Predicting reduction rates of energetic nitroaromatic compounds using calculated one-electron reduction potentials

Linear Free Energy Relationship for Predicting the Rate Constants of Munition Compound Reduction by the Fe(II)-Hematite and Fe(II)-Goethite Redox Couples

Abiotic reduction by iron minerals is arguably the most important fate process for munition compounds (MCs) in subsurface environments. No model currently exists that can predict the abiotic reduction rates of structurally diverse MCs by iron (oxyhydr)oxides. We performed batch experiments to measure the rate constants for the reduction of three classes of MCs (poly-nitroaromatics, nitramines, and azoles) by hematite or goethite in the presence of aqueous Fe2+. The surface area-normalized reduction rate constant (kSA) depended on the aqueous-phase one-electron reduction potential (EH1) of the MC and the thermodynamic state (i.e., pe and pH) of the iron oxide-Feaq2+ system. A linear free energy relationship (LFER), similar to that reported previously for nitrobenzene, successfully captures all MC reduction rate constants that span 6 orders of magnitude: log ( k S A ) = ( 1.12 ± 0.04 ) [ 0.53 E H 1 59 m V - ( p H + p e ) ] + ( 5.52 ± 0.23 ) . The finding that the rate constants of all the different classes of MCs can be described by a single LFER suggests that these structurally diverse nitro compounds are reduced by iron oxide-Feaq2+ couples through a common mechanism up to the rate-limiting step. Multiple mechanistic implications of the results are discussed. This study expands the applicability of the LFER model for predicting the reduction rates of legacy and emerging MCs and potentially other nitro compounds.

Overlooked Transformation of Nitrated Polycyclic Aromatic Hydrocarbons in Natural Waters: Role of Self-Photosensitization

Photochemical transformation is an important process that involves trace organic contaminants (TrOCs) in sunlit surface waters. However, the environmental implications of their self-photosensitization pathway have been largely overlooked. Here, we selected 1-nitronaphthalene (1NN), a representative nitrated polycyclic aromatic hydrocarbon, to study the self-photosensitization process. We investigated the excited-state properties and relaxation kinetics of 1NN after sunlight absorption. The intrinsic decay rate constants of triplet (³1NN*) and singlet (¹1NN*) excited states were estimated to be 1.5 × 10⁶ and 2.5 × 10⁸ s^-1, respectively. Our results provided quantitative evidence for the environmental relevance of ³1NN* in waters. Possible reactions of ³1NN* with various water components were evaluated. With the reduction and oxidation potentials of -0.37 and 1.95 V, ³1NN* can be either oxidized or reduced by dissolved organic matter isolates and surrogates. We also showed that hydroxyl (^•OH) and sulfate (SO₄^•-) radicals can be generated via the ³1NN*-induced oxidation of inorganic ions (OH^- and SO₄^2-, respectively). We further investigated the reaction kinetics of ³1NN* and OH^- forming ^•OH, an important photoinduced reactive intermediate, through complementary experimental and theoretical approaches. The rate constants for the reactions of ³1NN* with OH^- and 1NN with ^•OH were determined to be 4.22 × 10⁷ and 3.95 ± 0.01 × 10⁹ M^-1 s^-1, respectively. These findings yield new insights into self-photosensitization as a pathway for TrOC attenuation and provide more mechanistic details into their environmental fate.

Modified quantum mechanical approach for the estimation of single-electron reduction potential of nitroaromatic compounds in aqueous medium

The midpoint single-electron reduction potential of nitroaromatic compounds in aqueous medium at pH 7.0 (potential of ArNO₂/ArNO₂·^- couple, E_m7) frequently determines their therapeutic and/or toxic properties. However, its estimation remains a complex problem. We propose a modified method of E_m7 estimation by quantum mechanical calculations, based on the use of the dielectric continuum model together with a certain number of H₂O molecules at the vicinity of nitro group. The optimal number of H₂O molecules corresponds to a minimal difference between the experimentally determined and calculated values of E_m7, and/or the most negative value of calculated E_m7. This enabled us to calculate the E_m7 values for a number of ArNO₂ (n = 19) with the average deviation of 0.027 V from the experimentally determined ones. Apart from nitrobenzene derivatives, the application of this approach for the representatives of nitropyridines, nitrofurans, nitrothiophenes, and nitrothiazoles was demonstrated. In this case, nitroimidazole derivatives are an exception, evidently due to a strong proton accepting properties of N3 atom of their free radicals.

Predictive models for the aqueous phase reactivity of inorganic radicals with organic micropollutants

Single-electron transfer (SET) is one of the most common reaction mechanisms for degrading organic micropollutants (OMPs) in advanced oxidation processes. We collected 300 SET reactions (CO₃^•-, SO₄^•-, Cl₂^•-, and Br₂^•--mediated) and calculated three key parameters for understanding the SET mechanism: aqueous phase free energies of activation (ΔG^‡), free energies of reactions (ΔG), and orbital energy gaps of reactants (E_OMPsHOMO-E_RadiLUMO). Then, we classified the OMPs according to their structure, developed and evaluated linear energy relationships of the second-order rate constants (k) with ΔG^‡, ΔG, or E_OMPsHOMO-E_RadiLUMO in each class. Considering that a single descriptor cannot capture all the chemical diversity, we combined ΔG^‡, ΔG, and E_OMPsHOMO-E_RadiLUMO as inputs to develop multiple linear regression (MLR) models. Chemical classification is critical to the linear model described above. However, OMPs usually have multiple functional groups, making the classification challenging and uncertain. Therefore, we tried machine learning algorithms to predict k values without chemical classification. We found that decision trees (R² = 0.88-0.95) and random forest (R² = 0.90-0.94) algorithms show better performance on the prediction of the k values, whereas boosted tree algorithm cannot make an accurate prediction (R² = 0.19-0.36). Overall, our study provides a powerful tool to predict the aqueous phase reactivity of OMP to certain radicals without the need for chemical classification.

