140 citations · 1k across the 66 of their papers we have counts for
69 papers
On-the-fly -machine learned force fields for warm dense matter using a Yukawa reference model: Application to magnesium
Sayan Bhowmik, John E. Pask, Phanish Suryanarayana
We develop a framework for on-the-fly -machine learned force field (-MLFF) molecular dynamics (MD) simulations of warm dense matter (WDM). In particular, we employ a Yukawa r…
Highly Parallel Real-Space Random Phase Approximation Using Lanczos Quadrature and Interpolation
Abir Haque, Edmond Chow, Shikhar Shah +3
We present a highly parallelizable, matrix-free, real-space method for computing the random phase approximation (RPA) correlation energy within Kohn-Sham density functional theory.…
Unified open-boundary electrostatics in real-space density functional theory
Rajat Kumar, David Codony, Phanish Suryanarayana +1
We present an electrostatic formulation in real-space density functional theory that provides a systematic and unified treatment of the open-boundary electrostatics of isolated and…
Bulk Boundary Condition for Surface Calculations in Density Functional Theory
Sayan Bhowmik, Andrew J Medford, Phanish Suryanarayana
We present a bulk boundary condition formalism for surface calculations in Kohn--Sham density functional theory. The approach exploits the nearsightedness of electronic interaction…
SPARC-atomSFE: Spectral finite-element package for atomic structure calculations in density functional theory
Qihao Cheng, Shubhang Krishnakant Trivedi, Phanish Suryanarayana
We present SPARC-atomSFE, a spectral finite-element package for accurate and efficient atomic structure calculations within the framework of Kohn-Sham density functional theory. Th…
Assessing the suitability of the Thomas-Fermi-von Weizsäcker density functional for itinerant magnetism
Bishal Thapa, Phanish Suryanarayana, Igor I. Mazin
We assess the ability of the Thomas--Fermi--von Weizsacker (TFW) functional within orbital-free density functional theory (DFT) to describe itinerant magnetism. Magnetic stability…
Electronic manifolds for extrapolative alloy discovery
Pranoy Ray, Sayan Bhowmik, Phanish Suryanarayana +2
This study presents a computationally efficient framework for accelerated alloy discovery that uses the non-interacting electron density to capture intrinsic structure-property rel…
Spectral finite-element formulation of the optimized effective potential method for atomic structure in the random phase approximation
Shubhang Krishnakant Trivedi, Phanish Suryanarayana
We present a spectral finite-element formulation of the optimized effective potential (OEP) method for atomic structure calculations in the random phase approximation (RPA). In par…
Cyclic- and helical-symmetry-adapted phonon formalism within density functional perturbation theory
Abhiraj Sharma, Phanish Suryanarayana
We present a first-principles framework for the calculation of phonons in nanostructures with cyclic and/or helical symmetry. In particular, we derive a cyclic- and helical-symmetr…
Ab initio study of flexoelectricity in MXene monolayers
Shashikant Kumar, Zixi Zhang, Phanish Suryanarayana
We investigate flexoelectricity in MXene monolayers from first principles. Specifically, we compute the transverse flexoelectric coefficients of 126 MXene monolayers along their tw…
Real-space Hubbard-corrected density functional theory
Sayan Bhowmik, Andrew J. Medford, Phanish Suryanarayana
We present an accurate and efficient framework for real-space Hubbard-corrected density functional theory. In particular, we obtain expressions for the energy, atomic forces, and s…
Ab initio study of strain-driven vacancy clustering in aluminum
Sayan Bhowmik, Abhiraj Sharma, Andrew J. Medford +2
We present a first principles investigation of strain-driven vacancy clustering in aluminum. Specifically, we perform Kohn-Sham density functional theory calculations to study the…
Random Phase Approximation Correlation Energy using Real-Space Density Functional Perturbation Theory
Boqin Zhang, Shikhar Shah, John E. Pask +2
We present a real-space method for computing the random phase approximation (RPA) correlation energy within Kohn-Sham density functional theory, leveraging the low-rank nature of t…
GPU acceleration of hybrid functional calculations in the SPARC electronic structure code
Xin Jing, Abhiraj Sharma, John E. Pask +1
We present a GPU-accelerated version of the real-space SPARC electronic structure code for performing hybrid functional calculations in generalized Kohn-Sham density functional the…
SPARC-X-API: Versatile Python Interface for Real-space Density Functional Theory Calculations
Tian Tian, Lucas R Timmerman, Shashikant Kumar +3
Density Functional Theory (DFT) is the de facto workhorse for large-scale electronic structure calculations in chemistry and materials science. While plane-wave DFT implementations…
Cyclic and helical symmetry-informed machine learned force fields: Application to lattice vibrations in carbon nanotubes
Abhiraj Sharma, Shashikant Kumar, Phanish Suryanarayana
We present a formalism for developing cyclic and helical symmetry-informed machine learned force fields (MLFFs). In particular, employing the smooth overlap of atomic positions des…
Shock Hugoniot calculations using on-the-fly machine learned force fields with ab initio accuracy
Shashikant Kumar, John E. Pask, Phanish Suryanarayana
We present a framework for computing the shock Hugoniot using on-the-fly machine learned force field (MLFF) molecular dynamics simulations. In particular, we employ an MLFF model b…
Efficient real space formalism for hybrid density functionals
Xin Jing, Phanish Suryanarayana
We present an efficient real space formalism for hybrid exchange-correlation functionals in generalized Kohn-Sham density functional theory (DFT). In particular, we develop an effi…
Spectral scheme for atomic structure calculations in density functional theory
Sayan Bhowmik, John E. Pask, Andrew J. Medford +1
We present a spectral scheme for atomic structure calculations in pseudopotential Kohn-Sham density functional theory. In particular, after applying an exponential transformation o…
Overcoming the chemical complexity bottleneck in on-the-fly machine learned molecular dynamics simulations
Lucas R. Timmerman, Shashikant Kumar, Phanish Suryanarayana +1
We develop a framework for on-the-fly machine learned force field molecular dynamics simulations based on the multipole featurization scheme that overcomes the bottleneck with the…
On-the-fly machine learned force fields for the study of warm dense matter: application to diffusion and viscosity of CH
Shashikant Kumar, Xin Jing, John E. Pask +1
We develop a framework for on-the-fly machine learned force field (MLFF) molecular dynamics (MD) simulations of warm dense matter (WDM). In particular, we employ an MLFF scheme bas…
Kohn-Sham accuracy from orbital-free density functional theory via -machine learning
Shashikant Kumar, Xin Jing, John E. Pask +2
We present a -machine learning model for obtaining Kohn-Sham accuracy from orbital-free density functional theory (DFT) calculations. In particular, we employ a machine learned…
Accuracy of Kohn-Sham density functional theory for warm- and hot-dense matter equation of state
Phanish Suryanarayana, Arpit Bhardwaj, Xin Jing +2
We study the accuracy of Kohn-Sham density functional theory (DFT) for warm- and hot-dense matter (WDM and HDM). Specifically, considering a wide range of systems, we perform accur…
Self-consistent convolutional density functional approximations: Application to adsorption at metal surfaces
Sushree Jagriti Sahoo, Qimen Xu, Xiangyun Lei +5
The exchange-correlation (XC) functional in density functional theory is used to approximate multi-electron interactions. A plethora of different functionals is available, but near…