Two-dimensional ferroelectrics from high throughput computational screening

We report a high throughput computational search for two-dimensional ferroelectric materials.The starting point is 252 pyroelectric materials from the computational 2D materials database(C2DB)and from these we identify 63 ferroelectrics.In particular we find 49 materials with in-plane polarization,8 materials with out-of-plane polarization and 6 materials with coupled in-plane and out-of-plane polarization.Most of the known 2D ferroelectrics are recovered by the screening and the far majority of the predicted ferroelectrics are known as bulk van der Waals bonded compounds,which makes them accessible by direct exfoliation.For roughly 25%of the materials we find a metastable state in the non-polar structure,which may imply a first order transition to the polar phase.Finally,we list the magnetic pyroelectrics extracted from the C2DB and focus on the case of VAgP2Se6,which exhibits a three-state switchable polarization vector that is strongly coupled to the magnetic excitation spectrum.

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.

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).

Structural and chemical mechanisms governing stability of inorganic Janus nanotubes

One-dimensional inorganic nanotubes hold promise for technological applications due to their distinct physical/chemical properties,but so far advancements have been hampered by difficulties in producing single-wall nanotubes with a well-defined radius.In this work we investigate,based on Density Functional Theory(DFT),the formation mechanism of 135 different inorganic nanotubes formed by the intrinsic self-rolling driving force found in asymmetric 2D Janus sheets.We show that for isovalent Janus sheets,the lattice mismatch between inner and outer atomic layers is the driving force behind the nanotube formation,while in the non-isovalent case it is governed by the difference in chemical bond strength of the inner and outer layer leading to steric effects.From our pool of candidate structures we have identified more than 100 tubes with a preferred radius below 35Å,which we hypothesize can display distinctive properties compared to their parent 2D monolayers.Simple descriptors have been identified to accelerate the discovery of small-radius tubes and a Bayesian regression approach has been implemented to assess the uncertainty in our predictions on the radius.

Beyond the RPA and GW methods with adiabatic xc-kernels for accurate ground state and quasiparticle energies

We review the theory and application of adiabatic exchange–correlation(xc)-kernels for ab initio calculations of ground state energies and quasiparticle excitations within the frameworks of the adiabatic connection fluctuation dissipation theorem and Hedin’s equations,respectively.Various different xc-kernels,which are all rooted in the homogeneous electron gas,are introduced but hereafter we focus on the specific class of renormalized adiabatic kernels,in particular the rALDA and rAPBE.The kernels drastically improve the description of short-range correlations as compared to the random phase approximation(RPA),resulting in significantly better correlation energies.This effect greatly reduces the reliance on error cancellations,which is essential in RPA,and systematically improves covalent bond energies while preserving the good performance of the RPA for dispersive interactions.For quasiparticle energies,the xc-kernels account for vertex corrections that are missing in the GW self-energy.In this context,we show that the short-range correlations mainly correct the absolute band positions while the band gap is less affected in agreement with the known good performance of GW for the latter.The renormalized xc-kernels offer a rigorous extension of the RPA and GW methods with clear improvements in terms of accuracy at little extra computational cost.