001     902086
005     20220126143614.0
024 7 _ |a 10.1007/s10836-021-05968-8
|2 doi
024 7 _ |a 0923-8174
|2 ISSN
024 7 _ |a 1573-0727
|2 ISSN
024 7 _ |a 2128/28852
|2 Handle
024 7 _ |a WOS:000709238700001
|2 WOS
037 _ _ |a FZJ-2021-04026
082 _ _ |a 670
100 1 _ |a Poehls, L. M. Bolzani
|0 P:(DE-HGF)0
|b 0
|e Corresponding author
245 _ _ |a Review of Manufacturing Process Defects and Their Effects on Memristive Devices
260 _ _ |a Dordrecht [u.a.]
|c 2021
|b Springer Science + Business Media B.V
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 1643201752_9153
|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 Complementary Metal Oxide Semiconductor (CMOS) technology has been scaled down over the last forty years making possible the design of high-performance applications, following the predictions made by Gordon Moore and Robert H. Dennard in the 1970s. However, there is a growing concern that device scaling, while maintaining cost-effective production, will become infeasible below a certain feature size. In parallel, emerging applications including Internet-of-Things (IoT) and big data applications present high demands in terms of storage and computing capability, combined with challenging constraints in terms of size, power consumption and response latency. In this scenario, memristive devices have become promising candidates to complement the CMOS technology due to their CMOS manufacturing process compatibility, great scalability and high density, zero standby power consumption and their capacity to implement high density memories as well as new computing paradigms. Despite these advantages, memristive devices are also susceptible to manufacturing defects that may cause unique faulty behaviors that are not seen in CMOS, increasing significantly the complexity of test procedures. This paper provides a review about the manufacturing process of memristives devices, focusing on Valence Change Mechanism (VCM)-based memristive devices, and a comparative analysis of the CMOS and memristive device manufacturing processes. Moreover, this paper identifies possible manufacturing failure mechanisms that may affect these novel devices, completing the list of the already known mechanisms, and provides a discussion about possible faulty behaviors. Note that the identification of these mechanisms provides insights regarding the possible memristive devices’ defective behaviors, enabling to derive more accurate fault models and consequently, more suitable test procedures.
536 _ _ |a 5233 - Memristive Materials and Devices (POF4-523)
|0 G:(DE-HGF)POF4-5233
|c POF4-523
|f POF IV
|x 0
536 _ _ |a Verbundprojekt: Neuro-inspirierte Technologien der künstlichen Intelligenz für die Elektronik der Zukunft - NEUROTEC -, Teilvorhaben: Forschungszentrum Jülich (16ES1133K)
|0 G:(BMBF)16ES1133K
|c 16ES1133K
|x 1
588 _ _ |a Dataset connected to CrossRef, Journals: juser.fz-juelich.de
700 1 _ |a Fieback, M. C. R.
|0 P:(DE-HGF)0
|b 1
700 1 _ |a Hoffmann-Eifert, S.
|0 P:(DE-Juel1)130717
|b 2
700 1 _ |a Copetti, T.
|0 P:(DE-HGF)0
|b 3
700 1 _ |a Brum, E.
|0 P:(DE-HGF)0
|b 4
700 1 _ |a Menzel, Stephan
|0 P:(DE-Juel1)158062
|b 5
700 1 _ |a Hamdioui, S.
|0 P:(DE-HGF)0
|b 6
700 1 _ |a Gemmeke, T.
|0 P:(DE-HGF)0
|b 7
773 _ _ |a 10.1007/s10836-021-05968-8
|0 PERI:(DE-600)1479776-8
|p 1
|t Journal of electronic testing
|v 47
|y 2021
|x 1573-0727
856 4 _ |u https://juser.fz-juelich.de/record/902086/files/Poehls2021_Article_ReviewOfManufacturingProcessDe.pdf
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:902086
|p openaire
|p open_access
|p VDB
|p driver
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 2
|6 P:(DE-Juel1)130717
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 5
|6 P:(DE-Juel1)158062
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)POF4-5233
|x 0
914 1 _ |y 2021
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2021-01-27
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1230
|2 StatID
|b Current Contents - Electronics and Telecommunications Collection
|d 2021-01-27
915 _ _ |a Creative Commons Attribution CC BY 4.0
|0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
|d 2021-01-27
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b J ELECTRON TEST : 2019
|d 2021-01-27
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2021-01-27
915 _ _ |a DEAL Springer
|0 StatID:(DE-HGF)3002
|2 StatID
|d 2021-01-27
|w ger
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2021-01-27
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
|d 2021-01-27
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
|d 2021-01-27
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1160
|2 StatID
|b Current Contents - Engineering, Computing and Technology
|d 2021-01-27
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2021-01-27
915 _ _ |a Nationallizenz
|0 StatID:(DE-HGF)0420
|2 StatID
|d 2021-01-27
|w ger
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2021-01-27
920 1 _ |0 I:(DE-Juel1)PGI-7-20110106
|k PGI-7
|l Elektronische Materialien
|x 0
920 1 _ |0 I:(DE-82)080009_20140620
|k JARA-FIT
|l JARA-FIT
|x 1
920 1 _ |0 I:(DE-Juel1)PGI-10-20170113
|k PGI-10
|l JARA Institut Green IT
|x 2
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-Juel1)PGI-7-20110106
980 _ _ |a I:(DE-82)080009_20140620
980 _ _ |a I:(DE-Juel1)PGI-10-20170113
980 _ _ |a UNRESTRICTED
980 1 _ |a FullTexts


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21