Organic devices have been successfully applied to OLED TVs, while development for new applications as flexible devices is still progressing. Understanding the electronic transport properties of organic devices is fundamentally important for device-operation analysis and device design. Impedance spectroscopy is a non-destructive method and hence the transport properties of organic devices under operation can be studied. It is shown here that impedance spectroscopy can probe electron and hole mobilities, tail state distributions from the band edges, and bimolecular recombination constants of double-injection devices such as polymer light-emitting diodes. It is also shown that the dielectric properties of the gate insulator, the field effect mobility, and the interfacial localized states can be determined in organic transistors.

This paper demonstrates machine learning potential, providing an accurate description of the relationship between the energy and the crystal structure and its potential applications such as large-scale molecular dynamics simulations and global structure optimizations. This paper also describes machine-learning-based methods to perform crystal structure optimization from a vast number of candidate structures. Finally, the paper introduces a novel compact data structure of the zero-suppressed binary decision diagram (ZDD) to enumerate structures much more efficiently.

NMR crystallography approach using solid-state NMR and 3D electron diffraction (3D ED, microED) is demonstrated to solve structures of nano- to microcrystals. While 3D ED structure often involves uncertainty of hydrogen positions and ambiguity of carbon/nitrogen/oxygen assignments, solid-state NMR provides complementary information. Chemical-shift and dipolar-based NMR crystallography approaches are used to refine the 3D ED structures.

Nano-carbon materials such as carbon nanotubes (CNTs) and graphene are promising candidates for next-generation optoelectronic devices on silicon chips, which is difficult to achieve with compound semiconductors, owing to their unique electronic, optical and thermal properties. In this paper, we introduce graphene black-body radiation emitting devices, EL emitting devices using semiconducting CNTs film, CNT based single-photon sources at room temperature and telecommunication wavelength, and CNT photoluminescence devices combined with silicon photonics. In addition, we also discuss the prospects of nanocarbon optoelectronic devices for integrated optical devices and quantum information devices on silicon chips.

The bulk photovoltaic effect (BPVE) converts light energy to electric energy without need of built-in potential. Hence, its conversion efficiency will not be restricted by the Shockley-Queisser limit. However, the BPVE efficiency of existing bulk materials are quite small. Here, we introduced a nanotube made of the representative two-dimensional material WS₂ in the research field of BPVE. We not only observed BPVE for the first time in nano-materials, but also revealed a high conversion efficiency in WS₂ nanotube. Furthermore, our systematic study unveiled the importance of the polar structure on the enhancement of BPVE. Our results are anticipated to put forward the BPVE study based on polar nano-materials.

We developed a method called PDC (Phase Diagram Construction) that constructs a phase diagram using machine learning. In this method, based on uncertainty sampling, the most uncertain point in the phase diagram is selected as a candidate for the next experiments/simulations. Then, using experiments/simulations, the phase at the selected point is identified. Uncertainty sampling is performed again on the increased experimental data to select next candidates. By repeating this process, it is possible to draw a phase diagram quickly. By using PDC, an uninvestigated phase diagram for the deposition of Zn-Sn-P films by molecular beam epitaxy is constructed. In addition, we have released an application software for the phase diagram construction; the software can be executed on a Windows computer without any special settings.

Semiconductor technology is key to solve various social issues such as energy shortage, electricity shortage, traffic jam, medical shortage, environmental destruction. It is necessary to understand that the role of semiconductor is changing drastically as the world's power shortage is expected.