Fangfang Ma, Lihao Su, Weihao Tang, Rongjie Zhang, Qiaojing Zhao, Jingwen Chen and Hong-Bin Xie*,
{"title":"乙醇汽油车排放的胺增强硫酸驱动成核:机器学习模型和机理研究","authors":"Fangfang Ma, Lihao Su, Weihao Tang, Rongjie Zhang, Qiaojing Zhao, Jingwen Chen and Hong-Bin Xie*, ","doi":"10.1021/acs.est.4c0657810.1021/acs.est.4c06578","DOIUrl":null,"url":null,"abstract":"<p >The sulfuric acid (SA)-amine nucleation mechanism gained increasing attention due to its important role in atmospheric secondary particle formation. However, the intrinsic enhancing potential (IEP) of various amines remains largely unknown, restraining the assessment on the role of the SA-amines mechanism at various locations. Herein, machine learning (ML) models were constructed for high-throughput prediction of IEP of amines, and the nucleation mechanism of specific amines with high IEP was investigated. The formation free energy (Δ<i>G</i>) of SA-amines dimer clusters, a key parameter for assessing IEP, was calculated for 58 amines. Based on the calculated Δ<i>G</i> values, seven ML models were constructed and the best one was further utilized to predict the Δ<i>G</i> values of the remaining 153 amines. Diethylamine (DEA), mainly emitted from ethanol gasoline vehicles, was found to be one of the amines with the highest IEP for SA-driven nucleation. By studying larger SA-DEA clusters, it was found that the nucleation rate of DEA with SA is 3–7 times higher than that of dimethylamine, a well-known key base for SA-driven nucleation. The study provides a powerful tool for evaluating the actual role of amines on SA-driven nucleation and revealed that the mechanism could be particularly important in areas where ethanol gasoline vehicles are widely used.</p>","PeriodicalId":36,"journal":{"name":"环境科学与技术","volume":"58 50","pages":"22278–22287 22278–22287"},"PeriodicalIF":11.3000,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sulfuric Acid-Driven Nucleation Enhanced by Amines from Ethanol Gasoline Vehicle Emission: Machine Learning Model and Mechanistic Study\",\"authors\":\"Fangfang Ma, Lihao Su, Weihao Tang, Rongjie Zhang, Qiaojing Zhao, Jingwen Chen and Hong-Bin Xie*, \",\"doi\":\"10.1021/acs.est.4c0657810.1021/acs.est.4c06578\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >The sulfuric acid (SA)-amine nucleation mechanism gained increasing attention due to its important role in atmospheric secondary particle formation. However, the intrinsic enhancing potential (IEP) of various amines remains largely unknown, restraining the assessment on the role of the SA-amines mechanism at various locations. Herein, machine learning (ML) models were constructed for high-throughput prediction of IEP of amines, and the nucleation mechanism of specific amines with high IEP was investigated. The formation free energy (Δ<i>G</i>) of SA-amines dimer clusters, a key parameter for assessing IEP, was calculated for 58 amines. Based on the calculated Δ<i>G</i> values, seven ML models were constructed and the best one was further utilized to predict the Δ<i>G</i> values of the remaining 153 amines. Diethylamine (DEA), mainly emitted from ethanol gasoline vehicles, was found to be one of the amines with the highest IEP for SA-driven nucleation. By studying larger SA-DEA clusters, it was found that the nucleation rate of DEA with SA is 3–7 times higher than that of dimethylamine, a well-known key base for SA-driven nucleation. The study provides a powerful tool for evaluating the actual role of amines on SA-driven nucleation and revealed that the mechanism could be particularly important in areas where ethanol gasoline vehicles are widely used.</p>\",\"PeriodicalId\":36,\"journal\":{\"name\":\"环境科学与技术\",\"volume\":\"58 50\",\"pages\":\"22278–22287 22278–22287\"},\"PeriodicalIF\":11.3000,\"publicationDate\":\"2024-12-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"环境科学与技术\",\"FirstCategoryId\":\"1\",\"ListUrlMain\":\"https://pubs.acs.org/doi/10.1021/acs.est.4c06578\",\"RegionNum\":1,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ENVIRONMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"环境科学与技术","FirstCategoryId":"1","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acs.est.4c06578","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ENVIRONMENTAL","Score":null,"Total":0}
Sulfuric Acid-Driven Nucleation Enhanced by Amines from Ethanol Gasoline Vehicle Emission: Machine Learning Model and Mechanistic Study
The sulfuric acid (SA)-amine nucleation mechanism gained increasing attention due to its important role in atmospheric secondary particle formation. However, the intrinsic enhancing potential (IEP) of various amines remains largely unknown, restraining the assessment on the role of the SA-amines mechanism at various locations. Herein, machine learning (ML) models were constructed for high-throughput prediction of IEP of amines, and the nucleation mechanism of specific amines with high IEP was investigated. The formation free energy (ΔG) of SA-amines dimer clusters, a key parameter for assessing IEP, was calculated for 58 amines. Based on the calculated ΔG values, seven ML models were constructed and the best one was further utilized to predict the ΔG values of the remaining 153 amines. Diethylamine (DEA), mainly emitted from ethanol gasoline vehicles, was found to be one of the amines with the highest IEP for SA-driven nucleation. By studying larger SA-DEA clusters, it was found that the nucleation rate of DEA with SA is 3–7 times higher than that of dimethylamine, a well-known key base for SA-driven nucleation. The study provides a powerful tool for evaluating the actual role of amines on SA-driven nucleation and revealed that the mechanism could be particularly important in areas where ethanol gasoline vehicles are widely used.
期刊介绍:
Environmental Science & Technology (ES&T) is a co-sponsored academic and technical magazine by the Hubei Provincial Environmental Protection Bureau and the Hubei Provincial Academy of Environmental Sciences.
Environmental Science & Technology (ES&T) holds the status of Chinese core journals, scientific papers source journals of China, Chinese Science Citation Database source journals, and Chinese Academic Journal Comprehensive Evaluation Database source journals. This publication focuses on the academic field of environmental protection, featuring articles related to environmental protection and technical advancements.