Complex Reaction Mechanisms Research Articles

3D Kinetics, an Upgrade to the Classical Michaelis‐Menten Method

Most of the kinetic data published nowadays are derived from different extensions of what Michaelis and Menten introduced to this field more than hundred years ago. The key assumption to Michaelis‐Menten kinetics is the steady state approximation where the change in the concentration of any enzyme‐substrate intermediate complex is assumed to be zero. This assumption has two underlying requirements with the first one being [S]≫[E] and the second being the limitation of the reaction time to the short initial linear region of the progress curve. The historical need for the steady state assumption was to simplify data treatment to such a degree that the analytical mathematics could be done without need for an abundance of computing power. However, with the computation power at our disposal today, none of the limiting assumptions are necessary anymore especially considering that many of these assumptions rarely hold true. The time course of aldehyde oxidase with one of it substrates, O6‐benzylguanine, is provided here as an example of the statement above. In addition to the obvious instant curvature in the time course plot which makes it difficult to identify the precise linear region, the simulation done on the ES complex based on the data further proves how the steady state approximation is a poor assumption to make especially during the shorter “linear” region of the progress curve as this region is the one in which the concentration of ES is changing the most (Figure 1). The easiest way to approach kinetic data today is to parameterize realistically complex kinetic reaction mechanisms through 3D kinetics. 3D numerical modeling uses the data derived from experiments that monitor the product formation as a function of both incubation time and substrate concentration. With this approach, scientists would be able to derive both the traditional Km and Vmax values as well as the micro‐rate constants related to each step of the enzymatic reaction (Figure 2).Support or Funding InformationThis work was supported by the National Institutes of Health grant: GM100874A‐1) Numerical fitting of product formation with two different models (A‐2 and A‐3) shows that Michaelis Menten (dashed line) does not fit the data well over longer period of time. B) Simulation of the ES complex through the A‐3 model shows a significant change in this species’s concentration over the initial period of the time course where it is assumed to be a constant in deriving the Michaelis‐Menten equation.Figure 1A) Numerical fitting of the product formation over time of different initial substrate concentrations with the kinetic model provided on the right side of the graph to solve for the micro‐rate constants k3‐k5. B) Classical kinetic parameters such as Km and Vmax can be obtained from the same data set by plotting the rate versus substrate concentration for each time point.Figure 2

Mechanisms of Advanced Oxidation Processes, the Principle of Detailed Balancing, and Specifics of the UV/Chloramine Process.

Advanced oxidation processes tend to have very complex reaction mechanisms, and models containing over 150 steps have been developed to describe the chemistry. Without the aid of automation, it is extremely difficult to avoid the development of kinetic mechanisms that violate the principle of detailed balancing. Here, we apply DETBAL, a computer application, to systematically identify many violations of the principle of detailed balancing in a model proposed for the UV/chloramine process. We then show that these violations can also be found in dozens of other proposed models for advanced oxidation processes. Suggested repairs to these violations are provided. These repairs lead to no significant changes in the model predictions because the illegal loops include steps that are unnecessary under the conditions modeled. The model omits certain steps that do have significant effects on the model predictions.

Continuous electrooxidation of Methylene Blue in filter press electrochemical flowcell: CFD simulation and RTD validation

Methylene blue (MB) removal by means of a filter press electrochemical flowcell operating in recycle mode, equipped with graphite electrodes was surveyed. Hydrodynamics and mass transport inside flowcell were evaluated by Computational Fluid Dynamics (CFD) simulations and validated by experimental Residence Time Distribution (RTD) technique. Good agreement was observed between experimental data and simulated MB decay. Increasing flowrate from 0.31 to 0.51 L min−1 increased MB decay by 9% validating assumption of mass transfer controlled reaction at the anode. Increasing wastewater pH level from 3 to 9, significantly decreased MB decolorization by 20 %, which is attributed to complex reaction mechanism. Increasing applied electrical voltage from 3 to 7 V led to marginal change in MB concentration decay. By increasing initial MB concentration from 2 to 10 ppm, 5% decrease in MB decolorization was observed. Electrooxidation of 0.5 L synthetic wastewater under optimum operation conditions during 5 h (flowrate of 0.53 L min−1, pH = 3, 5 V applied voltage) led to MB concentration decay of 0.041, 0.059, and 0.08 for initial MB concentration of 2, 5, and 10 ppm, respectively. Results of current study in pre-pilot scale provide valuable information for large scale studies in the field of wastewater treatment.

