Physics-informed AI is speeding up molecular simulation—but validation is becoming the bottleneck

A reported hybrid AI framework combining machine learning with quantum mechanical calculations aims to simulate high-pressure chemical reactions far faster—reducing runtimes from months to days. Separately, a physics-informed ML method focuses on keeping AI outputs physically plausible even with sparse data, addressing reliability concerns common in scientific ML.