30 citations · 76 across the 8 of their papers we have counts for
4 papers · 1 filter
Thermal Stabilization of Defect Charge States and Finite-Temperature Charge Transition Levels
Tobias Hainer, Ethan Berger, Esmée Berger +3
Point defects introduce localized electronic states that critically affect carrier trapping, recombination, and transport in functional materials. The associated charge transition…
Predicting neutron experiments from first principles: A workflow powered by machine learning
Eric Lindgren, Adam J. Jackson, Erik Fransson +6
Machine learning has emerged as a powerful tool in materials discovery, enabling the rapid design of novel materials with tailored properties for countless applications, including…
NEP89: Universal neuroevolution potential for inorganic and organic materials across 89 elements
Ting Liang, Ke Xu, Eric Lindgren +16
While machine-learned interatomic potentials offer near-quantum-mechanical accuracy for atomistic simulations, many are material-specific or computationally intensive, limiting the…
Dynasor 2: From Simulation to Experiment Through Correlation Functions
Esmée Berger, Erik Fransson, Fredrik Eriksson +4
Correlation functions, such as static and dynamic structure factors, offer a versatile approach to analyzing atomic-scale structure and dynamics. By having access to the full dynam…