Optimal Feedback Control of Crystallization

Grover, Martha A.

Title:

Optimal Feedback Control of Crystallization

dc.contributor.author	Grover, Martha A.
dc.contributor.corporatename	Georgia Institute of Technology. Institute for Electronics and Nanotechnology	en_US
dc.contributor.corporatename	Georgia Institute of Technology. School of Chemical and Biomolecular Engineering	en_US
dc.date.accessioned	2017-02-02T18:45:35Z
dc.date.available	2017-02-02T18:45:35Z
dc.date.issued	2017-01-24
dc.description	Presented at the Nano@Tech Meeting on January 24, 2017 at 12:00 p.m. in room 1117-1118 of the Marcus Nanotechnology Building, Georgia Tech.	en_US
dc.description	Martha Grover is a Professor in the School of Chemical & Biomolecular Engineering at Georgia Tech. She earned her BS in Mechanical Engineering from the University of Illinois, Urbana-Champaign, and her MS and PhD in Mechanical Engineering from Caltech. She joined Georgia Tech as an Assistant Professor in 2002, and received an NSF CAREER award in 2004. In 2011 she received the Outstanding Young Researcher Award from the Computing and Systems Technology Division of AIChE. Her research program is dedicated to understanding, modeling, and engineering the self-assembly of atoms and small molecules to create larger scale structures and complex functionality. Her approach draws on process systems engineering, combining modeling and experiments in applications dominated by kinetics, including surface deposition, crystal growth, polymer reaction engineering, and colloidal assembly. She is a member of the NSF/NASA Center for Chemical Evolution, and the Georgia Tech Center for Organic Photonics and Electronics.	en_US
dc.description	Runtime: 56:56 minutes	en_US
dc.description.abstract	The organization of a large collection of particles into an ordered crystalline array is needed for many applications, including pharmaceutical separations, nuclear waste disposal, and optoelectronic metamaterials. Due to improvements in sensing technology, it is now becoming possible to monitor the crystalline state in real time during the crystallization process, and this sensor technology opens up new possibilities for feedback control. Here we monitor the crystalline state and use this data to build an empirical model. An optimal feedback policy is then calculated using the empirical model along with dynamic programming. Alternatively, the empirical model can be calculated from simulation “data” coming from a detailed particle-level simulation. Experimental results demonstrating the method will be presented for molecular crystallization and colloidal crystallization.	en_US
dc.format.extent	56:56 minutes
dc.identifier.uri	http://hdl.handle.net/1853/56431
dc.language.iso	en_US	en_US
dc.publisher	Georgia Institute of Technology	en_US
dc.relation.ispartofseries	Nano@Tech Lecture Series
dc.subject	Crystallization	en_US
dc.subject	Materials	en_US
dc.subject	Nanotechnology	en_US
dc.subject	Sensing	en_US
dc.title	Optimal Feedback Control of Crystallization	en_US
dc.type	Moving Image
dc.type.genre	Lecture
dspace.entity.type	Publication
local.contributor.author	Grover, Martha A.
local.contributor.corporatename	Institute for Electronics and Nanotechnology (IEN)
local.relation.ispartofseries	Nano@Tech Lecture Series
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