Full metadata record
DC FieldValueLanguage
dc.contributor.authorLin, Po-Juien_US
dc.contributor.authorSu, Chong-Zihen_US
dc.contributor.authorYao, Chih-Weien_US
dc.contributor.authorWatanabe, Hiroshien_US
dc.date.accessioned2019-04-02T05:59:13Z-
dc.date.available2019-04-02T05:59:13Z-
dc.date.issued2018-12-01en_US
dc.identifier.issn0021-4922en_US
dc.identifier.urihttp://dx.doi.org/10.7567/JJAP.57.124301en_US
dc.identifier.urihttp://hdl.handle.net/11536/148465-
dc.description.abstractThe random telegraph noise (RTN) time constants, capture (T-C) and emission (T-e) times, have been extensively used to identify the trap position in the gate oxide by comparing the measured T-C-over-T-e ratio with the Shockley-Read-Hall (SRH) statistics. However, various factors have been shown to affect the accuracy of the extracted trap depth from the SRH-type models, such as three-dimensional (3D) device electrostatics, atomistic doping, metal gate granularity, and Coulomb energy variation (CEV) of the trap. Focusing on CEV in this work, we assume the trap in gate oxide can be regarded as a floating island and then numerically studied the CEV of the trap with 3D drift-diffusion simulation. Analyzing the simulation data, the extracted trap depth without considering CEV in the SRH statistics are quantitatively compared with the data involved CEV. (C) 2018 The Japan Society of Applied Physicsen_US
dc.language.isoen_USen_US
dc.titleThree-dimensional device simulation of random telegraph noise spectroscopy with Coulomb energy variation of the trap in high-k gate oxideen_US
dc.typeArticleen_US
dc.identifier.doi10.7567/JJAP.57.124301en_US
dc.identifier.journalJAPANESE JOURNAL OF APPLIED PHYSICSen_US
dc.citation.volume57en_US
dc.contributor.department電機工程學系zh_TW
dc.contributor.department電信工程研究所zh_TW
dc.contributor.departmentDepartment of Electrical and Computer Engineeringen_US
dc.contributor.departmentInstitute of Communications Engineeringen_US
dc.identifier.wosnumberWOS:000450209000001en_US
dc.citation.woscount0en_US
Appears in Collections:Articles