4 papers
A Combined Theoretical and Experimental Study of Oxygen Vacancies in CoO for Liquid-Phase Oxidation Catalysis
Amir Omranpour, Lea Kämmerer, Catalina Leiva-Leroy +12
In the present work, we investigate oxygen vacancies (V) in CoO, both in the bulk phase and under liquid-phase ethylene glycol oxidation, by combining theoreti…
Insights into the Structure and Dynamics of Water at CoO(001) Using a High-Dimensional Neural Network Potential
Amir Omranpour, Jörg Behler
CoO is an important catalyst for the oxidation of organic molecules in the liquid phase. Still, understanding the atomistic details of CoO-water interfaces under op…
Machine Learning Potentials for Heterogeneous Catalysis
Amir Omranpour, Jan Elsner, K. Nikolas Lausch +1
The sustainable production of many bulk chemicals relies on heterogeneous catalysis. The rational design or improvement of the required catalysts critically depends on insights int…
A High-Dimensional Neural Network Potential for CoO
Amir Omranpour, Jörg Behler
The CoO spinel is an important material in oxidation catalysis. Its properties under catalytic conditions, i.e., at finite temperatures, can be studied by molecular dynamic…