TY - JOUR
T1 - Global Optimization of Molybdenum Subnanoclusters on Graphene
T2 - A Consistent Approach toward Catalytic Applications
AU - Wei, Yao
AU - Santana-Bonilla, Alejandro
AU - Kantorovich, Lev
N1 - Publisher Copyright:
© 2024 The Authors. Published by American Chemical Society.
PY - 2024/11/20
Y1 - 2024/11/20
N2 - The development of novel subnanometer clusters (SNCs) catalysts with superior catalytic performance depends on the precise control of clusters’ atomistic sizes, shapes, and accurate deposition onto surfaces. The intrinsic complexity of the adsorption process complicates the ability to achieve an atomistic understanding of the most relevant structure-reactivity relationships hampering the rational design of novel catalytic materials. In most cases, existing computational approaches rely on just a few structures to draw conclusions on clusters’ reactivity thereby neglecting the complexity of the existing energy landscapes thus leading to insufficient sampling and, most likely, unreliable predictions. Moreover, modeling of the actual experimental procedure that is responsible for the deposition of SNCs on surfaces is often not done even though in some cases this procedure may enhance the significance of certain (e.g., metastable) adsorption geometries. This study proposes a novel systematic approach that utilizes global search techniques, specifically, the particle swarm optimization (PSO) method, in conjunction with ab initio calculations, to simulate all stages in the beam experiments, from predicting the most relevant SNCs structures in the beam and on a surface, to their reactivity. To illustrate the main steps of our approach, we consider the deposition of Molybdenum SNC of 6 Mo atoms on a free-standing graphene surface, as well as their catalytic properties with respect to the CO molecule dissociation reaction. Even though our calculations are not exhaustive and serve only to produce an illustration of the method, they are still able to provide insight into the complicated energy landscape of Mo SNCs on graphene demonstrating the catalytic activity of Mo SNCs and the importance of performing statistical sampling of available configurations. This study establishes a reliable procedure for performing theoretical rational design predictions.
AB - The development of novel subnanometer clusters (SNCs) catalysts with superior catalytic performance depends on the precise control of clusters’ atomistic sizes, shapes, and accurate deposition onto surfaces. The intrinsic complexity of the adsorption process complicates the ability to achieve an atomistic understanding of the most relevant structure-reactivity relationships hampering the rational design of novel catalytic materials. In most cases, existing computational approaches rely on just a few structures to draw conclusions on clusters’ reactivity thereby neglecting the complexity of the existing energy landscapes thus leading to insufficient sampling and, most likely, unreliable predictions. Moreover, modeling of the actual experimental procedure that is responsible for the deposition of SNCs on surfaces is often not done even though in some cases this procedure may enhance the significance of certain (e.g., metastable) adsorption geometries. This study proposes a novel systematic approach that utilizes global search techniques, specifically, the particle swarm optimization (PSO) method, in conjunction with ab initio calculations, to simulate all stages in the beam experiments, from predicting the most relevant SNCs structures in the beam and on a surface, to their reactivity. To illustrate the main steps of our approach, we consider the deposition of Molybdenum SNC of 6 Mo atoms on a free-standing graphene surface, as well as their catalytic properties with respect to the CO molecule dissociation reaction. Even though our calculations are not exhaustive and serve only to produce an illustration of the method, they are still able to provide insight into the complicated energy landscape of Mo SNCs on graphene demonstrating the catalytic activity of Mo SNCs and the importance of performing statistical sampling of available configurations. This study establishes a reliable procedure for performing theoretical rational design predictions.
UR - http://www.scopus.com/inward/record.url?scp=85208702900&partnerID=8YFLogxK
U2 - 10.1021/acsami.4c13102
DO - 10.1021/acsami.4c13102
M3 - Article
SN - 1944-8244
VL - 16
SP - 64177
EP - 64189
JO - ACS Applied Materials and Interfaces
JF - ACS Applied Materials and Interfaces
IS - 46
ER -