1 citations · 2 across the 3 of their papers we have counts for
4 papers
qNEP: A highly efficient neuroevolution potential with dynamic charges for large-scale atomistic simulations
Zheyong Fan, Benrui Tang, Esmée Berger +13
Although electrostatics can be incorporated into machine-learned interatomic potentials, existing approaches are computationally very demanding, limiting large-scale, long-time sim…
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…
Revealing the Low Temperature Phase of FAPbI using A Machine-Learned Potential
Sangita Dutta, Erik Fransson, Tobias Hainer +4
FAPbI is a material of interest for its potential in solar cell applications, driven by its remarkable optoelectronic properties. However, the low-temperature phase of FAPbI$_3…
A Morphotropic Phase Boundary in MAFAPbI: Linking Structure, Dynamics, and Electronic Properties
Tobias Hainer, Erik Fransson, Sangita Dutta +2
Understanding the phase behavior of mixed-cation halide perovskites is critical for optimizing their structural stability and optoelectronic performance. Here, we map the phase dia…