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dc.contributor.authorNicholls, Jordan R
dc.contributor.authorDimitrijev, Sima
dc.description.abstractThe number of variables involved in the formation of Ohmic contacts to SiC is large, and their relationships to the final contact resistance are often unclear. As such, trial-and-error methods are typically employed to develop or improve SiC contacts. In pursuit of a better alternative, we developed and tested several regression models to predict the specific contact resistance of Ni, Ti, and Al based contacts on both n- and p-type SiC. Literature data was used to train linear regression, Gaussian process regression, and neural network (NN) ensemble models; of these, the NN ensemble was the most effective at predicting contact resistances. We then applied the model to optimize the annealing schedule for Ni contacts to n-type 4H-SiC, and Ti/Al contacts to p-type 4H-SiC. Finally, we use the model to generate optimal simultaneous contact recipes.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartofjournalIEEE Transactions on Semiconductor Manufacturing
dc.subject.fieldofresearchElectrical engineering
dc.titleRegression Model for the Specific Contact Resistance of SiC Ohmic Contacts
dc.typeJournal article
dc.type.descriptionC1 - Articles
dcterms.bibliographicCitationNicholls, JR; Dimitrijev, S, Regression Model for the Specific Contact Resistance of SiC Ohmic Contacts, IEEE Transactions on Semiconductor Manufacturing, 2021, 34 (4), pp. 493-499
gro.hasfulltextNo Full Text
gro.griffith.authorDimitrijev, Sima
gro.griffith.authorNicholls, Jordan R.

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