Prediction of electrochemical impedance spectroscopy of high-entropy alloys corrosion by using gradient boosting decision tree

Boxin Wei; Jin Xu; Jingyu Pang; Zheng Huang; Jiajun Wu; Zheng Cai; Mengdi Yan; Cheng Sun

doi:10.1016/j.mtcomm.2022.104047

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Prediction of electrochemical impedance spectroscopy of high-entropy alloys corrosion by using gradient boosting decision tree

Boxin Wei Jin Xu Jingyu Pang Zheng Huang Jiajun Wu Zheng Cai Mengdi Yan Cheng Sun

Year: 2022 Journal: Materials Today Communications Vol: 32 Pages: 104047-104047 Publisher: Elsevier BV

DOI: 10.1016/j.mtcomm.2022.104047

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Keywords:

Dielectric spectroscopy Materials science Boosting (machine learning) Corrosion Gradient boosting Decision tree Electrical impedance Entropy (arrow of time) Alloy Electrochemistry Analytical Chemistry (journal) Machine learning Computer science Metallurgy Thermodynamics Random forest Chromatography Physical chemistry

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High Entropy Alloys Studies

Physical Sciences → Engineering → Mechanical Engineering

High-Temperature Coating Behaviors

Physical Sciences → Engineering → Aerospace Engineering

Corrosion Behavior and Inhibition

Physical Sciences → Materials Science → Materials Chemistry

Prediction of electrochemical impedance spectroscopy of high-entropy alloys corrosion by using gradient boosting decision tree

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