Qualitative analysis of aromatic compounds via 1D TOCSY techniques

The aromatic compounds,including o-xylene,m-xylene,p-xylene,and ethylbenzene,primarily originate from the catalytic reforming of crude oil,and have a wide variety of applications.However,because of similar physical and chemical properties,these compounds are difficult to be identified by gas chromatography(GC)without standard samples.With the development of modern nuclear magnetic resonance(NMR)techniques,NMR has emerged as a powerful and efficient tool for the rapid analysis of complex and crude mixtures without purification.In this study,the parameters of one-dimensional(1D)total correlation spectroscopy(TOCSY)NMR techniques,including 1D selective gradient TOCSY and 1D chemicalshift-selective filtration(CSSF)with TOCSY,were optimized to obtain comprehensive molecular structure information.The results indicate that the overlapped signals in NMR spectra of nonpolar aromatic compounds(including o-xylene,m-xylene,p-xylene and ethylbenzene),polar aromatic compounds(benzyl alcohol,benzaldehyde,benzoic acid),and aromatic compounds with additional conjugated bonds(styrene)can be resolved in 1D TOCSY.More importantly,full molecular structures can be clearly distinguished by setting appropriate mixing time in 1D TOCSY.This approach simplifies the NMR spectra,provides structural information of entire molecules,and can be applied for the analysis of other structural isomers.

Simultaneous biodegradation of nitrogen-containing aromatic compounds in a sequencing batch bioreactor

Many nitrogen-containing aromatic compounds （NACs）, such as nitrobenzene （NB）, 4-nitrophenol （4-NP）, aniline （AN）, and 2,4-dinitrophenol （2,4-DNP）, are environmentally hazardous, and their removal from contaminated water is one of the main challenges facing wastewater treatment plants. In this study, synthetic wastewater containing NB, 4-NP, 2,4-DNP, and AN at concentrations ranging from 50 to 180 mg/L was fed into a sequencing batch reactor （SBR）. Analyses of the SBR system indicated that it simultaneously removed more than 99% of the NACs at loading rates of 0.36 kg NB/（m^3·d）, 0.3 kg 4-NP/（m^3·d）, 0.25 kg AN/（m^3·d）, and 0.1 kg 2,4-DNP/（m^3·d）. Bacterial groups of Bacteriodetes, Candidate division TM7, α-Proteobacteria, and β-Proteobacteria were dominant in the clone libraries of 16S rRNA genes retrieved from the microbial communities in the SBR system. ＂Cycle tests＂ designed to alter feeding and aeration parameters of the SBR system demonstrated that the resident microbial biome of the SBR system responded rapidly to changing conditions. Consumption of O2 was concomitant with the apparent mineralization of NACs. Aromatic ring-cleaving dioxygenase activities suggested that （1） AN and NB were degraded via catechol 2,3-dioxygenase; （2） 4-NP was degraded via 1,2,4-benzentriol 1,2-dioxygenase; and （3） 2,4-DNP was degraded via an unresolved pathway.

Aromatic compound degradation by iron reducing bacteria isolated from irrigated tropical paddy soils

Forty-six candidate phenol/benzoate degrading-iron reducing bacteria were isolated from long term irrigated tropical paddy soils by enrichment procedures.Pure cultures and some prepared mixed cultures were examined for ferric oxide reduction and phenol/benzoate degradation.All the isolates were iron reducers,but only 56.5%could couple iron reduction to phenol and/or benzoate degradation,as evidenced by depletion of phenol and benzoate after one week incubation.Analysis of degradative capability using Biolog...

Accelerated degradation of a variety of aromatic compounds by Spirodela polyrrhiza-bacterial associations and contribution of root exudates released from S. polyrrhiza

Removal experiments of phenol, aniline, 2,4-dichlorophenol, nonylphenol and bisphenol A （BPA） using Spirodela polyrrhiza- bacterial associations revealed that all compounds but BPA underwent accelerated removal. The mechanisms differed depending on the substrates. It was found that S. polyrrhiza has a great ability to release phenolic compound-rich root exudates, and the exudates seem to stimulate bacterial degradation of a variety of aromatic compounds.

