Predicting the work function of 2D MXenes using machine-learning methods

• Main Authors: Roy, Pranav, Rekhi, Lavie, Koh, See Wee, Li, Hong, Choksi, Tej S.
• Other Authors: School of Chemical and Biomedical Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Chemical engineering; Engineering::Mechanical engineering; Density Functional Theory; Machine Learning
• Online Access: https://hdl.handle.net/10356/170010
• Institution: Nanyang Technological University

MXenes, which are graphene-like two-dimensional transition metal carbides and nitrides, have tunable compositions and exhibit rich surface chemistry. This compositional flexibility has resulted in exquisitely tunable electronic, optical, and mechanical properties leading to the applications of MXene...