A General Materials Data Science Framework for Quantitative 2D Analysis of Particle Growth from Image Sequences

Nalin Venkat, Sameera; Ciardi, Thomas G.; Lu, Mingjian; DeLeo, Preston C.; Augustino, Jube; Goodman, Adam; Jimenez, Jayvic Cristian; Mondal, Anirban; Ernst, Frank; Orme, Christine A.; Wu, Yinghui; French, Roger H.; Bruckman, Laura S.

doi:10.1007/s40192-024-00342-w

A General Materials Data Science Framework for Quantitative 2D Analysis of Particle Growth from Image Sequences

Journal Article · Tue Feb 20 00:00:00 EST 2024 · Integrating Materials and Manufacturing Innovation

DOI:https://doi.org/10.1007/s40192-024-00342-w· OSTI ID:2309826

; ; ; DeLeo, Preston C.; Augustino, Jube; Goodman, Adam; ; ; ; ; ; ;

Abstract

Phase transformations are a challenging problem in materials science, which lead to changes in properties and may impact performance of material systems in various applications. We introduce a general framework for the analysis of particle growth kinetics by utilizing concepts from machine learning and graph theory. As a model system, we use image sequences of atomic force microscopy showing the crystallization of an amorphous fluoroelastomer film. To identify crystalline particles in an amorphous matrix and track the temporal evolution of the particle dispersion, we have developed quantitative methods of 2D analysis. 700 image sequences were analyzed using a neural network architecture, achieving 0.97 pixel-wise classification accuracy as a measure of the correctly classified pixels. The growth kinetics of isolated and impinged particles were tracked throughout time using these image sequences. The relationship between image sequences and spatiotemporal graph representations was explored to identify the proximity of crystallites from each other. The framework enables the analysis of all image sequences without the requirement of sampling for specific particles or timesteps for various materials systems.

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Research Organization:: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: AC52-07NA27344; NA0004104

OSTI ID:: 2309826

Alternate ID(s):: OSTI ID: 2316116

Report Number(s):: LLNL--JRNL-854818; PII: 342

Journal Information:: Integrating Materials and Manufacturing Innovation, Journal Name: Integrating Materials and Manufacturing Innovation Journal Issue: 1 Vol. 13; ISSN 2193-9764

Publisher:: Springer Science + Business MediaCopyright Statement

Country of Publication:: Germany

Language:: English

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