Kinetic Monte Carlo simulation for semiconductor processing: A review. (March 2018)

• Record Type: Journal Article
• Authors: Martin-Bragado, Ignacio; Borges, Ricardo; Balbuena, Juan Pablo; Jaraiz, Martin
• Is Part Of: Progress in materials science. Volume 92(2018)
• Page Start: 1
• Page End: 32
• Publication Date: 2018-03
• Subjects: Kinetic Monte Carlo -- Process simulation -- Semiconductor processing -- Silicon; Materials science -- Periodicals; Science des matériaux -- Périodiques; 620.1105
• DOI: 10.1016/j.pmatsci.2017.09.003
• Languages: English
• ISSNs: 0079-6425

Abstract

Abstract: 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.