Analytical modeling electrical conduction in resistive-switching memory through current-limiting-friendly combination frameworks

AIP ADVANCES(2020)

引用 5|浏览2
暂无评分
摘要
Resistive-switching memory (RSM) is one of the most promising candidates for next-generation edge computing devices due to its excellent device performance. Currently, a number of experimental and modeling studies have been reported to understand the conduction behaviors. However, a complete physical picture that can describe the conduction behavior is still missing. Here, we present a conduction model that not only fully accounts for the rich conduction behaviors of RSM devices by harnessing a combination of electronic and thermal considerations via electron mobility and trap-depth and with excellent accuracy but also provides critical insight for continued design, optimization, and application. A physical model that is able to describe both the conduction and switching behaviors using only a single set of expressions is achieved. The proposed model reveals the role of temperature, mobility of electrons, and depth of traps, and allows accurate prediction of various set and reset processes obtained by an entirely new set of general current-limiting parameters.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要