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金属离子水解常数pK1的人工神经网络研究

Study on Hydrolysis Constants pK1 of Metal Ions by using Artificial Neural Network

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【作者】 杨兴华印春生

【Author】 YANG Xing-Hua*,1 YIN Chun-Sheng2(1Department of Chemistry and Chemical Engineering,Huaihua University,Huaihua 418008)(2School of Environmental Science and Engineering,Shanghai Jiaotong University,Shanghai 200240)

【机构】 湖南怀化学院化学化工系上海交通大学环境科学与工程学院 怀化418008上海200240

【Abstract】 A functional-link net(FLN) was applied to study the relationships between the structural parameters of metal ions and their Hytrosis Constants pK1. These structural parameters such as radius, electric charge, electronegativity (electricity shouldering) and valence electron structure parameter of the metal ion. The results are satisfactory, and better than that obtained by using linearly statistic methods. Through comparing hytrolysis constants pK1 with hydration-energy ?H, the non-linear characteristic of pK1 have deeply discussed. 19 unknown pK1 of metal ion were predicted with the method.

【基金】 湖南省高校科研资助项目(No.01C035)
  • 【文献出处】 无机化学学报 ,Chinese Journal of Inorganic Chemistry , 编辑部邮箱 ,2004年11期
  • 【分类号】O614.33
  • 【被引频次】10
  • 【下载频次】172
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