The Role of Surface Annihilation in Annealing Investigated by Atomic Model Simulation

2005 ◽  
Vol 864 ◽  
Author(s):  
Min Yu ◽  
Xiao Zhang ◽  
Ru Huang ◽  
Xing Zhang ◽  
Yangyuan Wang ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Integrated Circuits ◽  
Point Defects ◽  
Model Simulation ◽  
Kinetic Monte Carlo ◽  
Boron Diffusion ◽  
Junction Depth ◽  
Kinetic Monte Carlo Method ◽  
Enhanced Diffusion

AbstractBehavior of point defects in annealing is investigated a lot in order to suppress the Transient Enhanced Diffusion (TED) of boron as is urged by the development of integrated circuits. Surface annihilation possibility for point defects is very important in determining junction depth in the case of ultra-shallow doping. However the understanding on it is still ambiguous considering the inconsistent results on surface annihilation behavior. In this paper the variation of surface annihilation possibility is studied. The simulation on boron diffusion as well as silicon diffusion is performed. The evolution of Si clusters is simulated. By explaining experimental results with Kinetic Monte Carlo method based simulation, we proposed that surface annihilation possibility varies in different cases.

Investigation of Fluorine Effect on the Boron Diffusion by Mean of Boron Redistribution in Shallow Delta-doped Layers

2004 ◽  
Vol 810 ◽  
Author(s):  
A. Halimaoui ◽  
J. M. Hartmann ◽  
C. Laviron ◽  
R. El-Farhane ◽  
F. Laugier
Keyword(s):  
Point Defects ◽  
Depth Profiling ◽  
Boron Diffusion ◽  
Enhanced Diffusion ◽  
Boron Doped ◽  
Transient Enhanced Diffusion ◽  
Sims Depth Profiling

ABSTRACTPreviously published articles have shown that co-implanted fluorine reduces transient enhanced diffusion of boron. However, it is not yet elucidated whether this effect is due to interaction of fluorine with point-defects or boron atoms. In this work, we have used boron redistribution in a shallow Delta-doped Si structures in order to get some insights into the role of fluorine in the boron diffusion. The structures consisted of 3 boron-doped layers separated by 40nm-thick undoped silicon. The samples were given to Ge preamorphization and F co-implant. SIMS depth profiling was used to analyse boron redistribution after annealing. The results we obtained strongly suggest that fluorine is not interacting with point-defects. The reduction in boron TED is most probably due to boron-fluorine interaction.

Monte Carlo simulation of Boron diffusion during low energy implantation and high temperature annealing

1997 ◽  
Vol 469 ◽  
Author(s):  
M.-J. Caturla ◽  
T. Diaz de la Rubia ◽  
J. Zhu ◽  
M. Johnson
Keyword(s):  
Monte Carlo ◽  
High Temperature ◽  
Kinetic Monte Carlo ◽  
Monte Carlo Model ◽  
Low Energy ◽  
High Temperature Annealing ◽  
Boron Diffusion ◽  
Enhanced Diffusion ◽  
Diffusion Enhancement ◽  
High Doses

ABSTRACTWe use a kinetic Monte Carlo model to simulate the implantation of low energy Boron in Silicon, from 0.5 to 1 keV, at high doses, 1015 ions/cm2. The damage produced by each ion is calculated using UT-Marlowe, based on a binary collision approximation. During implantation at room temperature,, silicon self-interstitials, vacancies and boron interstitials are allowed to migrate and interact. The diffusion kinetics of these defects and dopants has been obtained by ab initio calculations as well as Stillinger Weber molecular dynamics. Clustering of both self-interstitials, vacancies and boron atoms is included. We also model the diffusion of the implanted dopants after a high temperature annealing in order to understand the transient enhanced diffusion (TED) phenomenon. We observe two different stages of TED During the first stage vacancies are present in the lattice together with interstitials and the diffusion enhancement is small. The second stage starts after all the vacancies disappear and gives rise to most of the final TED.

Simulation of degradation of the organic contaminants ethylene glycol and phenol by iron nanoparticles using the kinetic Monte Carlo method

RSC Advances ◽  
2014 ◽  
Vol 4 (62) ◽  
pp. 32928-32933 ◽  
Author(s):  
Hamed Moradmand Jalali
Keyword(s):  
Hydrogen Peroxide ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Ethylene Glycol ◽  
Organic Contaminants ◽  
Iron Nanoparticles ◽  
Kinetic Monte Carlo ◽  
Kinetic Monte Carlo Method ◽  
System P

We applied kinetic Monte Carlo simulation to study the kinetics and mechanisms of the degradation of the organic pollutants ethylene glycol and phenol by iron(iii) nanoparticles and hydrogen peroxide as the catalytic system.

Kinetic Monte Carlo (KMC) Modeling for Boron Diffusion in Strained Silicon

2007 ◽  
Vol 50 (6) ◽  
pp. 1656
Author(s):  
Young-Kyu Kim ◽  
Kwan-Sun Yoon ◽  
Joong-Sik Kim ◽  
Taeyoung Won
Keyword(s):  
Monte Carlo ◽  
Kinetic Monte Carlo ◽  
Strained Silicon ◽  
Boron Diffusion

scholarly journals From Point to Filament Defects in Hybrid Nematic Films

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Cesare Chiccoli ◽  
Paolo Pasini ◽  
Claudio Zannoni ◽  
Gregor Skačej ◽  
Hiroyuki Yoshida ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Point Defects ◽  
Elastic Constants ◽  
3D Structure ◽  
Support Surface ◽  
Hybrid Films ◽  
Surface Ordering ◽  
Polarized Microscopy ◽  
Homeotropic Alignment

AbstractWe have studied nematic hybrid films with homeotropic alignment at the top surface and various controlled degrees of in plane ordering, going from a random degenerate organization to a completely uniform alignment along one direction, at the bottom one. We show, by Monte Carlo (MC) computer simulations and experiments on photopatterned films with the bottom support surface fabricated with in-plane order similar to the simulated ones, that the point defects observed in the case of random planar orientations at the bottom tend to arrange along a filament as the surface ordering is sufficiently increased. MC simulations complement the polarized microscopy texture observations allowing to inspect the 3D structure of the defects and examine the role of elastic constants.

Silver monolayer formation on Cu(110) by kinetic Monte Carlo method

2019 ◽  
Vol 134 (4) ◽  
Author(s):  
Moloudi Dardouri ◽  
Khalid Sbiaai ◽  
Abdessamad Hassani ◽  
Abdellatif Hasnaoui ◽  
Yahia Boughaleb ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Kinetic Monte Carlo ◽  
Kinetic Monte Carlo Method ◽  
Monolayer Formation
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