Comparative study of four QSAR models of aromatic compounds to aquatic organisms

Quantitative structure activity relationships(QSARs)were developed for 43 aromatic compounds toxicity to Photobacterium phosphoreum and Daphnia magna based on four methods: octanol/water partition coefficient, linear solvation energy relationship, molecular connectivity index and group contribution. Through the evaluation of four QSAR methods, LSER was proved to be the best. And it applied to the widest range of chemicals with the greatest accuracy.

A mild,efficient and selective iodination of aromatic compounds using iodine and 1,4-bis(triphenylphosphonium)-2-butene peroxodisulfate

A simple and efficient method for the iodination of aromatic compounds has been achieved in the presence of iodine and 1,4- bis（triphenylphosphonium）-2-butene peroxodisulfate.

Preparation of Polymeric Monolithic Column and Application to the Resolution of Aromatic Compounds in Capillary Electrochromatography

Polymeric monolithic capillary column-poly(GMA-co-EDMA-co-AMPS) was prepared andused for resolution of aromatic compounds (benzalcohol, 2-phenylethanol, toluene, ethylbenzene).

Quantitative Structure-biodegradability Relationship Study about the Aerobic Biodegradation of Some Aromatic Compounds

10 quantum chemical descriptors of 21 aromatic compounds have been calculated by the semi-empirical quantum chemical method AM1. The Quantitative Structure-Biodegradability Relationships （QSBR） studies were performed by the multiple linear regression （MLR）, principal component regression （PCR） and back propagation artificial neural network （BP-ANN）, respectively. The root mean square error （RMSE） of the training and validation sets of the BP-ANN model are 0.1363 and 0.0244, the mean absolute percentage errors （MAPE） are 0.1638 and 0.0326, the squared correlation coefficients （R^2） are 0.9853 and 0.9996, respectively. The results show that the BP-ANN model achieved a better prediction result than those of MLR and PCR. In addition, some insights into the structural factors affecting the aerobic biodegradation mechanism were discussed in detail.

Component characteristics of polycyclic aromatic compounds in sediments of the South Mid-Atlantic Ridge

10 samples of sediments obtained from the South Mid-Atlantic Ridge were measured for the abundances and distributions of polycyclic aromatic compounds（PAHs）. The total concentrations of PAHs（∑PAHs） ranged from 2.768 to 9.826 μg/g dry sediment. The ∑PAHs was higher in sample 22V-TVG10 and sample 26V-TVG05 which were close to hydrothermal fields, with the lowest value in sample 22V-TVG14 which was farthest from hydrothermal fields, suggesting a probable hydrothermal origin of ∑PAHs of samples. Approximately nine kinds of PAHs were identified, and low molecular mass tricyclic and tetracyclic aromatic compounds were predominant in the samples. The concentrations of fluoranthene which were typical as hydrothermal alteration compounds were the highest among PAHs with dry weight between 0.913–3.157 μg/g. The phenanthrene homologue was most abundant in the samples, and the ratios between parent phenanthrene and methylphenanthrene which probably reflected the degree of hydrothermal alteration ranged from 0.097 to 1.602. The sample 22V-TVG10 possessing a maximum ratio value showed the intense influence of the hydrothermal alteration on this sample, which might further imply that PAHs in sediments were mainly derived from the hydrothermal alteration.

Quantitative Structure-activity Relationship(QSAR) Study of Toxicity of Substituted Aromatic Compounds to Photobacterium Phosphoreum

With the artificial neural network（ANN） method combined with the multiple linear regression（MLR）,based on a series of quantum chemical descriptors and molecular connectivity indexes,quantitative structure-activity relationship（QSAR） models to predict the acute toxicity（-lgEC50） of substituted aromatic compounds to Photobacterium phosphoreum were established.Four molecular descriptors that appear in the MLR model,namely,the second order valence molecular connectivity index（2XV）,the energy of the highest occupied molecular orbital（EHOMO）,the logarithm of n-octyl alcohol/water partition coefficient（logKow） and the Connolly molecular area（MA）,were inputs of the ANN model.The root-mean-square error（RMSE） of the training and validation sets of the ANN model are 0.1359 and 0.2523,and the correlation coefficient（R） is 0.9810 and 0.8681,respectively.The leave-one-out（LOO） cross validated correlation coefficient（Q L2OO） of the MLR and ANN models is 0.6954 and 0.6708,respectively.The result showed that the two methods are complementary in the calculations.The regression method gave support to the neural network with physical explanation,and the neural network method gave a more accurate model for QSAR.In addition,some insights into the structural factors affecting the acute toxicity and toxicity mechanism of substituted aromatic compounds were discussed.

SYNTHESIS OF POLYSUBSTITUTED AROMATIC COMPOUNDS:Ⅰ.THE DIELS-ALDER REACTION OF SELENO SUBSTITUTED 3-SULFOLENES WITH DIMETHYL ACETYLENEDICARBOXYLATE

The seleno substituted aromatic compounds were prepared via the Diels-Alder reaction of seleno substituted 3-sulfolenes with dimethyl acetylenedicarboxylate followed by DDQ dehydrogenation.

Correlation of Quantitative Structure and Inhibition Phytotoxicity for Aromatic Compounds Using Ab Initio Method

29 aromatic compounds were computed at the HF/6-31G^＊ level. Based on linear solvation energy theory firstly, the parameters of molecular structure were taken as theoretical descriptors, and the corresponding linear solvation energy relationship （LSER） （r^2= 0.8993, q^2=0.8559） between the structural parameters and inhibition phytotoxicity to the seed germination rate of cucumis （-lgGC50） was thus obtained. Then the parameters of molecular structure and thermodynamics were taken as theoretical descriptors, and as a result the other corresponding correlation equation （r^2=0.9268, q^2=0.8960） relating to -lgGC50 was achieved. The two equations obtained in this work by HF/6-31G^＊ are both more advantageous than that from AM 1.

Benzylation of Aromatic Compounds with Benzyl Chloride Catalyzed by Nafion/SiO_2 Nanocomposite Catalyst

In the presence of Nafion/SiO2 nanocomposite catalyst, the benzylation of aromatic compounds with benzyl chloride proceeded to afford diphenylmethane derivatives in high yields. The catalyst showed high catalytic activity not only for electron-rich aromatic compounds, but also for electron-poor aromatic compounds. Under identical conditions, the self-benzylation of benzyl chloride, and dibenzylation and/or multi-benzylation of aromatic compounds were negligible.

Monitoring of Potential carcinogenic polycyclic aromatic compounds in the emission from coal combustion

A comprehensive summary for the study on the monitoring of potential carcinogenicpolycyclic aromatic compounds (PACs) in the emission of coal combustion is presented in this pa-per. Some PACs in the stack gases of coal-fired boiler have been determined with a procedure whichconsists of isokinetic stack sampling, extraction, preseparation and some instrumental analysis stepssuch as gas chromatographylmass spectrometry (GC/MS), high performance liquid chromatographyfHPLC), room temperature phosphorimetry (RTP) and synchronous fluorescence spectroscopy (SFS)and so on. The results indicate that the air pollution of PACs in China are related closely to thecoal combustion.

Development of QSAR Model for Predicting the Mutagenicity of Aromatic Compounds

Quantitative structure-activity relationship （QSAR） model was developed for pre- dicting the mutagenicity of aromatic compounds. The log revertants data of S. typhimurium TA98 strain from Ames test have been collected. 225 aromatic compounds were randomly divided into the training set with 186 molecules and test set with 39 molecules. Multiple linear regression （MLR） analysis was used to select six descriptors from thousands of descriptors calculated by semi- empirical AM l and E-dragon methods. The final QSAR model with six descriptors was internal and external validated. In addition, to validate the utility of our QSAR model for the chemical evaluation, three aromatic compounds were taken to test the predictive ability and reliability of the model experimentally. The compounds selected for testing were not based on the predictions, thus spanning the range of predicted probabilities. The subsequently generated results of the Ames test were in good correspondence with the predictions and confirmed this approach as a useful means of predicting likely mutagenic risk of aromatic compounds.

