From idea to molecule How agentic AI is changing materials R&D

What if identifying your next high-performance material — and mapping a viable synthetic route — could happen in a fraction of the time it takes today?

Discovering novel molecules for performance materials such as OLEDs remains one of the most resource-intensive challenges in materials R&D. Even when promising candidates are identified, translating them into synthesizable, scalable compounds can slow innovation and increase risk.

At the core of this challenge lies data — fragmented, heterogeneous, and often underleveraged. In this webinar, we explore how integrating high-quality chemical and materials datasets creates a stronger foundation for discovery. Combined with emerging agentic AI systems, these data-driven strategies enable teams to identify promising molecular candidates, assess synthetic feasibility, and iteratively refine pathways with greater confidence.

Rather than simply accelerating screening, this approach connects data, reasoning, and design across the full workflow — from molecular insight to practical synthesis.

Join us to learn how robust data ecosystems, coupled with augmented intelligence, are reshaping materials innovation and driving measurable gains in speed, efficiency, and competitive advantage.