动力学蒙特卡罗方法
材料科学
蒙特卡罗方法
半导体
外延
再结晶(地质)
晶体缺陷
硅
掺杂剂
统计物理学
半导体器件
半导体器件制造
退火(玻璃)
工程物理
纳米技术
兴奋剂
光电子学
凝聚态物理
物理
冶金
薄脆饼
古生物学
统计
生物
数学
图层(电子)
作者
Ignacio Martín-Bragado,Ricardo Borges,J.P. Balbuena,M. Jaraı́z
标识
DOI:10.1016/j.pmatsci.2017.09.003
摘要
The Kinetic Monte Carlo (KMC) algorithm is a particularly apt technique to simulate the complex processing of semiconductor devices. In this review, some of the main processes used for semiconductor industries to manufacture transistor from semiconductor materials, namely implantation, annealing and epitaxial growth are reviewed. The evolution of defects created during such processing for the particular, and well known case, of silicon, is commented. Kinetic Monte Carlo modeling is introduced and contrasted briefly with a continuum approach. Particular models of different phenomena, using both object and lattice KMC, are shown: point defect migration, cluster formation, dopant activation and deactivation, damage accumulation, amorphization, recrystallization, solid phase and selective epitaxial regrowth, etc. In this work we describe the models, its implementation into KMC, and we show several comparisons with significant experimental data validating the KMC approach and showing its capabilities. How extra capabilities can be included by extending the models to current problems in the semiconductor industry is also commented, in particular the use of SiGe alloys and the introduction of stress dependencies.
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