Light-Responsive Materials for Photo-Mechanics, and Brain-Machine Interfaces
Dec 1, 2023
2:30PM to 3:30PM
Date/Time
Date(s) - 01/12/2023
2:30 pm - 3:30 pm
Categories
Prof. Christopher Barrett
McGill University, Montreal Neurological Institute
Exciting applications in interfacing biology with technology require new advanced materials to mediate this communication, especially challenging for the interface between brain and machine. There is an effort underway for next-generation materials that rely on soft, wet biomaterials that more closely resemble real biological tissue than metals or inorganics, and to employ more natural signal communication pathways involving optical photons similar to the human eye, instead of electrical current. This talk will attempt to summarize some of these recent efforts at developing new biopolymers that improve biocompatibility with various parts of the human body, and that also allow transduction of neural signal processing using light at low intensities and visible wavelengths. Offshoots of these developments are new classes of materials that can respond mechanically to visible light, and that can also dis-assemble reversibly in sunlight.
Bio:
Christopher Barrett is from Port Dover ON, and studied at Queen’s University for B.Sc., M.Sc., and PhD. degrees in Physics and in Chemistry, ’92, ’94, and ’97. Christopher then joined the Harvard-MIT Program in Health Sciences and Technology in ’97, and the Centre for Materials Science and Engineering at MIT for 2 years postdoctoral study ’98–’99, working on the water-based self-assembly of biopolymer layers and multi-layers to bio-camouflage surfaces for improved implants and bio-interfaces. Prof. Barrett joined the McGill Chemistry Faculty in 2000, establishing Polymer BioMaterials and Laser Optics labs, in collaboration with McGill’s Centre for Physics of Materials, School of Environment, Institute for Advanced Materials, and the Montreal Neurological Institute.
In-Person: ABB 102
Online: https://mcmaster.zoom.us/j/97868793917
Meeting ID: 978 6879 3917
Passcode: 612695