000454551 001__ 454551
000454551 005__ 20250716151919.0
000454551 0247_ $$2doi$$a10.1016/j.jmst.2020.04.046
000454551 0247_ $$2WOS$$aWOS:000588638600021
000454551 0247_ $$2datacite_doi$$a10.3204/PUBDB-2021-00602
000454551 0247_ $$2openalex$$aopenalex:W3035812526
000454551 037__ $$aPUBDB-2021-00602
000454551 041__ $$aEnglish
000454551 082__ $$a670
000454551 1001_ $$0P:(DE-HGF)0$$aKunwar, Anil$$b0$$eCorresponding author
000454551 245__ $$aIntegration of machine learning with phase field method to model the electromigration induced Cu$_{6}$Sn$_{5}$ IMC growth at anode side Cu/Sn interface
000454551 260__ $$aShenyang$$bEd. Board, Journal of Materials Science & Technology$$c2020
000454551 3367_ $$2DRIVER$$aarticle
000454551 3367_ $$2DataCite$$aOutput Types/Journal article
000454551 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1631879999_22471
000454551 3367_ $$2BibTeX$$aARTICLE
000454551 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000454551 3367_ $$00$$2EndNote$$aJournal Article
000454551 520__ $$aCurrently, in the era of big data and 5G communication technology, electromigration has become a serious reliability issue for the miniaturized solder joints used in microelectronic devices. Since the effective charge number (Z*) is considered as the driving force for electromigration, the lack of accurate experimental values for Z* poses severe challenges for the simulation-aided design of electronic materials. In this work, a data-driven framework is developed to predict the Z* values of Cu and Sn species at the anode based LIQUID, Cu$_6$Sn$_5$ intermetallic compound (IMC) and FCC phases for the binary Cu-Sn system undergoing electromigration at 523.15 K. The growth rate constants (k$_{em}$) of the anode IMC at several magnitudes of applied low current density (j = 1 × 10$^6$ to 10 × 10$^6$ A/m$^2$) are extracted from simulations based on a 1D multi-phase field model. A neural network employing Z* and j as input features, whereas utilizing these computed k$_{em}$ data as the expected output is trained. The results of the neural network analysis are optimized with experimental growth rate constants to estimate the effective charge numbers. For a negligible increase in temperature at low j values, effective charge numbers of all phases are found to increase with current density and the increase is much more pronounced for the IMC phase. The predicted values of effective charge numbers Z* are then utilized in a 2D simulation to observe the anode IMC grain growth and electrical resistance changes in the multi-phase system. As the work consists of the aspects of experiments, theory, computation, and machine learning, it can be called the four paradigms approach for the study of electromigration in Pb-free solder. Such a combination of multiple paradigms of materials design can be problem-solving for any future research scenario that is marked by uncertainties regarding the determination of material properties.
000454551 536__ $$0G:(DE-HGF)POF3-6213$$a6213 - Materials and Processes for Energy and Transport Technologies (POF3-621)$$cPOF3-621$$fPOF III$$x0
000454551 536__ $$0G:(DE-HGF)2020_Join2-SWEDEN-DESY$$aSWEDEN-DESY - SWEDEN-DESY Collaboration (2020_Join2-SWEDEN-DESY)$$c2020_Join2-SWEDEN-DESY$$x1
000454551 588__ $$aDataset connected to CrossRef
000454551 693__ $$0EXP:(DE-MLZ)NOSPEC-20140101$$5EXP:(DE-MLZ)NOSPEC-20140101$$eNo specific instrument$$x0
000454551 7001_ $$aCoutinho, Yuri Amorim$$b1
000454551 7001_ $$0P:(DE-H253)PIP1085987$$aHektor, Johan$$b2
000454551 7001_ $$aMa, Haitao$$b3
000454551 7001_ $$aMoelans, Nele$$b4
000454551 773__ $$0PERI:(DE-600)2431914-4$$a10.1016/j.jmst.2020.04.046$$gVol. 59, p. 203 - 219$$p203 - 219$$tJournal of materials science & technology$$v59$$x1005-0302$$y2020
000454551 8564_ $$uhttps://bib-pubdb1.desy.de/record/454551/files/Kunwar_et_al_electromigration_2020_V1_postprint.pdf$$yPublished on 2020-12-15. Available in OpenAccess from 2021-12-15.
000454551 8564_ $$uhttps://bib-pubdb1.desy.de/record/454551/files/Kunwar_et_al_electromigration_2020_V1_postprint.pdf?subformat=pdfa$$xpdfa$$yPublished on 2020-12-15. Available in OpenAccess from 2021-12-15.
000454551 909CO $$ooai:bib-pubdb1.desy.de:454551$$pdnbdelivery$$pdriver$$pVDB$$popen_access$$popenaire
000454551 9101_ $$0I:(DE-588b)2008985-5$$6P:(DE-H253)PIP1085987$$aDeutsches Elektronen-Synchrotron$$b2$$kDESY
000454551 9101_ $$0I:(DE-HGF)0$$6P:(DE-H253)PIP1085987$$aExternal Institute$$b2$$kExtern
000454551 9131_ $$0G:(DE-HGF)POF3-621$$1G:(DE-HGF)POF3-620$$2G:(DE-HGF)POF3-600$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF3-6213$$aDE-HGF$$bForschungsbereich Materie$$lVon Materie zu Materialien und Leben$$vIn-house research on the structure, dynamics and function of matter$$x0
000454551 9141_ $$y2020
000454551 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2020-09-05
000454551 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2020-09-05
000454551 915__ $$0StatID:(DE-HGF)1230$$2StatID$$aDBCoverage$$bCurrent Contents - Electronics and Telecommunications Collection$$d2020-09-05
000454551 915__ $$0StatID:(DE-HGF)0530$$2StatID$$aEmbargoed OpenAccess
000454551 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bJ MATER SCI TECHNOL : 2018$$d2020-09-05
000454551 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2020-09-05
000454551 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2020-09-05
000454551 915__ $$0StatID:(DE-HGF)0400$$2StatID$$aAllianz-Lizenz / DFG$$d2020-09-05$$wger
000454551 915__ $$0StatID:(DE-HGF)9905$$2StatID$$aIF >= 5$$bJ MATER SCI TECHNOL : 2018$$d2020-09-05
000454551 915__ $$0StatID:(DE-HGF)1160$$2StatID$$aDBCoverage$$bCurrent Contents - Engineering, Computing and Technology$$d2020-09-05
000454551 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2020-09-05
000454551 915__ $$0StatID:(DE-HGF)0420$$2StatID$$aNationallizenz$$d2020-09-05$$wger
000454551 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2020-09-05
000454551 9201_ $$0I:(DE-H253)FS-PET-D-20190712$$kFS-PET-D$$lExperimentebetreuung PETRA III$$x0
000454551 980__ $$ajournal
000454551 980__ $$aVDB
000454551 980__ $$aUNRESTRICTED
000454551 980__ $$aI:(DE-H253)FS-PET-D-20190712
000454551 9801_ $$aFullTexts