ТРИКОМПОНЕНТНІ РЕАКЦІЇ НЕНАСИЧЕНИХ СПОЛУК З СОЛЯМИ АРЕНДІАЗОНІЮ І НЕЙТРАЛЬНИМИ НУКЛЕОФІЛАМИ. АРИЛСУЛЬФОНІЛЮВАННЯ

The results of recent achievements on the interaction of arenediazonium salts with unsaturated compounds in the presence of neutral nucleophiles are summarized. New examples of multicomponent transformations with the participation of such neutral nucleophiles as CO (arylcarbonylation), NO (arylnitrosylation), aceto¬nitrile (aminoarylation), SO2 (arylsulfonylation) and others are given. These reactions can be applied to alkenes, alkynes, aromatic compounds. Mild reaction conditions allow the use of reagents with different functional groups. Reactions of this type open up the possibility of one-step production of complex poly¬functional compounds. Catalytic systems are quite diverse for these transformations: it is catalysis involving transition metals, platinum group metals. Prospects for the use of arenediazonium salts in multicomponent transfor¬ma-tions according to the concepts of «green» chemistry are outlined – it is photoinitiation by visible and ultraviolet radiation, acid-base catalysis. The role of catalysis in the process, the role of complex intermediates and reaction mechanisms are analyzed. For most processes, the SET reaction mechanism is implemented through the formation of an alkene intermediate ion radical, the stability of which depends on the nature of the substituent near the double bond. Particular attention is paid to arylsulfonylation reactions, because the arylsulfonyl group is one of the many important biologically active molecules. Arylsulfonylation reactions of alkenes with the participation of transition metals or under conditions of metal-free catalysis are considered. Examples of arylsulfonylation of the C=C bond using sulfinic acids, their salts and hydrazides are given. An available method for producing functionalized sulfones is the multicomponent interaction of arenediazonium salts, alkenes and SO2. The arylsulfonylation reaction occurs as a series of successive reactions involving the generation of a catalyst, the decomposition of arenediazonium cations, the addition of an aryl group, a nucleophile to a multiple bond, and the formation of the final products. The use of functionalized alkenes allows to obtain functionalized arylsulfones in one step. This functionalization expands the scope of use of arylsulfones, in particular, for studies of biological activity. The progress made in the development of effective strategies for the production of arylsulfones opens new opportunities for further research.

Heavier Alkaline-Earth Catalyzed Dehydrocoupling of Silanes and Alcohols for the Synthesis of Metallo-Polysilylethers.

The dehydrocoupling of silanes and alcohols mediated by heavier alkaline-earth catalysts, [Ae{N(SiMe3 )2 }2 ⋅(THF)2 ] (I-III) and [Ae{CH(SiMe3 )2 }2 ⋅(THF)2 ], (IV-VI) (Ae=Ca, Sr, Ba) is described. Primary, secondary, and tertiary alcohols were coupled to phenylsilane or diphenylsilane, whereas tertiary silanes are less tolerant towards bulky substrates. Some control over reaction selectivity towards mono-, di-, or tri-substituted silylether products was achieved through alteration of reaction stoichiometry, conditions, and catalyst. The ferrocenyl silylether, FeCp(C5 H4 SiPh(OBn)2 ) (2), was prepared and fully characterized from the ferrocenylsilane, FeCp(C5 H4 SiPhH2 ) (1), and benzyl alcohol using barium catalysis. Stoichiometric experiments suggested a reaction manifold involving the formation of Ae-alkoxide and hydride species, and a series of dimeric Ae-alkoxides [(Ph3 CO)Ae(μ2 -OCPh3 )Ae(THF)] (3 a-c, Ae=Ca, Sr, Ba) were isolated and fully characterized. Mechanistic experiments suggested a complex reaction mechanism involving dimeric or polynuclear active species, whose kinetics are highly dependent on variables such as the identity and concentration of the precatalyst, silane, and alcohol. Turnover frequencies increase on descending Group 2 of the periodic table, with the barium precatalyst III displaying an apparent first-order dependence in both silane and alcohol, and an optimum catalyst loading of 3 mol % Ba, above which activity decreases. With precatalyst III in THF, ferrocene-containing poly- and oligosilylethers with ferrocene pendent to- (P1-P4) or as a constituent (P5, P6) of the main polymer chain were prepared from 1 or Fe(C5 H4 SiPhH2 )2 (4) with diols 1,4-(HOCH2 )2 -(C6 H4 ) and 1,4-(CH(CH3 )OH)2 -(C6 H4 ), respectively. The resultant materials were characterized by NMR spectroscopy, gel permeation chromatography (GPC) and DOSY NMR spectroscopy, with estimated molecular weights in excess of 20,000 Da for P1 and P4. The iron centers display reversible redox behavior and thermal analysis showed P1 and P5 to be promising precursors to magnetic ceramic materials.

