pywindow: Automated Structural Analysis of Molecular Pores

Area of Science:

• Materials Science
• Computational Chemistry
• Nanotechnology

Background:

• Understanding the structural characteristics of molecular pores is crucial for predicting their behavior in various states.
• Porous molecular materials, including molecular cages, metal-organic polyhedra, and framework materials, possess unique properties influenced by their pore structure.

Purpose of the Study:

• To introduce pywindow, a novel Python package designed for the automated structural analysis of porous molecular materials.
• To enable quantitative assessment of critical pore parameters such as cavity diameter, number and size of windows, and average molecular diameter.
• To facilitate the investigation of material flexibility through the analysis of molecular dynamics trajectories.

Main Methods:

• Development of a Python package, pywindow, for automated structural analysis.
• Implementation of algorithms to calculate cavity diameter, number of windows, window diameters, and average molecular diameter.
• Integration of molecular dynamics trajectory analysis to assess pore flexibility.

Main Results:

• pywindow successfully automates the analysis of structural features in diverse porous molecular materials.
• The package provides quantitative data on pore dimensions and window characteristics.
• Analysis of molecular dynamics trajectories reveals the impact of flexibility on pore behavior.

Conclusions:

• pywindow offers a robust and automated solution for the structural characterization of porous molecular materials.
• The tool is validated for molecular pores, metal-organic polyhedra, and framework materials.
• pywindow is freely accessible, promoting wider adoption in materials research.