Аннотация:In this paper, mathematical modeling of memristor has been discussed considering temperature effects and its variation during resistive switching. Temperature-affected parameters of memristor has been listed. A model of memristor has been carried out, including temperature influence on mobility of oxygen vacancies and self-heating effects. The model reveals that increasing temperature causes faster switching, also some problems of window function choice and model optimization have been discussed.
Источник:International Forum “Microelectronics – 2020”. Joung Scientists Scholarship “Microelectronics – 2020”. XIII International conference «Silicon – 2020». XII young scientists scholarship for silicon nanostructures and devices physics, material science, process and analysis
Ключевые слова:Advanced Memory and Neural Computing, Phase-change materials and chalcogenides, Transition Metal Oxide Nanomaterials
