Supervised ML framework for nanofiber orientation prediction. Many biological, bioinspired and synthetic materials exhibit/contain/are made of 3D networks of textured nanofibers. Their structure and properties are closely related to the fiber orientations (probabily more than one groups) within them.
We have a first step on trying to tackle orientation analysis problem with the supervised machine learning methods from the radially integrated 1D WAXD data. ML methods are probably to become a more convinient way to the automation of orientation analysis. This repository contains related code and data.