d -Block

First-principles electronic structure simulations are an invaluable tool for understanding chemical bonding and reactions. While machine-learning models such as interatomic potentials significantly accelerate the exploration of potential energy surfaces, electronic structure information is generally lost. Particularly in the field of heterogeneous catalysis, simulated electron band structures provide fundamental insights into catalytic reactivity. This ab initio knowledge is preserved in semiempirical methods such as density functional tight binding (DFTB), which extend the accessible computational length and time scales beyond first-principles approaches. In this paper here we present Shell-Optimized Atomic Confinement (SOAC) DFTB electronic-part-only parametrizations for bulk and surface band structures of all d-block transition metals that enable efficient predictions of electronic descriptors for large structures or high-throughput studies on complex systems outside the computational reach of density functional theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SPARC-X: Quantum simulations at extreme scale - reactive dynamics from first principles

We have developed the massively parallel electronic structure code SPARC-X: a computational framework for performing Kohn-Sham Density Functional Theory (DFT) calculations that can scale linearly with the number of atoms in the system, while being able to leverage petascale and emerging exascale parallel computers to study chemical phenomena at unprecedented length and time scales. SPARC-X exploits a recent breakthrough in electronic structure methodologies: systematically improvable, strictly local, orthonormal, discontinuous real-space bases that efficiently and systematically capture the local chemistry of the system. With further adaptation using new machine-learning techniques and the use of the massively parallel Spectral Quadrature (SQ) electronic structure method, the algorithmic complexity and prefactor associated with DFT calculations involving semilocal as well as hybrid functionals are dramatically reduced. Using petascale computational resources, SPARC-X enables quantum mechanical simulations at length and time scales previously accessible only by empirical approaches, e.g., 1,000,000 atoms for a few picoseconds using semilocal functionals or 1,000 atoms for a few picoseconds using hybrid functionals. Using exascale resources, the sizes and times targeted are two orders of magnitude larger. Such a capability has applications in a wide variety of chemical sciences, including reactive interfaces where large length- and/or long time-scales are needed and traditional force fields fail. This is particularly important in dynamic catalysis, where bond breaking and formation must be understood in detail. We developed, tested, and employed the SPARC-X framework to understand the photocatalytic properties of TiO 2 nanoparticles, revealing finite size effects that cannot be captured with standard model systems or functionals. This integrated development and application strategy ensures that SPARC-X remains a robust, efficient, and scalable software package for quantum simulations on current petascale and emerging exascale computing resources.

97 MATHEMATICS AND COMPUTING↗

Uncertainties in Simulating Flooding During Hurricane Harvey Using 2D Shallow Water Equations

Abstract Flooding is one of the most impactful weather‐related natural hazards. Numerical models that solve the two dimensional (2D) shallow water equations (SWE) represent the first‐principles approach to simulate all types of spatial flooding, such as pluvial, fluvial, and coastal flooding, and their compound dynamics. High spatial resolution (e.g., () m) is needed in 2D SWE simulations to capture flood dynamics accurately, resulting in formidable computational challenges. Thus, relatively coarser spatial resolutions are used for large‐scale simulations of flooding, which introduce uncertainties in the results. It is unclear how the uncertainty associated with the model resolution compares to the uncertainties in precipitation data sets and assumptions regarding boundary conditions when channelized flows interact with other water bodies. In this study, we compare these three sources of uncertainties in 2D SWE simulations for the 2017 Houston flooding event. Our results show that precipitation uncertainty and mesh resolution have more significant impacts on the simulated streamflow and inundation dynamics than the choice of the downstream boundary condition at the watershed outlet. We point out the viability to confine the uncertainty of coarsening mesh resolution by using the variable resolution mesh (VRM) which refines critical topographic features with far fewer grid cells. Specifically, in simulations with VRM, the simulated inundation depths over the refined region are comparable to that use the finest uniform mesh. This study contributes to understanding the challenges and pathways for applying 2D SWE models to improve the realism of flood simulations over large scales.

54 ENVIRONMENTAL SCIENCES↗

Machine Learning Reveals Memory of the Parent Phases in Ferroelectric Relaxors Ba(Ti$_{1-x}$,Zr x )O 3

Machine learning has been establishing its potential in multiple areas of condensed matter physics and materials science. Here, in this work, an unsupervised machine learning workflow is developed and used within a framework of first-principles-based atomistic simulations to investigate phases, phase transitions, and their structural origins in ferroelectric relaxors, Ba(Ti 1-x ,Zr x )O 3 . The applicability of the workflow is first demonstrated to identify phases and phase transitions in the parent compound, a prototypical ferroelectric BaTiO 3 . Then the workflow is applied for Ba(Ti 1-x ,Zrx)O 3 with x ≤ 0.25 to reveal i) that some of the compounds bear a subtle memory of BaTiO 3 phases beyond the point of the pinched phase transition, which could contribute to their enhanced electromechanical response; ii) the existence of peculiar phases with delocalized precursors of nanodomains—likely candidates for the controversial polar nanoregions; and iii) nanodomain phases for the largest concentrations of x.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Spatial coupling of gyrokinetic simulations, a generalized scheme based on first-principles

