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Theoretical Modeling of Epitaxial Graphene Growth on the Ir(111) Surface (Hardcover, 1st ed. 2017) Loot Price: R1,615
Discovery Miles 16 150
Theoretical Modeling of Epitaxial Graphene Growth on the Ir(111) Surface (Hardcover, 1st ed. 2017): Holly Alexandra Tetlow

Theoretical Modeling of Epitaxial Graphene Growth on the Ir(111) Surface (Hardcover, 1st ed. 2017)

Holly Alexandra Tetlow

Series: Springer Theses

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Loot Price R1,615 Discovery Miles 16 150 | Repayment Terms: R151 pm x 12*

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One possible method of producing high-quality graphene is to grow it epitaxially; this thesis investigates the mechanisms involved in doing so. It describes how the initial stages of growth on the Ir(111) surface are modelled using both rate equations and kinetic Monte Carlo, based upon nudged elastic band (NEB) calculated reaction energy barriers. The results show that the decomposition mechanism involves production of C monomers by breaking the C-C bond. In turn, the thesis explores the nucleation of carbon clusters on the surface from C monomers prior to graphene formation. Small arch-shaped clusters containing four to six C atoms, which may be key in graphene formation, are predicted to be long-lived on the surface. In closing, the healing of single vacancy defects in the graphene/Ir(111) surface is investigated, and attempts to heal said defects using ethylene molecules is simulated with molecular dynamics and NEB calculated energy barriers.

General

Imprint: Springer International Publishing AG
Country of origin: Switzerland
Series: Springer Theses
Release date: October 2017
First published: 2017
Authors: Holly Alexandra Tetlow
Dimensions: 235 x 155mm (L x W)
Format: Hardcover
Pages: 182
Edition: 1st ed. 2017
ISBN-13: 978-3-319-65971-8
Categories: Books > Professional & Technical > Technology: general issues > Nanotechnology
Books > Science & Mathematics > Physics > States of matter > Condensed matter physics (liquids & solids)
Books > Professional & Technical > Mechanical engineering & materials > Materials science > General
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LSN: 3-319-65971-5
Barcode: 9783319659718

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