<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-18T22:20:05Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/118095" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/118095</identifier><datestamp>2026-06-16T18:52:19Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131022</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Tomás Palacios.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Mackin, Charles Edward</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2018-09-17T15:57:18Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2018-09-17T15:57:18Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2018</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2018</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/118095</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">1052124112</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from PDF version of thesis. Page 199 blank.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 173-198).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">Graphene exhibits a unique combination of properties making it particularly promising for sensing applications. This thesis builds new graphene chemical and biological sensing technologies from the ground up by developing device models, systems, and applications. On the modeling side, this thesis develops a DC model for graphene electrolyte-gated field-effect transistors (EGFETs). It also presents a novel frequency-dependent (AC) small-signal model for graphene EGFETs and demonstrates the ability of these devices to operate as functional amplifiers for the first time. Graphene sensors are transitioned to the system level by developing a new sensor array architecture in conjunction with a compact and easy-to-use custom data acquisition system. The system allows for simultaneous characterization of hundreds of sensors and provides insight into graphene EGFET performance variations. The system is adapted to develop solution-phase ionized calcium sensors using a graphene EGFET array that has been functionalized using a polyvinyl chloride (PVC) membrane containing a neutral calcium ionophore. Sensors are shown to accurately quantify ionized calcium over several orders of magnitude while exhibiting excellent selectivity, reversibility, response time, and a virtually ideal Nernstian response of 30.1 mV/decade. A new variation-insensitive distribution matching technique is also developed to enable faster readout. Finally, the sensor system is employed to develop gas-phase chemiresistive ammonia sensors that have been functionalized using cobalt porphyrin. Sensors provide enhanced sensitivity over pristine graphene while providing selectivity over interfering compounds such as water and common organic solvents. Sensor responses exhibit high correlation coefficients indicating consistent sensor response and reproducibility of the cobalt porphyrin functionalization. Variations in sensitivity follow a Gaussian distribution and are shown to stem from variations in the underlying sensor source-drain currents. A detailed kinetic model is developed describing sensor response profiles that incorporates two ammonia adsorption mechanisms--one reversible and one irreversible.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Charles Mackin.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">Ph.D.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">199 pages</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Electrical Engineering and Computer Science.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Graphene chemical and biological sensors : modeling, systems, and applications</dim:field>
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   	&lt;Title>Graphene chemical and biological sensors : modeling, systems, and applications&lt;/Title>
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   	&lt;PublicationDate>2018&lt;/PublicationDate>
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        	&lt;DisplayName>Mackin, Charles Edward&lt;/DisplayName>
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    &lt;Keyword>Electrical Engineering and Computer Science.&lt;/Keyword>
   	&lt;Abstract>Graphene exhibits a unique combination of properties making it particularly promising for sensing applications. This thesis builds new graphene chemical and biological sensing technologies from the ground up by developing device models, systems, and applications. On the modeling side, this thesis develops a DC model for graphene electrolyte-gated field-effect transistors (EGFETs). It also presents a novel frequency-dependent (AC) small-signal model for graphene EGFETs and demonstrates the ability of these devices to operate as functional amplifiers for the first time. Graphene sensors are transitioned to the system level by developing a new sensor array architecture in conjunction with a compact and easy-to-use custom data acquisition system. The system allows for simultaneous characterization of hundreds of sensors and provides insight into graphene EGFET performance variations. The system is adapted to develop solution-phase ionized calcium sensors using a graphene EGFET array that has been functionalized using a polyvinyl chloride (PVC) membrane containing a neutral calcium ionophore. Sensors are shown to accurately quantify ionized calcium over several orders of magnitude while exhibiting excellent selectivity, reversibility, response time, and a virtually ideal Nernstian response of 30.1 mV/decade. A new variation-insensitive distribution matching technique is also developed to enable faster readout. Finally, the sensor system is employed to develop gas-phase chemiresistive ammonia sensors that have been functionalized using cobalt porphyrin. Sensors provide enhanced sensitivity over pristine graphene while providing selectivity over interfering compounds such as water and common organic solvents. Sensor responses exhibit high correlation coefficients indicating consistent sensor response and reproducibility of the cobalt porphyrin functionalization. Variations in sensitivity follow a Gaussian distribution and are shown to stem from variations in the underlying sensor source-drain currents. A detailed kinetic model is developed describing sensor response profiles that incorporates two ammonia adsorption mechanisms--one reversible and one irreversible.&lt;/Abstract>
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