We present a program that uses an optimization algorithm to fit rocking
curves of ion-implanted semiconductors. This is an inverse problem that
cannot be solved by simple methods. However, using recursion formulae
for rocking curve calculations and a model of ion distribution after
implantation, it is possible to fit experimental data with a
general-purpose optimization method. In our case, we use a modified
version of the genetic algorithm, which has been shown to be a good
technique for this problem. The program also calculates rocking curves
for a given ion profile, such as those generated by ion implantation
simulation programs. (C) 2004 Elsevier B.V. All rights reserved.
%0 Journal Article
%1 WOS:000222295000005
%A Bleicher, L
%A Sasaki, JM
%A Orloski, RV
%A Cardoso, LP
%A Hayashi, MA
%A Swart, JW
%C RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
%D 2004
%I ELSEVIER
%J COMPUTER PHYSICS COMMUNICATIONS
%K algorithms} diffraction; genetic implantation; ion {X-ray
%N 2
%P 158-165
%R 10.1016/j.cpc.2004.02.015
%T IonRock: software for solving strain gradients of ion-implanted
semiconductors by X-ray diffraction measurements and evolutionary
programming
%V 160
%X We present a program that uses an optimization algorithm to fit rocking
curves of ion-implanted semiconductors. This is an inverse problem that
cannot be solved by simple methods. However, using recursion formulae
for rocking curve calculations and a model of ion distribution after
implantation, it is possible to fit experimental data with a
general-purpose optimization method. In our case, we use a modified
version of the genetic algorithm, which has been shown to be a good
technique for this problem. The program also calculates rocking curves
for a given ion profile, such as those generated by ion implantation
simulation programs. (C) 2004 Elsevier B.V. All rights reserved.
@article{WOS:000222295000005,
abstract = {We present a program that uses an optimization algorithm to fit rocking
curves of ion-implanted semiconductors. This is an inverse problem that
cannot be solved by simple methods. However, using recursion formulae
for rocking curve calculations and a model of ion distribution after
implantation, it is possible to fit experimental data with a
general-purpose optimization method. In our case, we use a modified
version of the genetic algorithm, which has been shown to be a good
technique for this problem. The program also calculates rocking curves
for a given ion profile, such as those generated by ion implantation
simulation programs. (C) 2004 Elsevier B.V. All rights reserved.},
added-at = {2022-05-23T20:00:14.000+0200},
address = {RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS},
author = {Bleicher, L and Sasaki, JM and Orloski, RV and Cardoso, LP and Hayashi, MA and Swart, JW},
biburl = {https://www.bibsonomy.org/bibtex/24a5e8e06ba89ef5dffcb5b7a5a4d8fbc/ppgfis_ufc_br},
doi = {10.1016/j.cpc.2004.02.015},
interhash = {ea0f4ace3cddc488d1ca7ce1af2a88e1},
intrahash = {4a5e8e06ba89ef5dffcb5b7a5a4d8fbc},
issn = {0010-4655},
journal = {COMPUTER PHYSICS COMMUNICATIONS},
keywords = {algorithms} diffraction; genetic implantation; ion {X-ray},
number = 2,
pages = {158-165},
publisher = {ELSEVIER},
pubstate = {published},
timestamp = {2022-05-23T20:00:14.000+0200},
title = {IonRock: software for solving strain gradients of ion-implanted
semiconductors by X-ray diffraction measurements and evolutionary
programming},
tppubtype = {article},
volume = 160,
year = 2004
}