The properties of electrons in matter are of fundamental importance. They give rise to virtually all material properties and determine the physics at play in objects ranging from semiconductor devices to the interior of giant gas planets. Modeling and simulation of such diverse applications rely primarily on density functional theory (DFT), which has become the principal method for predicting the electronic structure of matter. While DFT calculations have proven to be very useful, their computational scaling limits them to small systems. We have developed a machine learning framework for predicting the electronic structure on any length scale. It shows up to three orders of magnitude speedup on systems where DFT is tractable and, more importantly, enables predictions on scales where DFT calculations are infeasible. Our work demonstrates how machine learning circumvents a long-standing computational bottleneck and advances materials science to frontiers intractable with any current solutions.
Abstract: 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. Graphical abstract: [Figure not available: see fulltext.].
The long-standing problem of predicting the electronic structure of matter on ultra-large scales (beyond 100,000 atoms) is solved with machine learning.
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.
We present a numerical modeling workflow based on machine learning (ML) 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.
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.
We present a numerical modeling workflow based on machine learning (ML) which reproduces the 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.
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.
Tin-germanium alloys are increasingly of interest as optoelectronic and thermoelectric materials as well as materials for Li/Na ion battery electrodes. However, the lattice incompatibility of bulk Sn and Ge makes creating such alloys challenging. By exploiting the unique strain tolerance of nanosized crystals, we have developed a facile synthetic method for homogeneous SnxGe1-x alloy nanocrystals with composition varying from essentially pure Ge to 95% Sn while still maintaining the cubic structure.
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.
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.
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.
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).
The application of first-principles calculations holds promise for greatly improving our understanding of semiconductor superlattices. By developing a procedure to accurately predict band gaps using hybrid density functional theory, it 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%.
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.
This report examines the temperature dependence of the capture rate of carriers by defects in gallium arsenide and compares two previously published theoretical treatments of this based on multi phonon emission (MPE). The objective is to reduce uncertainty in atomistic simulations of gain degradation in III-V HBTs from neutron irradiation. A major source of uncertainty in those simulations is poor knowledge of carrier capture rates, whose values can differ by several orders of magnitude between various defect types. Most of this variation is due to different dependence on temperature, which is closely related to the relaxation of the defect structure that occurs as a result of the change in charge state of the defect. The uncertainty in capture rate can therefore be greatly reduced by better knowledge of the defect relaxation.
We performed density functional theory (DFT) calculations for a bi-layered heterostructure combining a graphene layer with a MoS2 layer with and without intercalated Li atoms. Our calculations demonstrate the importance of the van der Waals (vdW) interaction, which is crucial for forming stable bonding between the layers. Our DFT calculation correctly reproduces the linear dispersion, or Dirac cone, feature at the Fermi energy for the isolated graphene monolayer and the band gap for the MoS2 monolayer. For the combined graphene/MoS2 bi-layer, we observe interesting electronic structure and density of states (DOS) characteristics near the Fermi energy, showing both the gap like features of the MoS2 layer and in-gap states with linear dispersion contributed mostly by the graphene layer. Our calculated total DOS in this vdW heterostructure reveals that the graphene layer significantly contributes to pinning the Fermi energy at the center of the band gap of MoS2. We also find that intercalating Li ions in between the layers of the graphene/MoS2 heterostructure enhances the binding energy through orbital hybridizations between cations (Li adatoms) and anions (graphene and MoS2 monolayers). Moreover, we calculate the dielectric function of the Li intercalated graphene/MoS2 heterostructure, the imaginary component of which can be directly compared with experimental measurements of optical conductivity in order to validate our theoretical prediction. We observe sharp features in the imaginary component of the dielectric function, which shows the presence of a Drude peak in the optical conductivity, and therefore metallicity in the lithiated graphene/MoS2 heterostructure.
Classical molecular dynamics (MD) provides a powerful and widely used approach to determining thermodynamic properties by integrating the classical equations of motion of a system of atoms. Time-Dependent Density Functional Theory (TDDFT) provides a powerful and increasingly useful approach to integrating the quantum equations of motion for a system of electrons. TDDFT efficiently captures the unitary evolution of a many-electron state by mapping the system into a fictitious non-interacting system. In analogy to MD, one could imagine obtaining the thermodynamic properties of an electronic system from a TDDFT simulation in which the electrons are excited from their ground state by a time-dependent potential and then allowed to evolve freely in time while statistical data are captured from periodic snapshots of the system. For a variety of systems (e.g., many metals), the electrons reach an effective state of internal equilibrium due to electron-electron interactions on a time scale that is short compared to electron-phonon equilibration. During the initial time-evolution of such systems following electronic excitation, electron-phonon interactions should be negligible, and therefore, TDDFT should successfully capture the internal thermalization of the electrons. However, it is unclear how TDDFT represents the resulting thermal state. In particular, the thermal state is usually represented in quantum statistical mechanics as a mixed state, while the occupations of the TDDFT wavefunctions are fixed by the initial state in TDDFT. We work to address this puzzle by (A) reformulating quantum statistical mechanics so that thermodynamic expectations can be obtained as an unweighted average over a set of many-body pure states and (B) constructing a family of non-interacting (single determinant) TDDFT states that approximate the required many-body states for the canonical ensemble.