A NEW METHOD FOR SYNTHESIS OF O-ISOPROPYL SUBSTITUTED AROMATIC COMPOUNDS

Heteroatom-directed aromatic lithiation reactions used for the regiospecific synthesis of o-isopropyl substituted phenolic and benzyl alcoholic compounds are described.

Synergistic Effect in Special Selectivity Mixed Gas Chromatographic Stationary Phase in the Separation of Aromatic Compounds

The gas chromatographic separations of aromatic compounds using special mixed stationary phases consisting of pp-beta-CD+AgNO3, pp-beta-CD+TINO3, pp-beta-CD+di-n-butly phthalate, pp-beta-CD+BPBHpB liquid crystalline, and bentone-34+AgNO3 were investigated. Besides pp-beta-CD+di-n-butyl phthalate, most of the separations deviated from the additivity and a synergistic effect was observed. The separation effects depend on the temperature and how mixing is accomplished.

Aromatic compounds-mediated synthesis of anatase-free hierarchical TS-1 zeolite:Exploring design strategies via machine learning and enhanced catalytic performance

Simultaneous achievement of constructing mesopores and eliminating anatase is a long-term pursuit for enhancing the catalytic performance of TS-1.Here,we developed an aromatic compounds-mediated synthesis method to prepare anatase-free and hierarchical TS-1 for olefin epoxidation.A series of hierarchical TS-1 zeolites were prepared by introducing aromatic compounds containing different functional groups via the crystallization process.The formation of intercrystalline mesopores and insertion of titanium into framework were facilitated at different extent.The synergistic coordination of carboxyl and hydroxyl in aromatic compounds with Ti(OH)4 realizes the uniform distribution of titanium species and eliminates the generation of anatase.Noteworthily,eight machine learning models were trained to reveal the mechanism of additive functional groups and preparation conditions on anatase formation and microstructure optimization.The prediction accuracy of most models can reach more than 80%.Benefiting from the larger mesopore volumes(0.37 cm3⋅g−1)and higher content of framework Ti species,TS-DHBDC-48h samples exhibit a higher catalytic performance than other zeolites,giving 1-hexene conversion of 49.3%and 1,2-epoxyhenane selectivity of 99.9%.The paper provides a facile aromatic compounds-mediated synthesis strategy and promotes the application of machine learning toward the design and optimization of new zeolites.

A Green and Efficient Trinitration System for Aromatic Compounds with Bi（NO3）3·5H2O/[HMIMICIO4 as Catalyst in HNO3/Ac2O

To investigate the green trinitration method of aromatic compounds, with Lewis acid/ionic liquid as catalyst and HNOJAc2O as nitration reagent, a Lewis acid/ionic liquid/HNO3/Ac2O system was established. In various combinations of Lewis acids and ionic liquids, Bi（NO3）3-5H2O/[HMIM]CIO4 proved to be a very efficient catalyst for the trinitration of activated aromatic compounds and reusable for 3 times. Reaction conditions for the trinitration were optimized and yields of the trinitro products were from mild to excellent. This sulfuric acid-free system has the advantages of strong trinitration ability, low environment pollution, low toxicity, low cost and high potential for industrial application.

Diels-Alder addition of some 6-and 5-member ring aromatic compounds on the Si(001)-2×1 surface: dependence of the binding energy on the resonance energy of the aromatic compounds

An energy decomposition scheme is proposed for understanding of the relative low binding energy of the [4+2] cycloaddition of benzene on the Si(001)-2×1 surface. By means of density functional cluster model calculations, this scheme is demonstrated to be applicable to some other 6- and 5-member ring aromatic compounds, giving a trend that the binding energy of the [4+2] cycloaddition products of those aromatic compounds on the Si(001) surface depends strongly on their resonance energy.