Polypyrrole (PPy) is a conducting polymer with a wide range of applications such as supercapacitors, sensors, batteries, actuators, and neural prosthetics. PPy is a popular polymer in experimentation not so easily accessed in computational modeling efforts. As such modeling and algorithmic improvements are crucial in its study. Presented here are both a novel coarse grain model for oxidized PPy and its efficient and scalable computing implementation of a Monte Carlo study of the energetics and thermodynamics of the PPy condensed phases. Systems containing 103 to 105 particles have been meticulously implemented in a range of computer platforms ranging from desktop class computing hardware to high performance clusters equipped with multiple GPUs. Our implementation utilizes a combination of CPUs and GPUs depending on system size. Reported properties are the density, enthalpy, cohesive energy, compressibility, thermal expansivity, Hildebrand solubility parameter, bulk modulus, and pair correlation functions at ambient conditions. All properties are consistent across the studied system sizes and in good agreement with experimental values if available. *Acknowledgment: Partial past support from the National Science Foundation, grant CHE-062611.
Journal: TechConnect Briefs
Volume: TechConnect Briefs 2022
Published: June 13, 2022
Pages: 197 - 200
Industry sector: Advanced Materials & Manufacturing
Topics: Informatics, Modeling & Simulation, Modeling & Simulation of Microsystems