Electron Transfer Energy and Hydrogen Atom Transfer Energy-Based Linear Free Energy Relationships for Predicting the Rate Constants of Munition Constituent Reduction by Hydroquinones

No single linear free energy relationship (LFER) exists that can predict reduction rate constants of all munition constituents (MCs). To address this knowledge gap, we measured the reduction rates of MCs and their surrogates including nitroaromatics [NACs; 2,4,6-trinitrotoluene (TNT), 2,4-dinitroanisole (DNAN), 2-amino-4,6-dinitrotoluene (2-A-DNT), 4-amino-2,6-dinitrotoluene (4-A-DNT), and 2,4-dinitrotoluene (DNT)], nitramines [hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) and nitroguanidine (NQ)], and azoles [3-nitro-1,2,4-triazol-5-one (NTO) and 3,4-dinitropyrazole (DNP)] by three dithionite-reduced quinones (lawsone, AQDS, and AQS). All MCs/NACs were reduced by the hydroquinones except NQ. Hydroquinone and MC speciations were varied by controlling pH, permitting the application of a speciation model to determine second-order rate constants (k) from observed pseudo-first-order rate constants. The intrinsic reactivity of MCs (oxidants) decreased upon deprotonation, while the opposite was true for hydroquinones (reductants). The rate constants spanned ∼6 orders of magnitude in the order NTO ≈ TNT > DNP > DNT ≈ DNAN ≈ 2-A-DNT > DNP^- > 4-A-DNT > NTO^- > RDX. LFERs developed using density functional theory-calculated electron transfer and hydrogen atom transfer energies and reported one-electron reduction potentials successfully predicted k, suggesting that these structurally diverse MCs/NACs are all reduced by hydroquinones through the same mechanism and rate-limiting step. These results increase the applicability of LFER models for predicting the fate and half-lives of MCs and related nitro compounds in reducing environments.

Long-term performance evaluation of zero-valent iron amended permeable reactive barriers for groundwater remediation - A mechanistic approach

Permeable reactive barriers (PRBs) are used for groundwater remediation at contaminated sites worldwide. This technology has been efficient at appropriate sites for treating organic and inorganic contaminants using zero-valent iron (ZVI) as a reductant and as a reactive material. Continued development of the technology over the years suggests that a robust understanding of PRB performance and the mechanisms involved is still lacking. Conflicting information in the scientific literature downplays the critical role of ZVI corrosion in the remediation of various organic and inorganic pollutants. Additionally, there is a lack of information on how different mechanisms act in tandem to affect ZVI-groundwater systems through time. In this review paper, we describe the underlying mechanisms of PRB performance and remove isolated misconceptions. We discuss the primary mechanisms of ZVI transformation and aging in PRBs and the role of iron corrosion products. We review numerous sites to reinforce our understanding of the interactions between groundwater contaminants and ZVI and the authigenic minerals that form within PRBs. Our findings show that ZVI corrosion products and mineral precipitates play critical roles in the long-term performance of PRBs by influencing the reactivity of ZVI. Pore occlusion by mineral precipitates occurs at the influent side of PRBs and is enhanced by dissolved oxygen and groundwater rich in dissolved solids and high alkalinity, which negatively impacts hydraulic conductivity, allowing contaminants to potentially bypass the treatment zone. Further development of site characterization tools and models is needed to support effective PRB designs for groundwater remediation.

Electrochemical Reduction of Halogenated Alkanes and Alkenes Using Activated Carbon-Based Cathodes

Granular activated carbon (GAC) is used to sorb a broad range of halogenated contaminant classes, but spent GAC disposal is costly. Taking advantage of GAC's conductivity, this study evaluated the conversion of the GAC to cathodes for electrochemical reductive dehalogenation of 15 halogenated alkanes and alkenes exhibiting a diversity of structures (type of halogen, number of halogens, functional groups) and including contaminants of practical importance (e.g., trichloroethylene). Alkane degradation rates increased with the number of halogens and in the order: chlorine < bromine < iodine. Quantitative structure-activity relationships (QSARs) correlating experimental first-order degradation rate constants for alkanes with molecular descriptors associated with an outer-sphere one-electron transfer calculated using density functional theory indicated that correlations with molecular descriptors improved in the order: aqueous phase reduction potentials (E^0,aq) < energy of the substrate's lowest unoccupied molecular orbital (E_LUMO) < Marcus theory activation free energies (ΔG^‡) ∼ gas-phase standard reduction free energies (ΔG^0,gas). Chlorinated alkene degradation rates increased with decreasing number of chlorines, and QSAR correlations were opposite those of alkanes, indicating a different reaction mechanism. Degradation timescales ranged from 1 min to 3 h with halides as predominant products. These results suggest that the electrochemical reduction of halogenated alkanes and alkenes can be used to regenerate spent GAC.

