688 citations · 7.1k across the 80 of their papers we have counts for
80 papers
Machine Learning-Aided First-Principles Calculations of Redox Potentials
Ryosuke Jinnouchi, Ferenc Karsai, Georg Kresse
Redox potentials of electron transfer reactions are of fundamental importance for the performance and description of electrochemical devices. Despite decades of research, accurate…
Machine learning density functionals from the random-phase approximation
Stefan Riemelmoser, Carla Verdi, Merzuk Kaltak +1
Kohn-Sham density functional theory (DFT) is the standard method for first-principles calculations in computational chemistry and materials science. More accurate theories such as…
How to verify the precision of density-functional-theory implementations via reproducible and universal workflows
Emanuele Bosoni, Louis Beal, Marnik Bercx +42
In the past decades many density-functional theory methods and codes adopting periodic boundary conditions have been developed and are now extensively used in condensed matter phys…
Phaseless auxiliary field quantum Monte Carlo with projector-augmented wave method for solids
Amir Taheridehkordi, Martin Schlipf, Zoran Sukurma +3
We implement the phaseless auxiliary field quantum Monte Carlo method using the plane-wave based projector augmented wave method and explore the accuracy and the feasibility of app…
Benchmark Phaseless Auxiliary-Field Quantum Monte Carlo Method for Small Molecules
Z. Sukurma, M. Schlipf, M. Humer +2
We report a scalable Fortran implementation of the phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) and demonstrate its excellent performance and beneficial scaling with re…
Quantum paraelectricity and structural phase transitions in strontium titanate beyond density-functional theory
Carla Verdi, Luigi Ranalli, Cesare Franchini +1
We demonstrate an approach for calculating temperature-dependent quantum and anharmonic effects with beyond density-functional theory accuracy. By combining machine-learned potenti…
Temperature-dependent anharmonic phonons in quantum paraelectric KTaO by first principles and machine-learned force fields
Luigi Ranalli, Carla Verdi, Lorenzo Monacelli +3
Understanding collective phenomena in quantum materials from first principles is a promising route toward engineering materials properties on demand and designing new functionaliti…
Approaching the basis-set limit of the dRPA correlation energy with explicitly correlated and Projector Augmented-wave methods
Moritz Humer, Michael E. Harding, Martin Schlipf +4
The direct random-phase approximation (dRPA) is used to calculate and compare atomization energies for the HEAT set and 10 selected molecules of the G2-1 set using both plane waves…
Combining Machine Learning and Many-Body Calculations: Coverage-Dependent Adsorption of CO on Rh(111)
Peitao Liu, Jiantao Wang, Noah Avargues +5
Adsorption of carbon monoxide (CO) on transition-metal surfaces is a prototypical process in surface sciences and catalysis. Despite its simplicity, it has posed great challenges t…
Zero-point Renormalization of the Band Gap of Semiconductors and Insulators Using the PAW Method
Manuel Engel, Henrique Miranda, Laurent Chaput +4
We evaluate the zero-point renormalization (ZPR) due to electron-phonon interactions of 28 solids using the projector-augmented-wave (PAW) method. The calculations cover diamond, m…
Core-hole excitations using the projector augmented-wave method and the Bethe-Salpeter equation
Martin Unzog, Alexey Tal, Georg Kresse
We present an implementation of the Bethe-Salpeter equation (BSE) for core-conduction band pairs within the framework of the projector augmented-wave method. For validation, the me…
Thermal transport and phase transitions of zirconia by on-the-fly machine-learned interatomic potentials
Carla Verdi, Ferenc Karsai, Peitao Liu +2
Machine-learned interatomic potentials enable realistic finite temperature calculations of complex materials properties with first-principles accuracy. It is not yet clear, however…
Phase Transitions of Zirconia: Machine-Learned Force Fields Beyond Density Functional Theory
Peitao Liu, Carla Verdi, Ferenc Karsai +1
We present an approach to generate machine-learned force fields (MLFF) with beyond density functional theory (DFT) accuracy. Our approach combines on-the-fly active learning and $Δ…
Optical and excitonic properties of transition metal oxide perovskites by the Bethe-Salpeter equation
Lorenzo Varrassi, Peitao Liu, Zeynep Ergönenc Yavas +3
We present a systematic investigation of the role and importance of excitonic effects on the optical properties of transitions metal oxide perovskites. A representative set of four…
Electronic state unfolding for plane waves: energy bands, Fermi surfaces and spectral functions
David Dirnberger, Georg Kresse, Cesare Franchini +1
Modern computing facilities grant access to first-principles density-functional theory study of complex physical and chemical phenomena in materials, that require large supercell t…
Optimized effective potentials from the random-phase approximation: Accuracy of the quasiparticle approximation
Stefan Riemelmoser, Merzuk Kaltak, Georg Kresse
The optimized effective potential (OEP) method presents an unambiguous way to construct the Kohn-Sham potential corresponding to a given diagrammatic approximation for the exchange…
Local embedding of Coupled Cluster theory into the Random Phase Approximation using plane-waves
Tobias Schäfer, Florian Libisch, Georg Kresse +1
We present an embedding approach to treat local electron correlation effects in periodic environments. In a single, consistent framework, our plane-wave based scheme embeds a local…
New insights into the 1D carbon chain through the RPA
Benjamin Ramberger, Georg Kresse
We investigated the electronic and structural properties of the infinite linear carbon chain (carbyne) using density functional theory (DFT) and the random phase approximation (RPA…
- phase transition of zirconium predicted by on-the-fly machine-learned force field
Peitao Liu, Carla Verdi, Ferenc Karsai +1
The accurate prediction of solid-solid structural phase transitions at finite temperature is a challenging task, since the dynamics is so slow that direct simulations of the phase…
Nonrad: Computing Nonradiative Capture Coefficients from First Principles
Mark E. Turiansky, Audrius Alkauskas, Manuel Engel +5
Point defects in semiconductor crystals provide a means for carriers to recombine nonradiatively. This recombination process impacts the performance of devices. We present the Nonr…
Comparative ab initio study of the structural, electronic, magnetic, and dynamical properties of LiOsO and NaOsO
Peitao Liu, Jiangang He, Bongjae Kim +4
Despite similar chemical compositions, LiOsO and NaOsO exhibit remarkably distinct structural, electronic, magnetic, and spectroscopic properties. At low temperature, LiOsO…
Accurate optical spectra through time-dependent density functional theory based on screening-dependent hybrid functionals
Alexey Tal, Peitao Liu, Georg Kresse +1
We investigate optical absorption spectra obtained through time-dependent density functional theory (TD-DFT) based on nonempirical hybrid functionals that are designed to correctly…
Electron-Phonon Interactions Using the PAW Method and Wannier Functions
Manuel Engel, Martijn Marsman, Cesare Franchini +1
We present an ab-initio density-functional-theory approach for calculating electron-phonon interactions within the projector augmented-wave method. The required electron-phonon mat…
Plane wave basis set correction methods for RPA correlation energies
Stefan Riemelmoser, Merzuk Kaltak, Georg Kresse
Electronic correlation energies from the random-phase approximation converge slowly with respect to the plane wave basis set size. We study the conditions, under which a short-rang…