We have produced the world's first 700 nm, ultra-fine polyester nanofiber via continuous research and development using stateof-the-art nanotechnology. The proposed sea/island composite-spinning technology has improved the quality of conventional mass-produced nanofibers. Sea/island composite spinning produces high-strength polyester nanofibers using conjugated (two components) spinning theory. The separation of sea-island components is based on the different degrees of polymer dissolution in alkali solution; specifically, resolution sea polymer (modified polyester) has dissolution rates that are 1000 times faster than that of island polymer (polyester). The resulting nanofibers have a large surface area, high absorption, and good distribution and filtration effects, which are suitable for a variety of applications, including functional sportswear, inner wear, skin-care products, filters, precision grinding cloths, and so on. Keywords: conjugated spinning theory; sea/island cross-section fibers; alkali solution hydrolysis; nano-size effects INTRODUCTIONWithin the synthetic fiber industry, a number of value-added products have been developed based on differentiation technology, including textiles and high tenacity, sense of touch and color tone materials. Nonetheless, owing to the strong cost competitiveness and improvement in the technologies used in developing countries such as those employed in South East Asia, deindustrialization (or the hollowing out of industries) has occurred in Japan, especially within the fiber industry. Therefore, the Japanese fiber industry must produce innovative fiber materials and develop functional applications based on precision-conjugated melt-spinning technology. Essentially, the fiber industry must develop finer and stronger fiber materials. In this regard, the expectations of new functionality and the opening of new markets as a result of novel nanotechnologies are high.As fiber manufacturing technology has progressed from microorder to nano-order and new functions in various fields have been rapidly developed, we have produced commercial polyester nanofibers with unprecedented uniform diameters and high tenacity. When the functionality of nano-size materials is used in actual products, new applications can be identified, and the functions of existing products can be dramatically improved. Thus, we expect new markets to open up for nanofiber materials.

Photonic crystal (PC) nanocavities with ultra-high quality (Q) factors and small modal volumes enable advanced photon manipulations, such as photon trapping. In order to improve the Q factors of such nanocavities, we have recently proposed a cavity design method based on machine learning. Here, we experimentally compare nanocavities designed by using a deep neural network with those designed by the manual approach that enabled a record value. Thirty air-bridge-type two-dimensional PC nanocavities are fabricated on silicon-on-insulator substrates, and their photon lifetimes are measured. The realized median Q factor increases by about one million by adopting the machine-learning-based design approach.

No abstract