Sulfuric Acid-Driven Nucleation Enhanced by Amines from Ethanol Gasoline Vehicle Emission: Machine Learning Model and Mechanistic Study DOI
Fangfang Ma, Lihao Su, Weihao Tang

и другие.

Environmental Science & Technology, Год журнала: 2024, Номер unknown

Опубликована: Дек. 5, 2024

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 assessment on SA-amines at locations. Herein, machine learning (ML) models were constructed for high-throughput prediction IEP amines, and specific with high was investigated. formation free energy (Δ

Язык: Английский

Quaternary Nucleation of Iodine and Sulfur Oxoacids in the Marine Atmosphere: Unexpected Role of Methanesulfonic Acid DOI
R. Y. Zhang, Hong‐Bin Xie, Fangfang Ma

и другие.

Journal of Geophysical Research Atmospheres, Год журнала: 2025, Номер 130(8)

Опубликована: Апрель 17, 2025

Abstract Sulfuric acid (SA), methanesulfonic (MSA), iodic (HIO 3 ), and iodous 2 ) are identified as key nucleation precursors can coexist in the marine atmosphere. Here, we investigated potential SA‐MSA‐HIO ‐HIO quaternary mechanism by exploring formation of (SA) w (MSA) x y z (0 ≤ + 3, 1 3) clusters with quantum chemical calculation kinetics modelling. The results indicate that effectively nucleate under atmospheric conditions. rate is up to 7 orders magnitude higher than SA/MSA‐HIO , ternary mechanisms, SA/MSA/HIO binary mechanisms at some specific mainly driven acid‐base reaction base) halogen bonds besides hydrogen bonds, three acids showing both competitive cooperative roles. More importantly, it was found contribution MSA aerosol comparable SA equal concentrations. unexpectedly high attributed its halogen‐bonding capacity SA. This study highlights need consider multicomponent atmosphere for accurate climate projections, may serve important proof weak even coexisting

Язык: Английский

Процитировано

0

Iodine Clusters in the Atmosphere I: Computational Benchmark and Dimer Formation of Oxyacids and Oxides DOI Creative Commons
Morten Engsvang, Haide Wu, Jonas Elm

и другие.

ACS Omega, Год журнала: 2024, Номер 9(29), С. 31521 - 31532

Опубликована: Июль 9, 2024

The contribution of iodine-containing compounds to atmospheric new particle formation is still not fully understood, but iodic acid and iodous are thought be significant contributors. While several quantum chemical studies have been carried out on clusters containing iodine, there no comprehensive benchmark study quantifying the accuracy applied methods. Here, we present first in a series that investigate role iodine species cluster formation. In this work, studied acid, tetroxide, pentoxide monomers their dimers formed with common precursors. We tested commonly methods for calculating geometry monomers, thermal corrections dimers, spin–orbit coupling finally, electronic energy correction calculated at different levels theory. find optimizing structures either ωB97X-D3BJ/aug-cc-pVTZ-PP or M06-2X/aug-cc-pVTZ-PP level achieves best binding free energy. can then ZORA-DLPNO–CCSD(T0) SARC-ZORA-TZVPP basis ma-ZORA-def2-TZVPP non-iodine atoms. methodology calculate energies dimer clusters, where confirm qualitative trends observed previous studies. However, identify overestimate stability by kcal/mol due neglect relativistic effects. This means contributions currently nucleation pathways likely overestimated.

Язык: Английский

Процитировано

1

Sulfuric Acid-Driven Nucleation Enhanced by Amines from Ethanol Gasoline Vehicle Emission: Machine Learning Model and Mechanistic Study DOI
Fangfang Ma, Lihao Su, Weihao Tang

и другие.

Environmental Science & Technology, Год журнала: 2024, Номер unknown

Опубликована: Дек. 5, 2024

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 assessment on SA-amines at locations. Herein, machine learning (ML) models were constructed for high-throughput prediction IEP amines, and specific with high was investigated. formation free energy (Δ

Язык: Английский

Процитировано

1