About this Abstract |
Meeting |
MS&T22: Materials Science & Technology
|
Symposium
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Grain Boundaries, Interfaces, and Surfaces: Fundamental Structure-Property-Performance Relationships
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Presentation Title |
Understanding Grain Boundary Properties and Transitions in Multiple Dimensions |
Author(s) |
Jian Luo |
On-Site Speaker (Planned) |
Jian Luo |
Abstract Scope |
Understanding and controlling grain boundaries (GBs) in 8+ dimensions – including 5 GB macroscopic degrees of freedom (DOFs), temperature, composition, and external fields – represent great opportunities and challenges. Here, deep learning was combined with atomistic simulations to predict GB properties as functions of five DOFs plus temperature and composition in a 7D space [Materials Today 2020]. Applied electric fields provide yet another dimension to alter the GB structure. We combined AC STEM, DFT calculations, and ab initio molecular dynamics to reveal an electrochemically induced GB transition that can cause enhanced or abnormal grain growth [Nature Communications 2021 & unpublished results]. Data driven prediction the GB properties as functions of four independent compositional degrees of freedoms and temperature in a 5D space for high-entropy alloys (HEAs) have been realized [Materials Horizon 2022]. More recent ongoing investigation of GBs in refractory HEAs and compositionally complex oxides will also be discussed. |