Computations in Science Seminars

Previous Talks: 2018

Jan 2018
10
Wed 12:15
Heinrich Jaeger, University of Chicago
e-mail:
The plot thickens: From discontinuous shear thickening to shear jamming

Over the last few years dense suspensions of hard particles in a simple liquid have become a model system in the soft condensed matter, granular materials, and rheology communities for the investigation of strongly non-Newtonian behavior. A key aspect underlying the recent surge of activity has been the realization that in addition to hydrodynamic interactions direct frictional contact between particles can occur. In fact, friction forces were found to be essential in order to explain some of the most striking phenomena observed in dense suspensions, such as an abrupt, essentially discontinuous onset of shear thickening, whereby the viscosity can jump up by over an order of magnitude as a critical shear rate is exceeded. So far, however, practically all theoretical models and simulations that include friction have treated it as a phenomenological parameter without considering its molecular origin. Furthermore, most models treated a situation in which shear is applied continuously, under steady-state conditions. This prevented these approaches from capturing the remarkable dynamic phenomena observed in dense suspensions, most notably the propagating jamming fronts associated with the transition from a merely shear-thickened to a solid-like jammed state. Thus, despite much recent progress, there remain fundamental questions both at the nano-scale, about the nature of the frictional interactions, and at the macro-scale, about the relation between steady-state and transient dynamic phenomena.

I will discuss recent experiments from our group that address these questions, focusing on the differences between discontinuous shear thickening (DST) and shear jamming (SJ). These experiments show how particle surface chemistry can play a central role in creating conditions that allow for SJ. We find the system’s ability to form interparticle hydrogen bonds when sheared into contact elicits SJ. We demonstrate this with charge stabilized polymer microspheres and non-spherical cornstarch particles, controlling hydrogen bond formation with solvents. The propensity for SJ is quantified by tensile tests and can be linked directly to an enhancement of the effective frictional interactions between particles, as measured by AFM and also observed by mapping out the steady-state rheology as a function of packing fraction.

Jan 2018
17
Wed 12:15
James Evans, University of Chicago
e-mail:
Host: William Irvine ()
Organizer: Delphine Coursault ()
Social Limits to Understanding

I provide an overview of my research tracing several ways in which social connection between scientists, engineers and citizens shape the limits of what a population can collectively know. This includes empirical demonstrations of how centralized networks decrease the truth value of collective certainty in biomedicine, how large teams shrink the search space of science and technology, and how flocking correlates investigations and limits the size of future understanding. I then explore how the complex system of science, technology and society generates productive social disconnection to accelerate advance through maintaining crossable boundaries between disciplines, ideologies, and the ways in which recombination are valued. To explore this last point, I model scientific discovery and technological invention as involved in the complex combination of contents including problems, methods and physical entities, which bridge contexts such as journals, subfields and conferences from which scientists and inventors drawn them. We can model the normal growth of ideas in articles and inventions by representing them as complex combinations of scientific and technical contents and contexts with a high-dimensional stochastic block model, which predicts more than 95% of new patents and articles in biomedicine and physics. The inverse probability of published papers and patents under this model--unlikely combinations of contents across contexts--predicts nearly 50% of the likelihood of revolutionary success, measured by outsized citations and major awards. I discuss the implication of these findings for science policy and practice.