Computational Predictions of the Hydrolysis of 2,4,6-Trinitrotoluene (TNT) and 2,4-Dinitroanisole (DNAN)

Hydrolysis is a common transformation reaction that can affect the environmental fate of many organic compounds. In this study, three proposed mechanisms of alkaline hydrolysis of 2,4,6-trinitrotoluene (TNT) and 2,4-dinitroaniline (DNAN) were investigated with plane-wave density functional theory (DFT) combined with ab initio and classical molecular dynamics (AIMD/MM) free energy simulations, Gaussian basis set DFT calculations, and correlated molecular orbital theory calculations. Most of the computations in this study were carried out using the Arrows web-based tools. For each mechanism, Meisenheimer complex formation, nucleophilic aromatic substitution, and proton abstraction reaction energies and activation barriers were calculated for the reaction at each relevant site. For TNT, it was found that the most kinetically favorable first hydrolysis steps involve Meisenheimer complex formation by attachment of OH^- at the C1 and C3 arene carbons and proton abstraction from the methyl group. The nucleophilic aromatic substitution reactions at the C2 and C4 arene carbons were found to be thermodynamically favorable. However, the calculated activation barriers were slightly lower than in previous studies, but still found to be ΔG^‡ ≈ 18 kcal/mol using PBE0 AIMD/MM free energy simulations, suggesting that the reactions are not kinetically significant. For DNAN, the barriers of nucleophilic aromatic substitution were even greater (ΔG^‡ > 29 kcal/mol PBE0 AIMD/MM). The most favorable hydrolysis reaction for DNAN was found to be a two-step process in which the hydroxyl first attacks the C1 carbon to form a Meisenheimer complex at the C1 arene carbon C1-(OCH₃)OH^-, and subsequently, the methoxy anion (-OCH₃) at the C1 arene carbon dissociates and the proton shuttles from the C1-OH to the dissociated methoxy group, resulting in methanol and an aryloxy anion.

Decomposition of 2,4,6-trinitrotoluene (TNT) and 5-nitro-2,4-dihydro-3H-1,2,4-triazol-3-one (NTO) by Fe13O13 nanoparticle: density functional theory study

To obtain more insight into the mechanisms of the decomposition of energetic compounds, we performed a computational study of the interaction of Fe₁₃O₁₃ nanoparticles with two energetic molecules such as 2,4,6-trinitrotoluene (TNT) and 5-nitro-2,4-dihydro-3H-1,2,4-triazol-3-one (NTO). The density functional theory using M06-2X, B3LYP, and BLYP density functionals was applied. We found that the reactivity of these molecules strongly depends on the place of adsorption (so-called top and bottom planes of Fe₁₃O₁₃). Namely, only the interaction with the bottom plane results in the thermodynamic characteristics of the decomposition that provide a medium reaction rate for the studied processes. Several pathways for such decomposition were found. One of them is the inter-complex oxygen transfer of nitro-group oxygen to Fe₁₃O₁₃. This pathway results in the formation of adsorbed nitroso compounds. The second pathway describes a more complex decomposition that includes the transfer of the nitro-group oxygen accompanied by the hydrogen transfer. In all cases, the interaction of energetic molecules with Fe₁₃O₁₃ nanoparticles takes place along with a barrier-less electron transfer from Fe₁₃O₁₃ to TNT or NTO species.

Molecular Structure and Sulfur Content Affect Reductive Dechlorination of Chlorinated Ethenes by Sulfidized Nanoscale Zerovalent Iron

Sulfidized nanoscale zerovalent iron (SNZVI) with desirable properties and reactivity has recently emerged as a promising groundwater remediation agent. However, little information is available on how the molecular structure of chlorinated ethenes (CEs) affects their dechlorination by SNZVI or whether the sulfur content of SNZVI can alter their dechlorination pathway and reactivity. Here, we show that the reactivity (up to 30-fold) and selectivity (up to 70-fold) improvements of SNZVI (compared to NZVI) toward CEs depended on the chlorine number, chlorine position, and sulfur content. Low CEs (i.e., vinyl chloride and cis-1,2-dichloroethene) and high CEs (perchloroethene) tended to be dechlorinated by SNZVI primarily via atomic H and direct electron transfer, respectively, while SNZVI could efficiently and selectively dechlorinate trichloroethene and trans-1,2-dichloroethene via both pathways. Increasing the sulfidation degree of SNZVI suppressed its ability to produce atomic H but promoted electron transfer and thus altered the relative contributions of atomic H and electron transfer to the CE dechlorination, resulting in different reactivities and selectivities. These were indicated by the correlations of CE dechlorination rates and improvements with CE molecular descriptors, H₂ evolution rates, and electron transfer indicators of SNZVI. These mechanistic insights indicate the importance of determining the structure-specific properties and reactivity of both SNZVI materials and their target contaminants and can lead to a more rational design of SNZVI for in situ groundwater remediation of various CEs.

Modeling the Reduction Kinetics of Munition Compounds by Humic Acids

Dissolved organic matter (DOM) comprises a sizeable portion of the redox-active constituents in the environment and is an important reductant for the abiotic transformation of nitroaromatic compounds and munition constituents (NACs/MCs). Building a predictive kinetic model for these reactions would require the energies associated with both the reduction of the NACs/MCs and the oxidation of the DOM. The heterogeneous and unknown structure of DOM, however, has prohibited reliable determination of its oxidation energies. To overcome this limitation, humic acids (HAs) were used as model DOM, and their redox moieties were modeled as a collection of quinones of different redox potentials. The reduction and oxidation energies of the NACs/MCs and hydroquinones, respectively, via hydrogen atom transfer (HAT) reactions were then calculated quantum chemically. HAT energies have been used successfully in a linear free energy relationship (LFER) to predict second-order rate constants for NAC reduction by hydroquinones. Furthermore, a linear relationship between the HAT energies and the reduction potentials of quinones was established, which allows estimation of hydroquinone reactivity (i.e., rate constants) from HA redox titration data. A training set of three HAs and two NACs/MCs was used to generate a mean HA redox profile that successfully predicted reduction kinetics in multiple HA/MC systems.

