Accelerating Sustainable Product Development in the Plastics Industry: A Machine Learning Approach for Polymer-Additive Interactions

Oligomaster Inc. is developing a Sustainable Product Development Tool that leverages molecular simulation and machine learning to streamline the formulation process for plastic and chemical manufacturers. As industry moves towards sustainable alternatives and faces tighter regulations on certain chemicals, including harmful plasticizers, traditional trial-and-error methods of formulation are no longer efficient or economically viable. This tool will enable manufacturers to predict and analyze interactions between polymers and plasticizers at a molecular level, providing insight into how alternative materials perform without extensive laboratory testing. By incorporating machine learning, the tool can learn from each simulation, improving accuracy and speed over time. This eliminates the need for repetitive and time-consuming experimental studies, allowing product developers to move quickly from concept to market-ready solutions. Additionally, the tool supports manufacturers in selecting safer, environmentally friendly plasticizers, aligning with sustainability goals and new environmental standards. Ultimately, Oligomaster’s tool empowers the industry to innovate responsibly, reducing product development cycles and minimizing the environmental footprint of plastic products. With sustainable chemistry becoming critical in global markets, this technology will be indispensable for companies looking to lead in eco-friendly product development while maintaining efficiency and compliance.

Faculty Supervisor:

Li Xi

Student:

Partner:

Oligomaster Inc

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

McMaster University

Program: