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Counterintuitive Oxidation of Alcohols at Air-Water Interfaces
酒精在空气-水界面上的反直觉氧化作用

Deming Xia, Jingwen Chen, Hong-Bin Xie,* Jie Zhong, and Joseph S. Francisco*
Deming Xia、Jingwen Chen、Hong-Bin Xie、* Jie Zhong 和 Joseph S. Francisco*

Cite This: J. Am. Chem. Soc. 2023, 145, 4791-4799
引用此文：J. Am.Chem.2023, 145, 4791-4799
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Abstract 摘要

This study shows that the oxidation of alcohols can rapidly occur at air-water interfaces. It was found that methanediols orient at air-water interfaces with a atom of the group pointing toward the gaseous phase. Counterintuitively, gaseous hydroxyl radicals do not prefer to attack the exposed group but the group that forms hydrogen bonds with water molecules at the surface via a waterpromoted mechanism, leading to the formation of formic acids. Compared with gaseous oxidation, the water-promoted mechanism at the air-water interface significantly lowers free-energy barriers from to and therefore accelerates the formation of formic acids. The study unveils a previously overlooked source of environmental organic acids that are bound up with aerosol formation and water acidity.
这项研究表明，醇类的氧化可在空气-水界面迅速发生。研究发现，甲二醇 在空气-水界面上定向时， 基团的 原子指向气相。与直觉相反，气态羟基自由基并不倾向于攻击暴露在外的 基团，而是攻击 基团，后者通过水促进机制与表面的水分子形成氢键，从而形成甲酸。与气态氧化相比，空气-水界面上的水促进机制大大降低了从 到 的自由能垒，因此加速了甲酸的形成。这项研究揭示了以前被忽视的与气溶胶形成和水酸性有关的环境有机酸来源。

■ INTRODUCTION 引言

Organic acids (OAs) that account for of total organic carbons are ubiquitous in the environment. In the atmosphere, OAs can directly participate in aerosol formation via enhancing new particle formation and contributing to secondary organic aerosols, affecting global climate and local air quality. In the hydrosphere (e.g., cloud, dew, and sea), increasing shreds of evidence have indicated that aqueousphase acidity is strongly influenced by OAs, of which heterogeneous chemistry is also highly related to local ozone and particle formation. In the pedosphere, mineral weathering, metal detoxification, and nutrient acquisition by plant roots are associated with the participation of OAs. Therefore, OAs play important roles in the environment.
占总有机碳 的有机酸（OAs）在环境中无处不在。 在大气中，有机酸可以通过增强新粒子的形成和促成二次有机气溶胶而直接参与气溶胶的形成， 从而影响全球气候和当地空气质量。在水圈（如云层、露水和海洋）中，越来越多的证据表明，水相酸度受到 OAs 的强烈影响，其中的异质化学性质也与当地臭氧和颗粒物的形成密切相关。 在土壤圈中，矿物风化、金属解毒和植物根系获取养分都与 OAs 的参与有关。 因此，OA 在环境中发挥着重要作用。
However, environmental sources of OAs remain elusive. Existing shreds of evidence from laboratory experiments and field observations suggested that most OAs are not emitted directly from primary sources (e.g., vegetation, microorganism, and biomass burning) but are produced from multitudinous secondary sources, especially oxidation of alcohols at their positions (i.e., the carbons nearest to the group of the alcohols). For example, gaseous oxidation of methanediol , the hydrated form of formaldehyde , by hydroxyl radicals (. ) has been recently shown to be a previously underestimated source of atmospheric formic acid -the simplest and the most abundant in the atmosphere. Nevertheless, the same pathway has also been found to be unimportant in explaining the mismatch in diurnal trends of simulated and observed concentrations. The disagreement implies some missing mechanisms of alcohol oxidation in addition to the gaseous oxidation.
然而，OAs 的环境来源仍然难以捉摸。 实验室实验和实地观察所获得的现有证据表明，大多数 OAs 并不是直接从原生源（如植被、微生物和生物质燃烧）排放的，而是从多种次生源产生的，特别是醇类在其 位置（即最靠近醇类 基团的碳）的氧化。 例如，甲二醇 （甲醛 的水合形式）被羟自由基（. ）气态氧化，最近已被证明是大气中甲酸 （大气中最简单、最丰富的甲酸 ）以前被低估的来源。 然而，同样的途径在解释模拟和观测到的 浓度昼夜变化趋势不一致时也被认为并不重要。 这种差异意味着除了气态氧化之外，酒精氧化的某些机制也存在缺失。