Nitroaromatic Hypoxia-Activated Prodrugs for Cancer Therapy

The presence of “hypoxic” tissue (with O₂ levels of <0.1 mmHg) in solid tumours, resulting in quiescent tumour cells distant from blood vessels, but capable of being reactivated by reoxygenation following conventional therapy (radiation or drugs), have long been known as a limitation to successful cancer chemotherapy. This has resulted in a sustained effort to develop nitroaromatic “hypoxia-activated prodrugs” designed to undergo enzyme-based nitro group reduction selectively in these hypoxic regions, to generate active drugs. Such nitro-based prodrugs can be classified into two major groups; those activated either by electron redistribution or by fragmentation following nitro group reduction, relying on the extraordinary difference in electron demand between an aromatic nitro group and its reduction products. The vast majority of hypoxia-activated fall into the latter category and are discussed here classed by the nature of their nitroaromatic trigger units.

Single- and Two-Electron Reduction of Nitroaromatic Compounds by Flavoenzymes: Mechanisms and Implications for Cytotoxicity

Nitroaromatic compounds (ArNO₂) maintain their importance in relation to industrial processes, environmental pollution, and pharmaceutical application. The manifestation of toxicity/therapeutic action of nitroaromatics may involve their single- or two-electron reduction performed by various flavoenzymes and/or their physiological redox partners, metalloproteins. The pivotal and still incompletely resolved questions in this area are the identification and characterization of the specific enzymes that are involved in the bioreduction of ArNO₂ and the establishment of their contribution to cytotoxic/therapeutic action of nitroaromatics. This review addresses the following topics: (i) the intrinsic redox properties of ArNO₂, in particular, the energetics of their single- and two-electron reduction in aqueous medium; (ii) the mechanisms and structure-activity relationships of reduction in ArNO₂ by flavoenzymes of different groups, dehydrogenases-electrontransferases (NADPH:cytochrome P-450 reductase, ferredoxin:NADP(H) oxidoreductase and their analogs), mammalian NAD(P)H:quinone oxidoreductase, bacterial nitroreductases, and disulfide reductases of different origin (glutathione, trypanothione, and thioredoxin reductases, lipoamide dehydrogenase), and (iii) the relationships between the enzymatic reactivity of compounds and their activity in mammalian cells, bacteria, and parasites.

Fe(II) Redox Chemistry in the Environment

Iron (Fe) is the fourth most abundant element in the earth's crust and plays important roles in both biological and chemical processes. The redox reactivity of various Fe(II) forms has gained increasing attention over recent decades in the areas of (bio) geochemistry, environmental chemistry and engineering, and material sciences. The goal of this paper is to review these recent advances and the current state of knowledge of Fe(II) redox chemistry in the environment. Specifically, this comprehensive review focuses on the redox reactivity of four types of Fe(II) species including aqueous Fe(II), Fe(II) complexed with ligands, minerals bearing structural Fe(II), and sorbed Fe(II) on mineral oxide surfaces. The formation pathways, factors governing the reactivity, insights into potential mechanisms, reactivity comparison, and characterization techniques are discussed with reference to the most recent breakthroughs in this field where possible. We also cover the roles of these Fe(II) species in environmental applications of zerovalent iron, microbial processes, biogeochemical cycling of carbon and nutrients, and their abiotic oxidation related processes in natural and engineered systems.

Quantitative structure activity relationships (QSARs) and machine learning models for abiotic reduction of organic compounds by an aqueous Fe(II) complex

Due to the increasing diversity of organic contaminants discharged into anoxic water environments, reactivity prediction is necessary for chemical persistence evaluation for water treatment and risk assessment purposes. Almost all quantitative structure activity relationships (QSARs) that describe rates of contaminant transformation apply only to narrowly-defined, relatively homogenous families of reactants (e.g., dechlorination of alkyl halides). In this work, we develop predictive models for abiotic reduction of 60 organic compounds with diverse reducible functional groups, including nitroaromatic compounds (NACs), aliphatic nitro-compounds (ANCs), aromatic N-oxides (ANOs), isoxazoles (ISXs), polyhalogenated alkanes (PHAs), sulfoxides and sulfones (SOs), and others. Rate constants for their reduction were measured using a model reductant system, Fe(II)-tiron. Qualitatively, the rates followed the order NACs > ANOs ≈ ISXs ≈ PHAs > ANCs > SOs. To develop QSARs, both conventional chemical descriptor-based and machine learning (ML)-based approaches were investigated. Conventional univariate QSARs based on a molecular descriptor E_LUMO (energy of the lowest-unoccupied molecular orbital) gave good correlations within classes. Multivariate QSARs combining E_LUMO with Abraham descriptors for physico-chemical properties gave slightly improved correlations within classes for NCs and NACs, but little improvement in correlation within other classes or among classes. The ML model obtained covers reduction rates for all classes of compounds and all of the conditions studied with the prediction accuracy similar to those of the conventional QSARs for individual classes (r² = 0.41-0.98 for univariate QSARs, 0.71-0.94 for multivariate QSARs, and 0.83 for the ML model). Both approaches required a scheme for a priori classification of the compounds for model training. This work offers two alternative modeling approaches to comprehensive abiotic reactivity prediction for persistence evaluation of organic compounds in anoxic water environments.

