Peisheng Ma

Estimations of enthalpies of vaporization of pure compounds at different temperatures by a corresponding-states group-contribution method

Abstract Two new equations (CSGC-HW1 and CSGC-HW2) for estimating enthalpies of vaporization at different temperatures with a corresponding-states group-contribution method (CSGC) are proposed. Group-contribution parameters for 76 groups were obtained by correlating the experimental enthalpies of vaporization at different temperatures (a total of 1647 data points) of 405 pure compounds including various alkanes, alkenes, cyclohydrocarbons, aromatic and oxygenated hydrocarbons as well as compounds containing sulphur, nitrogen, and halogen. Accurate estimations of enthalpies of vaporization of pure compounds are given by the CSGC-HW1 equation, which requires the normal boiling point datum and the experimental enthalpy of vaporization of the compound at the boiling point, Δ v H b . If the experimental Δ v H b is not available, the CSGC-HW2 equation can be used to yield satisfactory estimates.

Topological study on the toxicity of ionic liquids on Vibrio fischeri by the quantitative structure–activity relationship method

As environmentally friendly solvents, ionic liquids (ILs) are unlikely to act as air contaminants or inhalation toxins resulting from their negligible vapor pressure and excellent thermal stability. However, they can be potential water contaminants because of their considerable solubility in water; therefore, a proper toxicological assessment of ILs is essential. The environmental fate of ILs is studied by quantitative structure-activity relationship (QSAR) method. A multiple linear regression (MLR) model is obtained by topological method using toxicity data of 157 ILs on Vibrio fischeri, which are composed of 74 cations and 22 anions. The topological index developed in our research group is used for predicting the V. fischeri toxicity for the first time. The MLR model is precise for estimating LogEC50 of ILs on V. fischeri with square of correlation coefficient (R(2)) = 0.908 and the average absolute error (AAE) = 0.278.

Diffusion coefficients of l-proline, l-threonine and l-arginine in aqueous solutions at 25°C

Abstract The mutual diffusion coefficients of l -proline, l -threonine and l -arginine in aqueous solution at 25°C were determined by the metallic diaphragm cell method, which is characterized by accuracy, promptness and convenience. The viscosity of these solutions was also determined. Based on these data, a semi-empirical model for correlating the diffusion coefficients of amino acids in their aqueous solutions at 25°C was developed. The model was compared with literature data. Results showed that this model provides significant improvement in correlation of diffusion coefficients for many systems as compared with the original Gordon model, a semi-empirical model.

A new Corresponding-States Group-Contribution method (CSGC) for estimating vapor pressures of pure compounds

Abstract A new method was proposed by combining the Corresponding-States Theorem with the Group-Contribution Method (CSGC) and a new vapor-pressure equation was developed for estimating purpose. Group-contribution parameters of 117 functional groups were obtained by correlating 6540 datum points of experimental vapor pressures for 462 compounds, including alkanes, alkenes, cyclohydrocarbons, aromatics, halogenated hydrocarbons and compounds containing oxygen, sulfur and nitrogen etc. Predicted results for vapor pressures of 28 compounds show that the proposed equation with the normal boiling point temperature T b only is superior to the conventional Corresponding-States Methods. Furthermore, satisfactory results were also obtained by the proposed equation in estimating high vapor pressures of several compounds.

Quantitative Structure-Activity Relationship for High Affinity 5-HT1A Receptor Ligands Based on Norm Indexes.

Arylpiperazine derivatives are promising 5-hydroxytryptamine (5-HT) receptor ligands which can inhibit serotonin reuptake effectively. In this work, some norm index descriptors were proposed and further utilized to develop a model for predicting 5-HT1A receptor affinity (pKi) of 88 arylpiperazine derivatives. Results showed that this new model could provide satisfactory predictions with the square of the correction coefficient (R(2)) of 0.8891 and the squared correlation coefficient of cross-validation (Q(2)) of 0.8082, respectively. In addition, the applicability domain of this model was validated by using the leverage approach and results which suggested potential large scale for further utilization of this model. The results of statistical values and validation tests demonstrated that our proposed norm index based model could be successfully applied for predicting the affinity 5-HT1A receptor ligands of arylpiperazine derivatives.

