dc.contributor.advisor | Max M. Shulaker and Anantha P. Chandrakasan. | en_US |
dc.contributor.author | Amer, Aya G.(Aya Galal Mahdy ElSayed) | en_US |
dc.contributor.other | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. | en_US |
dc.date.accessioned | 2019-11-04T19:53:36Z | |
dc.date.available | 2019-11-04T19:53:36Z | |
dc.date.copyright | 2019 | en_US |
dc.date.issued | 2019 | en_US |
dc.identifier.uri | https://hdl.handle.net/1721.1/122693 | |
dc.description | This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. | en_US |
dc.description | Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019 | en_US |
dc.description | Cataloged from student-submitted PDF version of thesis. | en_US |
dc.description | Includes bibliographical references (pages 49-50). | en_US |
dc.description.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. | en_US |
dc.description.statementofresponsibility | by Aya G. Amer. | en_US |
dc.format.extent | 50 pages | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Massachusetts Institute of Technology | en_US |
dc.rights | 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. | en_US |
dc.rights.uri | http://dspace.mit.edu/handle/1721.1/7582 | en_US |
dc.subject | Electrical Engineering and Computer Science. | en_US |
dc.title | SHARC : self-healing analog with RRAM and CNFETs | en_US |
dc.type | Thesis | en_US |
dc.description.degree | S.M. | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | en_US |
dc.identifier.oclc | 1124852442 | en_US |
dc.description.collection | S.M. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science | en_US |
dspace.imported | 2019-11-04T19:53:34Z | en_US |
mit.thesis.degree | Master | en_US |
mit.thesis.department | EECS | en_US |