Photocatalysis enables redox reactions to proceed non-thermally under ambient conditions, offering a low-energy alternative to conventional thermocatalytic processes. Traditionally, it has been assumed that oxidation occurs exclusively at the semiconductor surface via photogenerated holes, while reduction takes place on metal cocatalysts that capture photogenerated electrons. However, the absence of microscopic insights into the detailed reaction mechanism has hindered rational design of catalysts. To address this, we employed kinetic analysis and operando infrared spectroscopy to directly monitor reactive species under reaction conditions. Our investigations reveal that metal cocatalysts also play a crucial role in oxidation by interacting with photogenerated holes, contrary to traditional understanding. Moreover, the reactive electrons are not located within the metal cocatalysts but are shallowly trapped in in-gap states of the semiconductor surface at their periphery. These findings redefine the concept of catalytic active sites and provide a basis for designing more efficient photocatalytic systems.

Electron beam powder bed fusion (EB-PBF), one of additive manufacturing, utilizes an electron beam as a heat source and has advantages such as a scanning strategy with high-speed operation, high thermal conversion efficiency, and residual stress relief by preheating process. On the other hand, it has inferior surface roughness, a powder scattering phenomenon known as smoke, and the need to remove pre-sintered powder. In addition to these general features of EB-PBF, other features of EB-PBF have been developed in recent years : high-quality electron beam, and defect detection through backscattered electron (BSE) image monitoring. EB-PBF is suitable for Ti-6Al-4V alloys, pure copper, Ni718 alloys and pure tungsten, and meets AMS standard certification, crack-free and microstructure control.

Hydrogen readily permeates various materials and modulates their physical properties. Identification of the hydrogen lattice location in crystals is key to understanding and controlling the hydrogen-induced phenomena. Combining nuclear reaction analysis (NRA) with the ion channeling technique, we experimentally determined the locations of H and D in epitaxial nanofilms of titanium hydrides. We found that 11 at.% of H are located at the octahedral site with the remaining H atoms in the tetrahedral site. Density functional theory calculations revealed that the partial octahedral site occupation is attributed to the Jahn-Teller effect induced by hydrogen. In contrast, D was found to solely occupy the tetrahedral site owing to the mass effect on the zero-point vibrational energy. This study demonstrates the potential to fabricate hydrides with arbitrary site occupancy by tuning the isotope ratio, which potentially allows for control over their electronic properties and leads to the discovery of novel phenomena.

The metal–insulator transition (MIT) in VO₂ is strongly governed by nanoscale morphology and structural defects. To elucidate the microscopic origin of this transition, we investigated the relationship between surface structure and MIT dynamics in VO₂ thin films epitaxially grown on TiO₂(110) via pulsed laser deposition. Operando X-ray diffraction confirmed a structural transformation from the monoclinic (insulating) to rutile (metallic) phase. Infrared scattering-type scanning near-field optical microscopy (s-SNOM) enabled direct visualization of individual anisotropic nanodomains with nanoscale resolution. The contrast in near-field amplitude allowed us to spatially resolve metallic and insulating phases across the surface. We observed that metallic domains nucleate and expand heterogeneously, influenced by local grain geometry and anisotropic strain along the [001] direction. These findings provide insight into the interplay between structural features and phase transition pathways in strongly correlated oxide systems.

Data science has emerged as the fourth scientific method, following experiment, theory, and computation. Since the launch of the Material Genome Initiative in 2011, data-driven approaches such as materials informatics and process informatics have been actively applied in materials. To integrate data science into traditional research, it is essential to understand research activities as a data cycle consisting of three phases : data generation, accumulation, and utilization. This cyclic process enhances the efficiency and scope of scientific research. To illustrate the impact of data science in materials research, this paper introduces Bayesian optimization for autonomous experimental system, machine learning potentials, personal databases using JSON format, and high-throughput automatic spectral analysis. These approaches contribute to the advancement of materials science through data-driven methodologies, accelerating the data cycle.