New Methods for Molecular Simulation of Polymeric Materials

This collaborative research, hosted by Carleton University and featuring an intern from Jagiellonian University, aims to deepen our understanding of polyurethane copolymers, specifically focusing on their shape memory properties. The project employs Neural Network Potentials (NNPs) for advanced computational simulations. The intern will be trained on molecular simulations using Neural Network Potentails using Digital Alliance facilities at Carleton University. The core scientific objectives involve constructing and parametrizing computational models for polyurethane copolymers, emphasizing a fundamental sequence of monomer subunits of polycaprolactone diol and hexamethylene diisocyanate. The subsequent evaluation phase includes meticulous test calculations and a comparative analysis with literature data to validate model accuracy. The final phase encompasses simulations and analyses of polymer shape deformation, particularly focusing on the scientific intricacies of hydrogen bonds. This collaborative research contributes to our scientific understanding and establish a new collaboration between researchers in Poland and Canada around the simulation of shape-deformation polymers.

Faculty Supervisor:

Christopher Rowley

Student:

Partner:

Jagiellonian University in Krakow

Discipline:

Physics

Sector:

Education

University:

Carleton University

Program: