Weekly seminars with guest speakers.

Thursdays 9:00AM - 10:00AM Tech M345

Juan de Pablo (Mah Lecture)

UChicago

Host: Randy Snurr

Additional lecture and reception held on October 16th

Soft matter design and characterization in the era of machine learning

Wednesday October 16th

Advances in molecular modeling algorithms, optimization strategies, and machine learning techniques, are 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. The way in which problems and questions are formulated is rapidly changing, and it is important to rethink the role of research scientists and engineers in the context of these advances. In this presentation I will illustrate some of these ideas by relying on a variety of examples taken from chemical engineering, physics, biology and materials science. In the first, I will discuss the coupling of experiments and molecular models, and how that coupling can be used to extract additional information from experiments that would otherwise be difficult to generate. In the second I will present models of biological systems - DNA and chromatin - that use machine learning to integrate experimental and computational information form a wide range of sources, and explain how the resulting information can be used to address important questions in epigenetics. In the third, I will discuss how evolutionary optimization and machine learning can be used to create new mechanical metamaterials with useful and unusual mechanical properties.

Liquid crystals - from simple self-assembling systems, to autonomous materials constructs

Thursday, October 17th

Polymeric materials that comprise mechano-chemically active components are able to undergo spontaneous structural rearrangements that generate internal stresses and motion. These stresses can be particularly large in the case of liquid crystalline polymers, where elasticity becomes important. At intermediate to high concentrations, such materials form nematic phases that are riddled with defects that serve as attractors for solutes or colloidal particles. As such, defects can also be used for directed self-assembly. Going beyond passive nematic systems, introducing internal activity leads to the emergence of new structural and dynamical features that are not found in materials at rest. Understanding how specific behaviors arise in active liquid crystals is important for design of autonomous materials systems capable of delivering desired functionalities, including the possibility of transporting colloidal particles in a programable manner. This lecture will focus on the relationship between structure, activity, and motion in lyotropic liquid crystalline polymeric systems that include colloidal particles. More specifically, results will be presented for actin and tubulin suspensions, where activity is generated by protein motors. A distinctive feature of these biopolymers is that characteristic contour lengths can range from hundreds of nanometers to tens of microns, thereby making them amenable for study by optical microscopy. By relying on molecular and meso-scale models, it is possible to arrive at a comprehensive description of these suspensions that helps explain the connections between molecular structure, the formation and shape of distinct topological defects, the localization of particles in such defects, activity, and defect dynamics. One of the outcomes of such a description is the realization that hydrodynamic interactions can in some cases exacerbate or mitigate the elasticity of the underlying materials, leading to non-intuitive phenomena that do not arise at equilibrium. These findings raise the prospect that, by balancing such effects, it might be possible to design functional materials where specific, autonomous macroscopic dynamical responses are programmed into a system to create function.