Electrotunable liquid sulfur\xa0microdroplets

Manipulating liquids with tunable shape and optical functionalities in real time is important for electroactive flow devices and optoelectronic devices, but remains a great challenge. Here, we demonstrate electrotunable liquid sulfur microdroplets in an electrochemical cell. We observe electrowetting and merging of sulfur droplets under different potentiostatic conditions, and successfully control these processes via selective design of sulfiphilic/sulfiphobic substrates. Moreover, we employ the electrowetting phenomena to create a microlens based on the liquid sulfur microdroplets and tune its characteristics in real time through changing the shape of the liquid microdroplets in a fast, repeatable, and controlled manner. These studies demonstrate a powerful in situ optical battery platform for unraveling the complex reaction mechanism of sulfur chemistries and for exploring the rich material properties of the liquid sulfur, which shed light on the applications of liquid sulfur droplets in devices such as microlenses, and potentially other electrotunable and optoelectronic devices.

Assessment of critical materials and cell design factors for high performance lithium-sulfur batteries using machine learning

In lithium-sulfur (Li-S) batteries, as a consequence of the highly complex reaction and degradation mechanisms, materials and cell design have a critical impact on the performance. Subsequently, Li-S batteries receive significant research attention. In this report, a comprehensive analysis on the effect of key factors on the battery performance, namely the peak discharge capacity and the cycle life, is conducted using machine learning. Data for 1660 cells from 353 papers in the literature are collected and analyzed via association rule mining. The analysis concludes that encapsulation material type and amount are critical for high capacities and enhanced cycle life. The use of structured carbons such as porous carbons or carbon nanotubes in encapsulated cathodes leads to superior battery performance. Likewise, electrolyte design has a key influence on the battery performance, particularly in electrolyte starved cells. The results confirm that the most promising pathway forward in Li-S batteries is materials design, predominantly design of encapsulation cathodes and electrolytes that succeed at low electrolyte-to-sulfur ratios and high sulfur loadings.

НОВЫЙ МЕТОД ИДЕНТИФИКАЦИИ МОДЕЛЕЙ СЛОЖНЫХ ХИМИЧЕСКИХ РЕАКЦИЙ

To study the mechanisms of complex chemical reactions and determine their kinetic parameters, the article proposes a method for reduction of optimization parameters. Using the proposed method, the parametric identification of a complex chemical reaction is considered: a set of kinetic constants is found that describes the experimental curves of the concentration-time dependence within this reaction model in the best way. The practical application of the method is illustrated by solving problems of parametric identification of complex chemical reactions using Mathcad. The proposed algorithm can be easily implemented using both traditional and free software.

Optimal Control of Iron-Removal Systems Based on Off-Policy Reinforcement Learning

The goethite iron-removal process is an important procedure to remove the iron ions from the zinc hydrometallurgy. However, as a coherent system with complex reaction mechanism, associated uncertainties, and interconnected adjacent reactors, it is difficult for the process to accurately control the ion concentration. Because a large amount of historical data can be obtained during the process, an optimal control algorithm based on off-policy reinforcement learning is proposed in this paper to overcome these difficulties. According to the historical data, the weights of neural network are learned offline, and the optimal control strategy is solved online. Firstly, a bounded function is introduced to define the maximum effect of the coherent system on the subsystem cost function and to extend the cost function of the nominal system, so that the decentralized guaranteed cost control problem can be expressed as the optimal control problem of the nominal system. Then, an approximate iterative control algorithm based on actor-critic structure is proposed. The actor and critic neural networks are used to approximate control strategies and cost functions respectively. To achieve complete off-line, a new neural network is added to the actor-critic structure to approximate a part of the unknown system structure, and the three neural network parameters are optimized by the state transition algorithm. Finally, the strategy update and strategy iteration operations are performed alternately to learn optimal control strategies. The effectiveness and flexibility of the proposed off-policy optimal control method is validated by data from a real industrial goethite iron-removal process.

