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h-BCN is an intriguing material system where the bandgap varies considerably depending on the atomic configuration, even at a fixed composition. Exploring stable atomic configurations in this system is crucial for discussing the energetic formability and controllability of desirable configurations. In this study, this challenge is tackled by combining first-principles calculations with Bayesian optimization. An encoding method that represents the configurations as vectors, while incorporating information about the local atomic environments, is proposed for the search. Although the optimization did not function with the conventional one-hot encoding that had been effective in other material systems, the proposed encoding proved efficient in the search. As a result, two interesting semiconductor configurations were discovered. These configurations exhibit qualitatively similar patterns to conventional models, and one of the two is more stable than the conventional ones with the same periodicity. Furthermore, the optimization behavior is discussed through principal component analysis, confirming that the ordered BN network and the C configuration features are well embedded in the search space. The proposed encoding method, which is easy to implement, is expected to expand the applicability of atomic configuration search using Bayesian optimization to a broader range of material systems., Comment: 7 pages, 5 figures

Fundamental properties of spontaneous and piezo polarization are reformulated and critically reviewed. It was demonstrated that Landau definition of polarization as a dipole density could be used to the infinite systems. The difference between the bulk polarization and surface polarity are distinguished thus creating clear identification of both components. The local model of spontaneous polarization was created and used to calculate spontaneous polarization as the electric dipole density. It was shown that the proposed local model correctly predicts c-axis spontaneous polarization values of the nitride wurtzite semiconductors. It was also shown that the proposed model predicts zero polarization in the plane perpendicular to the c-axis, in accordance with symmetry requirements. In addition, the model results are in accordance with polarization equal to zero for zinc blende lattice. These data confirm the basic correctness of the proposed model. The spontaneous polarization values obtained for all wurtzite III nitrides (BN, AlN, GaN and InN) are in basic agreement with the earlier calculations using Berry phase and slab models of Bernardini et al. {Bernardini et al. Phys Rev B 56 (2001) R10024 & 63 (2001) 193201} but not with Dreyer et al. {Dreyer et al. Phys. Rev X 6 (2016) 021038}. Wurtzite nitride superlattices ab initio calculations were performed to derive polarization-induced fields in the coherently strained lattices showing good agreement with the polarization values. The strained superlattice data were used to determine the piezoelectric parameters of wurtzite nitrides obtaining the values that were in basic agreement with the earlier data. Zinc blende superlattices were also modeled using ab initio calculations showing results that are in agreement with the absence of polarization of all nitrides in zinc blende symmetry., Comment: 36 pages, 13 figures, 53 references

On semiconductor growth surfaces, surface reconstructions appear. Estimation of the reconstructed structures is essential for understanding and controlling growth phenomena. In this study, the stability of a mixture of two different surface reconstructions is investigated. Since the number of candidate structures is enormous, the structures sampled by Bayesian optimization are analyzed. As a result, the local electron counting (EC) rule alone was found to be insufficient to explain such stability. Then, augmenting the EC rule, a data-driven Ising model is proposed. The model allows the evaluation of the whole enormous number of candidate structures. The approach is expected to be useful for theoretical studies of such mixtures on various semiconductor surfaces., Comment: 6 pages, 5 figures