{111} local configurations: The main source of silicon defects during solid phase epitaxial regrowth modeled by lattice kinetic Monte Carlo

2011 ◽  
Vol 98 (23) ◽  
pp. 233109 ◽  
Author(s):  
Ignacio Martin-Bragado
Keyword(s):  
Monte Carlo ◽  
Solid Phase ◽  
Kinetic Monte Carlo ◽  
Epitaxial Regrowth ◽  
Silicon Defects

Lattice kinetic Monte Carlo modeling of germanium solid phase epitaxial growth

2013 ◽  
Vol 11 (1) ◽  
pp. 93-96 ◽  
Author(s):  
J. L. Gomez-Selles ◽  
B. L. Darby ◽  
K. S. Jones ◽  
I. Martin-Bragado
Keyword(s):  
Monte Carlo ◽  
Epitaxial Growth ◽  
Solid Phase ◽  
Kinetic Monte Carlo ◽  
Monte Carlo Modeling

Modeling and Simulation of the Influence of SOI Structure on Damage Evolution and Ultra-shallow Junction Formed by Ge Preamorphization Implants and Solid Phase Epitaxial Regrowth

2006 ◽  
Vol 912 ◽  
Author(s):  
Caroline Mok ◽  
B. Colombeau ◽  
M. Jaraiz ◽  
P. Castrillo ◽  
J. E. Rubio ◽  
...  
Keyword(s):  
Damage Evolution ◽  
Solid Phase ◽  
Kinetic Monte Carlo ◽  
Silicon On Insulator ◽  
Bulk Silicon ◽  
Shallow Junction ◽  
Defect Interaction ◽  
Epitaxial Regrowth ◽  
Junction Formation ◽  
Ultra Shallow Junctions

AbstractPreamorphization implant (PAI) prior to dopant implantation, followed by solid phase epitaxial regrowth (SPER) is of great interest due to its ability to form highly-activated ultra-shallow junctions. Coupled with growing interest in the use of silicon-on-insulator (SOI) wafers, modeling and simulating the influence of SOI structure on damage evolution and ultra-shallow junction formation is required. In this work, we use a kinetic Monte Carlo (kMC) simulator to model the different mechanisms involved in the process of ultra-shallow junction formation, including amorphization, recrystallization, defect interaction and evolution, as well as dopant-defect interaction in both bulk silicon and SOI. Simulation results of dopant concentration profiles and dopant activation are in good agreement with experimental data and can provide important insight for optimizing the process in bulk silicon and SOI.

A Comprehensive Atomistic Kinetic Monte Carlo Model for Amorphization/Recrystallization and its Effects on Dopants

2008 ◽  
Vol 1070 ◽  
Author(s):  
Nikolas Zographos ◽  
Ignacio Martin-Bragado
Keyword(s):  
Activation Energy ◽  
Monte Carlo ◽  
Point Defects ◽  
Dopant Concentration ◽  
Solid Phase ◽  
Kinetic Monte Carlo ◽  
Monte Carlo Model ◽  
Atomistic Model ◽  
Recrystallization Front ◽  
Dopant Redistribution

ABSTRACTThis work shows a comprehensive atomistic model to describe amorphization and recrystallization, and its different effects on dopants in silicon. We begin by describing the physical basis of the model used, based on the transformation of ion-implanted dopants and generated point defects into amorphous pockets of different sizes. The growth and dissolution of amorphous pockets is simulated by the capture and recombination of point defects with different activation energies. In some cases, this growth leads to the formation of amorphous layers. These layers, composed of a set of amorphous elements, have an activation energy to be recrystallized. The recrystallization velocity is modeled not only depending on temperature, but also on dopant concentration. During the recrystallization, dopants move with the recrystallization front to simulate the dopant redistribution during solid phase epitaxial regrowth (SPER). At the edge of the amorphous-crystalline interface, the remaining damage forms end-of-range (EOR) defects.Once the model is explained, we discuss the calibration methodology used to reproduce several amorphous/crystalline (A/C) experiments, including the dependencies of the A/C transition temperature on dose rate and ion mass, and the A/C depth on ion implant energy.This calibrated model allows us to explore the redistribution of several dopants, including B, As, F, and In, during SPER. Experimental results for all these dopants are compared with relevant simulations.

Combined DFT and kinetic Monte Carlo study of a bridging-spillover mechanism on fluorine-decorating graphene

2020 ◽  
Author(s):  
Jing-hua Guo ◽  
Jin-Xiang Liu ◽  
Hongbo Wang ◽  
Haiying Liu ◽  
Gang Chen
Keyword(s):  
Monte Carlo ◽  
First Principles ◽  
Kinetic Monte Carlo ◽  
Monte Carlo Study ◽  
First Principles Calculations ◽  
Graphene Surface

In this work, combining the first-principles calculations with kinetic Monte Carlo (KMC) simulations, we constructed an irregular carbon bridge on the graphene surface and explored the process of H migration...

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