W. N. Lacey Lectureship in Chemical Engineering

The advent of innovative molecular modeling algorithms, optimization strategies, and machine learning techniques is ushering a new era of materials science and engineering in which computational tools are routinely used to probe, design, and interrogate matter and functional materials systems. In this presentation I will illustrate some of these ideas in the context of a variety of examples taken from chemical engineering, physics, biology and materials science. In the first, I will discuss the simultaneous interpretation of scattering data from multiple sources by relying on molecular models. In the second I will present models of biological systems that use machine learning to integrate experimental and computational information form a wide range of sources. In the third, I will discuss how evolutionary optimization and machine learning can be used to create new mechanical metamaterials.