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SHARC : self-healing analog with RRAM and CNFETs

Author(s)
Amer, Aya G.(Aya Galal Mahdy ElSayed)
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Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Max M. Shulaker and Anantha P. Chandrakasan.
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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. http://dspace.mit.edu/handle/1721.1/7582
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Abstract
Next-generation applications require processing on massive amount of data in real-time, exceeding the capabilities of electronic systems today. This has spurred research in a wide-range of areas: from new devices to replace silicon-based field-effect transistors (FETs) to new circuit and system architectures with fine-grained and dense integration of logic and memory. However, isolated improvements in just one area is insufficient. Rather, enabling these next-generation applications will require combining benefits across all levels of the computing stack: leveraging new devices to realize new circuits and architectures. For instance, carbon nanotube (CNT) field-effect transistors (CNFETs) for logic and Resistive Random-Access Memory (RRAM) for memory are two promising emerging nanotechnologies for energy-efficient electronics. However, CNFETs suffer from inherent imperfections (such as of metallic CNTs, m-CNTs), which have prohibited realizing large-scale CNFET circuits in the past. This work proposes a circuit design technique that integrates and combines the benefits of both CNFETs with RRAM to realize three-dimensional (3D) circuits that are immune to m-CNTs. Leveraging this technique, we show the first experimental demonstration of CNFET-based analog mixed-signal circuits.
Description
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
 
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019
 
Cataloged from student-submitted PDF version of thesis.
 
Includes bibliographical references (pages 49-50).
 
Date issued
2019
URI
https://hdl.handle.net/1721.1/122693
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

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