There are now many examples of naturally occurring materials that can exist in a two-dimensional form, that is, as atom-thick single layer materials. Graphene, and MoS2 are the classic examples, and more recently phosphorene [1], metal oxides, transition metal dichalcogenides and the more complex MXenes [2]. Many of these 2D layers have useful properties in their own regard, such as the recently discovered quantum emission from hBN [3] and are being combined to create hybrid materials and devices such as quantum LEDs [4]. In Nature in 2013, Geim and Grigorieva foreshadowed a rapid expansion in these van der Waals heterostructures: “with so many 2D crystals, sequences and parameters to consider, the choice of possible van der Waals structures is limited only by our imagination”, but caution that “even with the 2D components that have been shown to be stable, it will take time and effort to explore the huge parameter space”.
Density functional theory based calculations are important for understanding the properties of 2D materials in detail, for example the atomic origin of quantum emission in hBN [5,6]. They are too time intensive for undertaking rapid materials screening, however. We are interested in using these quantum chemical approaches as the starting point for materials discovery where machine learning and evolutionary approaches are used to rapidly explore the very large number of possible combinations of 2D building blocks. We are targeting materials with tailored light emission or adsorption properties for quantum LED and solar cell applications. This work is supported by resources provided by the National Computational Infrastructure (NCI), and Pawsey Supercomputing Centre with funding from the Australian Government and the Government of Western Australia. Financial support is provided by the Australian Research Council through grants DP150103317 and DP160101301

[1] M Bat-Erdene, M J Ford, J G Shapter et al., Small Methods 2017, 1 (12), 1700260
[2] B Anasori, M R Lukatskaya, Y Gogotsi, Nature Reviews Materials 2017, 2, 16098.
[3] T T Tran, K Bray, M J Ford, M Toth, I Aharonovich, Nature Nanotech, 2016 11 37.
[4] C Palacois-Berraquero et al, Nature Comms 2016 7 12978.
[5] A Sajid, Jeffrey R Reimers, Michael J Ford, Phys Rev B 2018 DOI: 10.1103/PhysRevB.97.064101
[6] J Reimers, S Ali, M Ford, J Chem Theory and Comp 2018 DOI: 10.1021/acs.jctc.7b01072