In situ growth optimization in focused electron-beam induced deposition
We present the application of an evolutionary genetic algorithm for the in situ optimization of nanostructures that are prepared by focused electron-beam-induced deposition (FEBID). It allows us to tune the properties of the deposits towards the highest conductivity by using the time gradient of the...
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doaj-0976a22193634b07baf9ac214a3875672020-11-25T02:01:53ZengBeilstein-InstitutBeilstein Journal of Nanotechnology2190-42862013-12-014191992610.3762/bjnano.4.1032190-4286-4-103In situ growth optimization in focused electron-beam induced depositionPaul M. Weirich0Marcel Winhold1Christian H. Schwalb2Michael Huth3Physikalisches Institut, Goethe Universität, Max-von-Laue-Str. 1, 60438 Frankfurt am Main, GermanyPhysikalisches Institut, Goethe Universität, Max-von-Laue-Str. 1, 60438 Frankfurt am Main, GermanyPhysikalisches Institut, Goethe Universität, Max-von-Laue-Str. 1, 60438 Frankfurt am Main, GermanyPhysikalisches Institut, Goethe Universität, Max-von-Laue-Str. 1, 60438 Frankfurt am Main, GermanyWe present the application of an evolutionary genetic algorithm for the in situ optimization of nanostructures that are prepared by focused electron-beam-induced deposition (FEBID). It allows us to tune the properties of the deposits towards the highest conductivity by using the time gradient of the measured in situ rate of change of conductance as the fitness parameter for the algorithm. The effectiveness of the procedure is presented for the precursor W(CO)6 as well as for post-treatment of Pt–C deposits, which were obtained by the dissociation of MeCpPt(Me)3. For W(CO)6-based structures an increase of conductivity by one order of magnitude can be achieved, whereas the effect for MeCpPt(Me)3 is largely suppressed. The presented technique can be applied to all beam-induced deposition processes and has great potential for a further optimization or tuning of parameters for nanostructures that are prepared by FEBID or related techniques.https://doi.org/10.3762/bjnano.4.103electron beam induced depositiongenetic algorithmnanotechnologytungsten |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Paul M. Weirich Marcel Winhold Christian H. Schwalb Michael Huth |
spellingShingle |
Paul M. Weirich Marcel Winhold Christian H. Schwalb Michael Huth In situ growth optimization in focused electron-beam induced deposition Beilstein Journal of Nanotechnology electron beam induced deposition genetic algorithm nanotechnology tungsten |
author_facet |
Paul M. Weirich Marcel Winhold Christian H. Schwalb Michael Huth |
author_sort |
Paul M. Weirich |
title |
In situ growth optimization in focused electron-beam induced deposition |
title_short |
In situ growth optimization in focused electron-beam induced deposition |
title_full |
In situ growth optimization in focused electron-beam induced deposition |
title_fullStr |
In situ growth optimization in focused electron-beam induced deposition |
title_full_unstemmed |
In situ growth optimization in focused electron-beam induced deposition |
title_sort |
in situ growth optimization in focused electron-beam induced deposition |
publisher |
Beilstein-Institut |
series |
Beilstein Journal of Nanotechnology |
issn |
2190-4286 |
publishDate |
2013-12-01 |
description |
We present the application of an evolutionary genetic algorithm for the in situ optimization of nanostructures that are prepared by focused electron-beam-induced deposition (FEBID). It allows us to tune the properties of the deposits towards the highest conductivity by using the time gradient of the measured in situ rate of change of conductance as the fitness parameter for the algorithm. The effectiveness of the procedure is presented for the precursor W(CO)6 as well as for post-treatment of Pt–C deposits, which were obtained by the dissociation of MeCpPt(Me)3. For W(CO)6-based structures an increase of conductivity by one order of magnitude can be achieved, whereas the effect for MeCpPt(Me)3 is largely suppressed. The presented technique can be applied to all beam-induced deposition processes and has great potential for a further optimization or tuning of parameters for nanostructures that are prepared by FEBID or related techniques. |
topic |
electron beam induced deposition genetic algorithm nanotechnology tungsten |
url |
https://doi.org/10.3762/bjnano.4.103 |
work_keys_str_mv |
AT paulmweirich insitugrowthoptimizationinfocusedelectronbeaminduceddeposition AT marcelwinhold insitugrowthoptimizationinfocusedelectronbeaminduceddeposition AT christianhschwalb insitugrowthoptimizationinfocusedelectronbeaminduceddeposition AT michaelhuth insitugrowthoptimizationinfocusedelectronbeaminduceddeposition |
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