Publications

The long-standing problem of predicting the electronic structure of matter on ultra-large scales (beyond 100,000 atoms) is solved with machine learning.

Due to a beneficial balance of computational cost and accuracy, real-time time-dependent density-functional theory has emerged as a promising first-principles framework to describe electron real-time dynamics. Here we discuss recent implementations around this approach, in particular in the context of complex, extended systems. Results include an analysis of the computational cost associated with numerical propagation and when using absorbing boundary conditions. We extensively explore the shortcomings for describing electron-electron scattering in real time and compare to many-body perturbation theory. Modern improvements of the description of exchange and correlation are reviewed. In this work, we specifically focus on the Qb@ll code, which we have mainly used for these types of simulations over the last years, and we conclude by pointing to further progress needed going forward.

The focus of this project is to accelerate and transform the workflow of multiscale materials modeling by developing an integrated toolchain seamlessly combining DFT, SNAP, LAMMPS, (shown in Figure 1-1) and a machine-learning (ML) model that will more efficiently extract information from a smaller set of first-principles calculations. Our ML model enables us to accelerate first-principles data generation by interpolating existing high fidelity data, and extend the simulation scale by extrapolating high fidelity data (10² atoms) to the mesoscale (10⁴ atoms). It encodes the underlying physics of atomic interactions on the microscopic scale by adapting a variety of ML techniques such as deep neural networks (DNNs), and graph neural networks (GNNs). We developed a new surrogate model for density functional theory using deep neural networks. The developed ML surrogate is demonstrated in a workflow to generate accurate band energies, total energies, and density of the 298K and 933K Aluminum systems. Furthermore, the models can be used to predict the quantities of interest for systems with more number of atoms than the training data set. We have demonstrated that the ML model can be used to compute the quantities of interest for systems with 100,000 Al atoms. When compared with 2000 Al system the new surrogate model is as accurate as DFT, but three orders of magnitude faster. We also explored optimal experimental design techniques to choose the training data and novel Graph Neural Networks to train on smaller data sets. These are promising methods that need to be explored in the future.

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We present a numerical modeling workflow based on machine learning which reproduces the total energies produced by Kohn-Sham density functional theory (DFT) at finite electronic temperature to within chemical accuracy at negligible computational cost. Based on deep neural networks, our workflow yields the local density of states (LDOS) for a given atomic configuration. From the LDOS, spatially resolved, energy-resolved, and integrated quantities can be calculated, including the DFT total free energy, which serves as the Born-Oppenheimer potential energy surface for the atoms. We demonstrate the efficacy of this approach for both solid and liquid metals and compare results between independent and unified machine-learning models for solid and liquid aluminum. Our machine-learning density functional theory framework opens up the path towards multiscale materials modeling for matter under ambient and extreme conditions at a computational scale and cost that is unattainable with current algorithms.

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Through a combination of single crystal growth, experiments involving in situ deposition of surface adatoms, and complimentary modeling, we examine the electronic transport properties of lithium-decorated ZrTe5 thin films. We observe that the surface states in ZrTe5 are robust against Li adsorption. Both the surface electron density and the associated Berry phase are remarkably robust to adsorption of Li atoms. Fitting to the Hall conductivity data reveals that there exist two types of bulk carriers: those for which the carrier density is insensitive to Li adsorption, and those whose density decreases during initial Li depositions and then saturates with further Li adsorption. We propose this dependence is due to the gating effect of a Li-adsorption-generated dipole layer at the ZrTe5 surface.

The self-interstitial atom (SIA) is one of two fundamental point defects in bulk Si. Isolated Si SIAs are extremely difficult to observe experimentally. Even at very low temperatures, they anneal before typical experiments can be performed. Given the challenges associated with experimental characterization, accurate theoretical calculations provide valuable information necessary to elucidate the properties of these defects. Previous studies have applied Kohn-Sham density functional theory (DFT) to the Si SIA, using either the local density approximation or the generalized gradient approximation to the exchange-correlation (XC) energy. The consensus of these studies indicates that a Si SIA may exist in five charge states ranging from -2 to +2 with the defect structure being dependent on the charge state. This study aims to re-examine the existence of these charge states in light of recently derived "approximate bounds"on the defect levels obtained from finite-size supercell calculations and new DFT calculations using both semi-local and hybrid XC approximations. We conclude that only the neutral and +2 charge states are directly supported by DFT as localized charge states of the Si SIA. Within the current accuracy of DFT, our results indicate that the +1 charge state likely consists of an electron in a conduction-band-like state that is coulombically bound to a +2 SIA. Furthermore, the -1 and -2 charge states likely consist of a neutral SIA with one and two additional electrons in the conduction band, respectively.

Recent years have seen an explosion in research efforts discovering and understanding novel electronic and optical properties of topological quantum materials (TQMs). In this LDRD, a synergistic effort of materials growth, characterization, electrical-magneto-optical measurements, combined with density functional theory and modeling has been established to address the unique properties of TQMs. Particularly, we have carried out extensive studies in search for Majorana fermions (MFs) in TQMs for topological quantum computation. Moreover, we have focused on three important science questions. 1) How can we controllably tune the properties of TQMs to make them suitable for quantum information applications? 2) What materials parameters are most important for successfully observing MFs in TQMs? 3) Can the physical properties of TQMs be tailored by topological band engineering? Results obtained in this LDRD not only deepen our current knowledge in fundamental quantum physics but also hold great promise for advanced electronic/photonic applications in information technologies. ACKNOWLEDGEMENTS The work at Sandia National Labs was supported by a Laboratory Directed Research and Development project. Device fabrication was performed at the Center for Integrated Nanotechnologies, an Office of Science User Facility operated for the U.S. Department of Energy (DOE) Office of Science. We are grateful to many people inside and outside Sandia for their support and fruitful collaborations. This report describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the United States Government. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

