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Meeting 7th World Congress on Integrated Computational Materials Engineering (ICME 2023)
Symposium ICME 2023
Presentation Title Fluoroelastomer Crystallization Kinetics Studied by Deep Learning Segmentation of Atomic Force Microscopy Images
Author(s) Sameera Nalin Venkat, Thomas Ciardi, Jube Augustino, Jayvic Cristian Jimenez, Peter Schlueter, Mingjian Lu, Frank Ernst, Yinghui Wu, Roger H. French, Laura S. Bruckman
On-Site Speaker (Planned) Sameera Nalin Venkat
Abstract Scope Atomic force microscopy (AFM) provides valuable insights into the crystallization of fluoroelastomers, which impacts performance in applications. Time-lapsed acquisition of AFM image sequences provides quantitative information on crystallization kinetics. However, corresponding datasets are large. Open-source software and tools are routinely used for data processing, but it can be time-consuming and challenging to process thousands of images. In this work, we integrate automated feature detection and segmentation algorithms, leveraging evaluation by convolutional neural networks. End-to-end frameworks, such as UNet image segmentation, allows for batch processing such as generating binarized masks which can be used to obtain image properties. This can help in quantifying the projected area fraction of the crystalline phase in each image. It can also track individual crystallites as a function of time when combined with an open-source software for AFM-image processing, which serves as the “ground truth” for comparison.
Proceedings Inclusion? Planned: Other


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3D Phase-field Modelling of Microstructure Evolution During Additive Manufacturing of Multi-component Single Crystal Ni-based Super Alloys
A Computational Tool For Microstructure Development In Multicomponent Alloys During Additive Manufacturing
A Data-driven Approach for Estimating Three-dimensional Microstructural Features of Bainitic Steels Using Phase-field Simulation Results
A Deep Learning Approach for Phase Detection in 2D-XRD Patterns of Ti-6Al-4V
A Framework for Multilevel Robust Co-design of Material and Product Systems
A Generative Adversarial Network for the Creation of Complex 3D Bimodal Polycrystalline Microstructures: Application to Cold-spray Al7050 Alloy
A Machine Learning-based Virtual Lab to Predict Yield Surfaces from Crystal Plasticity Simulation
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A Physics-based Correlation Study of Hot Cracking Phenomenon in the Processes of Additive Manufacturing
A Physics-Informed Multimodal Conditional Generative Model for Linking Process and Microstructure in Metal Additive Manufacturing
A Quantitative Phase Field Tool for Lithium-metal Battery Design
A Software Approach to Predict Creep Behavior in Time and Temperature Dependent Materials
Ab-initio Modelling of Phonon Transport in 2D High Entropy MXene Layers
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Alloy Evaluation and Flow Forming Process Modeling for Net Shape Aerospace Structures
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An Interpretable Machine Learning Model to Predict Molten Salt Corrosion of Compositionally Complex Alloys and Facilitate Understanding of Novel Corrosion Mechanisms
Analysis of AA6061 Cladding Diffusion Bonding Quality for the U-10Mo Monolithic Fuel Using Multi-fidelity Machine Learning Surrogate
Application of Deep Learning Object Detection and Image Segmentation Code Such as YOLO and U-Net for Detection of Helium Bubbles and Voids in Nuclear Reactor Materials
Applications of CALPHAD Based Tools to Additive Manufacturing
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Automated Hierarchical Screening of Refractory Multicomponent Alloys with High Intrinsic Ductility and Surface Passivation Potency
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Building Explainable Models - Determining Process-structure-property Relationships for Friction Stir Processed Metals
Cellular Automaton Simulation of Microstructure and Porosity Formation During Solidification Processing of Aluminum Alloys
Charge-density Based Convolutional Neural Networks for Stacking Fault Energy Prediction in Concentrated Alloys
Chemistry and Processing Prediction for Targeted Microstructure Morphology
Columnar to Equiaxed Transition During Solidification Under Additive Manufacturing Conditions
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Computationally Derived Correlations for Process-induced Cracking During AM of Nickel-based Superalloys
Coupled Thermal-solidification Process Simulation of Sapphire Growth
Damage Prediction of Sintered α-SiC Using Thermo-mechanical Coupled Fracture Model
Data-driven Modeling for Service Lifetime Prediction of Acrylic Polymers
Data-oriented Description of Microstructure-dependent Plastic Material Behavior
Database Design Strategies for Coordinated Simulation and Testing in Additive Manufacturing
Databasing Through the AM Pipeline: From Powder to Part
Decision Support System for Device Fabrication
Deep Learning Enabled Additive Manufacturing (AM) Lattice Segmentation
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Design of 3D-printed Nanocomposite Shields for Efficient EMI Shielding via Finite Element Modelling
Design of Manufacturing Process of Polymer Composite Through Multiscale Cure Analysis Using Bayesian Optimization
Design of Titanium Aluminum Reinforced with TiB2 Composite for Powder Manufacturing Using Integrated Computational Materials Engineering
Designing Aerospace Components with Model-based Definitions to Enable Location-specific Tailoring of Properties
Designing Fatigue Resistance of Metallic Alloys with a Hybrid of Deep Learning and Micromechanics
Development of a Fully Anisotropic Monte Carlo Potts Model to Study Grain Growth
Development of a Roadmap for Computational Materials-informed Qualification and Certification of Process Intensive Metallic Materials
