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Meeting 2024 TMS Annual Meeting & Exhibition
Symposium Novel Strategies for Rapid Acquisition and Processing of Large Datasets from Advanced Characterization Techniques
Presentation Title Understanding Relaxation Dynamics Beyond Equilibrium Using AI-Informed X-ray Photon Correlation Spectroscopy
Author(s) James P. Horwath, Xiao-Min Lin, Hongrui He, Qingteng Zhang, Eric M Dufresne, Miaoqi Chu, Subramanian K.R.S. Sankaranarayanan, Wei Chen, Suresh Narayanan, Mathew J. Cherukara
On-Site Speaker (Planned) James P. Horwath
Abstract Scope X-ray photon correlation spectroscopy (XPCS) is a synchrotron characterization technique which is unique in its ability to capture dynamics in out-of-equilibrium systems on μs-hour time scales and nm-μm length scales using two-time correlation functions (C2). However, the complexity and variability of C2, coupled with the lack of theoretical understanding of non-equilibrium systems, makes establishing connections between dynamics and material properties difficult. Improvements in detection and computing hardware, along with the commissioning of next-generation light sources, compound data analysis problems by drastically increasing the rate of data production. To address the challenges of data reduction and physics extraction from large experimental datasets we have developed an unsupervised deep learning framework for automated classification and interpretation of relaxation dynamics in complex fluids using XPCS C2. We will demonstrate how this approach is used to consider the full distribution of material behavior in experimental data, guide physical model selection, and quantify complex dynamics.
Proceedings Inclusion? Planned:
Keywords Characterization, Machine Learning, Modeling and Simulation

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

A Framework for the Optimal Selection of High-Throughput Data Collection Workflows by Autonomous Experimentation Systems
Advanced Mechanical Properties Prediction of Functionally Graded Materials through High-Throughput Characterization.
Advances in Atom Probe Crystallographic Analysis
Connectivity of Experimental Equipment and Interoperability of Experimental Data: Challenges and Opportunities
Data-driven Discovery of Dynamics from Time-resolved Coherent Scattering
Data Management in Additive Manufacturing – Lessons Learned and Opportunities
Data Management, Data Sharing and the Future of Federal Research Funding
Deep Learning-Driven Semantic Segmentation of large 4D Lab-Scale X-ray Tomography Data for Quantification of Microstructural Features
Directional Reflectance Microscopy: Beyond Conventional Crystal Orientation Mapping
Enabling Uninterrupted In-situ X-ray Experiments through Rapid Data Feedback and On-the-fly Experiment Optimization
G-19: Accessing the Microstructure State Space
G-20: TESCAN TENSOR a 4D-STEM for Multimodal Characterization of Challenging and Interesting Specimens
Galaxy: A Critical Framework for Large Data Volumes and Data-intensive Processing in the Synchrotron World
Hierarchical Bayesian Data Analysis for Accelerating Structural Materials Characterization
HPC+AI@Edge Enabled Real-Time Materials Characterization
Melt Pool Quantification from In Situ Radiography of Directed Energy Deposition of Nickel Superalloys
New Strong and Ductile Titanium-oxygen-iron Alloys Enabled by AM and Insights from Multiscale Microscopy
Probabilistic Orientation Analysis via Direct ODF Calculation from Far Field HEDM
Quantitative 2D and 3D Characterization of Precipitates Microstructure in the Additively Manufactured Titanium Alloy
Real-Time In-Situ Characterization with Web Technologies at Any Scale
Streamlining Engineering Diffraction Analysis Using the MAUD Interface Language Kit (MILK)
Understanding Relaxation Dynamics Beyond Equilibrium Using AI-Informed X-ray Photon Correlation Spectroscopy
Using Video Games for Training Data on Microstructural Design
Utilizing Advanced Computer Vision Techniques Based on Machine Learning and Artificial Neural Networks to Process Micrographs of Ni-base Superalloys
Utilizing Deep Learning Techniques to Accelerate X-ray Absorption and Diffraction Contrast Imaging

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