Quantum point defects in 2D materials-the QPOD database

Atomically thin two-dimensional(2D)materials are ideal host systems for quantum defects as they offer easier characterisation,manipulation and read-out of defect states as compared to bulk defects.Here we introduce the Quantum Point Defect(QPOD)database with more than 1900 defect systems comprising various charge states of 503 intrinsic point defects(vacancies and antisites)in 82 different 2D semiconductors and insulators.The Atomic Simulation Recipes(ASR)workflow framework was used to perform density functional theory(DFT)calculations of defect formation energies,charge transition levels,Fermi level positions,equilibrium defect and carrier concentrations,transition dipole moments,hyperfine coupling,and zero-field splitting.Excited states and photoluminescence spectra were calculated for selected high-spin defects.In this paper we describe the calculations and workflow behind the QPOD database,present an overview of its content,and discuss some general trends and correlations in the data.We analyse the degree of defect tolerance as well as intrinsic dopability of the host materials and identify promising defects for quantum technological applications.The database is freely available and can be browsed via a web-app interlinked with the Computational 2D Materials Database(C2DB).

Exploring and machine learning structural instabilities in 2D materials

We address the problem of predicting the zero-temperature dynamical stability (DS) of a periodic crystal without computing its fullphonon band structure. Here we report the evidence that DS can be inferred with good reliability from the phonon frequencies atthe center and boundary of the Brillouin zone (BZ). This analysis represents a validation of the DS test employed by theComputational 2D Materials Database (C2DB). For 137 dynamically unstable 2D crystals, we displace the atoms along an unstablemode and relax the structure. This procedure yields a dynamically stable crystal in 49 cases. The elementary properties of these newstructures are characterized using the C2DB workflow, and it is found that their properties can differ significantly from those of theoriginal unstable crystals, e.g., band gaps are opened by 0.3 eV on average. All the crystal structures and properties are available inthe C2DB. Finally, we train a classification model on the DS data for 3295 2D materials in the C2DB using a representation encodingthe electronic structure of the crystal. We obtain an excellent receiver operating characteristic (ROC) curve with an area under thecurve (AUC) of 0.90, showing that the classification model can drastically reduce computational efforts in high-throughput studies.