In recent years, “Materials Informatics,” which leverages data science for the exploration of novel materials, has gained significant attention. Among various approaches, “autonomous materials discovery,” which integrates robotics and materials simulations with machine learning, has emerged as a promising method for efficiently navigating vast material spaces. In this study, we employed a simulation-based autonomous materials discovery approach that combines first-principles calculations with Bayesian optimization to explore a broad space of magnetic alloys. As a result, we successfully discovered and synthesized novel alloys with high magnetization.

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.

Electron-phonon interaction is one of the most fundamental interactions. Anharmonic vibrational modes interact with the conductive electrons and provide fascinating phenomena such as unusual superconductivity or high thermoelectric properties. BaIr2Ge7, a cage-structured compound with encapsulated Ba atoms, shows superconductivity at Tc＝2.5 K. Although specific heat measurements suggest the presence of anharmonic phonon modes, the atomic displacement parameter (ADP) is unusually small. Thus, the existence of anharmonic phonon modes and their relationship with the electronic state has not been clarified. In this study, we performed micro-focused angle-resolved photoemission spectroscopy (ARPES) on BaIr2Ge7 to explore the existence of the anharmonic phonon mode through the temperature-dependent spectra. The presence of two domains was identified by scanning the electronic states of the cleavage surface. The anharmonic phonon modes, extracted from the temperature-dependent photoemission linewidth, provide insight into its relationship with electrical resistivity, specific heat, and ADP.

Electronic processes at interfaces embedded in organic electronic devices are essential for their functionalities. Surface science researches, whose one predominant concept is the usage of single crystal surfaces of the materials as substrates for “well-defined” interfaces, have disclosed crucial insights into such interfaces. However, studies targeting the electronic states of organic molecular single crystal surfaces and well-defined interfaces formed on these are quite limited so far mainly due to some technical hurdles for the application of photoelectron spectroscopy measurements on bulk molecular solid-state samples. This article is devoted to outlining experimental requirements and know-how for applying photoelectron spectroscopy measurements to molecular single crystal samples, taking our recent research using microscopic X-ray photoelectron spectroscopy as examples.

Achieving carbon neutrality by 2050 and transitioning to a sustainable society requires innovations in alternative energy technologies. Photocatalytic hydrogen production from H2O using solar energy offers a promising solution but faces significant challenges in bridging the “pressure gap” (reactions on earth occur in gas or solution phases rather than vacuum), “energy gap” (reactions on earth occur at ambient to high temperatures instead of cryogenic conditions), and “material gap” (most catalysts have ill-defined, heterogeneous surfaces rather than idealized single-crystal substrate surfaces). Addressing these gaps necessitates advanced operando experimental approach under realistic conditions. This study highlights our recent advancements in developing operando measurement and analysis techniques that can establish correlations between macroscopic functionalities with microscopic structural and dynamic properties. These approaches provide new insights into the reaction fields of photocatalytic water-splitting systems, focusing on interfacial molecular science and metal-semiconductor complex interface science.