Bello Abdullahi Umar, A. Uzairu, Gideon Adamu Shallangwa
{"title":"氨基酸及其相关化合物在酸性介质中对钢的缓蚀作用的量子建模和分子动力学模拟","authors":"Bello Abdullahi Umar, A. Uzairu, Gideon Adamu Shallangwa","doi":"10.4152/pea.202005313","DOIUrl":null,"url":null,"abstract":"The inhibition performance of twenty-five amino acids and related compounds was studied by theoretical techniques. The effect of the acidic solution was considered on the molecular dynamics simulation, and the calculated binding energies for most of the inhibitors was ˃100 kcal mol, suggesting chemisorptive interactions. Density Functional Theory (B3LYP/6-31G*) quantum substance chemical study was utilized to discover the upgraded geometry of the inhibitors. Also, a linear quantitative structureactivity relationship (QSAR) model was built by Genetic Function Approximation (GFA) method, to run the regression analysis and build up connections between various descriptors and the experimental inhibition efficiencies. The prediction of corrosion efficiencies of these inhibitors nicely matched the experimental measurements. The statistical parameters are: 0.973421, which indicates that the model was excellent. The proposed model has great dependability, strength, and consistency on checking, with inward and outside approval.","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":null,"pages":null},"PeriodicalIF":16.4000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Quantum Modeling and Molecular Dynamic Simulation of some Amino Acids and Related Compounds on their Corrosion Inhibition of Steel in Acidic Media\",\"authors\":\"Bello Abdullahi Umar, A. Uzairu, Gideon Adamu Shallangwa\",\"doi\":\"10.4152/pea.202005313\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The inhibition performance of twenty-five amino acids and related compounds was studied by theoretical techniques. The effect of the acidic solution was considered on the molecular dynamics simulation, and the calculated binding energies for most of the inhibitors was ˃100 kcal mol, suggesting chemisorptive interactions. Density Functional Theory (B3LYP/6-31G*) quantum substance chemical study was utilized to discover the upgraded geometry of the inhibitors. Also, a linear quantitative structureactivity relationship (QSAR) model was built by Genetic Function Approximation (GFA) method, to run the regression analysis and build up connections between various descriptors and the experimental inhibition efficiencies. The prediction of corrosion efficiencies of these inhibitors nicely matched the experimental measurements. The statistical parameters are: 0.973421, which indicates that the model was excellent. The proposed model has great dependability, strength, and consistency on checking, with inward and outside approval.\",\"PeriodicalId\":1,\"journal\":{\"name\":\"Accounts of Chemical Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":16.4000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Accounts of Chemical Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4152/pea.202005313\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of Chemical Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4152/pea.202005313","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Quantum Modeling and Molecular Dynamic Simulation of some Amino Acids and Related Compounds on their Corrosion Inhibition of Steel in Acidic Media
The inhibition performance of twenty-five amino acids and related compounds was studied by theoretical techniques. The effect of the acidic solution was considered on the molecular dynamics simulation, and the calculated binding energies for most of the inhibitors was ˃100 kcal mol, suggesting chemisorptive interactions. Density Functional Theory (B3LYP/6-31G*) quantum substance chemical study was utilized to discover the upgraded geometry of the inhibitors. Also, a linear quantitative structureactivity relationship (QSAR) model was built by Genetic Function Approximation (GFA) method, to run the regression analysis and build up connections between various descriptors and the experimental inhibition efficiencies. The prediction of corrosion efficiencies of these inhibitors nicely matched the experimental measurements. The statistical parameters are: 0.973421, which indicates that the model was excellent. The proposed model has great dependability, strength, and consistency on checking, with inward and outside approval.
期刊介绍:
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.