Estimations of surface tensions at different temperatures by a corresponding-states group-contribution method

Two new equations (CSGC-ST1 and CSGC-ST2) for estimating surface tensions by applying a corresponding-states group-contribution method (CSGC) were proposed. The CSGC-ST1 equation needs only the normal boiling point data of substances to estimate accurately the surface tensions of pure substances at different temperatures. On the other hand, if the surface tension data at 20°C are available, the CSGC-ST2 equation yields estimates with higher accuracies. Group-contribution parameters for 86 groups were obtained by correlating the surface tension experimental data at different temperatures (totally 3699 datum points) of 427 pure substances including various alkanes, alkenes, cyclo-, aromatic and oxygenated hydrocarbons as well as compounds containing sulfur, nitrogen and halogen. Correlated results showed that the new models provided a wide-range of applicability and their estimation accuracies were significantly superior over the conventional corresponding-states methods currently used.

Effect of pyrolysis temperature on characteristics and aromatic contaminants adsorption behavior of magnetic biochar derived from pyrolysis oil distillation residue.

The magnetic biochars were easily fabricated by thermal pyrolysis of Fe(NO3)3 and distillation residue derived from rice straw pyrolysis oil at 400, 600 and 800°C. The effects of pyrolysis temperature on characteristics of magnetic biochars as well as adsorption capacity for aromatic contaminants (i.e., anisole, phenol and guaiacol) were investigated carefully. The degree of carbonization of magnetic biochars become higher as pyrolysis temperature increasing. The magnetic biochar reached the largest surface area and pore volume at the pyrolysis temperature of 600°C due to pores blocking in biochar during pyrolysis at 800°C. Based on batch adsorption experiments, the used adsorbent could be magnetically separated and the adsorption capacity of anisole on magnetic biochars was stronger than that of phenol and guaiacol. The properties of magnetic biochar, including surface area, pore volume, aromaticity, grapheme-like-structure and iron oxide (γ-Fe2O3) particles, showed pronounced effects on the adsorption performance of aromatic contaminants.

Thermogravimetric investigation of the co-combustion between the pyrolysis oil distillation residue and lignite

Co-combustion of lignite with distillation residue derived from rice straw pyrolysis oil was investigated by non-isothermal thermogravimetric analysis (TGA). The addition of distillation residue improved the reactivity and combustion efficiency of lignite, such as increasing the weight loss rate at peak temperature and decreasing the burnout temperature and the total burnout. With increasing distillation residue content in the blended fuels, the synergistic interactions between distillation residue and lignite firstly increased and then decreased during co-combustion stage. Results of XRF, FTIR, (13)C NMR and SEM analysis indicated that chemical structure, mineral components and morphology of samples have great influence on the synergistic interactions. The combustion mechanisms and kinetic parameters were calculated by the Coats Redfern model, suggesting that the lowest apparent activation energy (120.19kJ/mol) for the blended fuels was obtained by blending 60wt.% distillation residue during main co-combustion stage.

Predicting the activity of hydroxamic acid analogues

Abstract In a novel therapeutic approach, hydroxamic acids analogues such as Histone deacetylases (HDACs) inhibitors, have been identified as attractive drugs to treat cancer and related diseases. In this work, based on the Euclidean distance matrix and property matrix of HDACs inhibitors’ structures, a new norm index was proposed, and then according which the pIC50 values (the half maximal inhibitory concentration) of 143 HDACs inhibitors were predicted using the quantitive structure–activity relationship (QSAR) method. Results suggested that this model could give satisfactory prediction effect with high relationship coefficient of leave-one-out/5-fold/10-fold cross-validation. Moreover, the application domain of this model was validated to be satisfaction by applying the leverage approach. The statistical and comparison results showed that this new model could effectively improve the accuracy and predictive ability for predicting the bioactivity of HDACs inhibitors. All the above could demonstrate that this developed QSAR model could be effectively utilised for the description of structure–activity relationship at the molecular level. Therefore, this norm index-based QSAR model could provide an effective method for predicting the bioactivity of hydroxamic acids analogues drugs, which also might be valuable for the design of potential leading drugs.