Anaerobic reduction of high-polarity nitroaromatic compounds by electrochemically active bacteria: Roles of Mtr respiratory pathway, molecular polarity, mediator and membrane permeability

Electrochemically active bacteria (EAB) are effective for the bioreduction of nitroaromatic compounds (NACs), but the exact reduction mechanisms are unclear yet. Therefore, 3-nitrobenzenesulfonate (NBS) was used to explore the biodegradation mechanism of NACs by EAB. Results show that NBS could be anaerobically degraded by Shewanella oneidensis MR-1. The generation of aminoaromatic compounds was accompanied with the NBS reduction, indicating that NBS was biodegraded via reductive approach by S. oneidensis MR-1. The impacts of NBS concentration and cell density on the NBS reduction were evaluated. The removal of NBS depends mainly on the transmembrane electron transfer of S. oneidensis MR-1. Impairment of Mtr respiratory pathway was found to mitigate the reduction of NBS, suggesting that the anaerobic biodegradation of NBS occurred extracellularly. Knocking out cymA severely impaired the extracellular reduction ability of S. oneidensis MR-1. However, the phenotype of ΔcymA mutant could be compensated by the exogenous electron mediators, implying the trans-outer membrane diffusion of mediators into the periplasmic space. This work provides a new insight into the anaerobic reduction of aromatic contaminants by EAB.

A Unified Linear Free Energy Relationship for Abiotic Reduction Rate of Nitroaromatics and Hydroquinones Using Quantum Chemically Estimated Energies

Determining the fate of nitroaromatic compounds (NACs) in the environment requires the use of predictive models for compounds and conditions for which experimental data are insufficient. Previous studies have developed linear free energy relationships (LFERs) that relate the thermodynamic energy of NAC reduction to its corresponding rate constant. We present a comprehensive LFER that incorporates both the reduction and oxidation half-reactions through quantum chemically calculated energies. Environ Toxicol Chem 2020;39:2389-2395. © 2020 SETAC.

Hydrogen Atom Transfer Reaction Free Energy as a Predictor of Abiotic Nitroaromatic Reduction Rate Constants: A Comprehensive Analysis

A linear free energy model is presented that predicts the second-order rate constant for the abiotic reduction of nitroaromatic compounds (NACs). Previously presented models use the one-electron reduction potential EH1(ArNO2) of the NAC reaction ArNO2+e-→ArNO2•- . If EH1(ArNO2) is not available, it has been proposed that EH1(ArNO2) be computed directly or estimated from the gas-phase electron affinity (EA). The model proposed uses the Gibbs free energy of the hydrogen atom transfer (HAT) reaction ArNO2+H•→ArNOOH• as the parameter in the linear free energy model. Both models employ quantum chemical computations for the required thermodynamic energies. The available and proposed models are compared using experimentally determined second-order rate constants from 5 investigations from the literature in which a variety of NACs were exposed to a variety of reductants. A comprehensive analysis utilizing all the NACs and reductants demonstrate that the HAT energy model and the experimental one-electron reduction potential model have similar root mean square errors and residual error probability distributions. In contrast, the model using the computed EA has a more variable residual error distribution with a significant number of outliers. The results suggest that a linear free energy model utilizing computed HAT reaction free energy produces a more reliable prediction of the NAC abiotic reduction second-order rate constant than previously available methods. The advantages of the proposed HAT energy model and its mechanistic implications are discussed as well. Environ Toxicol Chem 2020;39:1678-1684. © 2020 SETAC.

Probing extracellular reduction mechanisms of Bacillus subtilis and Escherichia coli with nitroaromatic compounds

Redox transformations of organic contaminants by bacterial extracellular polymeric substances (EPS) and the associated electron transfer mechanisms are rarely reported. Here we show that a nitroaromatic compound (1,3-dinitrobenzene) can be readily reduced to 3-hydroxylaminonitrobenzene and 3-nitroaniline in aqueous suspension of common bacteria (E. coli or B. subtilis) or in aqueous dissolved EPS extracted from the bacteria. The loss ratio of 1,3-dinitrobenzene by E. coli was unaffected after knocking out the nfsA gene encoding nitroreductase, but was suppressed by removing EPS attached to cells. In contrast, the loss ratio was enhanced by adding aqueous dissolved EPS to E. coli or B. subtilis suspension. The residual 1,3-dinitrobenzene and products formed after reduction were only presented outside the bacterial cells. Thus, bacterial reduction of 1,3-dinitrobenzene was mediated by nonenzymatic extracellular reduction. This was further corroborated by the observation that the stoichiometric demand of electrons in 1,3-dinitrobenzene reduction was nearly equal to the quantity of electrons donated by bacterial cells in the electrochemical cell experiment. Inhibition on the reduction of 1,3-dinitrobenzene by chemical probes combined with fluorescence detection demonstrated that reducing sugars in EPS might act as electron donors, while cytochromes and some low-molecular weight molecules (flavins and quinones) were involved as electron transfer mediators. Linear relationships were observed between the reduction kinetics and the one-electron reduction potentials for a series of substituted dinitrobenzenes in the presence of bacterial cells or dissolved EPS. Their close linear regression slope values suggest that the extracellular matrix and the exfoliated EPS utilized the same reducing agents (likely hydroquinones and reduced flavins) as terminal electron donors to reduce NACs. These results reveal a previously unrecognized mechanism for nonenzymatic extracellular reduction of NACs by common bacteria. CAPSULE: The extracellular matrix of E. coli or B. subtilis supplies both electron donors and electron transfer mediators to efficiently reduce nitroaromatic compounds.

