Atomic insights into device-scale phase-change memory materials using machine learning potential

Guanjie Wang; Zhimei Sun

doi:10.1016/j.scib.2023.11.038

Atomic insights into device-scale phase-change memory materials using machine learning potential

Guanjie Wang
, Zhimei Sun^*

^*Corresponding author for this work

School of Materials Science and Engineering

Beihang University

Research output: Contribution to journal › Comment/debate

6 Scopus citations

Original language	English
Pages (from-to)	3105-3107
Number of pages	3
Journal	Science Bulletin
Volume	68
Issue number	24
DOIs	https://doi.org/10.1016/j.scib.2023.11.038
State	Published - 30 Dec 2023

Access to Document

10.1016/j.scib.2023.11.038

Cite this

@article{b8fd74eb98624358830f71906e112098,

title = "Atomic insights into device-scale phase-change memory materials using machine learning potential",

author = "Guanjie Wang and Zhimei Sun",

year = "2023",

month = dec,

day = "30",

doi = "10.1016/j.scib.2023.11.038",

language = "英语",

volume = "68",

pages = "3105--3107",

journal = "Science Bulletin",

issn = "2095-9273",

publisher = "Elsevier B.V.",

number = "24",

}

TY - JOUR

T1 - Atomic insights into device-scale phase-change memory materials using machine learning potential

AU - Wang, Guanjie

AU - Sun, Zhimei

PY - 2023/12/30

Y1 - 2023/12/30

UR - https://www.scopus.com/pages/publications/85178017999

U2 - 10.1016/j.scib.2023.11.038

DO - 10.1016/j.scib.2023.11.038

M3 - 评论/辩论

AN - SCOPUS:85178017999

SN - 2095-9273

VL - 68

SP - 3105

EP - 3107

JO - Science Bulletin

JF - Science Bulletin

IS - 24

ER -

Atomic insights into device-scale phase-change memory materials using machine learning potential

Access to Document

Other files and links

Cite this