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Experimental determination of work function of metals is not only a difficult task but also characterized with certain degree of inaccuracy. The success of metallic plasma model (MPM) remains incomplete due to its inability to correctly estimate work functions of elemental semiconductors (Silicon and Germanium). Support vector machine (SVM) with accuracy of over 98% in the work function estimation is hereby proposed to address the limitations of MPM. The estimated work functions obtained using SVM approach were compared with the universally accepted experimental work functions as well as work functions obtained from MPM and other theoretical model. Work functions obtained using SVM approach agree well with the experimental values.

Support Vector Machines Approach for Estimating Work Function of Semiconductors: Addressing the Limitation of Metallic Plasma Model