A recently developed bounds-analysis approach has been used to interpret density-functional-theory (DFT) results for the As and Ga antisites in GaAs. The bounds analysis and subsequent processing of DFT results for the As antisite yielded levels - defined as the Fermi levels at which the defect charge state changes - in very good agreement with measurements, including the -1/0 level which is within 0.1 eV of the conduction-band edge. Good agreement was also obtained for the activation energies to transform the AsGa from its metastable state to its stable state. For the Ga antisite, the bounds analysis revealed that the -1 and 0 charge states are hole states weakly bound to a localized -2 charge state. The calculated levels are in good agreement with measurements.
Carrier recombination due to defects can have a major impact on device performance. The rate of defect-induced carrier recombination is determined by both defect levels and carrier capture cross-sections. Kohn-Sham density functional theory (DFT) has been widely and successfully used to predict defect levels in semiconductors and insulators, but only recently has work begun to focus on using DFT to determine carrier capture cross-sections. Lang and Henry worked out the fundamental theory of carrier-capture cross-sections in the 1970s and showed that, in most cases, room temperature carrier-capture cross-sections differ between defects primarily due to differences in the carrier capture activation energies. Here, we present an approach to using DFT to calculate carrier capture activation energies that does not depend on perturbation theory or an assumed configuration coordinate, and we demonstrate this approach for the -3/-2 level of the Ga vacancy in wurtzite GaN.
In modeling thermal transport in nanoscale systems, classical molecular dynamics (MD) explicitly represents phonon modes and scattering mechanisms, but electrons and their role in energy transport are missing. Furthermore, the assumption of local equilibrium between ions and electrons often fails at the nanoscale. We have coupled MD (implemented in the LAMMPS MD package) with a partial differential equation based representation of the electrons (implemented using finite elements). The coupling between the subsystems occurs via a local version of the two-temperature model. Key parameters of the model are calculated using the Time Dependent Density Functional Theory with either explicit or implicit energy flow. We will discuss application of this work in the context of the US DOE Center for Integrated Nanotechnologies (CINT).
Understanding internal dissipation in resonant mechanical systems at the micro- and nanoscale is of great technological and fundamental interest. Resonant mechanical systems are central to many sensor technologies, and microscale resonators form the basis of a variety of scanning probe microscopies. Furthermore, coupled resonant mechanical systems are of great utility for the study of complex dynamics in systems ranging from biology to electronics to photonics. In this work, we report the detailed experimental study of internal dissipation in micro- and nanomechanical oscillators fabricated from amorphous and crystalline diamond materials, atomistic modeling of dissipation in amorphous, defect-free, and defect-containing crystalline silicon, and experimental work on the properties of one-dimensional and two-dimensional coupled mechanical oscillator arrays. We have identified that internal dissipation in most micro- and nanoscale oscillators is limited by defect relaxation processes, with large differences in the nature of the defects as the local order of the material ranges from amorphous to crystalline. Atomistic simulations also showed a dominant role of defect relaxation processes in controlling internal dissipation. Our studies of one-dimensional and two-dimensional coupled oscillator arrays revealed that it is possible to create mechanical systems that should be ideal for the study of non-linear dynamics and localization.
A finite temperature version of 'exact-exchange' density functional theory (EXX) has been implemented in Sandia's Socorro code. The method uses the optimized effective potential (OEP) formalism and an efficient gradient-based iterative minimization of the energy. The derivation of the gradient is based on the density matrix, simplifying the extension to finite temperatures. A stand-alone all-electron exact-exchange capability has been developed for testing exact exchange and compatible correlation functionals on small systems. Calculations of eigenvalues for the helium atom, beryllium atom, and the hydrogen molecule are reported, showing excellent agreement with highly converged quantumMonte Carlo calculations. Several approaches to the generation of pseudopotentials for use in EXX calculations have been examined and are discussed. The difficult problem of finding a correlation functional compatible with EXX has been studied and some initial findings are reported.
We report the implementation of an iterative scheme for calculating the Optimized Effective Potential (OEP). Given an energy functional that depends explicitly on the Kohn-Sham wave functions, and therefore, implicitly on the local effective potential appearing in the Kohn-Sham equations, a gradient-based minimization is used to find the potential that minimizes the energy. Previous work has shown how to find the gradient of such an energy with respect to the effective potential in the zero-temperature limit. We discuss a density-matrix-based derivation of the gradient that generalizes the previous results to the finite temperature regime, and we describe important optimizations used in our implementation. We have applied our OEP approach to the Hartree-Fock energy expression to perform Exact Exchange (EXX) calculations. We report our EXX results for common semiconductors and ordered phases of hydrogen at zero and finite electronic temperatures. We also discuss issues involved in the implementation of forces within the OEP/EXX approach.
The potential for implementing quantum coherence in semiconductor self-assembled quantum dots has been investigated theoretically and experimentally. Theoretical modeling suggests that coherent dynamics should be possible in self-assembled quantum dots. Our experimental efforts have optimized InGaAs and InAs self-assembled quantum dots on GaAs for demonstrating coherent phenomena. Optical investigations have indicated the appropriate geometries for observing quantum coherence and the type of experiments for observing quantum coherence have been outlined. The optical investigation targeted electromagnetically induced transparency (EIT) in order to demonstrate an all optical delay line.