| LDR | | 00000nam u2200205 4500 |
| 001 | | 000000433906 |
| 005 | | 20200226110640 |
| 008 | | 200131s2019 ||||||||||||||||| ||eng d |
| 020 | |
▼a 9781687904935 |
| 035 | |
▼a (MiAaPQ)AAI22618949 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
| 082 | 0 |
▼a 620.11 |
| 100 | 1 |
▼a Goodwill, Jonathan M. |
| 245 | 10 |
▼a Understanding Threshold Switching in TaOx-based Selection Devices. |
| 260 | |
▼a [S.l.]:
▼b Carnegie Mellon University.,
▼c 2019. |
| 260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2019. |
| 300 | |
▼a 125 p. |
| 500 | |
▼a Source: Dissertations Abstracts International, Volume: 81-04, Section: B. |
| 500 | |
▼a Advisor: Skowronski, Marek. |
| 502 | 1 |
▼a Thesis (Ph.D.)--Carnegie Mellon University, 2019. |
| 506 | |
▼a This item must not be sold to any third party vendors. |
| 506 | |
▼a This item must not be added to any third party search indexes. |
| 520 | |
▼a In the future, Von Neumann and neuromorphic computing architectures will be made more energy efficient by incorporating novel memory technologies in between main memory and disk levels. By doing this it will help to alleviate the processor-memory bottleneck. Over the past decade numerous types of emerging memories have surfaced with the most promising being crossbar arrays because of the highest possible packing density. Currently, memory elements to store state have somewhat matured but another device is needed in series to limit the current in the crossbar array, a selection device. The selection device must sufficiently meet the needs of the memory element while, at the same time, have highly non-linear I-V characteristics. This requires the selector to be adaptable and still be able to retain its properties. Only by understanding the fundamental physics that give rise to the device properties will we be able to adapt them for certain memory elements.The purpose of the work shown herein is to provide a better understanding of the fundamental processes leading to threshold switching and electro-formation in TaOx selection devices. This is done by first developing a model for threshold switching based on an electro-thermal feedback loop between conductivity and temperature. The model is able to reproduce both transient and quasi-DC I-V characteristics as well as the spatial distributions of temperature, current density, and expansion. The model has been directly validated by the agreement between expansion distributions in simulation and experiment. Lastly, based on the knowledge gained about threshold switching, the electro-formation process was interpreted as a chemical runaway induced by the elevated temperatures experienced during threshold switching, and the position of a resistive gap, responsible for putting the device into a high resistance state, was determined. |
| 590 | |
▼a School code: 0041. |
| 650 | 4 |
▼a Materials science. |
| 690 | |
▼a 0794 |
| 710 | 20 |
▼a Carnegie Mellon University.
▼b Materials Science and Engineering. |
| 773 | 0 |
▼t Dissertations Abstracts International
▼g 81-04B. |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0041 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2019 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15493581
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
| 980 | |
▼a 202002
▼f 2020 |
| 990 | |
▼a ***1008102 |
| 991 | |
▼a E-BOOK |