Machine learning analysis to interpret the effect of the photocatalytic reaction rate constant (k) of semiconductor-based photocatalysts on dye removal.

Kim, Chang-Min; Jaffari, Zeeshan Haider; Abbas, Ather; Chowdhury, Mir Ferdous; Cho, Kyung Hwa

Kim, Chang-Min; Jaffari, Zeeshan Haider; Abbas, Ather; Chowdhury, Mir Ferdous; Cho, Kyung Hwa.

Affiliation

Kim CM; Future and Fusion Lab of Architectural, Civil and Environmental Engineering, Korea University, Seoul 02841, Republic of Korea.
Jaffari ZH; Department of Civil and Environmental Engineering, Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul 05029, Republic of Korea.
Abbas A; Physical Science and Engineering Division, 4700 King Abdullah University of Science and Technology, Thuwal, Mecca Province, Saudi Arabia.
Chowdhury MF; Department of Global Smart City, Sungkyunkwan University (SKKU), 2066, Seobu-ro, Jangan-gu, Suwon, Gyeonggi-do 16419, Republic of Korea.
Cho KH; School of Civil, Environmental, and Architectural Engineering, Korea University, Seoul 02841, Republic of Korea. Electronic address: khcho80@korea.ac.kr.

J Hazard Mater ; 465: 132995, 2024 Mar 05.

Article in En | MEDLINE | ID: mdl-38039815

Key words

Dye degradation; Machine learning; Photocatalysis; Reaction rate constant (k); Two-feature SHAP interactions

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Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: J Hazard Mater Journal subject: SAUDE AMBIENTAL Year: 2024 Document type: Article Country of publication: Netherlands

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