Electrical and Computer Engineering ETDs

Publication Date

8-25-2016

Abstract

State-of-the art neuromodulators are bulky, and they are mostly fabricated on rigid substrates. Furthermore, they are not provided with a feedback control loop re- sulting in undesired off-target effects. This thesis paves the way for fabrication of lightweight neural interfaces with the capability to implement closed-loop controlled neuromodulation down to a single-cell resolution. In this work, an approach based on hybrid optical-electrical devices to implement neuromodulation is presented. The rationale of this choice, design illustration, fabrication and characterization is discussed. In addition, a proof-of-concept neural interface is illustrated. Specif- ically, hybrid optical-electrical devices are developed based on inorganic thin films, i.e., nanomembranes (NMs) formed in ordered arrays of buckled channels on com- pliant substrates. The buckled NMs include light-emitting structures in the visible range (namely Si nano-crystals) and graphene electrodes to control and record neu- ral activity, respectively. The compliant substrates of choice is polydimethylsiloxane (PDMS). Buckled NMs are obtained by guided self-assembly of the supported thin films under compressive strain. The cross-sectional size of buckled NM channels is scaled to match the dimensions of single neurons. This work primarily focuses on the fabrication and integration of an optically active NM, with a conductive film, thus obtaining a hybrid optical-electrical platform for potential neuronal in-vitro studies. A process is established based on multiple layer releases and transfers which enables graphene electrodes to be fabricated on the inner side of the buckle-delaminated channels.In addition, structural characterization of the fabricated devices is performed, along with current/voltage measurements of the graphene electrodes, and photoluminescence spectroscopy to assess the optical emission from the buckled NMs.

Keywords

Semiconductor fabrication, Nanomembranes, Neuromodulation, 3D nanostructures

Document Type

Thesis

Language

English

Degree Name

Electrical Engineering

Level of Degree

Masters

Department Name

Electrical and Computer Engineering

First Committee Member (Chair)

Krishna, Sanjay

Second Committee Member

Shreve, Andrew

Third Committee Member

N/A

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