Please wait a minute...
中国腐蚀与防护学报  1998, Vol. 18 Issue (4): 283-288    
  研究报告 本期目录 | 过刊浏览 |
用神经网络研究异喹啉类缓蚀剂结构与性能的关系
胡芳;屈定荣;李志良;石鲜明
湖南大学化学化工学院;长沙410084;湖南大学化学化工学院;长沙410084;湖南大学化学化工学院;长沙410084重庆大学化学化工学院重庆400044;中国科学院化学研究所;北京100080
NEURAL NETWORK STUDY ON CORRELATION BETWEENELECTRONIC STRUCTURE AND CORROSION INHIBITIONPROPERTIES OF ISOQUINOLINE AND ITS DERIVATIVES
HU Fang QU Ding-rong SHI Xian-ming LI Zhi-liang(College of Chemical Engineering; Institute of Molecular Science; Hunan University;Changsha 410082)(Institute of Chemistry; Chinese Academy of Sciences; Beijing 100080) (College of Chemical Engineering; Chong
全文: PDF(531 KB)  
摘要: 运用人工神经网络反传算法研究了异喹啉及其衍生物电子结构与缓蚀性能之间的关系。以缓蚀剂分子氮净电荷、自由价、亲核前沿电荷密度等量子化学参数为输入变量,考察了异喹啉及其羟基、羧基衍生物在30℃,1.0mo1·dm~(-3)HCl溶液中对铁的缓蚀效率,建立了相应的预测模型。对于研究这类缓蚀剂分子在电极表面的吸附模型和缓蚀行为及定量预测同类新分子的缓蚀性能有一定价值。
关键词 神经网络异喹啉及其衍生物缓蚀效率    
Abstract:An approach of neural network was made on its application to the correlation between molecular electronic structure and corrosion inhibition properties of isoquinoline and its derivatives. It was indicated in a reference that the less the net charge and π charge of N atom are ,the higher the inhibition efficiency is, and the net charge of six atoms in pyridine ring increases. The inputs of neural networks were the molecular structure parameters, such as net charge and π charge of N atom, which were obtained by means of HMO and CNDO/2 methods. The neural network's outputs included the corrosion-inhibition efficiencies of isoquinoline and its hydroxyl and carboxyl derivatives for iron electrode in HCl solution or electrode parameters which were determined with electrochemical methods in 1.0 mol·dm-3 HCl solution at 30℃. The corresponding relationship and modeling prediction were established by using the neural networks with 7-15-6, 7-5-5, and 9-10-6 topological structures that were trained beforehand by modified backpropagation (MBP) algorithm respectively. The learning precision was high and the predicting performance was excellent. With the trained neural network the corrosion inhibition properties or electrode parameters of some unknown isoquinoline's derivatives could be predicted quantitatively and the results were quite good.
Key wordsNeural networks    Molecular electronic structure    Inhibitor    Isoquinoline
收稿日期: 1998-08-25     

引用本文:

胡芳;屈定荣;李志良;石鲜明. 用神经网络研究异喹啉类缓蚀剂结构与性能的关系[J]. 中国腐蚀与防护学报, 1998, 18(4): 283-288.
. NEURAL NETWORK STUDY ON CORRELATION BETWEENELECTRONIC STRUCTURE AND CORROSION INHIBITIONPROPERTIES OF ISOQUINOLINE AND ITS DERIVATIVES. J Chin Soc Corr Pro, 1998, 18(4): 283-288.

