Research field (1):
Material fabrication and microstructure control
Research keywords (3):
Corrosion
, Stainless steel
, Localized corrosion
Research theme for competitive and other funds (4):
2024 - 2027 機械学習を用いたすき間内電位分布の可視化と新規腐食評価法の確立
2021 - 2024 環境中の金属イオンがもたらすステンレス鋼の耐食性低下機構の解明
2019 - 2021 Development of New Corrosion Inhibition Technology for Localized Corrosion of Stainless Steel Using Chelating Incorporation Method
2015 - 2018 Improvement of Corrosion Resistance of Steels by controlling catalytic activity
Papers (10):
Igarashi Takahiro, Sugawara Yu*, Otani Kyohei, Aoyama Takahito. Evaluation of corrosion on steel surface using image processing. Tetsu To Hagane. 2024. 18
Takahito Aoyama, Tomonori Sato, Fumiyoshi Ueno, Chiaki Kato, Naruto Sano, Naoki Yamashita, Takahiro Igarashi. Effect of Dissolved 90Sr and 137Cs in HCl Solutions on the Corrosion Potential of Type 316L Stainless Steel. Zairyo-to-Kankyo. 2023. 72. 11. 284-288
Takahito Aoyama, Chiaki Kato. Introduction of Cu2+ to the inside of the crevice by chelation and its effect on crevice corrosion of Type 316L stainless steel. Corrosion Science. 2022. 210. 2. 110850-110850
Yamashita Naoki, Aoyama Takahito, Kato Chiaki, Sano Naruto, Tagami Susumu. Development of an electrochemical measurement method for carbon steels in radiation source dissolved solution and a corroded specimen analysis method using an imaging plate. JAEA-Technology 2023-028. 2024. 22
Lectures and oral presentations (26):
Recognition of corrosion area using image processing technique
(日本鉄鋼協会2024年春季大会(第187回))
Detection of radioactive materials in carbon steel rust layer using imaging plate
(腐食防食学会第70回材料と環境討論会)
Chemical researches assisting in Decommissioning Fukushima Daiichi Nuclear Power Station including material corrosion, radioactive nuclides behavior and waste solidification
(7th International Forum on the Decommissioning of the Fukushima Daiichi Nuclear Power Station)
The Effect of radioactive species on corrosion potential of Type 316L stainless steel in HCl
(材料と環境2023)
Recognition of corrosion image using machine learning
(日本鉄鋼協会2023年春季(第185回)講演大会)