摘要
通过失重法测试3种取代吡啶甲酰腙席夫碱化合物对铜在3.5%NaCl溶液中的缓蚀作用。结果表明:都有良好的缓蚀作用,缓蚀效率高达96%以上;其中尤以邻香草醛-2-吡啶甲酰腙(L2B)的效果最好,当浓度为50 mg/L时,缓蚀效率就已达到80%以上。用量子化学半经验AM1方法,在B3LYP/6-31G*基组水平上,研究3种席夫碱缓蚀性能与分子结构的关系、量子化学参数与缓蚀性能的关系及缓蚀机理,结果表明:3种缓蚀剂的缓蚀效率与分子的最高占有轨道能量EHOMO、氮氧原子的净电荷和热力学参数之间有很好的相关性。利用SPSS Statistics 17.0软件线性回归分析量子化学参数与缓蚀性能的相关性,结果表明:评价失重法对3种缓蚀剂对铜缓蚀能力的实验数据和理论计算相吻合。
The inhibition effect of three kinds of Schiff-base on the Cu in 3.5%NaCl solution were investigated by mass loss test.Mass loss test results indicate that these compounds can perform good inhibition for the Cu coating in 3.5%NaCl solution,and the highest inhibition efficiency is up to 96%.Among them,L2B shows the best performance with inhibition efficiency up to 80%when at a relatively low concentration of 50 mg/L.The relationships between corrosion inhibitor efficiency of three kinds of Schiff-base and their electronic properties of molecules have been studied by using the quantum chemistry method at the level of AM1 with the B3LYP/6-31G base sets.The relationships between the corrosion inhibitor efficiency and the result of the quantum chemistry calculation were discussed.It is found that the corrosion inhibition efficiencies of these inhibitors have a good linear relationship to the energy of Highest Occupied Molecular Orbital(HOMO),energy of Lowest Unoccupied Molecular Orbital (LUMO),energy gap between LUMO and HOMO,net charge of N,O atoms,and the thermodynamic parameters.The mechanism of corrosion inhibition was also discussed.The usage of SPSS Statistics 17.0 software for quantum chemical parameters associated with the corrosion performance of linear regression analysis results shows that:weight-loss method for three types of Cu corrosion inhibitors evaluation of experimental data was fit to theoretical calculation results.
出处
《计算机与应用化学》
CAS
CSCD
北大核心
2010年第7期901-905,共5页
Computers and Applied Chemistry
基金
广西高校优秀人才资助计划项目(N0.RC2007021)
广西研究生教育创新计划项目(2009105960817M22)
广西研究生教育创新人才联合培养基地项目
关键词
酰腙席夫碱
铜
量子化学
失重法
回归分析法
acyhydrazone Schiff-base
Cu
quantum chemistry
mass loss test
regression analytical method