Although the C–H bond of methane is very strong, it can be easily dissociated on the (110) surface of β-PtO2. This is because a very stable Pt–C bond is formed between the coordinatively unsaturated Pt atom and CH3 on the surface. Owing to the stable nature of the Pt–C bond, CH3 is strongly bound to the surface. When it comes to methanol synthesis from methane, the Pt–C bond has to be cleaved to form a C–O bond during the reaction process. However, this is unlikely to occur on the β-PtO2 surface: The activation energy of the process is calculated to be so large as 47.9 kcal/mol. If the surface can be modified in such a way that the ability for the C–H bond activation is maintained but the Pt–C bond is weakened, a catalyst combining the functions of C–H bond cleavage and C–O bond formation can be created. For this purpose, analyzing the orbital interactions on the surface is found to be very useful, resulting in a prediction that the Pt–C bond can be weakened by replacing the O atom trans to the C atom with a N atom. This would be a sort of process to make β-PtO2 a mixed anion compound. Density functional theory simulations of catalytic reactions on the β-PtO2 surface show that the activation energy of the rate-limiting step of methanol synthesis can be reduced to 27.7 kcal/mol by doping the surface with N.

Binary alloy catalysts have the potential to exhibit higher activity than monometallic catalysts in nitrogen activation reactions. However, owing to the multiple possible combinations of metal elements constituting binary alloys, an exhaustive search for the optimal combination is difficult. In this study, we searched for the optimal binary alloy catalyst for nitrogen activation reactions using a combination of Bayesian optimization and density functional theory calculations. The optimal alloy catalyst proposed by Bayesian optimization had a surface energy of ∼0.2 eV/Å 2 and resulted in a low reaction heat for the dissociation of the N�N bond. We demonstrated that the search for such binary alloy catalysts using Bayesian optimization is more efficient than random search.

In this paper, conductivity and magnetism in alternant hydrocarbons are discussed based on the topology of π-conjugated networks. In a molecular system with two spin centers, when the spins are separated by an odd-length walk, they interact antiferromagnetically with each other, but when they are separated by an even-length walk, they interact ferromagnetically. The conduction through the pathway connecting the two spins is expected to be effective for the former case, while ineffective for the latter case, but both show almost the same conductance in a magnetic system. This is because in the latter case, a feature in the electron transmission spectrum that causes destructive quantum interference is localized away from the Fermi level of the electrode and in a very narrow energy range, not affecting the zero-bias conductance. This tendency is further accentuated by generating weak coupling between the electrode surfaces and the spins to preserve the radical character of the molecule sandwiched between two electrodes. Although there is a challenge on how to stabilize radical molecules in a confined environment between electrodes, what is presented in this paper would give a clue on how to construct a system where magnetism and conductivity coexist.