Alcohols as well as many other organic tracers may be enriched at the air-water interfaces due to their "surfactantlike" structures, i.e., containing both hydrophilic and hydrophobic functional groups. Methanol and ethanol have been experimentally and computationally found to be accumulated at the airwater interfaces with adsorption-free-energies of -5.2 to -3.9 Furthermore, the water surface has been shown to affect the energies of the frontier orbitals of adsorbates (e.g., formaldehyde, the dehydrated form of ) via acting as an H-bond donor or acceptor. This could favor the reaction of free radicals with the adsorbates, triggering chain oxidation reactions. In addition, "surface preference" of at the air-water interfaces has also been reported. The above circumstantial evidence suggests that a unique and important transformation from alcohols to OAs may exist at the airwater interfaces.
醇类以及许多其他有机示踪剂由于其 "类似表面活性剂 "的结构（即同时含有亲水的 和疏水的 官能团），可能会在空气-水界面富集。 实验和计算发现，甲醇 和乙醇 在空气-水界面上积聚，吸附自由能为 -5.2 到 -3.9 此外，研究还表明，水面会影响吸附物（如：甲醛、脱水甲醛、脱水乙醇）前沿轨道的能量、 的脱水形式甲醛）。 这有利于自由基与吸附剂发生反应，引发链式氧化反应。 此外， 在空气-水界面的 "表面偏好 "也有报道。 上述间接证据表明，在空气-水界面上可能存在从醇到 OAs 的独特而重要的转化过程。
Despite difficulties in measuring interface phenomena experimentally, recent advances in machine learning make it possible to simulate interfacial reactions. In this study, a reactive machine-learning force field (MLFF) that can reach density-functional-theory-level quality with a significant decrease in computational costs was trained based on ab initio data selected from ca. configurations via an on-the-
尽管难以通过实验测量界面现象， 机器学习的最新进展使模拟界面反应成为可能。 在这项研究中，我们根据从约 个构型中选取的 ab initio 数据，训练了一个反应性机器学习力场（MLFF），它可以达到密度泛函理论级别的质量，同时显著降低计算成本。
Figure 1. Performance of trained machine-learning force field (MLFF) in predicting (A) energies ( 7,018 and 1,800 data points for the training and external validation sets, respectively), (B) forces ( and 408,300 data points for the training and external validation sets, respectively), (C) stresses ( 42,108 and 13,800 data points for the training and external validation sets, respectively), and radial distribution functions (RDFs) for (D) distances in the aqueous phase, (E) distances ( , and ( ) distances ( ) at water surfaces with experimental or initio molecular dynamics (AIMD) data as comparisons. (The white, gray, and red balls in panels represent , and atoms, respectively; the AIMD data in panels and were calculated using the functional with D4 correction in this study.)
图 1.训练有素的机器学习力场 (MLFF) 在预测 (A) 能量（训练集和外部验证集的数据点分别为 7,018 和 1,800 个）、(B) 力（训练集和外部验证集的数据点分别为 和 408,300 个）、(C) 应力（训练集和外部验证集的数据点分别为 42,108 和 13,800 个）以及 (D) 水相中 距离 的径向分布函数 (RDF) 方面的性能、(D) 水相中 距离 的径向分布函数 (RDF)，(E) 水表面 距离 ( ) 和 ( ) 距离 ( ) 的径向分布函数 (RDF)，以实验 或 初始分子动力学 (AIMD) 数据作为比较。(面板 中的白球、灰球和红球分别代表 和 原子；面板 和 中的 AIMD 数据是本研究中使用 函数和 D4 修正 计算得出的）。
fly algorithm. Based on the developed MLFF, a series of machine-learning-based molecular dynamics simulations with the assistance of ab initio molecular dynamics (AIMD), enhanced sampling techniques, and quantum chemical calculations was carried out to reveal the transformation mechanisms and kinetics of at the air-water interfaces. The heterogeneous mechanism presented here may facilitate elucidating the high levels of OAs that affect aerosol growth, cloud evolution, and water/soil acidity.
飞算法。 基于开发的MLFF，在ab initio分子动力学（AIMD）、增强采样技术和量子化学计算的辅助下，进行了一系列基于机器学习的分子动力学模拟，揭示了 在空气-水界面的转化机制和动力学。本文提出的异质机制可能有助于阐明影响气溶胶生长、云演变和水/土壤酸度的高浓度 OAs。