In this paper, we present a scheme that spatially couples two gyrokinetic codes using first-principles. Coupled equations are presented and a necessary and sufficient condition for ensuring accuracy is derived. This new scheme couples both the field and the particle distribution function. The coupling of the distribution function is only performed once every few time-steps, using a five-dimensional (5D) grid to communicate the distribution function between the two codes. This 5D grid interface enables the coupling of different types of codes and models, such as particle and continuum codes, or delta-f and total-f models. Transferring information from the 5D grid to the marker particle weights is achieved using a new resampling technique. Demonstration of the coupling scheme is shown using two XGC gyrokinetic simulations for both the core and edge. We also apply the coupling scheme to two continuum simulations for a one-dimensional advection–diffusion problem.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

$\alpha$-Clustering in atomic nuclei from first principles with statistical learning and the Hoyle state character

A long-standing crucial question with atomic nuclei is whether or not α clustering occurs there. An α particle (helium-4 nucleus) comprises two protons and two neutrons, and may be the building block of some nuclei. This is a very beautiful and fascinating idea, and is indeed plausible because the α particle is particularly stable with a large binding energy. However, direct experimental evidence has never been provided. Here, we show whether and how α(-like) objects emerge in atomic nuclei, by means of state-of-the-art quantum many-body simulations formulated from first principles, utilizing supercomputers including K/Fugaku. The obtained physical quantities exhibit agreement with experimental data. The appearance and variation of the α clustering are shown by utilizing density profiles for the nuclei beryllium-8, -10 and carbon-12. With additional insight by statistical learning, an unexpected crossover picture is presented for the Hoyle state, a critical gateway to the birth of life.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Monte Carlo Simulation of Background and Source Measurements with CSG and CAD Geometries

Detecting radioactive sources in an urban environment is difficult due to the large magnitude and variability of the background radiation. To support the search mission of the National Nuclear Security Administration, a project was undertaken to determine if first-principles modeling and simulation could be used to accurately predict the response of radiation detectors in urban environments. This study demonstrates that the simulated detector responses to photon radiation from both an isotopic source and the background compare well to benchmark-quality measurements in a large urban-like test environment. Simulation results using a traditional combinatorial solid geometry and a CAD model generated from LiDAR measurements gave very similar detector responses. With this validation, further simulations could be used to predict detector responses for various situations in real urban settings.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Self-Healing Ceramics and Mechanical Metamaterials

We performed large scale molecular dynamics (MD) simulations and reactive & quantum molecular dynamics simulations to investigate: (1) faceting, grain growth, and crack healing in ceramics; (2) stress-release mechanism and healing in fibers; and (3) mechanical properties of two-dimensional metamaterials. We also designed highly accurate interatomic potentials and forces using artificial neural networks (ANN) and first-principles molecular dynamics simulation data for use in our MD and reactive MD simulations. We demonstrated the efficacy of modeling quantum materials atomistic simulation data using unsupervised deep learning approaches on a quantum computer. These achievements are elaborated in the following sections.

36 MATERIALS SCIENCE↗

Deep learning-based predictive models for laser direct drive at the Omega Laser Facility

The rich and complex physics of inertial confinement fusion provides a unique and challenging space for high-fidelity first-principles modeling. Consequently, simulation codes that are used to design experiments are computationally expensive and lack the predictive capability required for extensive parameter exploration in search of a high-performing design for laser direct drive. In this article, we present two deep-learning-based predictive models intended to address these difficulties. The first model (TL DNN) acts as a fast emulator of simulations as well as experiments at the Omega Laser Facility. This model is trained on a simulation database and subsequently calibrated on experimental data using transfer learning. To facilitate the development of this model, an autoencoder is developed to reduce the dimensionality of the input space by compressing the laser pulse input. The model predicts key experimental scalar observables of Omega experiments with high accuracy and minimal computational cost. This deep neural net enables rapid exploration of a high-dimensional input parameter space for an optimal implosion design. The second model (DNN SM+) aims to extend the statistical modeling work of Lees et al. [Phys. Rev. Lett. 127, 105001 (2021)], by increasing the complexity of the model space and allowing for coupling between degradation terms. Since the model capacity of DNN SM+ is higher than the model of Lees et al., DNN SM+ can potentially provide an improvement in predictive capability, and we use this model to provide insight into complicated degradation dependencies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Dynamic Structure of Magnetized High Energy Density Plasmas (Final Report)

