Integrating a nanologic knowledge module Into an undergraduate logic design course

Srivastava, S. and Bhanja, S. (2008) Integrating a nanologic knowledge module Into an undergraduate logic design course. Education, IEEE Transactions on, 51 (3). pp. 349-355. ISSN 0018-9359

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This work discusses a knowledge module in an undergraduate logic design course for electrical engineering (EE) and computer science (CS) students, that introduces them to nanocomputing concepts. This knowledge module has a twofold objective. First, the module interests students in the fundamental logical behavior and functionality of the nanodevices of the future, which will motivate them to enroll in other elective courses related to nanotechnology, offered in most EE and CS departments. Second, this module can be used to let students analyze, synthesize, and apply their existing knowledge of the Karnaugh-map-based Boolean logic reduction scheme into a revolutionary design context with majority logic. Where many efforts focus on developing new courses on nanofabrication and even nanocomputing, this work is designed to augment the existing standard EE and CS courses by inserting knowledge modules on nanologic structures so as to stimulate student interest without creating a significant diversion from the course framework.

Keywords:Boolean functions, computer science education, electrical engineering education, logic design, nanoelectronics, Karnaugh-map-based Boolean logic reduction scheme, computer science students, electrical engineering students, nanocomputing concepts, nanodevices, nanofabrication, nanologic knowledge module, revolutionary design, undergraduate logic design course, CMOS technology, Circuits, Computer science, Electrical engineering, Logic devices, Nanotechnology, Quantum cellular automata, Quantum dots, rm K-maps, majority logic, quantum-dot cellular automata (QCA)
Subjects:X Education > X342 Academic studies in Higher Education
X Education > X990 Education not elsewhere classified
Divisions:College of Science > School of Computer Science
College of Science > School of Engineering
College of Social Science > School of Education
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ID Code:10736
Deposited On:17 Jul 2013 10:53

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