■ METHODS 方法

On-the-Fly Ab Initio Molecular Dynamics (AIMD) Simulation. All the AIMD simulations were performed using a recently developed SCAN functional with plane-wave basis sets cutoff in energy) on VASP 6.3. The D4 correction method was applied to account for weak dispersion interactions. The combination of and D4 (R्र ) has been recently proven to approach the accuracy of hybrid functionals for general chemical applications (especially for main group elements) with relatively low computational costs. The projector-augmented-wave pseudopotentials with nonspherical contributions were implemented to treat core electrons. The MLFFs were trained on-the-fly during the AIMD simulations based on the Bayesian linear regression in the NVT ensemble at ca. that was controlled by the Nosé-Hoover thermostat method. The time step was .
在线 Ab Initio 分子动力学（AIMD）模拟。所有的 AIMD 模拟都是在 VASP 6.3 上使用最近开发的 SCAN 函数和平面波基集 能量截止进行的。 采用了 D4 修正方法来考虑弱色散相互作用。 和 D4（R्र ）的组合最近已被证明能够以相对较低的计算成本接近混合函数在一般化学应用（特别是主族元素）中的精度。 采用了具有非球面贡献的投影增强波伪势来处理核心电子。 在AIMD模拟期间，根据NVT集合中的贝叶斯线性回归对MLFF进行了即时训练。 由 Nosé-Hoover 恒温器方法控制。 时间步长为 。
Major hyperparameters used for the MLFF construction were optimized with the on-the-fly AIMD simulations for six independent systems (Tables S1 and S2). In total, 7017 key first-principle points were sampled using an active-learning algorithm based on almost simulation steps ( ) of the on-the-fly simulations. The trained MLFF model consisted of 4336, 5053, and 2894 basis functions for , and elements, respectively. The MLFF model was first validated on an external data set that was not used for training the model. The data set consisted of 1800 structures covering different phases (i.e., gaseous phase, aqueous phase, and air-water interfaces) and reaction statuses (i.e., reactants, transition states, and products). The model was also validated by comparing the radial distribution functions calculated via the MLFF with available experimental and initio ones.
通过对六个独立系统（表 S1 和 S2）进行即时 AIMD 模拟，优化了用于构建 MLFF 的主要超参数。在近 个即时模拟步骤（ ）的基础上，使用主动学习算法对总共 7017 个关键第一原理点进行了采样。经过训练的 MLFF 模型分别由 4336、5053 和 2894 个基函数组成，用于 和 元素。MLFF 模型首先在未用于模型训练的外部数据集上进行了验证。该数据集包括 1800 个结构，涵盖不同的相位（即气相、水相和空气-水界面）和反应状态（即反应物、过渡态和产物）。该模型还通过比较通过 MLFF 计算出的径向分布函数与现有的实验 和 initio 函数进行了验证。
MLFF-Based Molecular Dynamics Simulation. The simulations were performed using VASP 6.3. The simulated system for the reactions at the air-water interface was a ÅÅÅ supercell that contains the reactants, molecules, and a Å vacuum layer (Figure S1). The aqueous phase system was a cubic cell with a Å side length that contained the reactants and molecules (Figure S2). The gaseous-phase system had the same size of the aqueous-phase system but only contains reactants (Figure S3). Free-energy profiles were calculated with several collective variables (CVs) using metadynamics sampling (detailed in the Supporting Information).
基于 MLFF 的分子动力学模拟。模拟使用 VASP 6.3 进行。 空气-水界面反应的模拟系统是一个 ÅÅÅ 超级池，其中包含反应物、 分子和 Å 真空层（图 S1）。水相系统是一个边长为 Å 的立方晶胞，其中包含反应物和 分子（图 S2）。气相体系的大小与水相体系相同，但只包含反应物（图 S3）。利用元动力学采样（详见《辅助资料》）计算了多个集合变量（CV）的自由能曲线。
The simulation time is 1 ns for all considered systems in MLFFbased molecular dynamics simulation, and one initial configuration was adopted. An early study suggests that approximately nanosecond level simulation is long enough to produce the precise free-profile. Our test simulations indicated that the error caused by four initial configurations is very small ( , Figure S4). Gibbs-freeenergy change between separated reactants and the corresponding transition state ( ) was calculated by subtracting Gibbs-freeenergy at the transition state and the separated reactants. Detailed parameters for metadynamics samplings are listed in Table S3.
在基于 MLFF 的分子动力学模拟中，所有考虑的系统的模拟时间均为 1 毫微秒，并采用一种初始构型。早期研究表明，大约纳秒级的模拟时间足以产生精确的自由轮廓。 我们的试验模拟表明，四种初始构型造成的误差非常小（ ，图 S4）。分离的反应物和相应过渡态之间的吉布斯自由能变化（ ）是通过减去过渡态和分离的反应物的吉布斯自由能计算出来的。表 S3 列出了元动力学取样的详细参数。
Quantum Chemical Calculations. Structural optimization and energy calculation were performed using Gaussian 16 and ORCA 4.0, respectively. For all the reactions involving and the organic molecules, geometry optimization and harmonic frequency calculation for the reactants, products, and transition states were carried out using the M06-2X-D3 /aug-cc-pVTZ methods. Intrinsic reaction coordinate calculation was performed to confirm the connection of the transition states with the reactants and products. Single-point energies were calculated at the aug-cc-pVTZ level (for " system) or DLPNO-CCSD aug-cc [for "HOCH " systems] based on the optimized geometries. The DLPNO-CCSD(T) aug-cc-pVTZ calculations were performed under the tightPNO condition. Zeropoint energies at the aug-cc-pVTZ level were adopted to correct the corresponding single-point energies.
量子化学计算。结构优化和能量计算分别使用高斯 16 和 ORCA 4.0 进行。 对于涉及 和有机分子的所有反应，使用 M06-2X-D3 /aug-cc-pVTZ 方法对反应物、产物和过渡态进行了几何优化和谐波频率计算。进行了本征反应坐标计算，以确认过渡态与反应物和生成物之间的联系。根据优化的几何结构，在 aug-cc-pVTZ 水平（针对 " 系统）或 DLPNO-CCSD aug-cc [针对 "HOCH " 系统] 下计算了单点能量。DLPNO-CCSD(T) aug-cc-pVTZ 计算是在紧PNO 条件下进行的。采用 aug-cc-pVTZ 水平的零点能量来修正相应的单点能量。
Figure 2. Adsorption of at air-water interfaces: (A) Gibbs-free-energy change ( ) profile of a molecule pulled into water as a function of distance Å between centers of and water slab [ density of water is indicated by the black curve and fitted via a hyperbolic tangent function; GDS indicates the Gibbs dividing surface, where equals bulk density of water.]; (B) probability distribution of nine typical configurations; and (C) their chemical structures at the water surface. (The white, gray, and red balls represent , and atoms, respectively. The dotted lines denote hydrogen bonds between and molecules.) (D) Definition of (E) probability density ( ) of at the water surface.
图 2.空气-水界面上的 吸附：(A) 吸入水中的 分子的吉布斯自由能变化 ( ) 曲线与 和水板中心间距离 Å 的函数关系 [ 黑色曲线表示水的密度 ，并通过双曲正切函数拟合；GDS 表示吉布斯分界面，其中 等于水的体积密度 。]；(B) 九种典型构型的概率分布；(C) 它们在水面上的化学结构。(白球、灰球和红球分别代表 原子和 原子。虚线表示 和 分子之间的氢键）。(D) 的定义 (E) 在水面的概率密度 ( )。

