Ning-Zheng Li

Exploring the chemical space of transition-metal cluster thermodynamics via automated first-principles calculations and machine learning

Atomic clusters serve as the embryos of materials, yet their enormous and compositionally complex chemical space has long hindered systematic exploration of thermodynamic stability. Here, we show that a unified first-principles and machine-learning framework enables large-scale mapping of transition metal cluster therm...