This report summarizes results of project DE-SC0022202 ``Dynamic Structure of Magnetized High Energy Density Plasmas,'' which was originally funded for the period 08/01/2021 - 7/31/2022, but was no-cost extended to 7/31/2023. The primary objectives of the work, as stated in the original proposal, were ``develop a theory to describe a novel state of magnetized high energy density plasmas, benchmark the theory using first-principles molecular dynamics simulations, and apply the results to develop a means to interpret x-ray scattering measurements in future experiments.'' These were the goals of the original project proposal, which was for a 3 year project. The project was ultimately funded for 1 year, and so the work completed focused on the goals described for only the first year of the proposed work. This included further developing a kinetic theory for strongly magnetized plasmas, applying it to compute fluid-scale (MHD) transport coefficients, and to test the predictions using molecular dynamics simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Chlorine gas and anion radical reactivity in molten salts and the link to chlorobasicity

Next-generation nuclear power plants may include exciting novel designs in which molten salts are the coolant or a combination of the coolant and fuel. Whereas it is straightforward to see why having a low volatility coolant can be advantageous for safety, much is not understood about the production of volatile halogen gases as a result of radiation and even less is known about the distribution of these species at and away from interfaces. Using first principles molecular dynamics simulations, we investigate the product of the disproportionation reaction between chlorine anion radicals (nominally Cl 2 ˙ − ) in the bulk and slab configurations. We find that the product depends on the chlorobasicity of the medium. For example, in ZnCl 2 , Cl 2 forms, but in a eutectic mixture of LiCl and KCl, Cl 3 − is formed as a product. We also find that Cl 3 − prefers to form at the vapor interface and this may have implications for corrosion and reactivity. Furthermore, the mechanisms of the mobility of Cl 2 and Cl 3 − are radically different, the first one being vehicular and the second Grotthus-like. Chlorobasicity is linked to the electronic structure of the host melt; ZnCl 2 forms extended networks along which metal ions and anionic counterions have significant electronic orbital overlap forming long, linear, molecular-like constructs; the opposite is true for the alkali metal eutectic salt.

Nguyen, Hung H. [Univ. of Iowa, Iowa City, IA (Uni↗

Neutron thermalization in nuclear graphite: A modern story of a classic moderator

Graphite has been of great interest since the dawn of the nuclear era. In this work, we will focus on the thermal neutron scattering of two types of nuclear graphite that have different microstructures, namely, the historic PGA which has a very anisotropic medium-grained needle coke, and the new G347A which is a near-isotropic fine-grained graphite. We report the results of room temperature inelastic neutron scattering measurements for the scattering function, double differential scattering cross-section, and phonon density of states. The obtained results are discussed in conjunction with results extracted from first-principles lattice dynamics simulations of crystalline graphite, using the incoherent approximation and by also including the coherent-one phonon contribution. Excellent agreements have been found between the measured and calculated scattering functions and phonon densities of states. The inclusion of the coherent-one phonon scattering shows a significant improvement of the calculated scattering functions, double differentials, and inelastic scattering cross-sections. We also highlight the physical concerns about the current thermal neutron scattering ENDF/B-VIII of nuclear graphite library and its corresponding phonon density of states. This work aims to provide a new presentation of neutron thermalization by graphite and offers a new set of high quality experimental and computational data for consideration.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Extended Lagrangian Born–Oppenheimer molecular dynamics using a Krylov subspace approximation

It is shown how the electronic equations of motion in extended Lagrangian Born–Oppenheimer molecular dynamics simulations can be integrated using low-rank approximations of the inverse Jacobian kernel. This kernel determines the metric tensor in the harmonic oscillator extension of the Lagrangian that drives the evolution of the electronic degrees of freedom. The proposed kernel approximation is derived from a pseudoinverse of a low-rank estimate of the Jacobian, which is expressed in terms of a generalized set of directional derivatives with directions that are given from a Krylov subspace approximation. The approach allows a tunable and adaptive approximation that can take advantage of efficient preconditioning techniques. The proposed kernel approximation for the integration of the electronic equations of motion makes it possible to apply extended Lagrangian first-principles molecular dynamics simulations to a broader range of problems, including reactive chemical systems with numerically sensitive and unsteady charge solutions. This can be achieved without requiring exact full calculations of the inverse Jacobian kernel in each time step or relying on iterative non-linear self-consistent field optimization of the electronic ground state prior to the force evaluations as in regular direct Born–Oppenheimer molecular dynamics. We note the low-rank approximation of the Jacobian is directly related to Broyden’s class of quasi-Newton algorithms and Jacobian-free Newton–Krylov methods and provides a complementary formulation for the solution of nonlinear systems of equations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