RESULTS AND DISCUSSION 结果与讨论

Performance of the Developed MLFF. To investigate the adsorption and transformation of at air-water interfaces, an MLFF model was trained based on a series of AIMD simulations with and without metadynamics samplings for gaseous, aqueous, and interfacial systems. An active-learning strategy that has succeeded in many aqueousphase, interface, and material systems was adopted to select key initio data for constructing the model. Figure 1 and Table S4 display performance of the trained MLFF model using SCAN-D4 level data as benchmarks, which is evaluated by mean absolute error (MAE), and root-mean- square error (RMSE) for training sets (i.e., data sets used for training the model) and external validation sets (i.e., data sets not used for training the model).
开发的 MLFF 的性能。为了研究 在空气-水界面上的吸附和转化，我们基于一系列有元动力学采样 和无元动力学采样 的 AIMD 模拟，对气体、水和界面系统进行了 MLFF 模型训练。我们采用了在许多水相、界面和材料系统中取得成功的主动学习策略来选择用于构建模型的关键 初始数据。 图 1 和表 S4 显示了以 SCAN-D4 级 数据为基准训练的 MLFF 模型的性能，该性能通过训练集（即用于训练模型的数据集）和外部验证集（即未用于训练模型的数据集）的平均绝对误差 (MAE) 和均方根误差 (RMSE) 进行评估。
In general, the trained MLFF model has good performance in energy (Figure 1A), force (Figure 1B), and stress (Figure 1C) predictions for the training (gray), and external validation (blue) sets. It can be seen that the MAE and RMSE values for the training and the external validation sets are immensely close (Table S4), indicating a high generalization ability of the model. The trained model also well reproduced experimental radial distribution functions of in in , and in , which were either determined
总体而言，经过训练的 MLFF 模型在训练集（灰色）和外部验证集（蓝色）的能量（图 1A）、力（图 1B）和应力（图 1C）预测方面表现良好。可以看出，训练集和外部验证集的 MAE 值和 RMSE 值非常接近（表 S4），表明模型具有很高的泛化能力。训练模型还很好地再现了 中 、 中 、 中 的实验径向分布函数。
Figure 3. Gaseous free-energy ( , kcal-mol ) landscapes for initial oxidation of by at (A) - group with (B) corresponding representative snapshots, and at (C) group and (D) corresponding representative snapshots. , and in panels A and C represent approximate locations of the observed separated reactants, reactants, transition states, and products, respectively. The contour lines in panels and are spaced apart. , and in panels and stand for coordinate numbers of the atom in (excluding the original of ), the atoms in , and the atom in , respectively. The white, gray, and red balls in panels and stand for , and atoms, respectively.]
图 3.在 (A) - 组和 (B) 相应的代表性快照，以及在 (C) 组和 (D) 相应的代表性快照中， 被 初始氧化的气体自由能 ( , kcal-mol ) 分布图。面板 A 和 C 中的 和 分别代表观察到的分离反应物、反应物、过渡态和产物的大致位置。面板 和 中的等高线间距为 。面板 和 中的 和 分别代表 中 原子（不包括 中的原始 原子）、 中 原子和 中 原子的 坐标。面板 和 中的白球、灰球和红球分别代表 和 原子]。
experimentally (Figure 1D) or calculated via the AIMD simulations (Figure 1E,F). Hence, the MLFF model can be employed to simulate the behavior of at air-water interfaces.
（图 1D）或通过 AIMD 模拟计算得出的结果（图 1E、F）。因此，MLFF 模型可用于模拟 在空气-水界面上的行为。
Enrichment of on Water Surfaces. Gibbsfree-energy changes for transferring an molecule from the gaseous phase to the interior region of water were computed using the trained MLFF, as shown in Figure . Based on the between the gaseous and aqueous phases, Henry's law constant for was calculated to be (see details in the Supporting Information) and located in a previously determined range to . Due to the hydrophobic nature of the group and hydrogen bonding of the group in the molecule, the minimum of was observed at the interface rather than in the interior region of water or the gaseous phase. The results indicate a notable "surface preference" of , like its dehydration form .
水表面 的富集。如图 所示，使用训练有素的 MLFF 计算了将 分子从气相转移到水内部区域的吉布斯自由能变化 。根据气相和水相之间的 ，计算出 的亨利定律常数 为 （详见《辅助信息》），并位于先前确定的 至 范围内。由于 基团的疏水性和 分子中 基团的氢键作用， 的最小值出现在界面而不是水或气相的内部区域。结果表明， 与其脱水形式 一样，具有明显的 "表面偏好"。
To explore mechanisms for the "surface preference", configurations of at the water surface were further analyzed based on unbiased MLFF-MD simulations. Nine most abundant configurations (with probabilities ) and the corresponding probabilities are shown in panels and of Figure 2, respectively. At , the isolate configuration in Figure 2C) exhibits a quite low probability ( ), indicating that is always -bonded with molecules at the water surface. Most of the observed configurations interact with the surface water molecules via 24 hydrogen bonds. Such multiple favorable interactions between and decrease the tendency of evaporation from water droplets, which resulted in the low indicated in Figure 2A.
为了探索 "表面偏好 "的机制，我们在无偏 MLFF-MD 模拟的基础上进一步分析了 在水面的构型。图 2 的 和 面板分别显示了九种最丰富的构型（概率为 ）和相应的概率。在 处，图 2C 中的分离构型 显示出相当低的概率 ( )，表明 总是 与水面上的 分子结合。观察到的大多数 构型都通过 24 个氢键与表面水分子相互作用。 和 之间的这种多重有利相互作用降低了 从水滴中蒸发的趋势，从而导致图 2A 中所示的低 。
