Modeling electric response of materials, a million atoms at a time
Researchers in the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have developed a machine learning framework that can predict with quantum-level accuracy how materials respond to electric fields, up to the scale of a million atoms—vastly accelerating simulations beyond quantum mechanical methods, which can model only a few hundred atoms at a time.
Researchers in the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have developed a machine learning framework that can predict with quantum-level accuracy how materials respond to electric fields, up to the scale of a million atoms—vastly accelerating simulations beyond quantum mechanical methods, which can model only a few hundred atoms at a time.
