# Atomistic survey of grain boundary dislocation interactions in FCC Nickel

## TL;DR

This study uses molecular dynamics simulations to analyze how grain boundaries in FCC Nickel influence dislocation transmission, identifying key geometric factors that predict dislocation behavior.

## Contribution

It provides a comprehensive molecular dynamics analysis of 132 dislocation-GB interactions in FCC Nickel and highlights geometric properties as strong predictors of dislocation transmission.

## Key findings

- Geometric criteria effectively predict slip system transmission.
- RBV and grain disorientation are key indicators of dislocation transmission.
- Machine learning identifies geometric properties as stronger predictors than stress.

## Abstract

It is well known that grain boundaries (GBs) have a strong influence on mechanical properties of polycrystalline materials. Not as well-known is how different GBs interact with dislocations to influence dislocation movement. This work presents a molecular dynamics study of 33 different FCC Ni bicrystals, each subjected to four different strain states to induce incident dislocation-GB interactions for 132 unique configurations. The resulting simulations are analyzed to determine properties of the interaction that affect the likelihood of transmission of the dislocation through the GB in an effort to better inform mesoscale models of dislocation movement within polycrystals. It is found that the ability to predict the slip system of a transmitted dislocation using common geometric criteria is confirmed. Furthermore, machine learning processes are implemented revealing that geometric properties, such as the minimum potential residual Burgers vector (RBV) and the disorientation between the two grains, are stronger indicators of whether or not a dislocation would transmit than other properties, such as the resolved shear stress.