Accelerated Polymer Electronics Development Through Artificial Intelligence-Powered Autonomous Experimentation (AI/AE)

The rapid growth of global electronics requires significant advancements in material innovation, particularly in the development of materials with specific, targeted properties. Polymer-based electronics, with their unique characteristics such as flexibility, biocompatibility, self-healing, degradability, and mixed electron-ion conductivity, have unlocked transformative applications in skin-like devices, biosensors, printed electronics, and neuromorphic computing. However, the traditional R&D process for developing these materials is time-intensive, often requiring years of research, testing, and validation to reach market readiness. Recent breakthroughs in AI-powered autonomous experimentation (AI/AE) present a promising solution to accelerate this process. By integrating automated experimentation with AI-driven planning, AI/AE enables a faster, data-driven design-validation cycle, significantly reducing development time. In this talk, I will present recent innovations in sustainable polymer electronics and discuss how AI/AE accelerates the cycle from design hypothesis to experimental validation.