688 citations · 7.1k across the 80 of their papers we have counts for
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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…