A deep neural network combined with molecular fingerprints (DNN-MF) to develop predictive models for hydroxyl radical rate constants of water contaminants

This work combined a Deep Neural Network (DNN) with molecular fingerprints (MF) to develop models to predict the OH radical rate constants of 593 organic contaminants. Molecular descriptors, most often used in establishing quantitative structural-activity relationships (QSARs), were not used here because of their complicated generation processes that rely on advanced physicochemical and computational knowledge. Instead, we only fed the most basic information of the contaminant structures, i.e., MF encoding the types of atoms and how they are connected, to DNN and DNN then developed predictive models automatically. Here, a dataset containing 457 contaminants and their OH rate constants was first used to develop predictive models by DNN-MF. The hence developed models showed comparable accuracy to the traditional QSARs. The root mean square error (RMSE) values of the test sets were 0.358-0.384. The length of 2048 bits for the MF and 3 hidden layers (each with 1024 neurons) were found to be the optimal parameters for DNN. The model containing additional 89 micorpollutants in the training set was then successfully applied to predict the OH rate constants of 17 organophosphorus flame retardants and 29 additional micropollutants, with comparable accuracy to the reported molecular descriptors-based QSARs.

Electrochemical, Spectroscopic, and Computational Investigations on Redox Reactions of Selenium Species on Galena Surfaces

Despite previous studies investigating selenium (Se) redox reactions in the presence of semiconducting minerals, Se redox reactions mediated by galena (PbS) are poorly understood. In this study, the redox chemistry of Se on galena is investigated over a range of environmentally relevant Eh and pH conditions (+0.3 to −0.6 V vs. standard hydrogen electrode, SHE; pH 4.6) using a combination of electrochemical, spectroscopic, and computational approaches. Cyclic voltammetry (CV) measurements reveal one anodic/cathodic peak pair at a midpoint potential of +30 mV (vs. SHE) that represents reduction and oxidation between HSeO3− and H2Se/HSe−. Two peak pairs with midpoint potentials of −400 and −520 mV represent the redox transformation from Se(0) to HSe− and H2Se species, respectively. The changes in Gibbs free energies of adsorption of Se species on galena surfaces as a function of Se oxidation state were modeled using quantum-mechanical calculations and the resulting electrochemical peak shifts are (−0.17 eV for HSeO3−/H2Se, −0.07 eV for HSeO3−/HSe−, 0.15 eV for Se(0)/HSe−, and −0.15 eV for Se(0)/H2Se). These shifts explain deviation between Nernstian equilibrium redox potentials and observed midpoint potentials. X-ray photoelectron spectroscopy (XPS) analysis reveals the formation of Se(0) potentials below −100 mV and Se(0) and Se(−II) species at potentials below −400 mV.

Experimental Validation of Hydrogen Atom Transfer Gibbs Free Energy as a Predictor of Nitroaromatic Reduction Rate Constants

Nitroaromatic compounds (NACs) are a class of prevalent contaminants. Abiotic reduction is an important fate process that initiates NAC degradation in the environment. Many linear free energy relationship (LFER) models have been developed to predict NAC reduction rates. Almost all LFERs to date utilize experimental aqueous-phase one-electron reduction potential ( E_H¹) of NAC as a predictor, and thus, their utility is limited by the availability of E_H¹ data. A promising new approach that utilizes computed hydrogen atom transfer (HAT) Gibbs free energy instead of E_H¹ as a predictor was recently proposed. In this study, we evaluated the feasibility of HAT energy for predicting NAC reduction rate constants. Using dithionite-reduced quinones, we measured the second-order rate constants for the reduction of seven NACs by three hydroquinones of different protonation states. We computed the gas-phase energies for HAT and electron affinity (EA) of NACs and established HAT- and EA-based LFERs for six hydroquinone species. The results suggest that HAT energy is a reliable predictor of NAC reduction rate constants and is superior to EA. This is the first independent, experimental validation of HAT-based LFER, a new approach that enables rate prediction for a broad range of structurally diverse NACs based solely on molecular structures.

Quantitative structure-activity relationship models for predicting reaction rate constants of organic contaminants with hydrated electrons and their mechanistic pathways

The hydrated electron (e_aq^-)-based reduction processes are promising for removing organic pollutants in water engineering systems. The reductive kinetics, especially the second order rate constants ( [Formula: see text] ) of e_aq^- with organic compounds, is important for evaluating and modeling the advanced reduction processes. In this study, the [Formula: see text] values for aliphatic compounds and phenyl-based compounds are, for the first time, modeled by the quantitative structure-activity relationship (QSAR) method. The structural features governing the reactivity of two classes of organic compounds toward e_aq^- were revealed, and the energy of the lowest unoccupied molecular orbital (E_LUMO), one-electron reduction potential (E_RED) and polarizability (α) were found to be the important molecular parameters in both two models. The built QSAR models provide robust predictive tools for estimating the removal of emerging pollutants using e_aq^- during wastewater treatment processes. Additionally, quantum chemical calculations were employed to probe into the mechanism and feasibility of the single electron transfer (SET) pathway in the e_aq^--based reduction process. The thermodynamic investigation suggests that the compounds with electron-withdrawing groups tend to possess higher [Formula: see text] and lower Gibbs free energy (ΔG_SET) and Gibbs free energies of activation (∆^‡G_SET^∘) than the ones with electron-donating groups, indicating the SET process occurs more readily. It is also found that the refractory halogenated compounds can achieve dehalogenation via the SET pathway.

