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

Journal Article · · Integrating Materials and Manufacturing Innovation
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  1. Case Western Reserve University, Cleveland, OH (United States)
  2. Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States). Physical and Life Sciences Directorate
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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.

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; 1079242
Journal Information:
Integrating Materials and Manufacturing Innovation, Vol. N/A, Issue N/A; ISSN 2193-9764
Publisher:
SpringerCopyright Statement
Country of Publication:
United States
Language:
English

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36 MATERIALS SCIENCE
image analysis
particle growth kinetics
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