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Detailed understanding of solid–solid interface structure–function relationships is critical for the improvement and wide deployment of all-solid-state batteries. The interfaces between lithium phosphorous oxynitride (LiPON) solid electrolyte material and lithium metal anode, and between LiPON and LixCoO2 cathode, have been reported to generate solid–electrolyte interphase (SEI)-like products and/or disordered regions. Using electronic structure calculations and crystalline LiPON models, we predict that LiPON models with purely P−N−P backbones are kinetically inert towards lithium at room temperature. In contrast, transfer of oxygen atoms from low-energy LixCoO2(104) surfaces to LiPON is much faster under ambient conditions. The mechanisms of the primary reaction steps, LiPON structural motifs that readily reacts with lithium metal, experimental results on amorphous LiPON to partially corroborate these predictions, and possible mitigation strategies to reduce degradations are discussed. LiPON interfaces are found to be useful case studies for highlighting the importance of kinetics-controlled processes during battery assembly at moderate processing temperatures.

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The formulation of carrier transport through heterojunctions by tunneling and thermionic emission is derived from first principles. The treatment of tunneling is discussed at three levels of approximation: numerical solution of the one-band envelope equation for an arbitrarily specified potential profile; the WKB approximation for an arbitrary potential; and, an analytic formulation assuming constant internal field. The effects of spatially varying carrier chemical potentials over tunneling distances are included. Illustrative computational results are presented. The described approach is used in exploratory physics models of irradiated heterojunction bipolar transistors within Sandia's QASPR program.

The energy-dependent probability density of tunneled carrier states for arbitrarily specified longitudinal potential-energy profiles in planar bipolar devices is numerically computed using the scattering method. Results agree accurately with a previous treatment based on solution of the localized eigenvalue problem, where computation times are much greater. These developments enable quantitative treatment of tunneling-assisted recombination in irradiated heterojunction bipolar transistors, where band offsets may enhance the tunneling effect by orders of magnitude. The calculations also reveal the density of non-tunneled carrier states in spatially varying potentials, and thereby test the common approximation of uniform- bulk values for such densities.

We show scaling results for materials of interest in Sandia Radiation-Effects and High-Energy-Density-Physics Mission Areas. Each timing is from a self-consistent calculation for bulk material. Two timings are given: (1) walltime for the construction of the CR exchange operator (Exchange-Operator) and (2) walltime for everything else (non-Exchange-Operator).

Predicting transient effects caused by short - pulse neutron irradiation of electronic devices is an important part of Sandia's mission. For example , predicting the diffusion of radiation - induced point defects is needed with in Sandia's Qualification Alternative to the Sandia Pulsed Reactor (QASPR) pro gram since defect diffusion mediates transient gain recovery in QASPR electronic devices. Recently, the semiconductors used to fabricate radiation - hard electronic devices have begun to shift from silicon to III - V compounds such as GaAs, InAs , GaP and InP . An advantage of this shift is that it allows engineers to optimize the radiation hardness of electronic devices by using alloy s such as InGaAs and InGaP . However, the computer codes currently being used to simulate transient radiation effects in QASP R devices will need to be modified since they presume that defect properties (charge states, energy levels, and diffusivities) in these alloys do not change with time. This is not realistic since the energy and properties of a defect depend on the types of atoms near it and , therefore, on its location in the alloy. In particular, radiation - induced defects are created at nearly random locations in an alloy and the distribution of their local environments - and thus their energies and properties - evolves with time as the defects diffuse through the alloy . To incorporate these consequential effects into computer codes used to simulate transient radiation effects, we have developed procedures to accurately compute the time dependence of defect energies and properties and then formulate them within compact models that can be employed in these computer codes. In this document, we demonstrate these procedures for the case of the highly mobile P interstitial (I P ) in an InGaP alloy. Further dissemination only as authorized to U.S. Government agencies and their contractors; other requests shall be approved by the originating facility or higher DOE programmatic authority.

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The application of first-principles calculations holds promise for greatly improving our understanding of semiconductor superlattices. Developing a procedure to accurately predict band gaps using hybrid density functional theory lays the groundwork for future studies investigating more nuanced properties of these structures. Our approach allows a priori prediction of the properties of SLS structures using only the band gaps of the constituent materials. Furthermore, it should enable direct investigation of the effects of interface structure, e.g., intermixing or ordering at the interface, on SLS properties. In this paper, we present band gap data for various InAs/GaSb type-II superlattice structures calculated using the generalized Kohn-Sham formulation of density functional theory. A PBE0-type hybrid functional was used, and the portion of the exact exchange was tuned to fit the band gaps of the binary compounds InAs and GaSb with the best agreement to bulk experimental values obtained with 18% of the exact exchange. The heterostructures considered in this study are 6 monolayer (ML) InAs/6 ML GaSb, 8 ML InAs/8 ML GaSb and 10 ML InAs/10 ML GaSb with deviations from the experimental band gaps ranging from 3% to 11%.

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Carrier transport and recombination are modeled for a heterojunction diode containing irradiation defects. Detailed attention is given to the role of band-to-trap tunneling and how it is affected by band offsets at the junction. Tunneled states are characterized by numerical solution of the one-band effective-mass envelope equation. The interaction with traps is treated assuming capture by the multi-phonon-emission mechanism. It is shown that tunneling can increase carrier recombination at defects by orders of magnitude in the presence of large band offsets. This explains why Npn InGaP/GaAs/GaAs heterojunction bipolar transistors with displacement damage from energetic-particle irradiation are observed to have high carrier recombination in the emitter-base depletion region.

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