Paper Details

Abstract

Pentagonal two-dimensional (2D) materials, such as penta-XP$_5$ (X = Al, Ga, In), exhibit promising properties for thermoelectric and optoelectronic applications. However, their thermal transport characteristics remain underexplored due to the high computational cost of first-principles phonon calculations. In this study, we employ on-the-fly machine learning potentials (FMLP) combined with DFT to investigate the lattice thermal conductivity of penta-XP$_5$ monolayers. All structures are found to be thermodynamically and mechanically stable. At room temperature, thermal conductivities are predicted to be 6.09, 6.51, and 1.82 ~W/mK for AlP$_5$, GaP$_5$, and InP$_5$, respectively. These results highlight the potential of penta-XP$_5$ monolayers for nanoscale thermal management and thermoelectric applications.

Keywords
Machine learning latiice thermal conductivity penta-XP5 monolayer
Contact Information
Vo Khuong Dien (Corresponding Author)
FPT University - Cantho campus, Vietnam
0793178769

All Authors (4)

Vo Khuong Dien C

Affiliation: FPT University - Cantho campus

Country: Vietnam

Email: dienvk@fpt.edu.vn

Phone: 0793178769

Nguyen Thi Han

Affiliation: Department of Basic Sciences, Hung Yen University of Technology and Education, Hung Yen, Viet Nam

Country: Vietnam

Email: nguyenthihan@utehy.edu.vn

Phone: 0793178768

Thai Van Thanh

Affiliation: Faculty of Basic Sciences, Vinh Long University of Technology and Education, No. 73, Nguyen Hue, Ward 1, Vinh Long city, Vinh Long province, Vietnam

Country: Vietnam

Email: thanhtv@vlute.edu.vn

Phone: 0793178768

Nguyen Thanh Tien

Affiliation: College of Natural Sciences, Can Tho University, 3-2 Road, Can Tho City 94000, Vietnam

Country: Vietnam

Email: nttien@ctu.edu.vn

Phone: 0793178768