Abstract
Diffusion Monte Carlo (DMC) calculations have been performed to study the adsorption of a single Pt atom on pristine graphene. We obtain the adsorption energy curves of a single Pt atom adsorbed at three different adsorption sites (bridge, on-top, hollow) as functions of the vertical distance from a graphene surface for both spin singlet and triplet states. The bridge-site adsorption in a singlet spin state is found to be energetically most stable, which is consistent with previous theoretical predictions. As the Pt atom moves away from a graphene surface, spin triplet states are favored over spin singlet states for all three adsorption sites, reflecting that the ground state of an isolated Pt atom is in a spin triplet state. Furthermore, our DMC calculations reveal local-minimum features in the triplet region which is understood to be due to van der Waals interaction between the Pt atom and graphene. This provides a comprehensive understanding for a spin crossing from a physisorbed triplet state to a chemisorbed singlet state in the adsorption process of a single Pt atom on graphene.
Original language | English |
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Pages (from-to) | 22147-22154 |
Number of pages | 8 |
Journal | Physical Chemistry Chemical Physics |
Volume | 23 |
Issue number | 38 |
DOIs | |
State | Published - Oct 14 2021 |
Externally published | Yes |
Funding
This paper was supported by Konkuk University in 2019. We also acknowledge the support from the Supercomputing Center/Korea Institute of Science and Technology Information with supercomputing resources (KSC-2019-CRE-0200) that were used for DFT-PBE calculations. H.S and A.B were supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division, as part of the Computational Materials Sciences Program and Center for Predictive Simulation of Functional Materials. An award of computer time was provided by the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program and was used to generate all DMC results. This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under contract DE-AC02-06CH11357.