Modeling Cu thin film growth

James Adams; Zhiyong Wang; Youhong Li

doi:10.1016/S0040-6090(99)01047-0

Modeling Cu thin film growth

James Adams, Zhiyong Wang, Youhong Li

Chemical Engineering

Research output: Contribution to journal › Article › peer-review

51 Scopus citations

Abstract

A general overview of methods of modeling thin film growth on an atomic scale is provided, focusing on molecular dynamics (MD), energy minimization, and Monte Carlo methods. We emphasize how different methods can be integrated to provide a more powerful predictive capability. We give examples of how one can use atomic-level information to predict nucleation rates and facet growth rates of Cu island.

Original language	English (US)
Pages (from-to)	201-210
Number of pages	10
Journal	Thin Solid Films
Volume	365
Issue number	2
DOIs	https://doi.org/10.1016/S0040-6090(99)01047-0
State	Published - Apr 17 2000

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Surfaces and Interfaces
Surfaces, Coatings and Films
Metals and Alloys
Materials Chemistry

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10.1016/S0040-6090(99)01047-0

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title = "Modeling Cu thin film growth",

abstract = "A general overview of methods of modeling thin film growth on an atomic scale is provided, focusing on molecular dynamics (MD), energy minimization, and Monte Carlo methods. We emphasize how different methods can be integrated to provide a more powerful predictive capability. We give examples of how one can use atomic-level information to predict nucleation rates and facet growth rates of Cu island.",

author = "James Adams and Zhiyong Wang and Youhong Li",

note = "Funding Information: The authors wish to thank Tim Cale of RPI for his early encouragement of our KLMC work and for useful discussions. We also thank Len Borucki, Roland Stumpf, Chun-Li Liu, Xiang-Yang (Benjamin) Liu, and Bill Johnson of Motorola for many helpful discussions. We thank David Richards for his assistance in guiding the development of the KLMC algorithms and code, and for many useful discussions. We thank S.F. Foiles, M.I. Baskes and M.S. Daw for use of the DYNAMO code. We thank NSF for funding this work through grant ASC97-40300, via a subcontract from NCSA. We thank NCSA for providing computational support on their SGI Origin cluster. ",

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doi = "10.1016/S0040-6090(99)01047-0",

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AU - Adams, James

AU - Wang, Zhiyong

AU - Li, Youhong

N1 - Funding Information: The authors wish to thank Tim Cale of RPI for his early encouragement of our KLMC work and for useful discussions. We also thank Len Borucki, Roland Stumpf, Chun-Li Liu, Xiang-Yang (Benjamin) Liu, and Bill Johnson of Motorola for many helpful discussions. We thank David Richards for his assistance in guiding the development of the KLMC algorithms and code, and for many useful discussions. We thank S.F. Foiles, M.I. Baskes and M.S. Daw for use of the DYNAMO code. We thank NSF for funding this work through grant ASC97-40300, via a subcontract from NCSA. We thank NCSA for providing computational support on their SGI Origin cluster.

PY - 2000/4/17

Y1 - 2000/4/17

N2 - A general overview of methods of modeling thin film growth on an atomic scale is provided, focusing on molecular dynamics (MD), energy minimization, and Monte Carlo methods. We emphasize how different methods can be integrated to provide a more powerful predictive capability. We give examples of how one can use atomic-level information to predict nucleation rates and facet growth rates of Cu island.

AB - A general overview of methods of modeling thin film growth on an atomic scale is provided, focusing on molecular dynamics (MD), energy minimization, and Monte Carlo methods. We emphasize how different methods can be integrated to provide a more powerful predictive capability. We give examples of how one can use atomic-level information to predict nucleation rates and facet growth rates of Cu island.

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Modeling Cu thin film growth

Abstract

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