NanoTerasu is about to start operation in April 2024. It is a next-generation synchrotron radiation facility under construction at Tohoku University Aobayama New Campus (Sendai City). Speaking of synchrotron radiation facilities, SPring-8 in Hyogo Prefecture, which began operation in 1997, is well known to the general public. After about a quarter of a century, new facilities developed and operated by the government have appeared. The accelerator technology that produces light is based on the unique technology of synchrotron radiation science in Japan, which has been honed at Spring Eight. However, SPring-8 and NanoTerasu have completely different uses. This is because, while SPring-8 is strong in the use of hard X-rays, NanoTerasu has strengths in the use of soft X-rays. Leveraging this strength, we are trying to contribute to solving the social issues we face, such as the creation of a carbon-neutral society. Our challenge with NanoTerasu will be described in detail.

In this article, non-volatile memory transistors utilizing Hf-based ferroelectric thin films are described. Ferroelectric-gate transistors, MFSFET (Metal-Oxide-Si Field-Effect Transistor), are explained utilizing ferroelectric HfO₂ and HfN thin films which are able to be formed directly on the Si substrate as a gate insulator. Furthermore, FeNOS-type non-volatile memory transistors that is the MONOS (Metal-Oxide-Nitride-Oxide-Si)-type flash memory with ferroelectric HfO₂ thin films which realizes the precise threshold voltage control utilizing polarization and charge trap characteristics are explained.

In recent years, the rapid advancements in machine learning have significantly influenced its broader application within society. Concurrently, the prospects of utilizing the computational strengths of quantum computers for machine learning have been a focal point since the 2010s. As quantum hardware continues to evolve, there's a notable shift towards crafting algorithms specifically for the current and near-future quantum systems. This article offers a concise overview of machine learning as facilitated by quantum computing.

Using molecular beam epitaxial crystal growth, we have synthesized large-capacity, high-quality compound semiconductor GaAs-based nanowires on a 2-inch silicon substrate. In addition, we explored novel nanowires materials by the growth of GaInNAsBi compounds, crystal polymorphism including stable zincblende and metastable hexagonal structure, and material conversion by oxidation. These materials show various functions as a light source in the near-infrared band or white light, and show nonlinear optical effects.

Organic semiconductors (OSCs) based on π-electron systems are expected to be applied to high-end devices such as radio frequency identification (RF-ID) tags and multi-purpose sensors for the Internet of Things (IoT) because of their excellent features such as solution processability, light weight and mechanical flexibility. Since it was reported that carriers in OSCs with high mobility exceeding 10 cm²/Vs are band-like charge transport behavior, the authors have been developing materials research on OSCs using their molecular technology based on the band theory. In this paper, I describe the state-of-the-art molecular technology for the fabrication of high-mobility organic semiconductors by means of mixed-orbital charge transport strategy.

In this study, we analyzed the behavior of hydrogen diffusion from the CH₄N-implanted region. As a result, we found that hydrogen forms two peaks in the CH₄N-implanted region. We believe that the desorption of hydrogen from the carbon aggregate and EOR defect regions enhances the hydrogen termination effect at the SiO₂/Si interface. We also believe that CH₄N-implanted epitaxial silicon wafers have important characteristics for improving the performance of three-dimensional stacked CMOS image sensors.

Single nitrogen-vacancy (NV) centers in diamond are promising sensors for nano-scale quantum measurements. The electrons of NV centers lend themselves to optical spin state initialization, fluorescent spin state readout, and may be manipulated coherently even in ambient conditions. Here, methods to use a low-end FPGA board for the quantum sensing are introduced .