Analytical modeling electrical conduction in resistive-switching memory through current-limiting-friendly combination frameworks
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 physica...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2020-08-01
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| Series: | AIP Advances |
| Online Access: | http://dx.doi.org/10.1063/5.0019266 |
| _version_ | 1818350912764116992 |
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| author | Qishen Wang Karthekeyan Periasamy Yi Fu Ya-Ting Chan Cher Ming Tan Natasa Bajalovic Jer-Chyi Wang Desmond K. Loke |
| author_facet | Qishen Wang Karthekeyan Periasamy Yi Fu Ya-Ting Chan Cher Ming Tan Natasa Bajalovic Jer-Chyi Wang Desmond K. Loke |
| author_sort | Qishen Wang |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-13T18:29:23Z |
| format | Article |
| id | doaj.art-2802a607e03d4c9d9ee4fb40dbb5641f |
| institution | Directory Open Access Journal |
| issn | 2158-3226 |
| language | English |
| last_indexed | 2024-12-13T18:29:23Z |
| publishDate | 2020-08-01 |
| publisher | AIP Publishing LLC |
| record_format | Article |
| series | AIP Advances |
| spelling | doaj.art-2802a607e03d4c9d9ee4fb40dbb5641f2022-12-21T23:35:32ZengAIP Publishing LLCAIP Advances2158-32262020-08-01108085117085117-610.1063/5.0019266Analytical modeling electrical conduction in resistive-switching memory through current-limiting-friendly combination frameworksQishen Wang0Karthekeyan Periasamy1Yi Fu2Ya-Ting Chan3Cher Ming Tan4Natasa Bajalovic5Jer-Chyi Wang6Desmond K. Loke7Department of Science, Mathematics and Technology, Singapore University of Technology and Design, 8 Somapah Road, 487372, SingaporeDepartment of Science, Mathematics and Technology, Singapore University of Technology and Design, 8 Somapah Road, 487372, SingaporeDepartment of Electronic Engineering, Chang Gung University, Guishan District, Taoyuan City 33302, TaiwanDepartment of Electronic Engineering, Chang Gung University, Guishan District, Taoyuan City 33302, TaiwanDepartment of Electronic Engineering, Chang Gung University, Guishan District, Taoyuan City 33302, TaiwanDepartment of Science, Mathematics and Technology, Singapore University of Technology and Design, 8 Somapah Road, 487372, SingaporeDepartment of Electronic Engineering, Chang Gung University, Guishan District, Taoyuan City 33302, TaiwanDepartment of Science, Mathematics and Technology, Singapore University of Technology and Design, 8 Somapah Road, 487372, SingaporeResistive-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.http://dx.doi.org/10.1063/5.0019266 |
| spellingShingle | Qishen Wang Karthekeyan Periasamy Yi Fu Ya-Ting Chan Cher Ming Tan Natasa Bajalovic Jer-Chyi Wang Desmond K. Loke Analytical modeling electrical conduction in resistive-switching memory through current-limiting-friendly combination frameworks AIP Advances |
| title | Analytical modeling electrical conduction in resistive-switching memory through current-limiting-friendly combination frameworks |
| title_full | Analytical modeling electrical conduction in resistive-switching memory through current-limiting-friendly combination frameworks |
| title_fullStr | Analytical modeling electrical conduction in resistive-switching memory through current-limiting-friendly combination frameworks |
| title_full_unstemmed | Analytical modeling electrical conduction in resistive-switching memory through current-limiting-friendly combination frameworks |
| title_short | Analytical modeling electrical conduction in resistive-switching memory through current-limiting-friendly combination frameworks |
| title_sort | analytical modeling electrical conduction in resistive switching memory through current limiting friendly combination frameworks |
| url | http://dx.doi.org/10.1063/5.0019266 |
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