2DMatPedia and High-throughput Discovery of Novel 2D Functional Materials
Shen Lei1, Zhou Jun2, Yang Tong3, Yang Ming3, Feng Yuanping4*
1 Department of Mechanical Engineering, National University of Singapore, Singapore
2 Institute of Materials Research and Engineering, Agency for Science, Technology and Research, Singapore
3 Department of Applied Physics, Hong Kong Polytechnic University, Hong Kong, China
4 Department of Physics, National University of Singapore, Singapore
EXTENDED ABSTRACT: Two-dimensional (2D) materials have been extensively studied because of their unique properties which can lead to new technologies. Although the number of experimentally discovered 2D materials is growing, the speed has been slow and only a few dozen 2D materials have been synthesized or exfoliated. It is thus important to speed up the discovery of 2D materials and explore their technological applications. The emerging high-throughput computational materials design, which combines quantummechanical theory, materials genome, and database construction with intelligent data mining, is expected to greatly accelerate the discovery, design and application of 2D materials, by creating databases containing a large collection of 2D materials with calculated fundamental properties, and performing intelligent mining (via highthroughput automation or machine learning) of the database to screen 2D materials for desired properties for particular applications, such as energy conversion, electronics, spintronics, and optoelectronics. In this presentation, I will provide a quick update on our recent progress in the development of the 2D materials database - 2D Materials Encyclopedia (2DMatPedia for short), which includes structural, thermodynamic, mechanical, electronic, and magnetic properties of more than 6,000 2D materials. Then I will discuss several applications of novel 2D materials based on 2DMatPedia, including electrocatalysis, magnetic tunnel junctions, piezo-/ferroelectricity, topological superconductor and solar cells. Such an open 2D materials database with high-throughput calculations and proper advanced models will greatly reduce the experimental effort in trial and error, narrow down the scope for both experimental and theoretical explorations, and thus boost the fast and sustainable development in the area of 2D materials.
REFERENCES
[1]Jun Zhou et al., 2DMatPedia, an open computational database of two-dimensional materials from top-down
and bottom-up approaches, Scientific Data 6, 86 (2019)
[2]http://www.2dmatpedia.org/
[3]Lei Shen et al. High-throughput Discovery and Intelligent Design of 2D Functional Materials for Various
Applications, submitted.
Yuan Ping Feng received his Ph.D from Illinois Institute of Technology in 1987. After completing his postdoc training at Purdue University, he joined the National University of Singapore (NUS) as a faculty member in 1990. His research interest is in computational materials physics, focusing mainly on understanding of fundamental properties of materials for advanced technologies, and prediction of new materials based on ab initio electronic structure calculations and genomic approach. Y P Feng is a fellow of the American Physical Society, a fellow of the Institute of Physics, Singapore, and an Academician of the Asian Pacific Academy of Materials. He is currently the Second Vice President of International Union of Materials Research Societies, and a Vice President of Materials Research Society of Singapore.