Frances C. Hill

Toward robust computational electrochemical predicting the environmental fate of organic pollutants

A number of density functionals was utilized for the calculation of electron attachment free energy for nitrocompounds, quinones and azacyclic compounds. Different solvation models have been tested on the calculation of difference in free energies of solvation of oxidized and reduced forms of nitrocompounds in aqueous solution, quinones in acetonitrile, and azacyclic compounds in dimethylformamide. Gas‐phase free energies evaluated at the mPWB1K/tzvp level and solvation energies obtained using SMD model to compute solvation energies of neutral oxidized forms and PCM(Pauling) to compute solvation energies of anion‐radical reduced forms provide reasonable accuracy of the prediction of electron attachment free energy, difference in free solvation energies of oxidized and reduced forms, and as consequence yield reduction potentials in good agreement with experimental data (mean absolute deviation is 0.15 V). It was also found that SMD/M05‐2X/tzvp method provides reduction potentials with deviation of 0.12 V from the experimental values but in cases of nitrocompounds and quinones this accuracy is achieved due to the cancelation of errors. To predict reduction ability of naturally occurred iron containing species with respect to organic pollutants we exploited experimental data within the framework of Pourbaix (Eh − pH) diagrams. We conclude that surface‐bound Fe(II) as well as certain forms of aqueous Fe(II)aq are capable of reducing a variety of nitroaromatic compounds, quinones and novel high energy materials under basic conditions (pH > 8). At the same time, zero‐valent iron is expected to be active under neutral and acidic conditions.

Can the Gibbs Free Energy of Adsorption Be Predicted Efficiently and Accurately: An M05-2X DFT Study

This study presents new insight into the prediction of partitioning of organic compounds between a carbon surface (soot) and water, and it also sheds light on the sluggish desorption of interacting molecules from activated and nonactivated carbon surfaces. This paper provides details about the structure and interactions of benzene, polycyclic aromatic hydrocarbons, and aromatic nitrocompounds with a carbon surface modeled by coronene using a density functional theory approach along with the M05-2X functional. The adsorption was studied in vacuum and from water solution. The molecules studied are physisorbed on the carbon surface. While the intermolecular interactions of benzene and hydrocarbons are governed by dispersion forces, nitrocompounds are adsorbed also due to quite strong electrostatic interactions with all types of carbon surfaces. On the basis of these results, we conclude that the method of prediction presented in this study allows one to approach the experimental level of accuracy in predicting thermodynamic parameters of adsorption on a carbon surface from the gas phase. The empirical modification of the polarized continuum model leads also to a quantitative agreement with the experimental data for the Gibbs free energy values of the adsorption from water solution.

Application of Quantum Chemical Approximations to Environmental Problems: Prediction of Water Solubility for Nitro Compounds

Water solubility values for 27 nitro compounds with experimentally measured values were computed using the conductor-like screening model for real solvent (COSMO-RS) based on the density functional theory and COSMO technique. We have found that the accuracy of the COSMO-RS approach for prediction of water solubility of liquid nitro compounds is impressively high (the errors are lower than 0.1 LU). However, for some solid nitro compounds, especially nitramines, there is sufficient disagreement between calculated and experimental values. In order to increase the accuracy of predictions the quantitative structure-property relationship (QSPR) part of the COSMO-RS approach has been modified. The solubility values calculated by the modified COSMO-RS method have shown much better agreement with the experimental values (the mean absolute errors are lower than 0.5 LU). Furthermore, this technique has been used for prediction of water solubility for an expanded set of 23 nitro compounds including nitroaromatic, nitramines, nitroanisoles, nitrogen rich compounds, and some their nitroso and amino derivatives with unknown experimental values. The solubility values predicted using the proposed computational technique could be useful for the determination of the environmental fate of military and industrial wastes and the development of remediation strategies for contaminated soils and waters. This predictive capability is especially important for unstable compounds and for compounds that have yet to be synthesized.

DFT M06-2X investigation of alkaline hydrolysis of nitroaromatic compounds

The nitroaromatic compounds 2,4,6-trinitrotoluene (TNT), 2,4-dinitrotoluene (DNT) and 2,4-dinitroanisole (DNAN) are potential environmental contaminants and their transformations under a variety of environmental conditions are consequently of great interest. One possible method to safely degrade these nitrocompounds is alkaline hydrolysis. A mechanism of the initial stages of this reaction was investigated computationally. Simulations of UV-VIS and NMR spectra for this mechanism were also produced. The results obtained were compared to available experimental data on the alkaline hydrolysis of TNT and suggest that the formation of Meisenheimer complexes and an anion of TNT are potential first-step intermediates in the reaction path. As the reaction proceeds, computational results indicate that polynegative complexes dominate the degradation pathway, followed by cycles of carbon chain opening and breaking. A second possible pathway was identified that leads to polymeric products through Janovsky complex formation. Results from this study indicate that the order of increasing resistance to alkaline hydrolysis is TNT, DNT and DNAN.

Theoretical study of ionization and one‐electron oxidation potentials of N‐heterocyclic compounds

A number of density functionals was utilized to predict gas‐phase adiabatic ionization potentials (IPs) for nitrogen‐rich heterocyclic compounds. Various solvation models were applied to the calculation of difference in free energies of solvation of oxidized and reduced forms of heterocyclic compounds in acetonitrile (AN) for correct reproduction of their standard oxidation potentials. We developed generally applicable protocols that could successfully predict the gas‐phase adiabatic ionization potentials of nitrogen‐rich heterocyclic compounds and their standard oxidation potentials in AN. This approach is supported by a MPW1K/6‐31+G(d) level of theory which uses SMD(UA0) approximation for estimation of solvation energy of neutral molecules and PCM(UA0) model for ionized ones. The mean absolute derivation (MAD) and root mean square error (RMSE) of the current theoretical models for IP are equal to 0.22 V and 0.26, respectively, and for oxidation potentials MAD = 0.13 V and RMSE = 0.17.

