001     1023073
005     20250203103404.0
024 7 _ |a 10.1149/2162-8777/acd720
|2 doi
024 7 _ |a 2162-8769
|2 ISSN
024 7 _ |a 2162-8777
|2 ISSN
024 7 _ |a WOS:000999127900001
|2 WOS
037 _ _ |a FZJ-2024-01646
082 _ _ |a 660
100 1 _ |a Frauenrath, M.
|0 P:(DE-HGF)0
|b 0
|e Corresponding author
245 _ _ |a Advances in In Situ Boron and Phosphorous Doping of SiGeSn
260 _ _ |a Pennington, NJ
|c 2023
|b ECS
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1709021315_548
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a Dopant concentrations higher than 1 × 1019 cm−3 are required to improve the performances of various GeSn based devices such as photodetectors, electrically pumped lasers and so on. In this study, the in situ Boron and Phosphorous doping of SiGeSn was investigated, building upon recent studies on in situ B or P doped GeSn. The surfaces of intrinsic and lowly doped pseudomorphic SiGeSn layers were rough. By contrast, a 〈110〉 cross hatch was recovered and surfaces as smooth as the Ge Strain-Relaxed Buffers underneath were obtained for the highest B2H6 or PH3 mass-flows. The surface Root Mean Square roughness and Zrange values were then as low as 0.36 nm and 2.86 nm for SiGeSn:B, and 0.47 nm and 4.60 nm for SiGeSn:P. In addition, Si contents as high as 25% were obtained, notably in SiGeSn:B layers. Dopants were almost fully electrically active in those SiGeSn:B and SiGeSn:P layers, with carrier concentrations as high as 2.0 × 1020 cm−3 and 2.7 × 1020 cm−3, respectively. For SiGeSn:P, the shortcoming of in situ doped GeSn:P was overcome, that is the formation of electrically inactive SnmPnV clusters for high PH3 mass-flows. Such electrically active carrier concentrations will be beneficial for (Si)GeSn based devices, but also for all Group-IV based devices with extremely low thermal budget constraints.
536 _ _ |a 5234 - Emerging NC Architectures (POF4-523)
|0 G:(DE-HGF)POF4-5234
|c POF4-523
|f POF IV
|x 0
588 _ _ |a Dataset connected to CrossRef, Journals: juser.fz-juelich.de
700 1 _ |a Concepción Díaz, Omar
|0 P:(DE-Juel1)188576
|b 1
|u fzj
700 1 _ |a Gauthier, N.
|0 P:(DE-HGF)0
|b 2
700 1 _ |a Nolot, E.
|0 P:(DE-HGF)0
|b 3
700 1 _ |a Buca, D.
|0 P:(DE-Juel1)125569
|b 4
700 1 _ |a Hartmann, J.-M.
|0 P:(DE-HGF)0
|b 5
773 _ _ |a 10.1149/2162-8777/acd720
|g Vol. 12, no. 6, p. 064001 -
|0 PERI:(DE-600)2674149-0
|n 6
|p 064001 -
|t ECS journal of solid state science and technology
|v 12
|y 2023
|x 2162-8769
856 4 _ |u https://juser.fz-juelich.de/record/1023073/files/Frauenrath_2023_ECS_J._Solid_State_Sci._Technol._12_064001.pdf
856 4 _ |u https://juser.fz-juelich.de/record/1023073/files/Frauenrath_2023_ECS_J._Solid_State_Sci._Technol._12_064001.gif?subformat=icon
|x icon
856 4 _ |u https://juser.fz-juelich.de/record/1023073/files/Frauenrath_2023_ECS_J._Solid_State_Sci._Technol._12_064001.jpg?subformat=icon-1440
|x icon-1440
856 4 _ |u https://juser.fz-juelich.de/record/1023073/files/Frauenrath_2023_ECS_J._Solid_State_Sci._Technol._12_064001.jpg?subformat=icon-180
|x icon-180
856 4 _ |u https://juser.fz-juelich.de/record/1023073/files/Frauenrath_2023_ECS_J._Solid_State_Sci._Technol._12_064001.jpg?subformat=icon-640
|x icon-640
909 C O |o oai:juser.fz-juelich.de:1023073
|p VDB
910 1 _ |a External Institute
|0 I:(DE-HGF)0
|k Extern
|b 0
|6 P:(DE-HGF)0
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)188576
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 4
|6 P:(DE-Juel1)125569
913 1 _ |a DE-HGF
|b Key Technologies
|l Natural, Artificial and Cognitive Information Processing
|1 G:(DE-HGF)POF4-520
|0 G:(DE-HGF)POF4-523
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Neuromorphic Computing and Network Dynamics
|9 G:(DE-HGF)POF4-5234
|x 0
914 1 _ |y 2024
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b ECS J SOLID STATE SC : 2022
|d 2023-08-24
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2023-08-24
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2023-08-24
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2023-08-24
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2023-08-24
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1160
|2 StatID
|b Current Contents - Engineering, Computing and Technology
|d 2023-08-24
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1150
|2 StatID
|b Current Contents - Physical, Chemical and Earth Sciences
|d 2023-08-24
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
|d 2023-08-24
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)PGI-9-20110106
|k PGI-9
|l Halbleiter-Nanoelektronik
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-Juel1)PGI-9-20110106
980 _ _ |a UNRESTRICTED


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21