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Spy Code: A Learning Module Linking Nano-tubes Research Experience to
Author(s) -
Mohamed Abdelrahman,
Reza Nekovei,
Alexandra Chincarini
Publication year - 2020
Language(s) - English
Resource type - Conference proceedings
DOI - 10.18260/1-2--21930
Subject(s) - code (set theory) , electronics , monomial , component (thermodynamics) , computer science , carbon nanotube , engineering , nanotechnology , mathematics , electrical engineering , materials science , physics , programming language , set (abstract data type) , discrete mathematics , thermodynamics
This paper focuses on presenting the experience of a mathematics teacher participating in a Research Experience for Teacher program at Texas A&M University-Kingsville. The research experience was focused on carbon nanotubes (CNTs) as suitable replacements for transistors. As transistors, they would be smaller, faster, less resistant, and cheaper to manufacture than anything currently in use. The greatest problem with studying CNTs and producing new electronics with CNTs as the chief component has been their size. Little experimental research has been conducted on actual CNTs to measure their output currents when voltages are applied to them. This research focused on collecting and presenting data on the electrical properties of bundles of CNTs, particularly in regards to how CNTs respond to the presence or absence of light. Finding a link between this research experience based on sophisticated equipment and advanced electronics and teaching algebra has been a challenge. The paper describes a learning module that is based on simplified models of CNTs. It challenges the students to use simple electronic circuits to design and implement secret codes of blinking lights. The modules are based on the concept of the Legacy Cycle. It covers various topics in algebra including graphing lines, finding relations, solving equations, and manipulation of monomials.

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