Real-time dynamics and structures of supported subnanometer catalysts via multiscale simulations

Understanding the performance of subnanometer catalysts and how catalyst treatment and exposure to spectroscopic probe molecules change the structure requires accurate structure determination under working conditions. Experiments lack simultaneous temporal and spatial resolution and could alter the structure, and similar challenges hinder first-principles calculations from answering these questions. Here, we introduce a multiscale modeling framework to follow the evolution of subnanometer clusters at experimentally relevant time scales. We demonstrate its feasibility on Pd adsorbed on CeO2(111) at various catalyst loadings, temperatures, and exposures to CO. We show that sintering occurs in seconds even at room temperature and is mainly driven by free energy reduction. It leads to a kinetically (far from equilibrium) frozen ensemble of quasi-two-dimensional structures that CO chemisorption and infrared experiments probe. CO adsorption makes structures flatter and smaller. High temperatures drive very rapid sintering toward larger, stable/metastable equilibrium structures, where CO induces secondary structure changes only. Understanding the catalysts' structure evolution under working conditions is challenging. Here the authors use a multiscale simulation approach and machine learning to study the structures and nucleation of CeO2-supported Pd clusters and single atoms at various catalyst loadings, temperatures, and exposures to CO.

Automated summary

Understanding the evolution of the catalyst's structure under working conditions is challenging. The study introduces a multiscale modeling framework and machine learning to investigate the structures and nucleation of CeO2-supported Pd clusters and single atoms at different catalyst loadings, temperatures, and exposures to CO. Experimental data lacks simultaneous temporal and spatial resolution, hindering accurate structure determination.