Low-temperature oxidation reactions of crude oils using TGA–DSC techniques

In this research, combustion behaviour of three crude oils with different °API gravities was analysed. The thermogravimetric analyser (TGA) and differential scanning calorimeter (DSC) experiments were performed using three different heating rates (2, 5, and 10 °C min−1) under air atmosphere. The reaction regions, burn-out temperatures, and peak temperatures were determined accordingly. Two main reaction regions, particularly the low-temperature oxidation (LTO) and high-temperature oxidation (HTO) reactions, were figured out in TGA and DSC curves, which suggested exothermic behaviour. Kinetic parameters of the crude oils were determined using model free methods (Ozawa–Flynn–Wall, OFW, and Kissinger–Akahira–Sunose, KAS), which allows the calculation of kinetic properties at progressive conversion degrees without the requirement of any reaction models and f(α) estimations. The variation in activation energy with respect to the conversion degree pointed out that the LTO reaction stage can be subdivided into three subzones. The results indicated that the activation energies were changing depending on the conversion degree, which is an indication of complex reaction mechanisms. The change in activation energy with respect to conversion degree showed slight variation for heavy crude oil compared with that in light crude oil.

Activation energy characteristics of chemically reacting species in multi-route complex reaction mechanism

The multi-route reversible inhomogeneous chemical reaction involving seven chemical species is deliberated. To inspect the behavior of the common species, their activation energy and transition period have been measured before attaining equilibrium. It has been observed that some reaction routes complete their cycle before the others. The reason behind their completion is related to the species time period that remained involved in the reaction. Steady state behavior of chemical species is perceived. Graphical results are used to describe the physical aspects of measurements, while the difference is comparable in the tabulated form. The procedure is adopted by using MATLAB.

Quasi-DNS Dataset of a Piloted Flame with Inhomogeneous Inlet Conditions

A quasi-DNS of the partially premixed turbulent Sydney flame in configuration FJ200-5GP-Lr75-57 has been conducted using detailed molecular diffusion for multi-component mixtures and complex reaction mechanisms. In order to study flame dynamics like regime transition in this flame for the development of new combustion models and to directly compare the quasi-DNS to different LES models, the simulation results are compiled into a data base. Because the simulation was performed with OpenFOAM, we demonstrate the quasi-DNS capabilities of OpenFOAM by performing canonical test cases. They attest that OpenFOAM’s cubic discretization has lower numerical diffusion compared to classical central difference schemes and can reach higher than second order convergence rate in some cases. The quasi-DNS of the Sydney flame is conducted with a self-developed reacting flow solver which is able to accurately compute molecular diffusion coefficients from kinetic gas theory and employs a fast implementation for detailed reaction mechanisms. The computational mesh is shown to be able to resolve the flow as well as the flame front sufficiently for the quasi-DNS. Comparisons with experimental data also show that the simulation can quantitatively reproduce measured time-mean and time-RMS statistics.

Graph-Theoretic Interpretation of Inverse Problems of Chemical Kinetics

The subject of this study is the inverse problems of identifying the mechanisms of complex chemical reactions. A graph-theoretic method for determining the basis of the parametric functions of the kinetic parameters of mathematical models for complex catalytic reactions is proposed. Based on the developed algorithm, a program for analyzing the information content of a mathematical model of the mechanism of catalytic reactions has been implemented. The operation of the algorithm is illustrated by the reaction of isotopic exchange of protium for deuterium.

Large‐Scale Quasi‐DNS of Mixed‐Mode Turbulent Combustion

AbstractIn many applications like gas turbines, the combustion process can take place in partially‐premixed environments, where fuel and oxidizer are not fully mixed before combustion. These partially‐premixed or mixed‐mode flames have become a focus of combustion research in the last few years. In this work, a quasi‐DNS of an experimentally measured burner configuration has been conducted. The simulation employs a complex reaction mechanism and detailed molecular diffusion coefficients for each chemical species. Due to the highly resolved numerical grids and the detailed thermo‐physical and chemical properties, the simulation results allow to characterize the flame with the help of flame markers in greater detail than the experiments can provide. The investigated flame exhibits characteristics of a premixed flame near the nozzle. Further downstream both premixed and non‐premixed combustion modes become equally important in terms of the heat release rate. The dataset from the simulation also allows to form joint probability density functions of commonly used control variables to study their correlations depending on the combustion regime.

