Using Machine Learning Potentials to Explore Interdiffusion at Metal–Chalcogenide Interfaces-Reference-Cited by-同舟云学术

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Using Machine Learning Potentials to Explore Interdiffusion at Metal–Chalcogenide Interfaces

Published:2022-12-14 Issue:51 Volume:14 Page:56963-56974
ISSN:1944-8244
Container-title:ACS Applied Materials & Interfaces
language:en
Short-container-title:ACS Appl. Mater. Interfaces

Author:

Achar Siddarth K.¹²³^ORCID,Schneider Julian⁴,Stewart Derek A.³^ORCID

Affiliation:

1. Computational Modeling & Simulation Program, University of Pittsburgh, Pittsburgh, Pennsylvania15260, United States

2. Department of Chemical & Petroleum Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania15261, United States

3. Western Digital Corporation, 5601 Great Oaks Pkwy, San Jose, California95119, United States

4. Synopsys Inc., Fruebjergvej 3, 2100Copenhagen, Denmark

Funder

Western Digital

Publisher

American Chemical Society (ACS)

Subject

General Materials Science

Link

https://pubs.acs.org/doi/pdf/10.1021/acsami.2c16254

Reference59 articles.

1. Phase Change Memory

2. Interface controlled thermal resistances of ultra-thin chalcogenide-based phase change memory devices

3. Reversible Electrical Switching Phenomena in Disordered Structures

4. Why are chalcogenide glasses the materials of choice for Ovonic switching devices?

5. Ovonic threshold switching selectors for three-dimensional stackable phase-change memory

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