Nanotechnology (NANO)

School of Computational Sciences

500 Introduction to Nanomaterials and Interactions (3:3:0) Prerequisite: Admission to graduate certificate in nanotechnology and nanoscience. Introduction to nanotechnology. Discussion of the Feynman challenge and its relation to modern science. Applications to nanostructures of charges, currents, diamagnetics, paramagnetics and ferromagnetics.

510 Strategies for Nanocharacterization (3:3:0) Prerequisites: NANO 500 and admission to graduate certificate in nanotechnology and nanoscience. Introduces various nanocharacterization techniques, with a discussion of which techniques are most useful in various applications. Includes gates and bridges; chemical thermodynamics; kinetics; and solid-state reactions.

520 Survey of Nanostructures (3:3:0) Prerequisites: NANO 500 and 510, and admission to graduate certificate in nanotechnology and nanoscience. Discusses nanomechanical oscillators and nanoresonators; nanofibers; conducting polymer nanowires. Nanomechanical beams for reacting ion etching. Electron-beam lithography and photolithography.

530 Nanofabrication (3:3:0) Prerequisites: NANO 500 and 510, and admission to graduate certificate in nanotechnology and nanoscience. Covers pulsed laser deposition; molecular beam epitaxy; controlled vapor deposition; reactive sputtering; and doping and implant isolation.

610 Nanoelectronics (3:3:0) Prerequisites: NANO 500, 510, 520, and 530, and admission to graduate certificate in nanotechnology and nanoscience. Introduces basic elements of nanoelectronic structures, including quantum layers, quantum wires, and quantum dots. Covers sub-band structure; transport in quantum layers; behavior in the presence of magnetic fields; Coulomb blockades; CMOS nanodevices and nanoelectronics; and SOI multigate device physics and modeling.

620 Computational Modeling in Nanoscience (3:3:0) Prerequisites: NANO 500, 510, and 520, and admission to graduate certificate in nanotechnology and nanoscience. Introduction to simulation methods used in nanoscience. Covers computational approaches to modeling molecular and condensed matter at the nanoscale level, including interatomic and molecular potentials; molecular mechanics; molecular dynamics; monte carlo averaging; ensemble distributions; numerical sampling; thermodynamic functions; dynamic structure; and introduction to cellular automata.