Orientations of the adsorbed were further investigated, which are characterized by a variable ( :
我们进一步研究了吸附的 的取向，其特征是一个变量 ( ：
where and are the angles between the two bonds and the upward normal vector of the water surface (Figures ). For , at least one atom is exposed to the gaseous phase. When , both atoms at the site are submerged in the water. Figure shows that exclusively lies at . Therefore, one atom at the group of the molecule was exposed to the gaseous phase with a very high probability ( ), increasing its vulnerability to be attacked by the reactive atmospheric species (e.g., ). Therefore, heterogeneous transformation of the molecule at the air-water interface becomes important.
其中 和 是两个 键与水面向上法向量的夹角（图 ）。对于 ，至少有一个 原子暴露在气相中。当 时，位于 位点的两个 原子都浸没在水中。图 显示， 完全位于 处。因此， 分子的 基团上的一个 原子极有可能暴露在气相中（ ），从而增加了其受大气中活性物种（如 ）攻击的可能性。因此， 分子在空气-水界面的异质转化变得非常重要。
Rapid Oxidation of by at Air-Water Interfaces. Gaseous oxidation of has been previously found to be a crucial source of atmospheric Here, free-energy landscapes of oxidation by at the water surface were obtained via MLFF-MD simulations coupled with metadynamics samplings, along with the oxidation in the gaseous phase for comparisons.
在空气-水界面被 快速氧化。以前曾发现， 的气态氧化是大气中 的一个重要来源。在此，我们通过 MLFF-MD 模拟和元动力采样，获得了 在水面被 氧化的自由能谱，并与气态氧化进行了比较。
The gaseous reaction of with proceeds via direct atom abstraction at the and groups (Figure ), leading to formation of and . , respectively. Compared with the reaction at the group, the oxidation at the group is more
与 的气态反应通过在 和 基团上直接抽取 原子进行（图 ），从而分别形成 和 。 。与 基团上的反应相比， 基团上的氧化反应更为剧烈。
(B)
(D)
(F)
Figure 4. Interfacial Gibbs-free-energy ( , kcal mol ) landscapes for initial oxidation of by at (A) - group with (B) corresponding representative snapshots, and at ( and ) group with ( and ) corresponding representative snapshots at air-water interfaces. , and in panels and represent approximate locations of the observed separated reactants, reactants, transition states, and products, respectively. The contour lines in panels and are spaced by , and in panels and stand for coordinate numbers of the atom in (excluding the original of ), the atoms in , and the atom in , respectively. The white, gray, and red balls in panels , and stand for , and atoms, respectively.]
图 4.在 (A) - 组中， 被 初始氧化时的界面吉布斯自由能 ( , kcal mol ) 分布图，以及在 ( 和 ) 组中，( 和 ) 的界面吉布斯自由能分布图、和 ( 和 ) 组，以及 ( 和 ) 空气-水界面处的相应代表性快照。面板 和 中的 和 分别代表观察到的分离反应物、反应物、过渡态和产物的大致位置。面板 和 中的等高线间隔为 ，面板 和 中的 代表 中 原子的 坐标数（不包括 的原始 ）、中的 原子，以及 中的 原子。面板 和 中的白球、灰球和红球分别代表 和 原子]。
favorable ( 7.4 vs ). The are also close to those calculated at the aug-cc-pVTZ aug-cc-pVTZ level (Figure S5), suggesting the reliability of the MLFF.
( 7.4 vs )。 也与 aug-cc-pVTZ aug-cc-pVTZ 水平的计算结果接近（图 S5），表明 MLFF 的可靠性。
For the interface systems, was initially placed above the water surface. As the group of the molecule is exposed to the gaseous phase (Figure 2), gaseous . was observed to directly attack the bonds (i.e., the Eley-Rideal mechanism), producing a intermediate (Figure 4A,B). Compared with the gaseous abstraction, this interfacial pathway displays a decrease in ( ).
对于界面系统， 最初被置于水面之上。当 分子中的 基团暴露在气相中时（图 2），气态 .据观察， 直接攻击 键（即 Eley-Rideal 机制），产生 中间体（图 4A、B）。与气态抽取相比，这种界面途径显示出 的减少（ ）。
To further elucidate the decrease in , the hydrogen bonds surrounding the and at the transitionstate regions were analyzed. Figure S6 indicates that the HO complex at the transition-state regions typically acts as a hydrogen-bond acceptor and thus is stabilized by positive electrostatic potential resulting from solvent responses, promoting the atom abstraction. Notably, the hydrogen bonds mostly act on the group rather than the - group, suggesting that a substantial decease in might exist in the -abstraction at the groups.
为了进一步阐明 的减少，我们分析了过渡态区域 和 周围的氢键。图 S6 表明，过渡态区域的 HO 复合物通常充当氢键受体，从而在溶剂反应产生的正静电势作用下保持稳定， 促进了 原子的抽取。值得注意的是，氢键大多作用于 基团而不是 - 基团，这表明 的大量减少可能存在于 - 在 基团上的萃取。
Figure 4C,E displays free-energy landscapes for abstraction at the group. Two independent oxidation pathways were observed via the Eley-Rideal and the Langmuir-Hinshelwood mechanisms, respectively (Figure . For the first one, directly attacks the group that acts as -bond acceptors. Different from the group oxidation, a hydrogen-bond network between and water molecules at the surface can always be observed at the transition-state region, further facilitating the reactions. Benefiting from the stabilization effects due to the -bond networks between , and for the group oxidation via the Eley-Rideal mechanism at the water surface is significantly lower than that in the gaseous phase by . Given that for the oxidation is also lower than that for the oxidation at the interface ( 4.3 vs , Figure ), has more opportunities to abstract atoms at the groups directly, relative to the oxidation at the group.