Combined Experimental and Theoretical Studies of the O(3P) + 1-Butene Reaction Dynamics: Primary Products, Branching Fractions, and Role of Intersystem Crossing.

Information on the detailed mechanism and dynamics (primary products, branching fractions (BFs), and channel specific rate constants as a function of temperature) for many important combustion reactions of O(3P) with unsaturated hydrocarbons is still lacking. We report synergistic experimental/theoretical studies on the mechanism and dynamics of the O(3P) + 1-C4H8 (1-butene) reaction by combining crossed molecular beam (CMB) experiments with soft electron ionization mass-spectrometric detection and time-of-flight analysis at 10.5 kcal/mol collision energy (Ec) to high-level ab initio electronic structure calculations of the underlying triplet and singlet potential energy surfaces (PESs) and statistical Rice-Ramsperger-Kassel-Marcus/Master Equation (RRKM/ME) computations of BFs including intersystem crossing (ISC). The reactive interaction of O(3P) with 1-butene is found to mainly break apart the 4-carbon atom chain, leading to the radical product channels ethyl + vinoxy (BF = 0.34 ± 0.11), methyl + C3H5O (BF = 0.28 ± 0.09), formyl + propyl (BF = 0.17 ± 0.05), ethyl + acetyl (BF = 0.014 ± 0.007), and butanal radical (ethylvinoxy) + H (BF = 0.013 ± 0.004), and molecular product channels formaldehyde + propenylidene/propene (BF = 0.15 ± 0.05) and butenone (ethyl ketene) + H2 (BF = 0.037 ± 0.015). As some of these products can only be formed via ISC from triplet to singlet PESs, from BFs an extent of ISC of 50% is inferred. This value is significantly larger than that recently observed for O(3P) + propene (22%) at similar Ec, underlying the question of how important it is to consider nonadiabatic effects for these and similar combustion reactions. Comparison of the derived BFs with those of statistical (RRKM/ME) simulations on the ab initio coupled triplet/singlet PESs shows good agreement, warranting the use of the RRKM/ME approach to provide information on the variation of BFs with temperature and to derive channel specific rate constants as a function of temperature (T) and pressure (p). Notably, ISC is predicted to decrease strongly with increasing temperature (from about 70% at 300 K to 46% at Ec = 10.5 kcal/mol, and about 1% at 2000 K). The present results lead to a detailed understanding of the complex reaction mechanism of O(3P) + 1-butene and, by providing channel specific rate constants as a function of T and p, should facilitate the improvement of current fossil-fuel (1-butene) as well as biofuel (1-butanol) combustion models.

Comparative study on the effects of meteorological and pollutant parameters on ANN modelling for prediction of SO2

Variations in meteorological parameters, different transportation mechanisms, complex reaction mechanisms and insufficient control measures have made control of ambient air pollution, a challenge. Prediction mechanisms for pollutant concentrations in advance have become necessary to regulate parameters within the acceptable limits. Artificial neural network (ANN) modelling can be used for predicting the concentrations of pollutants by establishing functional relationships between complex and nonlinear predictor variables and outputs. The application of time-series ANN models to predict air quality parameters was investigated by using six pollutant variables, five meteorological parameters and three time parameters to predict the concentration of SO2. An industrial belt in the southern part of India was selected as the study area. Two years of input parameters and feed-forward back propagation algorithm were used to construct the ANN model. Input parameters were optimized using forward selection and backward elimination techniques. Mean squared error and coefficient of determination were used to evaluate the models. The developed model exhibited very promising performance evaluation characteristics with the best model resulting in MSE of 0.0115 and R2 value of 0.8979. The hybrid ANN models employing input parameter optimization techniques resulted in better performance characteristic values than conventional models. Any model exhibited a minimum reduction in MSE by 9% and 3% improvement in correlation. Pollutant parameters were found to affect the ANN models when compared to the meteorological parameters. Predicted values compared to the National Ambient Air Quality Standards were as low as 55% of the maximum allowable concentration in ambient air.

