Optically detected magnetic resonance (ODMR) microscopy is a new type of microscopy using nitrogen-vacancy (NV) centers in diamonds. The ODMR microscope enables us to detect the magnetic-field, the electric-field, and the temperature with high sensitivity and high spatial resolution under ambient conditions. Phenomena which cannot be accessed by conventional methods, such as the observation of nuclear magnetic resonance at nano-scale detection volumes, have been demonstrated. In this article, the basics of the NV center in diamonds and the principles of the ODMR microscope will be explained, and then, applications of the ODMR microscope in a wide range of fields will be shown.

Artificial molecular motors based on an overcrowded alkene structure are highly attractive from the viewpoint of chirality switching during rotational steps. However, the integration of these molecular switches into solid-state devices is still challenging. Herein, we present an example of a solid-state spin-filtering device that can switch the spin polarization direction by light irradiation or thermal treatment. This device utilizes the chirality inversion of molecular motors as a light-driven reconfigurable spin filter owing to the chiral-induced spin selectivity effect. Through this device, we found that flexibility at the molecular scale is essential for the electrodes in solid-state devices using molecular machines. The present results are beneficial to the development of solid-state functionalities emerging from nanosized motions of molecular switches.

We are developing Rib structures to enable the manufacturing of thin-type Si solar cells with a wafer thickness of 100μm or less. In Rib solar cells, a part of the Si wafer is left as a rib to maintain mechanical strength, and the other parts are made thinner to enhance the open-circuit voltage. In this paper, we first introduce the fabrication process of the Rib structure and the passivation technology for fabricating heterojunction solar cells. In the Rib solar cell, a thick region and a thin region of Si are distributed in the plane. Then, the effective carrier lifetime, photoluminescence and electroluminescence were measured to investigate the in-plane distribution of electrical properties. Finally, the future vision for this work is reviewed.

This paper introduces the recent progress in our understanding of the short-circuiting mechanism of inorganic-solid-state electrolytes during charging/discharging of an Li metal anode in a solid-state battery.　Solid-state electrolytes are recognized as a key material, which could pave the path to realizing high-energy-density-secondary batteries.　Cubic-Li₇La₃Zr₂O₁₂ (LLZ) is a strong candidate as a solid-state electrolyte to achieve a highly reversible Li metal anode.　However, a short-circuiting event is inevitable with LLZ.　The mechanism for a softer Li to penetrate a more rigid LLZ remains unelucidated, but it has been understood that tiny voids, which are formed near the Li/LLZ interface during Li stripping, cause an increase in local current density.　This increased local current density eventually exceeds the threshold for short-circuiting to occur.

Protonic solid oxide fuel cells (H⁺-SOFCs) have limited application below 500 ℃ owing to their high ohmic and polarisation resistances. Hence, efforts are ongoing to develop advanced fuel cells based on semiconductor device science. Here, we demonstrate that hydrogen-permeable metal-supported fuel cells (HMFCs) exhibit improved energy conversion efficiency at relatively low temperatures due to the retardation of secondary oxide ion conduction at the oxide/metal heterointerface. The electrolyte membrane in HMFCs is forced to gain extra protons to compensate for the charge from the oxide ions accumulating via blocking, resulting in extremely high proton conductivity. Simultaneously, the heavily hydrated membrane pumps out the cathode-side protons during cell operation. Hence, HMFCs can operate at high efficiency even at relatively low temperatures.

The Matthias Law played an important role in the early days of the search for superconducting materials. This is an empirical rule that the critical temperature T_c of transition metals and their alloys is maximized for a certain material parameter combination, which led to the discovery of many superconducting materials. Recently, a new T_c prediction method may have been generated. Using a superconducting database and machine learning, the computer learns combinations of elements of known substances and their experimental T_c values to create a prediction model. The T_c for any substance can be predicted using this model. This is what is called the 21st century version of the Matthias Law. The present report relates to this new superconducting material search method.

In order to realize a sustainable society, it is necessary to prevent undesirable conditions and improve efficiency by eliminating waste everywhere. For that purpose, it is required to monitor various objects on the Earth and to convey the necessary information to society, with the necessary timing, at low cost, by AI. To achieve this, it is necessary to reduce the weight of devices, including batteries, while maintaining long-life operation. To reduce wireless communication power, it is necessary to highly compress data at the edge device by employing a high-performance recognizer. This article describes the significance and direction of low-power AI technology for the future IoT society, taking high-performance low-power SoC, AI tools, and LPWA technologies as examples.