图 4C,E 显示了 在 基团上抽取的自由能图谱。分别通过 Eley-Rideal 和 Langmuir-Hinshelwood 机制观察到两种独立的氧化途径（图 。在第一种氧化途径中， 直接攻击作为 键受体的 基团。与 基团氧化不同，在过渡态区域总是可以观察到 与表面水分子之间的氢键网络，这进一步促进了反应的进行。得益于 与 之间的氢键网络所产生的稳定效应， 通过 Eley-Rideal 机理在水表面进行的 基团氧化反应的速率明显低于气相中的 。鉴于 氧化作用的 也低于界面上 氧化作用的 （4.3 对 ，图 ），相对于 基团的氧化作用， 有更多机会直接抽取 基团上的 原子。
Quantum chemical calculations were additionally performed to probe the favorable oxidation compared with oxidation by investigating the reaction systems containing only , and (Table 1 and Figure S7). It was found that for the -abstraction at the and sites decreased slightly at the DLPNO-CCSD / aug-cc-pVTZ /aug-cc-pVTZ and M06-2X /aug-cc-pVTZ levels of theory for -containing systems. In the system containing molecules, a substantial decrease in for oxidation wasTable 1. Calculated Gibbs-Free-Energy Barriers
此外，还通过研究仅含有 和 的反应体系（表 1 和图 S7），进行了量子化学计算，以探究 氧化与 氧化相比是否有利。研究发现，在 DLPNO-CCSD / aug-cc-pVTZ /aug-cc-pVTZ 和 M06-2X /aug-cc-pVTZ 理论水平下，含有 的体系的cc-pVTZ 和 M06-2X /aug-cc-pVTZ 。在含有 分子的体系中， 氧化的 大幅下降。计算的吉布斯自由能垒
for H Abstraction of by at the and
为 H 在 处用 抽象 和
-OH Sites for Water Molecules and Air-Water
水分子和空气-水的-OH 位点
Interface Systems Using Trained Machine-Learning Force
使用训练有素的机器学习力的界面系统
Field (MLFF), M06-2X-D3/aug-cc-pVTZ, and DLPNO-
场（MLFF）、M06-2X-D3/aug-cc-pVTZ 和 DLPNO-
CCSD(T)/aug-cc-pVTZ//M06-2X-D3/aug-cc-pVTZ
Methods 方法
Table 1. Calculated Gibbs-Free-Energy Barriers ( ) for Abstraction of by at the - and Sites for 0-4 Water Molecules and Air-Water Interface Systems Using Trained Machine-Learning Force Field (MLFF), M06-2X-D3/aug-cc-pVTZ, and DLPNO /aug-cc-pVTZ//M06-2X-D3/aug-cc-pVTZ Methods
表 1.使用训练机器学习力场（MLFF）计算的 0-4 水分子和空气-水界面系统的 在 - 和 位点被 萃取 的吉布斯自由能垒 ( )、M06-2X-D3/aug-cc-pVTZ 和 DLPNO /aug-cc-pVTZ//M06-2X-D3/aug-cc-pVTZ 方法
systems 系统
 反应场所
reaction
sites
MLFF
M06-2X-
D3/aug-cc-
pVTZ
DLPNO-CCSD(T)/aug-cc-
aug-cc-
7.4 6.9 9.1
10.7 8.3 11.6
7.3 9.5
8.4 11.6
6.8 9.1
8.3 12.4
6.9 9.3
6.5 10.2
5.8 8.5
4.1 8.3
nterface 接口 6.5
4.3 N/A
observed compared with - oxidation, leading to favorable abstraction. The results also suggested that the favorable oxidation required the participation of more water molecules.
与 - 氧化相比，观察到的 氧化有利于 的抽取。结果还表明，有利的 氧化需要更多水分子的参与。
For the Langmuir-Hinshelwood mechanism, initially adsorbs on the water surface and then attacks a surficial molecule that is close to the molecule, leading to formation of a new (Figure 4D). The formed can be continuously transferred on the surface via the ". " reaction, until the formation of an that directly interacts with via a hydrogen bond. The ". transfer" process can involve direct participation of molecules nearby . Once the complex is formed on the surface, the -abstraction at the group of subsequently occurs, resulting in the formation of . . The rate-determining step for this pathway is the ". transfer" with of , which is close to for the oxidation ( ). Different from the group oxidation that requires a direct collision between and , the LangmuirHinshelwood mechanism allows the group oxidation to also begin with a collision between and , which is far more abundant than (Figure 4F). Thus, the two pathways at the groups have shown stronger competitiveness than that at the group.
在朗缪尔-欣舍伍德机理中， 最初吸附在水面上，然后攻击靠近 分子的表面 分子，导致形成新的 （图 4D）。形成的 可以通过". "反应在表面不断转移，直至形成 ，通过氢键与 直接相互作用。在"。 转移 "过程中， 分子可能会直接参与附近的 。一旦 复合物在表面上形成， - 在 的 基团上的萃取就会随之发生，从而形成 . 。这一途径的速率决定步骤是 的 的". 转移"，它接近于 氧化 ( ) 的 。与 基团氧化需要 和 之间的直接碰撞不同，Langmuir-Hinshelwood 机制允许 基团氧化也从 和 之间的碰撞开始，而 的含量远远高于 （图 4F）。因此， 基团上的两种途径比 基团上的途径显示出更强的竞争性。
Subsequent Reactions. Several subsequent elementary reactions were also observed in the MLFF-MD simulations and quantum chemical calculations. For the formed , three subsequent pathways have been identified, including isomerization to (Figure S8), dissociation of an (Figure S9), and bimolecular reaction with to produce (Figure S10). Among the considered three pathways, the bimolecular reaction with (eq 2) is the most favorable. Based on the calculated the pseudo-first-order rate constant (details in the Supporting Information) of with was estimated to be (assuming atmospheric concentration, i.e., molecules. ), which is much higher than the pseudo-first-order rate constant of oxidation assuming molecules of gaseous-phase concentration ).
后续反应。在 MLFF-MD 模拟和量子化学计算中还观察到了几个后续基本反应。对于形成的 ，确定了三种后续途径，包括异构化为 （图 S8）、解离出 （图 S9）以及与 发生双分子反应生成 （图 S10）。在所考虑的三种途径中，与 的双分子反应（式 2）最为有利。根据计算得出的 ，估计 与 的伪一阶速率常数（详见佐证资料）为 （假定 浓度为大气浓度，即 分子。 ），远高于假定气相 浓度为 的 分子 氧化 的伪一阶速率常数 。）
