19 projects
M3Learning-Util
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DataFed-TorchFlow
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RHEED-Learn
RHEED-Learn is a Python package for analyzing and visualizing Reflection High-Energy Electron Diffraction (RHEED) data, designed to streamline the processing of thin-film growth data and assist with materials characterization.
Auto4DSTEM
Incorporating Developed Cycle-Consistent-Spatial-Transforming Autoencoder for 4-D STEM analysis.
AFM-Learn
A Python package for visualizing and analyzing Atomic Force Microscopy(AFM) and Piezoelectric Force Microscopy(PFM) experimental data, offering tools to process, visualize, and extract meaningful insights from AFM images and measurements.
XRD-Learn
A Python package for visualizing and analyzing X-ray Diffraction (XRD) experimental data, providing tools to process, visualize, and extract meaningful insights from XRD patterns and measurements.
Plume-Learn
A Python package for visualizing and analyzing plume dynamics during thin-film growth, providing tools to process, visualize, and extract meaningful insights from in-situ plume images captured during Pulsed Laser Deposition (PLD) experiments.
MEM679-snake
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AutoPhysLearn
A python package for physics constrained machine learning by the M3-learning research group at Drexel University
ENGR131-Util-2024
Drexel Midterm Utility Functions
drexel-jupyter-logger
drexel jupyter logger package
ENGR131-2024
ENGR131_2024 package
Wallpaper-Group-Symmetry-Dataset
A Python toolkit for generating and analyzing symmetry datasets, based on the mathematical symmetry principle of wallpaper groups.
m3-learning
Tutorials, Projects, and datasets from the M3-learning research group
sci-memex
Scientific Data Memex
Engr131-Winter-2022
Utilities for ENGR131
Engr-131-util
Utilities for ENGR131
DeepMatter
Tool for machine learning in materials Science
Recursive-Symmetry-Aware-Materials-Microstructure-Explorer
Tool for recursive symmetry aware searching of materials microstructure images
