Abstract
Two-dimensional (2D) materials have been a hot research topic in the last decade, due to novel fundamental physics in the reduced dimension and appealing applications. Systematic discovery of functional 2D materials has been the focus of many studies. Here, we present a large dataset of 2D materials, with more than 6,000 monolayer structures, obtained from both top-down and bottom-up discovery procedures. First, we screened all bulk materials in the database of Materials Project for layered structures by a topology-based algorithm and theoretically exfoliated them into monolayers. Then, we generated new 2D materials by chemical substitution of elements in known 2D materials by others from the same group in the periodic table. The structural, electronic and energetic properties of these 2D materials are consistently calculated, to provide a starting point for further material screening, data mining, data analysis and artificial intelligence applications. We present the details of computational methodology, data record and technical validation of our publicly available data (http://www.2dmatpedia.org/).
Highlights
Background & SummaryAtomically thin two-dimensional (2D) materials have attracted tremendous research interest for both novel fundamental physics and extremely appealing applications
We use both a top-down approach, in which materials from the inorganic bulk crystals in the Materials Project are screened for layered structures which are theoretically exfoliated to 2D monolayers, and a bottom-up approach, in which elemental substitution is systematically applied to the unary and binary 2D materials obtained from the top-down approach
It is noted that the “discovery process” here only indicates how a 2D material is generated in this work, which is not necessarily related to its experimental synthesis method
Summary
Thin two-dimensional (2D) materials have attracted tremendous research interest for both novel fundamental physics and extremely appealing applications. To accelerate development and deployment of novel advanced materials, the US White House launched the “Materials Genome Initiative” in 2011 (https://www.mgi.gov/) This approach integrates high throughput computation, data analytics together with experimental research and represents a new paradigm for materials discovery. The data-driven material discovery can significantly reduce the cost from many long iterations of trial-and-error experiments by providing the most promising candidates from high-throughput computations. This approach is more flexible as different screenings can be conducted to target materials with. Some criteria on the stability and exfoliation energy were applied to predict potentially exfoliatable stable monolayers[24,26] This method allows a systematic screening of 3D materials for layered structures. The whole database is publicly available at http://www.2dmatpedia.org/
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