Similar to the , a previous study found that bimolecular reaction with , forming (eq 3), is also most favorable for formed and is even barrierless. Therefore, the initial and oxidations are the rate-determining step for the formation of from the oxidation of .
与 类似，先前的研究发现，与 发生双分子反应，形成 （式 3），也最有利于形成 ，甚至是无障碍的。<因此，最初的 和 氧化是 氧化形成 的速率决定步骤。
Implications. Given the "surface preference" and rapid transformation of at the air-water interface, heterogeneous oxidation of by may also be a source of atmospheric organic acids that play important roles in atmospheric chemistry. To primarily evaluate the contribution of the interfacial oxidation to atmospheric budget, a contribution ratio between interfacial and gaseous oxidation was introduced:
影响。鉴于 在空气-水界面的 "表面偏好 "和快速转化， 被 异相氧化也可能是大气有机酸的来源之一，这些有机酸在大气化学中发挥着重要作用。为了主要评估界面氧化对大气 预算的贡献，引入了界面氧化和气体氧化之间的贡献比 ：
where and are reaction rate coefficients of oxidized by at the air-water interface and in the gaseous phase (Table S5), respectively; stands for the surface area of water in a unit volume of air , where and are surface areas and volume of air, respectively) and is under typical cloud conditions; represents the thickness of water surface and equals and represent concentrations of in the gaseous phase and at the air-water interface, respectively; and represent concentrations of in the gaseous phase and at the air-water interface, respectively
其中 和 分别是 在空气-水界面和气相中被 氧化的反应速率系数（表 S5）； 代表单位体积空气中水的表面积 ，其中 和 分别为表面积和空气体积），在典型云条件下为 ； 表示水面厚度，等于 和 分别表示气相中和空气-水界面上 的浓度； 和 分别表示气相中和空气-水界面上 的浓度
As times required for ) and ( ns estimated based on the two-film theory ) to reach thermal equilibrium are significantly shorter than the lifetime of cloud-droplet (dozens of seconds ), the adsorption processes of and are mostly thermodynamically controlled. Thus, eq 4 can be deduced as
由于 ) 和 ( ns 根据双膜理论 估计 ) 达到热平衡所需的时间大大短于云滴的寿命（几十秒 ），因此 和 的吸附过程主要受热力学控制。因此，公式 4 可以推导为
where is and stand for equilibrium constants of and at the airwater interface, respectively; is the temperature (ca. ) and , Figure ) are the adsorption free-energy of and , respectively.
其中， 为 ， 分别代表 和 在空气-水界面的平衡常数； 为温度 （约为 ）和 ，图中 ）分别为 和 的吸附自由能。
At ca. was calculated to be , indicating that the interfacial oxidation produces 50 -times faster than in the gaseous-phase oxidation in a unit volume of cloud air. It is noted that a previous study found that the photolysis (finally forming and ) and oxidation by are the main sinks of atmospheric and they have comparable contributions for the removal of When the newly revealed pathway at air-water interfaces is considered, the contribution of the oxidation should be increased greatly and the oxidation would play a dominant role in the removal of in moist atmospheres, due to the high value. This definitely improves the yield of for the transformation. Precise evaluation on the contribution of oxidation to the removal of needs a box model simulation, which deserves future investigations. In addition, identifications of possible intermediates (e.g., ) involved in the and . reactions at air-water interfaces via advanced mass and optical spectra might be performed to verify the revealed mechanism in the future.
在约计算得出 为 ，表明在单位体积的云气中，界面氧化产生的 比气相氧化快 50 倍。值得注意的是，先前的一项研究发现，光解（最终形成 和 ）和 氧化是大气 的主要吸收汇，它们对 的清除具有相当的贡献、在潮湿的大气中，由于 值较高，氧化作用的贡献应该会大大增加，而且氧化作用将在去除 的过程中发挥主导作用。这无疑会提高 转化过程中 的产量。要精确评估氧化作用对 的去除所起的作用，需要进行箱式模型模拟，这值得在今后进行研究。此外，还需要确定参与 和 . 反应的可能中间产物（如 ），以验证所揭示的机理。
The proposed water-promoted mechanism could be extended to the oxidation of other alcohols. According to eq 5 , the contribution of the interfacial oxidation for the removal of alcohols will highly depend on by simply taking the and as the case for the system. The interfacial oxidations for the alcohols with adsorption-free energies (e.g., alcohols with , and group) should be important, contributing to the formation of organic acids. Hence, the proposed water-promoted mecha- nism could be a nonnegligible source of organic acids and in turn influences the formation of aerosol particles and the value of waters and soils.
所提出的水促进机理可扩展到其他醇类的氧化。根据公式 5，通过简单地将 和 视为 系统的情况，界面氧化对醇类去除的贡献将在很大程度上取决于 。具有无吸附能的醇类（例如具有 和 基团的醇类）的界面氧化作用应该很重要，有助于有机酸的形成。因此，拟议的水促进机制可能是有机酸的一个不可忽视的来源，进而影响气溶胶粒子的形成以及水和土壤的 值。
In addition, oxidation of the alcohols to produce corresponding carbonyl and carboxyl compounds is also important in modern organic synthesis. 55,56 Water commonly serves as a solvent for many alcohols that have high water solubilities. It may also be helpful to design new synthesis routes of target compounds to take advantage of the "surface preference" and rapid group oxidation of alcohols at the water surfaces.
此外，醇类氧化生成相应的羰基和羧基化合物在现代有机合成中也很重要。55,56 水通常是许多高水溶性醇类的溶剂。 利用醇在水表面的 "表面偏好 "和快速 基团氧化作用，设计目标化合物的新合成路线可能也会有所帮助。

