Simu-D: A Simulator-Descriptor Suite for Polymer-Based Systems under Extreme Conditions.

Area of Science:

• Materials Science
• Computational Chemistry
• Polymer Science

Background:

• Atomistic simulations are crucial for understanding material properties.
• Monte Carlo methods are widely used but often limited in applicability.
• Simulating polymers under diverse conditions presents significant challenges.

Purpose of the Study:

• To introduce Simu-D, a software suite for simulating and analyzing polymer systems.
• To enhance the applicability of Monte Carlo methods for diverse conditions.
• To provide tools for identifying local structures in complex polymer assemblies.

Main Methods:

• Development of the Simu-D software suite.
• Implementation of various Monte Carlo algorithms (localized, chain-connectivity-altering, identity-exchange, cluster-based).
• Integration of a descriptor for comparing simulated configurations with reference crystals.

Main Results:

• Simu-D successfully simulates polymer-based nanocomposites, confined assemblies, and grafted macromolecules.
• The software handles various conditions, including bulk, surfaces, and interfaces.
• The descriptor accurately identifies structural similarities to reference crystals.

Conclusions:

• Simu-D offers a versatile platform for simulating polymer systems under extreme conditions.
• The software facilitates the study of phase transitions, adsorption, and self-organization.
• Simu-D enhances the general applicability of Monte Carlo simulations in polymer science.