Related papers: SiC-TGAP: A machine learning interatomic potential…
We present a swift walk-through of our recent work that uses machine learning to fit interatomic potentials based on quantum mechanical data. We describe our Gaussian Approximation Potentials (GAP) framework, discussing a variety of…
We outline a partial-fractions decomposition method for determining the one-particle spectral function and single-particle density of states of a correlated electronic system on a finite lattice in the non self-consistent T-matrix…
Silicon carbide (SiC) is an excellent substrate for growth and manipulation of large scale, high quality epitaxial graphene. On the carbon face (the ($\bar{1}\bar{1}\bar{1}$) or $(000\bar{1}$) face, depending on the polytype), the onset of…
Machine learning interatomic potentials (ML-IAPs) enable quantum-accurate, classical molecular dynamics simulations of large systems, beyond reach of density functional theory (DFT). Yet, their efficiency and ability to predict systems…
Radiation hardening of the MOSFET is of the highest priority for sustaining high-power systems in the space radiation environment. SiC-based power electronics are being looked at as a strong alternative for high power spaceborne power…
Silicon carbide (SiC), is an artificial semiconductor used for high-power transistors and blue LEDs, for its extraordinary properties. SiC would be attractive for more applications, but large-scale or large-surface area fabrication, with…
A three-way coupled thermo-mechanical fracture model is presented to predict the damage of brittle ceramics, in particular {\alpha}-SiC, over a wide range of temperatures (20-1400 C). Predicting damage over such a range of temperatures is…
Using a combination of kinetic Activation Relaxation Technique with empirical potential and ab initio based climbing image nudged elastic band method, we perform an extensive search of the migration and rotation paths of the most stable…
We describe the parameterization of a tungsten-hydrogen empirical potential designed for use with large-scale molecular dynamics simulations of highly irradiated tungsten containing hydrogen isotope atoms, and report test results.…
Using molecular dynamics simulations we study the thermodynamic behavior of a single-component covalent material described by the recently proposed Environment-Dependent Interatomic Potential (EDIP). The parameterization of EDIP for silicon…
We propose a novel active learning scheme for automatically sampling a minimum number of uncorrelated configurations for fitting the Gaussian Approximation Potential (GAP). Our active learning scheme consists of an unsupervised machine…
Semi-empirical interatomic potentials have been developed for Al, alpha-Ti, and gamma-TiAl within the embedded atomic method (EAM) by fitting to a large database of experimental as well as ab-initio data. The ab-initio calculations were…
Metal-semiconductor interfaces play a central role in micro and nano-electronic devices as heat dissipation or temperature drop across these interfaces can significantly affect device performance. Prediction of accurate thermal boundary…
In this work, the implications of high field bias conditions in radiation-induced defect recovery in 3C-SiC crystals is studied. It is well known that transient heating effects (or thermal spikes) occur when energetic swift heavy ions…
Constructing an accurate atomistic model for the high-pressure phases of tin (Sn) is challenging because properties of Sn are sensitive to pressures. We develop machine-learning-based deep potentials for Sn with pressures ranging from 0 to…
Dynamical models based on relativistic fluid dynamics provide a powerful tool to extract the properties of the strongly-coupled quark-gluon plasma (QGP) produced by ultrarelativistic nuclear collisions. The largest source of uncertainty in…
The accurate treatment of electronic effects in multi-million atom simulations of radiation-induced collision cascades is crucial for reliable predictions of primary radiation damage. In this work, we explore the performance of a recently…
Path-integral molecular dynamics simulations in the isothermal-isobaric (NPT) ensemble have been carried out to study the dependence of the lattice parameter of 3C-SiC upon isotope mass. This computational method allows a quantitative and…
In this study, large-scale molecular dynamics simulations with the Vashishta potential and the analytic bond-order potential (ABOP) were performed to investigate the effect of extended defects on the elastic properties of cubic silicon…
The dielectric breakdown (BD) of thermal oxide (SiO2) grown on cubic silicon carbide (3C-SiC) was investigated comparing the electrical behavior of macroscopic metal-oxidesemiconductor (MOS) capacitors with nanoscale current and capacitance…