Linking Thermodynamics to Pollutant Reduction Kinetics by Fe2+ Bound to Iron Oxides

Numerous studies have reported that pollutant reduction rates by ferrous iron (Fe²⁺) are substantially enhanced in the presence of an iron (oxyhydr)oxide mineral. Developing a thermodynamic framework to explain this phenomenon has been historically difficult due to challenges in quantifying reduction potential ( E_H) values for oxide-bound Fe²⁺ species. Recently, our group demonstrated that E_H values for hematite- and goethite-bound Fe²⁺ can be accurately calculated using Gibbs free energy of formation values. Here, we tested if calculated E_H values for oxide-bound Fe²⁺ could be used to develop a free energy relationship capable of describing variations in reduction rate constants of substituted nitrobenzenes, a class of model pollutants that contain reducible aromatic nitro groups, using data collected here and compiled from the literature. All the data could be described by a single linear relationship between the logarithms of the surface-area-normalized rate constant ( k_SA) values and E_H and pH values [log( k_SA) = - E_H/0.059 V - pH + 3.42]. This framework provides mechanistic insights into how the thermodynamic favorability of electron transfer from oxide-bound Fe²⁺ relates to redox reaction kinetics.

Informing Efforts to Develop Nitroreductase for Amine Production

Nitroreductases (NRs) hold promise for converting nitroaromatics to aromatic amines. Nitroaromatic reduction rate increases with Hammett substituent constant for NRs from two different subgroups, confirming substrate identity as a key determinant of reactivity. Amine yields were low, but compounds yielding amines tend to have a large π system and electron withdrawing substituents. Therefore, we also assessed the prospects of varying the enzyme. Several different subgroups of NRs include members able to produce aromatic amines. Comparison of four NR subgroups shows that they provide contrasting substrate binding cavities with distinct constraints on substrate position relative to the flavin. The unique architecture of the NR dimer produces an enormous contact area which we propose provides the stabilization needed to offset the costs of insertion of the active sites between the monomers. Thus, we propose that the functional diversity included in the NR superfamily stems from the chemical versatility of the flavin cofactor in conjunction with a structure that permits tremendous active site variability. These complementary properties make NRs exceptionally promising enzymes for development for biocatalysis in prodrug activation and conversion of nitroaromatics to valuable aromatic amines. We provide a framework for identifying NRs and substrates with the greatest potential to advance.

A Novel Method for Enhancing Strains' Biodegradation of 4-Chloronitrobenzene

This paper introduces a novel approach to enhance the strains' biodegradation of 4-chloronitrobenzene by utilizing the synergistic effect of the organic reductant mannitol and the substrate beef extraction. Our results demonstrate that 4-chloronitrobenzene could not be an available nitrogen source to support target strains' growth, which induced the limited 4-chloronitrobenzene biodegradation. In addition, the organic reducing agent and substrate had a better synergistic effect than inorganic reducing agent and substrate to enhance the strains' 4-chloronitrobenzene cometabolic biodegradation. Employing the synergistic effect of the optimal mixture (mannitol and beef extraction), the biodegradation rates of 50mgL^-1 4-chloronitrobenzene by seven of the ten target strains were enhanced up to 100% from previous removals of no more than 19.1% after 7days. Three of the strains could even completely degrade 100mgL^-1 4-chloronitrobenzene while five strains degraded over 91.4%. The method has good potential to enhance bioremediation of various 4-Chloronitrobenzene-contaminated environments as mannitol and beef extraction are non-toxic to the environment.

Chemical structure-based predictive model for the oxidation of trace organic contaminants by sulfate radical

Second-order rate constants [Formula: see text] for the reaction of sulfate radical anion (SO₄^•-) with trace organic contaminants (TrOCs) are of scientific and practical importance for assessing their environmental fate and removal efficiency in water treatment systems. Here, we developed a chemical structure-based model for predicting [Formula: see text] using 32 molecular fragment descriptors, as this type of model provides a quick estimate at low computational cost. The model was constructed using the multiple linear regression (MLR) and artificial neural network (ANN) methods. The MLR method yielded adequate fit for the training set (R_training²=0.88,n=75) and reasonable predictability for the validation set (R_validation²=0.62,n=38). In contrast, the ANN method produced a more statistical robustness but rather poor predictability (R_training²=0.99andR_validation²=0.42). The reaction mechanisms of SO₄^•- reactivity with TrOCs were elucidated. Our result shows that the coefficients of functional groups reflect their electron donating/withdrawing characters. For example, electron donating groups typically exhibit positive coefficients, indicating enhanced SO₄^•- reactivity. Electron withdrawing groups exhibit negative values, indicating reduced reactivity. With its quick and accurate features, we applied this structure-based model to 55 discrete TrOCs culled from the Contaminant Candidate List 4, and quantitatively compared their removal efficiency with SO₄^•- and OH in the presence of environmental matrices. This high-throughput model helps prioritize TrOCs that are persistent to SO₄^•- based oxidation technologies at the screening level, and provide diagnostics of SO₄^•- reaction mechanisms.

Batch soil adsorption and column transport studies of 2,4-dinitroanisole (DNAN) in soils

The explosive 2,4,6-trinitrotoluene (TNT) is currently a main ingredient in munitions; however the compound has failed to meet the new sensitivity requirements. The replacement compound being tested is 2,4-dinitroanisole (DNAN). DNAN is less sensitive to shock, high temperatures, and has good detonation characteristics. However, DNAN is more soluble than TNT, which can influence transport and fate behavior and thus bioavailability and human exposure potential. The objective of this study was to investigate the environmental fate and transport of DNAN in soil, with specific focus on sorption processes. Batch and column experiments were conducted using soils collected from military installations located across the United States. The soils were characterized for pH, electrical conductivity, specific surface area, cation exchange capacity, and organic carbon content. In the batch rate studies, change in DNAN concentration with time was evaluated using the first order equation, while adsorption isotherms were fitted using linear and Freundlich equations. Solution mass-loss rate coefficients ranged between 0.0002h^-1 and 0.0068h^-1. DNAN was strongly adsorbed by soils with linear adsorption coefficients ranging between 0.6 and 6.3Lg^-1, and Freundlich coefficients between 1.3 and 34mg^1-nLⁿkg^-1. Both linear and Freundlich adsorption coefficients were positively correlated with the amount of organic carbon and cation exchange capacity of the soil, indicating that similar to TNT, organic matter and clay minerals may influence adsorption of DNAN. The results of the miscible-displacement column experiments confirmed the impact of sorption on retardation of DNAN during transport. It was also shown that under flow conditions DNAN transforms readily with formation of amino transformation products, 2-ANAN and 4-ANAN. The magnitudes of retardation and transformation observed in this study result in significant attenuation potential for DNAN, which would be anticipated to contribute to a reduced risk for contamination of ground water from soil residues.

