Leveraging machine learning in the innovation of functional materials

The development of novel functional materials holds enormous potential in various fields. This preview highlights the application of theoretical methods and machine learning techniques in a recent issue of Patterns, focusing on the exploration of two-dimensional doped tellurene and the efficient screening of suitable candidates for fin field-effect transistors. The development of novel functional materials holds enormous potential in various fields. This preview highlights the application of theoretical methods and machine learning techniques in a recent issue of Patterns, focusing on the exploration of two-dimensional doped tellurene and the efficient screening of suitable candidates for fin field-effect transistors.