Machine learning framework accelerates theoretical design of nonlinear optical materials

Machine learning framework accelerates theoretical design of nonlinear optical materials

A research team from the Xinjiang Technical Institute of Physics and Chemistry of the Chinese Academy of Sciences has made strides in the theoretical design of nonlinear optical (NLO) materials by leveraging machine learning techniques. The team introduced a new strategy to explore uncharted chemical spaces, enabling the quantitative prediction of second harmonic generation (SHG) coefficients for complex NLO systems spanning infrared to deep ult…