Development of an ML Interatomic Potential for SiC for Extreme Environments
Development of Digital Model Predicting Mechanical Properties of Inconel 718 for Powder Based Additive Manufacturing
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Digital Transformation of Materials Enabled and Accelerated by ICME
Directed Energy Deposition of Al-0.5Sc-0.5Si Alloy: Effect of Thermal Cycles in Microstructure and Mechanical Properties
Discovery of Multi-functional Polyimides through High-throughput Screening using Explainable Machine Learning
Discrete Dislocation Dynamics Simulation Analysis of Plasticity and Size Effect in Additive Manufactured Metals
Discriminative Object Tracking by Domain Contrast
Effect of Cooling Rates on the Evolution of Microstructure, Phase Transformation, and Strain in Ti-6Al-4V Studied by High Speed Synchrotron X-ray Diffraction
Effects of Surface Segregations in Catalytic AgAuCuPdPt High Entropy Alloy
Elastic Constants Predictions in Multi-principal Element Alloys from DFT and Machine Learning
Enabling Molecular Dynamics Simulations of Helium Bubble Formation in Tritium-containing Austenitic Stainless Steels: An Fe-Ni-Cr-H-He Potential
Enhancement of Grain Refinement and Heat Resistance in Tib2-Reinforced Tial Matrix Composite Powder Manufactured by Spark Plasma Sintering
Evolution of Model-based Material Definitions
Examining Phonon Transport in High Entropy Oxides: An Advanced Thermal Barrier Coating Material
ExtremeMat: Quantification of the Effect of Microstructure and Composition on the Creep Rupture Life of Steels
FAIR Data in PMD: Development of MSE Mid-level and Standard-compliant Application Ontologies
First-principles and Data-driven Discovery of High-entropy Alloys for Corrosion Protection
Fluoroelastomer Crystallization Kinetics Studied by Deep Learning Segmentation of Atomic Force Microscopy Images
Geospatiotemporal Modeling of Near Subsurface Temperatures of the Continental United States for Assessment of Materials Degradation
High-throughput Computation and Process Design for Metal Additive Manufacturing
HIP Diffusion Bonding Process Modeling for Fabrication of U-10Mo LEU Fuel
HPC+AI@Edge Enabled Real-time Materials Characterization
ICMD: ICME-based Genomic Materials Design
ICME and ML Framework to Predict the Microstructure During U-10Mo Fuel Fabrication
ICME Design Approach Based on Multi-scale FEM, Phase-field and Ab-initio Simulations
ICME for DNA-templated Dye Aggregate Design for Quantum Information Applications
ICME Modeling of Can Body Stock
Identifying Scaling Laws for Discretization Error in Process-Structure Simulations of Laser Powder Bed Fusion
Image Processing Pipeline for Fluoroelastomer Crystallite Detection in Atomic Force Microscopy Images
Impact of Dendrite Tip Velocity Formulation on Simulated Microstructures of Powder Bed Fusion Ti-6Al-4V
Influence Of Interfacial Voids And Grain Boundary Conductivity On Depletion Kinetics Of Sodium Metal Anodes In All-solid-state Batteries
Integrated Computational Materials Engineering Toolkit to Understand Process-structure-property Relationships of Additively Manufactured Metals
Integrated Framework for Cure-informed Progressive Damage and Failure Analysis of Composite Structures
Integrating Crystal Plasticity and Thermo-mechanical Constitutive Modeling
Intelligent Design & Manufacturing of High-performance Iron Castings Using AI/ML
Irradiance Simulation of Real World Field for PV Backsheets Degradation
Irradiation Effects in MARMOT: Enhancing UO2 Grain Growth Modeling and Validation
Machine-learned Structural Descriptors for Metallic and Covalent Glassy Materials
Machine Intuitive Development of Army Steels - MIDAS
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Machine Learning Driven Prediction of Capacity Fade in Lithium-ion Batteries
Managing Uncertainty in the Strength of Ceramics
Material And Process Parameter Optimization for Additive Manufacturing Using High-throughput Kinetic Simulations
Materials Commons and FAIR Data
Materials Data & Informatics: Curation, Frameworks, Access, and Potential for Discovery and Design
Micromechanical Modeling of Cyclic Damage in Metallic Materials
Microscopy Data Acquisition and Analysis Workflows for Microstructure Quantification
Microstructural Analysis of Stainless Steel SEM Images by Combining EBSD Data and Deep Learning
Microstructural Evolution During Closed Die Forging of UDIMET720 and Prediction of Mechanical Properties
Microstructure-based Modelling Approach to Determine Hydrogen Diffusion and Trapping in Steels
Microstructure-sensitive Materials Design via Efficient Uncertainty Propagation and Process-structure-property Linkages
Microstructure Informed Modelling of Ductile-to-brittle Transition in Ferritic Steels
Microstructure Variability Prediction in Powder Bed Metal Additive Manufacturing
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Predicting the Performance Degradation of Advanced Devices Exposed to Ionizing Radiation
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Towards Deep Learning of Dislocations from TEM Images: The Problem of “Never Enough Training Data”
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True Multiscale Simulations of Virtual Coupon Tests in Composites.
Uncertainty Quantification in Internal Stress Distribution Via Integrated High-energy Synchrotron X-ray Experiments and Crystal Plasticity Simulations
Uncertainty Reduction of Profilometry-based Indentation Plastometry Using Optical Profilometry
Understanding Grain Growth Using a Physics-regularized Interpretable Machine Learning Model
Unravelling the Ultrahigh Modulus of Resilience of Core-Shell SU-8 Nanocomposite Nanopillars Fabricated by Vapor-Phase Infiltration
Using Unsupervised Learning to Identify Small Crack Characteristics and Link to Fatigue Life
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VPSC’s New Clothes: Developing a Modern MATLAB API for Automating High-throughput VPSC Experiments

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