nanoNET: Machine Learning Platform for Predicting Nanoparticles Distribution in a Polymer Matrix

We have RDF data of each simulation in cartesian coordinate saved in folder named "rdf".

All the cartesian coordinate data are converted to respective RDF plots and saved in the folder "figures".

Each simulaion is done by varying five set of parameters namely 'Interaction Between Polymer and NP','Interaction Between NP and NP','Size of the NP','Number Density of NP','Chain Length of Polymer'. The csv file "input.csv" has set of all the combination of these features used for our simulation.

RDF plots and their corresponding simulation parameters are shown in the "to_get_graphs" file.

The nanoNET has two parts namely "autoencoder" and "Random_Forest".