Chemistry

Coupled cluster finite temperature simulations of periodic materials via machine learning

B. Herzog, A. Gallo, et al.

Dive into groundbreaking research by Basile Herzog, Alejandro Gallo, and their colleagues, showcasing a cutting-edge method for finite-temperature coupled cluster simulations of periodic materials. By integrating machine learning with traditional chemistry, they unveil a more efficient approach to predicting thermodynamic properties like CO2 adsorption in zeolites, achieving remarkable accuracy against experimental data. Don't miss out on the future of computational chemistry!