<?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>2026-09-19T22:44:42Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/127019" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/127019</identifier><datestamp>2026-06-16T18:53:41Z</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">Anantha P. Chandrakasan.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Garcha, Preetinder(Preetinder Kaur)</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" lang="en_US">Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2020-09-03T17:42:16Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2020-09-03T17:42:16Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2020</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2020</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">https://hdl.handle.net/1721.1/127019</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">1191624846</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, May, 2020</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from the official PDF of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 145-151).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">The continued expansion of Internet of Things has led to a proliferation of wireless sensors and systems across the globe. The application space for sensors is wide-ranging: from industries, to serve the upcoming era of Industry 4.0, to consumer products, like body wearable sensors. The rise to billions of sensors relies on two key trends in sensor systems: miniaturization and energy-efficiency. This work explores the use of integrated magnetics in microelectronics to enable low power, energy-efficient sensing, as well as energy harvesting to power the sensors, in a compact form factor. For industrial applications, we present the design of a bandwidth-scalable, integrated fluxgate magnetic-to-digital converter for energy-efficient contactless current sensing in smart connectors. The system uses mixed signal front-end design to en-able duty cycling and quick convergence techniques leading to 20x reduction in power consumption at low bandwidths of 1 kHz for power monitoring. It also employs fast read-out circuits to achieve a bandwidth of 125 kHz for machine health diagnosis. For personal body wearable electronics and beyond, we present the design of a cold start system with integrated magnetics for ultra low voltage startup in thermal energy harvesting applications. The Meissner Oscillator analysis with on-chip magnetics allows co-optimization of magnetics and circuits to achieve start up from as low as 25 mV input voltage to the circuits, despite 1000x lower inductance than off-chip transformers. Given the recent push towards artificial intelligence and a growing need for data, along with sensors to collect that data, we need to explore novel uses of technologies to meet the demands for small form factor and low power operation, as the number of sensors scale. The ideas presented in this thesis, with two very different applications of the integrated magnetics technology, can contribute to the continued growth towards trillions of sensors.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Preetinder Garcha.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">Ph.D.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="collection" lang="en_US">Ph.D. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">151 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 may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.</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">Low power circuits with integrated magnetics for sensors and energy harvesting systems</dim:field>
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   <dim:field mdschema="mit" element="thesis" qualifier="degree" lang="en_US">Doctoral</dim:field>
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   	&lt;Title>Low power circuits with integrated magnetics for sensors and energy harvesting systems&lt;/Title>
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   	&lt;PublicationDate>2020&lt;/PublicationDate>
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        	&lt;DisplayName>Garcha, Preetinder(Preetinder Kaur)&lt;/DisplayName>
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    &lt;Keyword>Electrical Engineering and Computer Science.&lt;/Keyword>
   	&lt;Abstract>The continued expansion of Internet of Things has led to a proliferation of wireless sensors and systems across the globe. The application space for sensors is wide-ranging: from industries, to serve the upcoming era of Industry 4.0, to consumer products, like body wearable sensors. The rise to billions of sensors relies on two key trends in sensor systems: miniaturization and energy-efficiency. This work explores the use of integrated magnetics in microelectronics to enable low power, energy-efficient sensing, as well as energy harvesting to power the sensors, in a compact form factor. For industrial applications, we present the design of a bandwidth-scalable, integrated fluxgate magnetic-to-digital converter for energy-efficient contactless current sensing in smart connectors. The system uses mixed signal front-end design to en-able duty cycling and quick convergence techniques leading to 20x reduction in power consumption at low bandwidths of 1 kHz for power monitoring. It also employs fast read-out circuits to achieve a bandwidth of 125 kHz for machine health diagnosis. For personal body wearable electronics and beyond, we present the design of a cold start system with integrated magnetics for ultra low voltage startup in thermal energy harvesting applications. The Meissner Oscillator analysis with on-chip magnetics allows co-optimization of magnetics and circuits to achieve start up from as low as 25 mV input voltage to the circuits, despite 1000x lower inductance than off-chip transformers. Given the recent push towards artificial intelligence and a growing need for data, along with sensors to collect that data, we need to explore novel uses of technologies to meet the demands for small form factor and low power operation, as the number of sensors scale. The ideas presented in this thesis, with two very different applications of the integrated magnetics technology, can contribute to the continued growth towards trillions of sensors.&lt;/Abstract>
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