Evolutionary Search and Theoretical Study of Silicene Grain Boundaries' Mechanical Properties
Jianan Zhang, Aditya Koneru, Subramanian K. R. S. Sankaranarayanan and, Carmen M. Lilley

TL;DR
This study uses evolutionary algorithms and DFT calculations to predict diverse silicene grain boundary structures, analyze their mechanical properties, and reveal how atomic configurations influence strength and failure behavior.
Contribution
It introduces a novel application of evolutionary algorithms to identify diverse silicene GBs and systematically studies their mechanical properties using DFT.
Findings
Pentagon-heptagon GBs have comparable or higher stiffness than pristine silicene.
Adatoms at specific sites can significantly weaken GB mechanical strength.
GB structures with atoms outside the plane tend to undergo phase transitions before failure.
Abstract
Defects such as grain boundaries (GBs) are almost inevitable during the synthesis process of 2D materials. To take advantage of the fascinating properties of 2D materials, understanding the nature and impact of various GB structures on the pristine 2D sheet is crucial. In this work, using an evolutionary algorithm search, we predict a wide variety of silicene GB structures with very different atomic structures compared to those found in graphene or hexagonal boron-nitride. Twenty-one GBs with the lowest energy were validated by density functional theory (DFT) - a majority of which were previously unreported to our best knowledge. Based on the diversity of the GB predictions, we found that the formation energy and mechanical properties can be dramatically altered by adatoms positions within a GB and certain types of atomic structures, such as four-atom rings. To study the mechanical…
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Taxonomy
TopicsGraphene research and applications · 2D Materials and Applications · Topological Materials and Phenomena