Quantum chemical study on ·Cl-initiated degradation of ethyl vinyl ether in atmosphere

ABSTRACT A theoretical investigation on oxidation reaction of ethyl vinyl ether (EVE) and .Cl are carried out in this paper. By employing M06-2x/6-31 + g(d,p)//6-311++g(3df,2p) method, complex reaction mechanisms are assumed on the basis of thermodynamic data. All the .Cl-addition reactions are dominant channels. The corresponding major products, such as ethyl formate, acetaldehyde and several chloro compounds, are generated from .Cl-addition to double bond of EVE. These products play an important role in the formation of secondary organic aerosol. By employing MESMER grogram, rate coefficients of the primary reactions are computed in the temperature range of 200–400 K and the pressure range of 500–2000 Torr. Combined with the kinetic data and temperature, an Arrhenius equation is fitted as k EVE+Cl = 1.54 × 10−10 exp (121.9/T). Also, the rate constant at 298 K and 760 Torr is calculated to be 2.17 × 10−10 cm3 molecule−1 s−1. Furthermore, the atmospheric lifetime of EVE with respect to .Cl is estimated to be 4.3–11.9 h in different regions. The short lifetime indicates that ·Cl-initiated oxidation is competitive in the degradation of EVE in some special areas. This work could confirm the experimental investigation and serve as the supplement of our previous theoretical studies.

In-Situ Infrared Spectroscopy Applied to the Study of the Electrocatalytic Reduction of CO2 : Theory, Practice and Challenges.

The field of electrochemical CO2 conversion is undergoing significant growth in terms of the number of publications and worldwide research groups involved. Despite improvements of the catalytic performance, the complex reaction mechanisms and solution chemistry of CO2 have resulted in a considerable amount of discrepancies between theoretical and experimental studies. A clear identification of the reaction mechanism and the catalytic sites are of key importance in order to allow for a qualitative breakthrough and, from an experimental perspective, calls for the use of in-situ or operando spectroscopic techniques. In-situ infrared spectroscopy can provide information on the nature of intermediate species and products in real time and, in some cases, with relatively high time resolution. In this contribution, we review key theoretical aspects of infrared reflection spectroscopy, followed by considerations of practical implementation. Finally, recent applications to the electrocatalytic reduction of CO2 are reviewed, including challenges associated with the detection of reaction intermediates.

A Plasmonic Approach to Study Protein Interaction Kinetics through the Dimerization of Functionalized Ag Nanoparticles

Understanding the kinetics of protein interactions plays a key role in biology with significant implications for the design of analytical methods for disease monitoring and diagnosis in medical care, research and industrial applications. Herein, we introduce a novel plasmonic approach to study the binding kinetics of protein-ligand interactions following the formation of silver nanoparticles (Ag NPs) dimers by UV-Vis spectroscopy that can be used as probes for antigen detection and quantification. To illustrate and test the method, the kinetics of the prototype biotin-streptavidin (Biot-STV) pair interaction was studied. Controlled aggregates (dimers) of STV functionalized Ag NPs were produced by adding stoichiometric quantities of gliadin-specific biotinylated antibodies (IgG-Biot). The dimerization kinetics was studied in a systematic way as a function of Ag NPs size and at different concentrations of IgG-Biot. The kinetics data have shown to be consistent with a complex reaction mechanism in which only the Ag NPs attached to the IgG-Biot located in a specific STV site are able to form dimers. These results help in elucidating a complex reaction mechanism involved in the dimerization kinetics of functionalized Ag NPs, which can serve as probes in surface plasmon resonance-based bioassays for the detection and quantification of different biomarkers or analytes of interest.

Electrochemistry as a Tool for Studies of Complex Reaction Mechanisms: The Case of the Atmospheric Aqueous-Phase Aging of Catechols.

The ultimate goal in the understanding of complex chemical processes is a complete description of the underlying reaction mechanism. In the present study and for this purpose, a novel experimental platform is introduced that builds upon electrochemistry capable of generating reactive intermediate species at the electrode surface. The atmospherically relevant nitration of catechols is taken as a case example. First, we confirm the recently proposed nitration mechanism, advancing the understanding of atmospheric brown carbon formation in the dark. We are able to selectively quantify aromatic isomers, which is beyond the limits of conventional electroanalysis. Second, we identify a new pathway of nitrocatechol hydroxylation, which proceeds simply by oxidation and the addition of water. This pathway can be environmentally significant in the dark aqueous-phase formation of secondary organic aerosols. Third, the developed methodology is capable of selectively detecting a wide range of nitroaromatics; a possible application in environmental monitoring is proposed.