中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
机构
海洋研究所 [3]
采集方式
OAI收割 [3]
内容类型
期刊论文 [3]
发表日期
2024 [3]
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Machine learning models and computational simulation techniques for prediction of anti-corrosion properties of novel benzimidazole derivatives
期刊论文
OAI收割
MATERIALS TODAY COMMUNICATIONS, 2024, 卷号: 41, 页码: 23
作者:
Ekeocha, Christopher Ikechukwu
;
Uzochukwu, Ikechukwu Nelson
;
Etim, Ini-Ibehe Nabuk
;
Onyeachu, Benedict Ikenna
;
Oguzie, Emeka Emmanuel
  |  
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2024/12/20
Corrosion inhibitors
DFT
MD simulation
predictive model
machine learning
Synergism of Computational Simulation Technique and Machine Learning Algorithm for Prediction of Anticorrosion Properties of Some Antipyrine Derivatives
期刊论文
OAI收割
JOURNAL OF PHYSICAL CHEMISTRY A, 2024, 页码: 25
作者:
Ekeocha, Christopher Ikechukwu
;
Uzochukwu, Ikechukwu Nelson
;
Onyeachu, Ikenna Benedict
;
Etim, Ini-Ibehe Nabuk
;
Oguzie, Emeka Emmanuel
  |  
收藏
  |  
浏览/下载:1/0
  |  
提交时间:2024/12/20
Theoretical study of novel antipyrine derivatives as promising corrosion inhibitors for mild steel in an acidic environment
期刊论文
OAI收割
STRUCTURAL CHEMISTRY, 2024, 页码: 17
作者:
Ekeocha, Christopher Ikechukwu
;
Uzochukwu, Ikechukwu Nelson
;
Onyeachu, Ikenna Benedict
;
Etim, Ini-Ibehe Nabuk
;
Oguzie, Emeka Emmanuel
  |  
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2024/12/20
Acid cleaning
Antipyrine derivatives
Corrosion inhibitors
DFT
MD simulation
Mild steel