Large-scale Integration of Experimental and Computational Data for 2D Materials

TL;DR

This work identifies 370 unique 2D materials that have been realized in monolayer or few-layer form, and link them to their digital counterparts in computational databases, enabling consistent ab initio characterization of their properties across monolayer, bilayer and bulk forms.

Abstract

The past decade has seen rapid growth in the number of experimentally realized two-dimensional (2D) materials with diverse chemical and physical properties. However, information on their crystal structure, synthesis routes, and measured or predicted properties, remains scattered across thousands of publications. Here we consolidate this fragmented knowledge by establishing X2DB - an open infrastructure that integrates experimental and computational data on 2D materials. Using extensive literature mining and direct community uploads, we identify 370 unique 2D materials that have been realized in monolayer or few-layer form, and link them to their digital counterparts in computational databases, enabling consistent ab initio characterization of their properties across monolayer, bilayer and bulk forms. We describe the structure and content of the database highlighting its support for community uploads, illustrate how it can be used to generate new scientific insight and introduce a hierarchical classification of the known set of 2D materials. Our work provides a foundation for the integration and cross-fertilization of experimental and theoretical knowledge, opening new avenues for data-driven, predictive synthesis of novel 2D materials.

Figures (6)

• Figure 1: Workflow used to identify experimentally reported 2D materials and link them to C2DB. Relevant publications are identified by searching the abstract for specific keywords that indicate that the paper reports on the synthesis or exfoliation of a material in atomically thin form. The materials reported in the papers are linked to structures in the C2DB monolayer database using manual inspection of the crystal structure. Finally, the information describing the reported material and the employed synthesis and characterization methods, is extracted and classified according to the 2D materials taxonomy.
• Figure 2: Papers published on experimentally realized 2D materials since 2010. More precisely, the graph shows the 200k publications selected by the search criteria in the green box in Fig. \ref{['fig:workflow']}, sorted according to publication year.
• Figure 3: The Experimental 2D Materials Database. The taxonomy (left) provides a controlled language for describing 2D materials. Colored boxes represent the taxonomy's top-level categories each containing sub-categories and predefined labels as detailed in the SI. Experimental materials can be linked to corresponding structures in computational databases of monolayers, bilayers, and bulk solids. An associated confidence level (number between 1 and 3) is used to indicate the reliability of the link. New records - defined by the material (chemical formula) and a related publication DOI -- can be registered by external users via a simple web form.
• Figure 4: Statistical Overview of Selected Data from X2DB. (a) Morphological parameters (lateral size and thickness) of experimentally realized 2D materials as a function of synthesis method. (b-e) Distributions of the most frequently reported characterization methods, synthesis methods, crystal systems (for both the 2D in-plane lattice and the 3D lattice), and substrates used for growth or transfer. Each plot highlights the top 10 most common reports, while all other, less frequent entries are grouped in a single combined bar to provide a comprehensive overview.
• Figure 5: Computational Properties of Experimentally Realized 2D Materials. All colored data refers to materials from X2DB that have been produced in few-layer form with thickness below 10 nm and have been linked to a monolayer in C2DB with high confidence level. (a) Interlayer binding energies calculated with the PBE-D3 method. The contribution of the dispersive D3-term to the binding energy is plotted as function of the total binding energy, $E_\mathrm{B}$. Grey symbols show all materials in the computational bilayer database BiDB. Materials in X2DB are highlighted depending on whether they were mechanically exfoliated (orange), exfoliated bu other techniques (green), or directly grown (blue). The type of interlayer bonding can be classified according to whether it is dominated by dispersive forces (vdW bonding), covalent or ionic bonding (non-vdW bonding), or a mixture of both (mixed bonding regime). (b) Distribution of the calculated electronic and magnetic properties of the monolayer form of the materials in X2DB. The outer ring shows the fraction of metallic vs. non-metallic monolayers. The inner ring shows the fraction of magnetic vs. non-magnetic materials further separated into metallic and non-metallic categories. (c) The band gap distribution for non-metallic materials, as calculated with the HSE06 xc-functional.