@phdthesis{oai:kitami-it.repo.nii.ac.jp:02000197, author = {JEONG CHANYANG and チョン チャンヤン}, month = {Mar}, note = {In this study, WO3 NPs dispersion ink with excellent adhesion was developed for the fabrication of electrochromic devices capable of wet coating, device fabrication tests were performed using the developed materials, and performance was predicted and demonstrated using machine learning. To improve the adhesion between the WO3 nanoparticles and the substrate of the ink, polyvinyl alcohol (PVA) was added as an additive. PVA was adjusted to 0-10 wt.%, and electrochemical properties and EC properties were studied. As a result, the WO3 thin film prepared with 1 wt.% PVA addition showed excellent adhesion between WO3 nanoparticles and substrate. In addition, it was found that the composition of the WO3 thin film exhibiting excellent electrochemical properties with the largest coloration efficiency of 35 cm2/C and electrochromic properties with a change in visible light (λ = 633 nm) transmittance of 90%⇔13%. To fabricate the next-generation EC device, we investigated the fabrication of flexible ECD using a PET substrate. For the preparation of EC materials, coated WO3 and PB films were prepared using the WO3 synthesized in Chapter 3 and the PB ink originally developed by Adhesion and Interface Research Group at National Institute of Advanced Industrial Science and Technology (AIST), and these were assembled to prepare a flexible EC device. The prepared flexible PET EC device showed a dramatic color change from transparent to dark blue and showed higher coloring efficiency (123.32 cm2 / C) than the conventional glass EC device (86.44 cm2 / C). Furthermore, it showed electrochemical stability without deterioration up to 100 cycles, and mechanically excellent durability against repeated bending and twisting experiments. Finally, machine learning was applied to obtain the optimal WO3 NPs dispersed ink preparation condition for the application of EC materials. The predicted value obtained through simulation showed an accuracy of more than 90% with the experimental value. In addition, the highest coloring efficiency value of 38.2 cm2/C obtained through this study was improved by about 10% compared to the coloring efficiency value (35.0 cm2/C) of Chapter 3. Therefore, we believe that it is possible to develop an optimized process for the preparation of EC materials using machine learning. In the future, we will focus on the development of functional nano-dispersion inks optimized to prepare functional thin films using various parameters (materials, manufacturing conditions, atmosphere, etc.) through simulation prediction using more advanced algorithms.}, school = {北見工業大学}, title = {Fabrication and Evaluation of Functional Thin Films and Electrochemical Devices and Application of Machine Learning}, year = {2022} }