Coding Chemistry: How AI is Rewriting Polymer Design

What if polymer discovery could be accelerated with experiments, simulations, and AI continuously informing one another in a closed loop? Join Adam Gormley of Rutgers University and Plexymer, Inc. and Arthi Jayaraman of the University of Delaware to learn how self-driving laboratories and hybrid modeling approaches are converging to transform the way we design, understand, and deploy polymer materials.

First, Adam Gormley will present on the development of a self-driving biomaterials laboratory, a closed-loop platform that integrates synthesis, characterization, and AI-guided decision-making to rapidly explore vast design spaces. By coupling molecular modeling, simulation, and machine learning with automated experimentation, this approach accelerates the identification of polymer systems that function in harmony with biological complexity.

Then, Arthi Jayaraman will demonstrate how physics-based modeling and data-driven methods can be combined to elucidate structure–property relationships in polymeric materials. Using case studies from industry and academic labs, she will show how integrating chemical intuition with machine learning enables faster design, synthesis, and optimization of high-performance polymer systems.

This ACS Webinar is moderated by Dominik Konkolewicz of the Miami University and co-produced with the Polymeric Materials: Science and Engineering (PMSE) Division at the American Chemical Society.

What You Will Learn

• How AI/ML and automation are transforming polymer biomaterials design
• How self-driving labs work
• How you can build your own self-driving lab
• When to apply machine learning vs. molecular modeling and simulation
• Key challenges in polymer characterization data and how to address them
• Strategies for effective collaboration across chemistry, materials science, and data science

Event Details

• Thursday, April 30, 2026 @ 2-3:30pm ET
• Free to attend
• Slides will be available on day of the webinar

Co-Produced With

Division of Polymeric Materials: Science and Engineering