activity
20052026
most citedCombining GW calculations with exact-exchange density-functional theory: An analysis of valence-band photoemission for compound semiconductors

290 citations · 979 across the 24 of their papers we have counts for

collaborators

26 papers

cond-mat.mtrl-sci2026

Electrostatic Phenomenology Benchmarks for Machine-Learned Interatomic Potentials in Electrochemistry: Beyond the Energy-Force Metric

Barbara Sumić, Ria Vasdev, Sudheesh Kumar Ethirajan +8

Accurate treatment of long-range interactions in machine learning interatomic potentials (MLIPs) is essential for electrochemical simulations. However, aggregate energy and force e…

cond-mat.mtrl-sci2025

User-defined Electrostatic Potentials in DFT Supercell Calculations: Implementation and Application to Electrified Interfaces

Samuel Mattoso, Jing Yang, Florian Deißenbeck +5

Introducing electric fields into density functional theory (DFT) calculations is essential for understanding electrochemical processes, interfacial phenomena, and the behavior of m…

physics.chem-ph2025

Computing Solvation Shell Dynamics and Energetics in Electron Transfer Reactions via Molecular Dynamics Simulations

Zhenyu Wang, Mira Todorova, Christoph Freysoldt +1

Marcus theory is fundamental to describing electron transfer reactions and quantifying their rates, effectively representing the energy surface associated with an electron transfer…

cond-mat.mtrl-sci2024

Roadmap on Data-Centric Materials Science

Stefan Bauer, Peter Benner, Tristan Bereau +58

Science is and always has been based on data, but the terms "data-centric" and the "4th paradigm of" materials research indicate a radical change in how information is retrieved, h…

cond-mat.mtrl-sci2024★ 1 cited

Understanding atom probe's analytical performance for iron oxides using correlation histograms and ab initio calculations

Se-Ho Kim, Shalini Bhatt, Daniel K. Schreiber +4

Field evaporation from ionic or covalently bonded materials often leads to the emission of molecular ions. The metastability of these molecular ions, particularly under the influen…

physics.chem-ph2023★ 20 cited

A machine learning framework for quantifying chemical segregation and microstructural features in atom probe tomography data

Alaukik Saxena, Nikita Polin, Navyanth Kusampudi +7

Atom probe tomography (APT) is ideally suited to characterize and understand the interplay of chemical segregation and microstructure in modern multicomponent materials. Yet, the q…