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Resistive Switching in Stabilized Zirconia Films Studied by Conductive Atomic Force Microscopy
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作者 Dmitry Filatov Dmitry Antonov +2 位作者 Ivan Antonov Alexander Kasatkin oleg gorshkov 《Journal of Materials Science and Chemical Engineering》 2017年第1期8-14,共7页
We have applied Conductive Atomic Force Microscopy (CAFM) to study the microscopic mechanism of resistive switching in the ultrathin (3 - 5 nm) yttria stabilized zirconia (YSZ) films. Using CAFM, we were able to trace... We have applied Conductive Atomic Force Microscopy (CAFM) to study the microscopic mechanism of resistive switching in the ultrathin (3 - 5 nm) yttria stabilized zirconia (YSZ) films. Using CAFM, we were able to trace the growth of the individual conductive filaments, which are considered now to be responsible for the resistive switching effect in the transition metal oxides. The growth of the filaments has been proven to be initiated by the defects in the film material including the ones, which are the concentrators of the electric field, in particular, by the roughness (hillocks) of the film/substrate interface. The electron transport via individual filaments has been studied. Besides the butterfly-type hysteresis in the current-voltage (I-V) curves of the probe- to-sample contact typical for the bipolar resistive switching, we have observed the I-V curves with resonant peaks attributed to the resonant electron tunneling via the localized electron states in the filaments. 展开更多
关键词 Resistive Switching YTTRIA STABILIZED ZIRCONIA CONDUCTIVE ATOMIC Force Microscopy
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Estimating the number of data clusters via the contrast statistic
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作者 Yuriy Lyakh Vitaliy Gurianov +1 位作者 oleg gorshkov Yuriy Vihovanets 《Journal of Biomedical Science and Engineering》 2012年第2期95-99,共5页
A new method (the Contrast statistic) for estimating the number of clusters in a set of data is proposed. The technique uses the output of self-organising map clustering algorithm, comparing the change in dependency ... A new method (the Contrast statistic) for estimating the number of clusters in a set of data is proposed. The technique uses the output of self-organising map clustering algorithm, comparing the change in dependency of “Contrast” value upon clusters number to that expected under a uniform distribution. A simulation study shows that the Contrast statistic can be used successfully either, when variables describing the object in a multi-dimensional space are independent (ideal objects) or dependent (real biological objects). 展开更多
关键词 SOM NEURAL Network Clustering Gap Statistic SILHOUETTE Statistic
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