Pothos: A Python Package for Polymer Chain Orientation and Microstructure Evolution Monitoring.

Area of Science:

• Materials Science
• Computational Chemistry
• Polymer Science

Background:

• Experimental polymer characterization often requires time-consuming simulations.
• In silico methods can optimize experimental techniques for polymer analysis.
• Accurate determination of polymer crystallites and chain orientation is crucial.

Purpose of the Study:

• To introduce Pothos, a Python package for analyzing polymer crystallites and chain orientation.
• To provide a user-friendly tool for in silico optimization of experimental polymer techniques.
• To support various simulation types, including atomistic and coarse-grained models.

Main Methods:

• Utilizes a modified DBSCAN algorithm to identify crystalline regions in polymer melts.
• Calculates common order parameters (⟨P2⟩, ⟨P4⟩, ⟨P6⟩) based on the chain chord vector.
• Supports analysis of both atomistic and coarse-grained molecular dynamics simulations.

Main Results:

• Successfully determines polymer crystallite structures within molecular dynamics simulations.
• Quantifies chain orientation parameters with high accuracy.
• Outputs analysis results to text and LAMMPS dump files for further investigation.

Conclusions:

• Pothos offers an efficient and accessible method for polymer structure analysis.
• The package facilitates the integration of computational and experimental approaches in polymer science.
• Enables streamlined optimization of experimental polymer characterization through in silico analysis.