Recently, neutron detections have been applied in various fields, and the development of each neutron detector suitable for widespread neutron detections is expected. BGaN has been proposed as a novel neutron semiconductor detection material. BGaN is a ternary nitride alloy including B atoms, and is a material capable of capturing neutrons and detecting signals in the sensitive layer.In this report, the BGaN epitaxial growth using a new B metal-organic source, TMB, which suppresses gas-phase reactions, is presented. By improving the growth conditions, thick growth was achieved and vertical-type thick BGaN pin-diodes were fabricated. The neutron energy spectrum was measured using the fabricated BGaN diodes. These results indicate that BGaN diodes can be used as effective neutron detectors.

The development of light sources that enable arbitrary color rendering is attracting attention not only for next-generation lighting but also for optical wireless communication (Li-Fi) applications. In order to achieve this, it is important to explore the science and develop technologies for controlling the emission spectrum and modulating each emission wavelength on and off at high speed. The author's laboratory is developing research aimed at synthesis of emission wavelengths using nitride semiconductor three-dimensional structures, as well as highly efficient emission through polarization control and plasmonic effects. This paper presents the results of research on luminescence synthesis and describes current issues and future prospects.

Development of organic semiconductors (OSCs) showing very high layered crystallinity has recently prompted considerable evolution of printed organic field-effect transistors. Herein, we first illustrate several intriguing aspects of highly layered-crystalline OSCs and also discuss molecular origin of the high layered crystallinity. Then we show that it is possible to manufacture highly uniform and ultrathin crystalline semiconductor layers by taking advantage of the self-organized growth of OSC layers through solution processes. Particularly, a unique method allows to produce extremely clean semiconductor interfaces that provide practical device performances showing very sharp and stable switching operation at low voltages. We report the present status of basic studies on the printed electronics technology.

Cryogenic-CMOS (Cryo-CMOS) technology, which is operated at temperatures of several Kelvin or less, has attracted a lot of attention for realizing the large-scale quantum computer. To develop Cryo-CMOS circuits, establishing a circuit compact model that can be applied to cryogenic operation is required. However, cryogenic MOSFET performance is quite different from that at the room temperature and device physics are not fully understood. This article provides an overview of Cryo-CMOS technology, with a particular focus on device performance, and presents future outlook.

Direct writing technique of metal/metal oxide microstructures using femtosecond laser pulse-induced photothermochemical reduction was demonstrated. 2D/3D microstructures were fabricated using linear optical absorption-induced thermochemical reduction of CuO, NiO, and their mixed nanoparticles. Cu-rich and Cu₂O-rich patterns were selectively formed by controlling the degree of reduction of CuO nanoparticles by changing the writing speed. Thermosensors such as a thermistor type Cu-rich/Cu₂O-rich sensor and a thermoelectric type Cu₂O/NiO (p-type) and Cu-Ni-rich (n-type) sensor were demonstrated. In addition, Cu-based 3D microstructures were fabricated using nonlinear optical absorption-induced thermochemical reduction of Cu₂O nanospheres. The thermochemical reduction was induced around the focal spot inside the nanosphere ink. Such direct writing technique is useful for fabrication of microdevices consisting of various functional materials.

In recent years, research on the application of artificial neural networks to the modeling and simulation of physical phenomena has been attracting much attention. In addition to modeling phenomena without known governing equations, such research is expected to accelerate and improve physical simulations. In this paper, we first explain the Hamiltonian neural network which is a representative example of such research. Then two improved models, the neural symplectic form and DGNet, are explained.

X-ray diffraction measurement techniques are widely used to characterize the crystallinity of various functional thin film materials. Automated X-ray diffraction apparatus compatible with many measurement techniques are commercially available. However, situations are sometimes found where inappropriate techniques were applied leading to wrong conclusions. In this article, basics of the X-ray diffraction measurement techniques applied for thin film analysis are shortly explained.