MRS Meetings and Events

 

MD02.07.08 2023 MRS Spring Meeting

A Workflow to Track Time-Resolved Dislocation Behavior in High Temperature Aluminum

When and Where

Apr 13, 2023
5:00pm - 7:00pm

Moscone West, Level 1, Exhibit Hall

Presenter

Co-Author(s)

Holland Stacey1,Naomi Mo1,Lichao Fang1,Leora Dresselhaus-Marais1

Stanford University1

Abstract

Holland Stacey1,Naomi Mo1,Lichao Fang1,Leora Dresselhaus-Marais1

Stanford University1
<br/>Studying dislocation behavior furthers our understanding of their effects on the mechanical, thermal, and electronic properties of materials. Previous observation-based research on dislocation motion has primarily been conducted with TEM and thus typically concerns dislocations near or at the surface (&lt; 2 μm thick foils). While models for subsurface dislocation movement exist, many of these models have yet to be validated by experiments with comparable samples. Dark-Field X-Ray Microscopy (DFXM) is a new technique developed in the last decade to study subsurface dislocations. We use DFXM to track deep subsurface dislocations approximately 200 μm beneath the surface of single crystalline FCC aluminum at 96% of the melting temperature. In this work, we present a 5-step workflow to automatically track time-resolved dislocation movement in DFXM scans, including a Stationary Wavelet Transform (SWT) approach, convolution kernels, adaptive thresholding, structuring elements, and an image segmentation tool. This workflow allows us to identify and quantify the position of dislocations in DFXM images over time, paving the way to discovering more about dislocation dynamics at tri-junctions.

Keywords

Al | dislocations | grain boundaries

Symposium Organizers

Soumendu Bagchi, Los Alamos National Laboratory
Huck Beng Chew, The University of Illinois at Urbana-Champaign
Haoran Wang, Utah State University
Jiaxin Zhang, Oak Ridge National Laboratory

Symposium Support

Bronze
Patterns and Matter, Cell Press

Session Chairs

Soumendu Bagchi
Haoran Wang

In this Session

MD02.07.01
Automated Defect Analysis of CdSe Nanoparticles through Supervised Learning with Large Simulated Databases

MD02.07.02
STEM Image Analysis Based on Deep Learning—Identification of Vacancy of Defects and Polymorphs of MoS2

MD02.07.03
Beyond Single Molecules: Intermolecular Interference Effects

MD02.07.04
Insight into the Reactivity of Electrocatalytic Glycerol Oxidation—The Strength of the Hydroxyl Group Bonding on Surface

MD02.07.05
Ripplocation Boundaries and Kink Boundaries in Layered Solids

MD02.07.06
Data-Driven Electrode Optimization for Vanadium Redox Flow Battery by Reduced Order Model

MD02.07.07
Application of Baysian Super Resolution to Spectroscopic Data Analysis

MD02.07.08
A Workflow to Track Time-Resolved Dislocation Behavior in High Temperature Aluminum

MD02.07.09
Investigation of Solidification in Supercooled Water Drops using Large Data Sets of Synchronized Optical Images and X-ray Diffraction Patterns

MD02.07.10
Characterizing Dislocations by formulating the Invisibility Criterion for DFXM

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Publishing Alliance

MRS publishes with Springer Nature