Evaluation of the dependence of aqueous solubility of nitro compounds on temperature and salinity: A COSMO-RS simulation

The solubility in pure and saline water at various temperatures was calculated for selected nitro compounds (nitrobenzene, 1,3,5-trinitrobenzene, 2-nitrotoluene, 3-nitrotoluene, 4-nitrotoluene, 2,4-dinitrotoluene, 2,6-dinitrotoluene, 2,3-dinitrotoluene, 3,4-dinitrotoluene, 2,4,6-trinitrotoluene) using the Conductor-like Screening model for Real Solvents (COSMO-RS). The results obtained were compared with experimental values. The COSMO-RS predictions have shown high accuracy in reproducing the trends of aqueous solubilities for both temperature and salinity. The proposed methodology was then applied to predict the aqueous solubilities of 19 nitro compounds in the temperature range of 5-50°C in saline solutions. The salting-out parameters of the Setschenow equation were also calculated. The predicted salting-out parameters were overestimated when compared to the measured values, but these parameters can still be used for qualitative estimation of the trends.

Predictions of Gibbs Free Energies for the Adsorption of Polyaromatic and Nitroaromatic Environmental Contaminants on Carbonaceous Materials: Efficient Computational Approach

The adsorption of benzene, polycyclic aromatic hydrocarbons (PAHs), and nitroaromatic compounds (NACs) on the carbonaceous surfaces from the gas phase and water solution was investigated. Several different levels of theory were applied, including DFT-, MP2-, and CCSD(T)-based methods, to find an approach that is computationally inexpensive and can provide accurate thermodynamic parameters for studied adsorption phenomena. The methods and techniques used (including cluster and periodic approximations) were evaluated on the basis of comparison with available experimental data. The optimized structures of calculated complexes are obtained, and the interaction energies and Gibbs free energies are predicted. Good agreement was revealed for the theoretical and experimental adsorption energies of benzene and PAHs adsorbed on the carbon surfaces. The adsorption of benzene, PAHs, and NACs on carbon is suggested to be effective from the gas phase for all studied compounds and for PAHs and NACs also from water solution at room temperature.

Application of Random Forest and Multiple Linear Regression Techniques to QSPR Prediction of an Aqueous Solubility for Military Compounds

The relationship between the aqueous solubility of more than two thousand eight hundred organic compounds and their structures was investigated using a QSPR approach based on Simplex Representation of Molecular Structure (SiRMS). The dataset consists of 2537 diverse organic compounds. Multiple Linear Regression (MLR) and Random Forest (RF) methods were used for statistical modeling at the 2D level of representation of molecular structure. Statistical characteristics of the best models are quite good (MLR method: R2=0.85, Q2=0.83; RF method: R2=0.99, R2oob=0.88). The external validation set of 301 compounds (including 47 nitro‐, nitroso‐ and nitrogen‐rich compounds of military interest) which were not included in the training set and modeling process, was used for evaluation of the models predictivity. Thus, well‐fitted and robust (R2test(MLR)=0.76 and R2test(RF)=0.82) models were obtained for both statistical techniques using descriptors based on the topological structural information only. The predicted solubility values for military compounds are in good agreement with experimental ones. Developed QSPR models represent powerful and easy‐to‐use virtual screening tool that can be recommended for prediction of aqueous solubility.

Comprehensive Investigations of Kinetics of Alkaline Hydrolysis of TNT (2,4,6-Trinitrotoluene), DNT (2,4-Dinitrotoluene), and DNAN (2,4-Dinitroanisole)

Combined experimental and computational techniques were used to analyze multistep chemical reactions in the alkaline hydrolysis of three nitroaromatic compounds: 2,4,6-trinitrotoluene (TNT), 2,4-dinitrotoluene (DNT), and 2,4-dinitroanisole (DNAN). The study reveals common features and differences in the kinetic behavior of these compounds. The analysis of the predicted pathways includes modeling of the reactions, along with simulation of UV-vis spectra, experimental monitoring of reactions using LC/MS techniques, development of the kinetic model by designing and solving the system of differential equations, and obtaining computationally predicted kinetics for decay and accumulation of reactants and products. Obtained results suggest that DNT and DNAN are more resistant to alkaline hydrolysis than TNT. The direct substitution of a nitro group by a hydroxide represents the most favorable pathway for all considered compounds. The formation of Meisenheimer complexes leads to the kinetic first-step intermediates in the hydrolysis of TNT. Janovsky complexes can also be formed during hydrolysis of TNT and DNT but in small quantities. Methyl group abstraction is one of the suggested pathways of DNAN transformation during alkaline hydrolysis.

New QSPR equations for prediction of aqueous solubility for military compounds

The development of a new quantitative structure-property relationship (QSPR) model to predict aqueous solubility (S(w)) accurately for compounds of military interest is presented. The ability of the new model to predict solubility is assessed and compared to available experimental data. A large set of structurally diverse organic compounds was used in this analysis. SiRMS methodology was employed to develop PLS models based on 135 training compounds and predictive accuracy was tested for 155 compounds selected for that purpose. The use of descriptors calculated only from the 2D level of representation of molecular structure produces a well-fitted and robust QSPR model (R(2)=0.90; Q(2)=0.87). Predictive ability for the model produced in this study on external test set (R(test)(2)=0.81) is comparable to the predictive ability of EPI Suite 4.0. Consensus solubility predictions using SiRMS and EPI models for 25 compounds of military interest (not included into the training set) have been completed.