CONCLUSIONS 结 论

This study unveils, for the first time, the preferential adsorption of at water surfaces via hydrogen bonds, with one atom at the group of the molecule exposed to the gaseous phase. This finding is counterintuitive to the usual expectation that atmospheric does not prefer to attack the exposed atom but the groups that form hydrogen bonds with water molecules at the surfaces via a water-promoted mechanism. The mechanism significantly facilitates the formation of with the activation-freeenergy barrier lowered from in the gaseous phase to on the water surfaces. Overall, the molecular-level insights gained from the study demonstrate that the oxidation of as well as other alcohols at the air-water interfaces plays a greater than expected role in organic acid formation in the environment.
这项研究首次揭示了 通过 氢键优先吸附于水表面，其中一个 原子位于暴露于气相中的 分子的 基团上。大气中的 并不喜欢攻击暴露在外的 原子，而是喜欢攻击通过水促进机制在表面与水分子形成氢键的 基团，这一发现与通常的预期相反。该机制大大促进了 的形成，无活化能势垒从气相中的 降低到了水表面的 。总之，从这项研究中获得的分子层面的见解表明， 以及其他醇类在空气-水界面上的氧化作用在环境中有机酸的形成中所起的作用比预期的要大。

ASSOCIATED CONTENT 相关内容

(s) Supporting Information
(s) 佐证资料

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/jacs.2c13661.
辅助信息可从 https://pubs.acs.org/doi/10.1021/jacs.2c13661 免费获取。
Additional computational methods, simulated systems, standard deviation, gaseous-phase Gibbs free energy barriers for the reactions of , the average number of hydrogen bonds, Gibbs free energy barriers for the reactions of "HOCH systems, to isomerization, dissociation of reaction, major hyperparameters, six systems for sampling initio points, detailed parameters for metadynamics samplings, performances of trained MLFF, estimated reaction rate coefficients, and Cartesian coordinates and corresponding energies (PDF)
其他计算方法、模拟系统、标准偏差、 反应的气相吉布斯自由能垒、氢键平均数量、"HOCH 系统、 到 异构化 "反应的吉布斯自由能垒、 反应的解离、主要超参数、用于 初始点采样的六个系统、元动力采样的详细参数、训练有素的 MLFF 的性能、估计的反应速率系数以及笛卡尔坐标和相应的能量 (PDF)

AUTHOR INFORMATION 作者信息

Corresponding Authors 通讯作者

Hong-Bin Xie - Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), Dalian Key Laboratory on Chemicals Risk Control and Pollution Prevention Technology, School of Environmental Science and Technology, Dalian University of Technology, Dalian 116024, China; ๑ orcid.org/0000-0002-9119-9785; Email: hbxie@ dlut.edu.cn
谢宏斌 - 大连理工大学环境科学与技术学院工业生态与环境工程教育部重点实验室、大连市化学品风险控制与污染防治技术重点实验室，大连 116024；๑ orcid.org/0000-0002-9119-9785；电子邮件：hbxie@ dlut.edu.cn
Joseph S. Francisco - Department of Earth and Environmental Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104-6316, United States; ๑ orcid.org/0000-0002-5461-1486; Email: frjoseph@ sas.upenn.edu

Authors 作者

Deming Xia - Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), Dalian Key Laboratory on Chemicals Risk Control and Pollution Prevention Technology, School of Environmental Science and Technology, Dalian University of Technology, Dalian 116024, China
Deming Xia - 大连理工大学环境科学与技术学院工业生态与环境工程（教育部）重点实验室、大连市化学品风险控制与污染防治技术重点实验室，大连 116024
Jingwen Chen - Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), Dalian Key Laboratory on Chemicals Risk Control and Pollution Prevention Technology, School of Environmental Science and Technology, Dalian University of Technology, Dalian 116024, China; orcid.org/0000-0002-5756-3336
Jingwen Chen - 大连理工大学环境科学与技术学院工业生态与环境工程（教育部）重点实验室、大连市化学品风险控制与污染防治技术重点实验室，大连 116024；orcid.org/0000-0002-5756-3336
Jie Zhong - School of Petroleum Engineering and School of Materials Science and Engineering, China University of Petroleum (East China), Qingdao 266580 Shandong, China
钟杰 - 中国石油大学（华东）石油工程学院、材料科学与工程学院，山东青岛 266580
Complete contact information is available at:
完整联系信息请访问

Notes 说明

The authors declare no competing financial interest.
作者声明不存在任何经济利益冲突。

- ACKNOWLEDGMENTS - 致谢

This study was supported by the National Natural Science Foundation of China (22136001, 22206019, and 22176022), the China National Post-Doctoral Program for Innovative Talents (BX20220050), the Supercomputing Center of Dalian University of Technology, and the Sugon Supercomputing Center. D.X. acknowledges Qi Jiang and Lihao Su from Dalian University of Technology and Tong Xu from Hebei University of Science and Technology for useful discussions.
本研究得到了国家自然科学基金（22136001、22206019 和 22176022）、国家博士后创新人才计划（BX20220050）、大连理工大学超级计算中心和曙光超算中心的资助。D.X.感谢大连理工大学的姜琦、苏立浩和河北科技大学的徐彤提供的有益讨论。

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  1. Received: December 22, 2022
    收到：2022 年 12 月 22 日
    Published: February 16, 2023
    出版日期2023 年 2 月 16 日