Published October 8, 2019
| Version v0.1
Software
Open
kowarik-labs/AI-reflectivity: v0.1
Description
AI-reflectivity is a code based on artificial neural networks trained with simulated reflectivity data that quickly predicts film parameters from experimental X-ray reflectivity curves. This project has a common root with (ML-reflectivity)[https://github.com/schreiber-lab/ML-reflectivity] and evolved in parallel. Both are linked to the follwoing publication:
Fast Fitting of Reflectivity Data of Growing Thin Films Using Neural Networks A. Greco, V. Starostin, C. Karapanagiotis, A. Hinderhofer, A. Gerlach, L. Pithan, S. Liehr, F. Schreiber, S. Kowarik (2019). J. Appl. Cryst.
For an online live demonstration using a pre-trained network have a look at github
Files
kowarik-labs/AI-reflectivity-v0.1.zip
Files
(6.3 MB)
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Additional details
Related works
- Is supplement to
- https://github.com/kowarik-labs/AI-reflectivity/tree/v0.1 (URL)