To accurately predict grain boundary (GB) atomic structures and their energetics in CdTe, the present study constructs an artificial-neural-network (ANN) interatomic potential. To cover a wide range of atomic environments,...
ABSTRACTWe have studied the photoconductivity of grain boundaries in p–type silicon. The result demonstrates the applicability of the technique for the measurement of minority carrier recombination velocity at the grain boundary. The experimental data are consistent with the thought that the recombination velocity increases with the boundary state density and light intensity.
Application of machine learning potentials to predict grain boundary properties in fcc elemental metals