链接本文:

https://www.jcscp.org/CN/      或      https://www.jcscp.org/CN/Y1998/V18/I4/283

1 张敬畅,曹维良,王作新.中国腐蚀与防护学报,1986,6(3):217
2 罗明道,毕刚,旷富贵,姚禄安,颜肖慈.化学学报,1994,52:620
3 罗明道,姚禄安,吴庆余,颜肖慈,余晓东,邹津耘,欧阳礼.中国腐蚀与防护学报,1996,16(3):195
4 宁世光,石明理,刘奉岭,余立新,李延芳,章荣玲,程在英.中国腐蚀与防护学报,1990,10(3):383
5 唐子龙,宋诗哲.中国腐蚀与防护学报,1995,15(3):229
6 刘振宇,王昭东,王国栋,张强.钢铁研究学报,1995,7(4):61
7 郭稚弧,金名惠,桂修文,孟厦兰,邢政良,罗逸.腐蚀科学与防护技术,1995,7(3):258
8 郭稚弧,邢政良,金名惠,孟厦兰.中国腐蚀与防护学报,1996,6(4):307
9 李志良,曾鸽鸣,李梦龙,王树信,吉田H,宫下Y,佐佐木S.科学通报,1995,40:16320
[1] 郭宝会, 邱友绪, 李海龙. 人工神经网络在钛合金表面Ni-SiC复合电镀工艺中的应用[J]. 中国腐蚀与防护学报, 2017, 37(4): 389-394.
[2] 刘静,李晓禄,朱崇伟,张涛,曾冠鑫,孟国哲,邵亚薇. 利用人工神经网络技术预测气田环境下316L不锈钢临界点蚀温度[J]. 中国腐蚀与防护学报, 2016, 36(3): 205-211.
[3] 王春霞,陈敬平,张晓红,王赪胤. 溴化N-辛烷异喹啉在盐酸溶液中对Q235碳钢的缓蚀行为[J]. 中国腐蚀与防护学报, 2016, 36(3): 245-252.
[4] 邓志安,李姝仪,李晓坤,王珊,王晓军. 基于模糊神经网络的海洋管线腐蚀速率预测新方法[J]. 中国腐蚀与防护学报, 2015, 35(6): 571-576.
[5] 江依义, 陈宇, 叶正扬, 张昭, 张鉴清. 十七烯基咪唑啉的制备及其缓蚀性能评价[J]. 中国腐蚀与防护学报, 2013, 33(4): 325-330.
[6] 孙宝财,李淑欣,俞树荣,曾海龙. 改进BP算法的腐蚀管道剩余强度预测[J]. 中国腐蚀与防护学报, 2011, 31(5): 404-408.
[7] 汪川,王振尧,魏伟,谢陈平,柯伟. 腐蚀研究中的统计分析方法和预测模型[J]. 中国腐蚀与防护学报, 2010, 30(4): 306-312.
[8] 王静,李德刚,于先进,董云会,张丽鹏. 十二烷基硫醇在Fe表面自组装成膜及对其的腐蚀保护[J]. 中国腐蚀与防护学报, 2010, 30(3): 207-212.
[9] 栾瑞鹏,贲可荣,萧 星, 田立业. 基于改进型S算子BP神经网络的钢材大气腐蚀影响因子评估模型[J]. 中国腐蚀与防护学报, 2010, 30(3): 227-230.
[10] 刘威; 赵选民; 邓春龙; 李文军 . 灰色神经网络模型在海水腐蚀预测中的应用[J]. 中国腐蚀与防护学报, 2008, 28(4): 201-204 .
[11] 尹成先; 胥勋源; 李旭; 兰新哲; 冯耀荣 . 新型缓蚀剂TG500在高CO2和Cl-环境中的缓蚀行为[J]. 中国腐蚀与防护学报, 2007, 27(1): 23-26 .
[12] 王海涛; 韩恩厚; 柯伟 . 基于人工神经网络模型的铝合金大气腐蚀的预测[J]. 中国腐蚀与防护学报, 2006, 26(5): 272-274 .
[13] 郁大照; 陈跃良; 段成美 . 基于神经网络的飞机结构腐蚀损伤统计研究[J]. 中国腐蚀与防护学报, 2006, 26(1): 19-21 .
[14] 王守琰; 宋诗哲 . 小波分析和神经网络研究纯锌大气腐蚀[J]. 中国腐蚀与防护学报, 2005, 25(5): 257-261 .
[15] 高志明; 宋诗哲; 徐云海 . 涂层失效过程电化学阻抗谱的神经网络分析[J]. 中国腐蚀与防护学报, 2005, 25(2): 106-109 .