摘要
润滑油添加剂对保障机械运行的稳定性和安全性、延长设备的使用寿命、节约能耗具有重要作用,由于通过实验获得数据费时费力,故用定量结构摩擦性能关系研究方法,来获取抗磨损性能数据成为一种简便而高效的方法.为研究酰肼类及磷酸类润滑油添加剂抗磨损性能与结构的关系,定义并建构了新的氢谱修饰指数^(0)H,并计算36个酰肼类及磷酸类分子的电性距离矢量,筛选了M_(2)、M_(3)、M_(21)和M_(59),将这5个结构描述符作为BP神经网络的输入变量,磨损体积量度V s作为神经网络输出变量,用5-3-1的神经网络结构,构建了神经网络法预测模型,模型相关系数0.944,磨损体积量度V s的预测值与文献实验值的平均相对误差为2.61%,优于文献方法结果.结果表明:酰肼类及磷酸类润滑油添加剂抗磨损性能与氢谱修饰指数有良好的非线性关系,影响抗磨损性能的主要因素是分子中原子特性、基团片段的—CH_(3)、—CH_(2)—、>CH—、—O、—N—和—P—等.该研究对指导合成新型抗磨损性能好的化合物分子有理论意义.
Lubricant additives play important roles in ensuring the stability and safety of mechanical operation,extending the service life of equipment,and saving energy consumption.Since it is time-consuming and labor-intensive to obtain the data through experiments,it is a simple and efficient method to obtain the anti-wear performance data by using quantitative structure-friction performance relationship research.In order to study the relationship between anti-wear performance and structure of hydrazide and phosphoric acid lubricant additives,a new hydrogen spectrum modification index^(0)H was defined and constructed,and the electrical distance vectors of 36 hydrazide and phosphoric acid molecules were calculated,and M_(2),M_(3),M_(21)and M_(59)were screened.Using these five structural descriptors as input variables for the BP neural network and the wear volume measurement V s as the output variable,a neural network prediction model was constructed using a 5-3-1 neural network structure.The model correlation coefficient was 0.944,and the average relative error between the predicted value and the experimental value in the literature of the wear volume measurement V s was 2.61%,which was better than the results using the literature method.The results show that the anti-wear performance of hydrazide and phosphate lubricant additives has a good non-linear relationship with the hydrogen spectrum modification index,and the main factors affecting the anti-wear performance are the atomic properties of the molecules,the group fragments of—CH_(3),—CH_(2)—,>CH—,—CH_(3),—CH_(2)—,>CH—,—O,—N—and—P—,etc.The study is of theoretical significance in guiding the synthesis of new compound molecules with good anti-wear properties.
作者
堵锡华
徐艳
宋明
石春玲
DU Xihua;XU Yan;SONG Ming;SHI Chunling(School of Materials and Chemical Engineering,Xuzhou University of Technology,Xuzhou 221018,China)
出处
《徐州工程学院学报（自然科学版）》
CAS
2024年第2期33-44,共12页
Journal of Xuzhou Institute of Technology(Natural Sciences Edition)
基金
江苏省自然科学基金项目(BK20171169)
江苏省产学研合作项目(BY20231344)。
关键词
润滑油添加剂
抗磨性能
氢谱修饰指数
电性距离矢量
定量结构摩擦性能关系
lubricant additives
anti-wear performance
hydrogen spectrum modification index(HSMI)
electrical distance vector
quantitative structure tribo-ability relationship(QSTR)
