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Meeting MS&T25: Materials Science & Technology
Symposium Enhancing the Accessibility of Machine Learning-Enabled Experiments
Presentation Title Ptychography Data Pipelines at the Advanced Photon Source
Author(s) Steven Henke, Hannah Parraga, Albert Vong, Oliver Hoidn, Nicholas Schwarz
On-Site Speaker (Planned) Steven Henke
Abstract Scope Ptychography is an imaging technique that is used to characterize the nanostructure of complex materials, devices, and biological samples. The recently upgraded Advanced Photon Source (APS) delivers a substantially brighter, more coherent beam, which particularly benefits ptychographic techniques. Accordingly, APS now features approximately ten specialized ptychography instruments, each capable of exceeding 10 TB of raw data production per day. To keep pace with this prolific data generation, we are developing (1) pipelines to leverage edge and leadership computing resources for automated processing during data acquisition, (2) a machine learning model called PtychoPINN to increase processing throughput, and (3) a user-friendly analysis application called Ptychodus to make the advanced algorithms and workflows portable across instruments and accessible to general users. These tools ensure that facility users can maximize the scientific output of their current experiments and pave the way for future innovations in experiment automation.

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

Accelerating Scientific Discovery with Machine Learning: Data Analysis for Computational Beamlines
Adaptive Workflows for Lab of the Future
ATOMIC: Autonomous Characterization of 2D Materials Through Foundation Models
Autonomous Atomic Force Microscopy using Large Language Model Agents
DiffractGPT: Atomic Structure Determination from X-ray Diffraction Patterns Using a Generative Pretrained Transformer
Foundational Workflows for Processing Legacy Data and Realizing Domain-Specific Multi-Modal AI Models
From automated to autonomous – creating a general active learning service for self-driving laboratories
High-throughput, Ultra-fast Laser Sintering of Ceramics and Machine-learning Based Prediction on Processing-Microstructure-Property Relationships
Hypothesis Formation and Predictive Modeling of 2D Perovskite Spacer Cations Using Retrieval Augmented LLMs and Deep Kernel Learning
Ptychography Data Pipelines at the Advanced Photon Source
Pycroscopy, AEcroscopy, and data workflows: integrating customized control, data analysis and workflows in an autonomous microscopy facility

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