In silico environmental chemical science: properties and processes from statistical and computational modelling

Quantitative structure-activity relationships (QSARs) have long been used in the environmental sciences. More recently, molecular modeling and chemoinformatic methods have become widespread. These methods have the potential to expand and accelerate advances in environmental chemistry because they complement observational and experimental data with "in silico" results and analysis. The opportunities and challenges that arise at the intersection between statistical and theoretical in silico methods are most apparent in the context of properties that determine the environmental fate and effects of chemical contaminants (degradation rate constants, partition coefficients, toxicities, etc.). The main example of this is the calibration of QSARs using descriptor variable data calculated from molecular modeling, which can make QSARs more useful for predicting property data that are unavailable, but also can make them more powerful tools for diagnosis of fate determining pathways and mechanisms. Emerging opportunities for "in silico environmental chemical science" are to move beyond the calculation of specific chemical properties using statistical models and toward more fully in silico models, prediction of transformation pathways and products, incorporation of environmental factors into model predictions, integration of databases and predictive models into more comprehensive and efficient tools for exposure assessment, and extending the applicability of all the above from chemicals to biologicals and materials.

Boron-doped diamond electrode: Preparation, characterization and application for electrocatalytic degradation of m-dinitrobenzene

Boron-doped diamond (BDD) electrode was successfully prepared via microwave plasma chemical vapor deposition method and it was used in electrocatalytic degradation of m-dinitrobenzene (m-DNB). The electrocatalytic degradation efficiency of m-DNB was evaluated under different experimental parameters including current density, temperature, pH, Na₂SO₄ concentration and initial m-DNB concentration. Under optimal parameters, degradation efficiency of m-DNB reached up to 82.7% after 150min. The degradation process of m-DNB was fitted well with pseudo first-order kinetics. Moreover, UV and HPLC analyses implied that m-DNB was totally destroyed and mineralized after 240min degradation, and the proposed mechanism during the electrocatalytic degradation process was analyzed. All these results demonstrated that BDD electrode possessed excellent electrocatalytic property and showed a great potential application in wastewater treatment.

Structure-Activity Relationships for Rates of Aromatic Amine Oxidation by Manganese Dioxide

New energetic compounds are designed to minimize their potential environmental impacts, which includes their transformation and the fate and effects of their transformation products. The nitro groups of energetic compounds are readily reduced to amines, and the resulting aromatic amines are subject to oxidation and coupling reactions. Manganese dioxide (MnO2) is a common environmental oxidant and model system for kinetic studies of aromatic amine oxidation. In this study, a training set of new and previously reported kinetic data for the oxidation of model and energetic-derived aromatic amines was assembled and subjected to correlation analysis against descriptor variables that ranged from general purpose [Hammett σ constants (σ(-)), pKas of the amines, and energies of the highest occupied molecular orbital (EHOMO)] to specific for the likely rate-limiting step [one-electron oxidation potentials (Eox)]. The selection of calculated descriptors (pKa, EHOMO, and Eox) was based on validation with experimental data. All of the correlations gave satisfactory quantitative structure-activity relationships (QSARs), but they improved with the specificity of the descriptor. The scope of correlation analysis was extended beyond MnO2 to include literature data on aromatic amine oxidation by other environmentally relevant oxidants (ozone, chlorine dioxide, and phosphate and carbonate radicals) by correlating relative rate constants (normalized to 4-chloroaniline) to EHOMO (calculated with a modest level of theory).

Chemical Reactivity Probes for Assessing Abiotic Natural Attenuation by Reducing Iron Minerals

Increasing recognition that abiotic natural attenuation (NA) of chlorinated solvents can be important has created demand for improved methods to characterize the redox properties of the aquifer materials that are responsible for abiotic NA. This study explores one promising approach: using chemical reactivity probes (CRPs) to characterize the thermodynamic and kinetic aspects of contaminant reduction by reducing iron minerals. Assays of thermodynamic CRPs were developed to determine the reduction potentials (ECRP) of suspended minerals by spectrophotometric determination of equilibrium CRP speciation and calculations using the Nernst equation. ECRP varied as expected with mineral type, mineral loading, and Fe(II) concentration. Comparison of ECRP with reduction potentials measured potentiometrically using a Pt electrode (EPt) showed that ECRP was 100-150 mV more negative than EPt. When EPt was measured with small additions of CRPs, the systematic difference between EPt and ECRP was eliminated, suggesting that these CRPs are effective mediators of electron transfer between mineral and electrode surfaces. Model contaminants (4-chloronitrobenzene, 2-chloroacetophenone, and carbon tetrachloride) were used as kinetic CRPs. The reduction rate constants of kinetic CRPs correlated well with the ECRP for mineral suspensions. Using the rate constants compiled from literature for contaminants and relative mineral reduction potentials based on ECRP measurements, qualitatively consistent trends were obtained, suggesting that CRP-based assays may be useful for estimating abiotic NA rates of contaminants in groundwater.