Mechanics of Active Networks – Lessons from Fire Ant Aggregations

Sridhar, Shankar Lalitha; Vernerey, Franck; Fernandez-Nieves, Alberto; Shen, Tong

Title:

Mechanics of Active Networks – Lessons from Fire Ant Aggregations

dc.contributor.author	Sridhar, Shankar Lalitha
dc.contributor.author	Vernerey, Franck
dc.contributor.author	Fernandez-Nieves, Alberto
dc.contributor.author	Shen, Tong
dc.contributor.corporatename	Georgia Institute of Technology. Center for the Science and Technology of Advanced Materials and Interfaces	en_US
dc.contributor.corporatename	Georgia Institute of Technology. School of Physics	en_US
dc.contributor.corporatename	University of Colorado Boulder	en_US
dc.date.accessioned	2018-06-01T16:19:07Z
dc.date.available	2018-06-01T16:19:07Z
dc.date.issued	2018-04-19
dc.description	Presented at the Symposium on Soft Matter Forefronts "Contributed Talks", April 19, 2018, from 10:20 a.m.-11:10 a.m. at the Marcus Nanotechnology Building, Rooms 1116-1118, Georgia Tech.	en_US
dc.description	Chairs: Michael Tennenbaum & Alberto Fernandez-Nieves (Georgia Tech).	en_US
dc.description	Shankar Lalitha Sridhar, Franck Vernerey, and Tong Shen are with the University of Colorado Boulder, Mechanical Engineering.	en_US
dc.description	Alberto Fernandez-Nieves is with the Georgia Institute of Technology, School of Physics.	en_US
dc.description	Runtime: 11:56 minutes	en_US
dc.description.abstract	Biological assemblies in nature are seen as active matter due to their ability to perform intelligent collective motion based on neighbor interactions and sometimes without any centralized control or leadership. Fire ants are a great example in this context and display a rich class of material behaviors, including elasticity, viscous flow, and self-healing. Although classical theories in mechanics have enabled us to mechanically characterize this system, there is still a gap in our understanding on how individual ant behavior affects the emerging response of the aggregation. I will discuss an alternative approach from a statistical perspective where the population distribution of ants evolves due to mechanical deformation, and individual ant’s leg detachment and attachment events. Numerical simulations of the aggregation’s response in diverse situations, such as jamming (density) and shear thinning (reduced viscosity) will be presented and compared to experimental measurements.	en_US
dc.description.sponsorship	Georgia Institute of Technology. College of Sciences	en_US
dc.description.sponsorship	Georgia Institute of Technology. Institute for Materials	en_US
dc.description.sponsorship	Georgia Institute of Technology. Parker H. Petit Institute for Bioengineering and Bioscience	en_US
dc.description.sponsorship	Georgia Institute of Technology. School of Materials Science and Engineering	en_US
dc.description.sponsorship	Georgia Institute of Technology. School of Physics	en_US
dc.description.sponsorship	American Physical Society	en_US
dc.description.sponsorship	Exxon Mobil Corporation	en_US
dc.description.sponsorship	National Science Foundation (U.S.)	en_US
dc.format.extent	11:56 minutes
dc.identifier.uri	http://hdl.handle.net/1853/59978
dc.language.iso	en_US	en_US
dc.publisher	Georgia Institute of Technology	en_US
dc.subject	Ant behavior	en_US
dc.subject	Fire ants	en_US
dc.subject	Material behaviors	en_US
dc.subject	Soft matter	en_US
dc.title	Mechanics of Active Networks – Lessons from Fire Ant Aggregations	en_US
dc.type	Moving Image
dc.type.genre	Lecture
dspace.entity.type	Publication
local.contributor.author	Fernandez-Nieves, Alberto
local.contributor.corporatename	Soft Matter Incubator
local.contributor.corporatename	Center for the Science and Technology of Advanced Materials and Interfaces
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