Source: Schrödinger
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Integrating AI and Machine Learning to Accelerate Composite Resin Formulation

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This webinar will demonstrate how integrating machine learning with molecular simulation enables faster, more informed development of next-generation resin formulations.

Presented By:

Artificial intelligence and machine learning have entered into everyday usage, but what impact can they have on polymer and ceramic matrix composites development?

Composite performance depends heavily on matrix properties that govern processability and operational stability. Increased digitization is providing clear value across industries, but successful application in composite resin formulations requires a clear understanding of the key questions and insight into the critical design factors. Combining expert know-how and atomic-level detail with powerful artificial intelligence and machine learning tools enables resin formulation teams to maximize successful design initiatives.

This webinar will demonstrate how integrating machine learning with molecular simulation enables faster, more informed development of next-generation resin formulations.

Andrea Browning

Presenter 1:

Andrea Browning

Senior Director of Polymers and Soft Matt, Schrödinger

Andrea Browning, Senior Director of Polymers and Soft Matter at Schrödinger, leads initiatives in polymer and soft matter simulations. Prior to Schrödinger, Andrea was a lead research engineer and project manager at Boeing, where she focused on translating engineering problems into fundamental materials insights. She brings over a decade of experience in connecting industrial and engineering problems to root materials issues and how simulations can be used to inform industrial decisions. Andrea earned her Ph.D. in Chemical Engineering from the University of California, Santa Barbara, where she was a National Science Foundation Graduate Research Fellow.

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