US scientists bring quantum-level accuracy to molecular modeling

Researchers at the University of Michigan have developed a novel method that significantly enhances the accuracy of molecular modeling by improving density functional theory (DFT), a widely used quantum chemistry simulation approach. DFT simplifies quantum calculations by focusing on electron densities rather than tracking every electron, enabling simulations of larger systems with hundreds of atoms. However, its accuracy has been limited by the need to approximate the exchange-correlation (XC) functional, which governs electron interactions. The University of Michigan team, supported by the US Department of Energy, used quantum many-body theory combined with machine learning to identify a more precise, universal XC functional that can apply broadly across molecules, metals, and semiconductors. This breakthrough addresses a longstanding challenge in quantum chemistry by moving closer to the exact form of the XC functional, which has remained unknown despite its critical role in determining chemical bonds, reactivity, and electrical behavior. The improved functional is material-agnostic, making it valuable for diverse applications such as battery development, drug design, and quantum