pseudo4D-analysis-guide

The published notebooks are a guide for users analyzing pseudo-4D data. The goal is to share the code and methods used for this research. We hope this will provide a useful starting point for scientists planning to do their own studies.

Chao, P., Lindemann, G. R., Hunter, A. H., & Shahani, A. J. (2022). Pseudo-4D view of the growth and form of locked eutectic colonies. Acta Materialia, 118335. https://doi.org/10.48550/arXiv.2206.11667

_{Abstract: We investigate solidification of an Al-Cu alloy as a model system to understand the emergence of patterns (such as lamellar, rod and maze-like) within eutectic colonies. To uncover the morphological transitions in situ and in 3D, we introduce here a new synchrotron-based procedure termed pseudo-4D X-ray imaging. Our method simultaneously maximizes the temporal (200 ms) and spatial resolution (0.69 um²/pixel) over that of traditional imaging approaches. The wealth of information obtained from this procedure enables us to visualize the development of a crystallographically ‘locked’ eutectic microstructure in the presence of thermosolutal convection. This data provides direct insight into the mechanism of the lamella-to-rod transition as the eutectic accommodates fluctuations in interfacial composition and growth velocity. We offer evidence to show that this transition is diffusive. It is brought about by impurity-driven forces acting on the solid-solid-liquid trijunction that must overcome the stiffness of the solid-solid interfaces. Our pseudo-4D imaging strategy holds broad appeal to the solidification science community, as it can overcome the space-time trade-off in conventional in situ X-ray microtomography.}

About

While the analysis was done in Matlab, Jupyter notebooks are an excellent format to share equations, computational output, visualizations, and other multimedia resources, along with explanatory text in a single document. Furthermore, it is very convenient to share and view the notebook in Github. As such, all codes are set up in Matlab-Jupyter in an effort to create a clear and understandable workflow.

The data can be accessed online through XX

Support

Reach out to the maintainer at the email located in their GitHub profile

License

This project is licensed under the MIT license. Feel free to edit and distribute as you like. Please reference the scientific publication in addition to this repository if you found this work useful.

See LICENSE for more information.

Acknowledgements

This project was completed during my time at the University of Michigan as a PhD student in the Shahani Group.

_{AJS and PC gratefully acknowledge financial support from the National Science Foundation (NSF) CAREER program under Award No. 1847855. GRL acknowledges support from the Air Force Office of Scientific Research (AFOSR) under Award No. FA9550-21-1-0260. We thank Dr. Caleb Reese, Aaron Gladstein, Dr. Francesco De Carlo, and Pavel Shevshenko for assisting in the synchrotron-based experiment. We also thank Drs. Silvère Akamatsu and Sabine Bottin-Rousseau for fruitful discussions. This research used resources of the Advanced Photon Source, a U.S. Department of Energy (DOE) Office of Science User Facility operated for the DOE Office of Science by Argonne National Laboratory under Contract No. DE-AC02-06CH11357. We acknowledge the University of Michigan College of Engineering for financial support and the Michigan Center for Materials Characterization for use of the instruments and Bobby Kerns, Dr. Nancy Senabulya Muyanja, Dr. Tao Ma, and Dr. Haiping Sun for their assistance.}

Thanks for these awesome resources that were used during the development of this repo

• https://thoughtbot.com/blog/how-to-write-a-great-readme