Photocatalytic degradation of crystal violet by thiourea-doped TiO2 thin film fixed bed photoreactors under visible irradiation: Optimisation using central composite designs and kinetics studies by multivariate curve resolution

In this study, optimisation of the photocatalytic behaviour of crystal violet (CV) by thiourea (Tu)-codoped TiO2 thin film in fixed bed photoreactor was investigated by central composite designs (CCDs). The effective variables were pH, the concentration of CV dye, flow rate and reaction time. The results of the CCD model showed a good agreement with experimental results, with R2 = 0.9680 (p < 0.0001) and maximum degradation efficiency was obtained at the optimum conditions: dye concentration 8.5 mg/L, pH 9, flow rate 6 mL/min and reaction time 80 min. Subsequently, three absorbing chemical compounds presented in the degradation reaction were obtained by using singular value decomposition (SVD) method and evolving factor analysis (EFA). Then a multivariate curve resolution with alternating least squares (MCR-ALS) was performed to achieve the concentration and spectral profiles for each component. Finally, a hard modelling method was applied to determine the kinetic constants of distinct reactions occurred in the photocatalytic degradation process. The reaction rate constants were calculated for the first and second steps as k1 = 0.08327 (SD = ±0.0015) /min and k2 = 0.045 (SD = ±0.0006)/min, respectively.               KEY WORDS: TiO2 thin film, Photocatalytic degradation, Central composite designs, Multivariate curve resolution, Kinetic studying Bull. Chem. Soc. Ethiop. 2017, 31(3), 383-396.DOI: http://dx.doi.org/10.4314/bcse.v31i3.

Photocatalytic degradation of crystal violet by thiourea-doped TiO2 thin film fixed bed photoreactors under visible irradiation: Optimisation using central composite designs and kinetics studies by multivariate curve resolution

In this study, optimisation of the photocatalytic behaviour of crystal violet (CV) by thiourea (Tu)-codoped TiO2 thin film in fixed bed photoreactor was investigated by central composite designs (CCDs). The effective variables were pH, the concentration of CV dye, flow rate and reaction time. The results of the CCD model showed a good agreement with experimental results, with R2 = 0.9680 (p < 0.0001) and maximum degradation efficiency was obtained at the optimum conditions: dye concentration 8.5 mg/L, pH 9, flow rate 6 mL/min and reaction time 80 min. Subsequently, three absorbing chemical compounds presented in the degradation reaction were obtained by using singular value decomposition (SVD) method and evolving factor analysis (EFA). Then a multivariate curve resolution with alternating least squares (MCR-ALS) was performed to achieve the concentration and spectral profiles for each component. Finally, a hard modelling method was applied to determine the kinetic constants of distinct reactions occurred in the photocatalytic degradation process. The reaction rate constants were calculated for the first and second steps as k1 = 0.08327 (SD = ±0.0015) /min and k2 = 0.045 (SD = ±0.0006)/min, respectively

Determination of the Acidity Constant of Drugs Using the Hard–Soft Net Analyte Signal Method

The newly proposed hard–soft net analyte signal (HS-NAS) method was employed to determine the acidity constants of drugs. The spectrophotometric data obtained through monitoring of the pH-metric titrations of the acids (both experimental and simulated data) were analyzed by the HS-NAS method, and accurate results were obtained. As experimental data sets, tetracycline as a triprotic acid and <i>p</i>-aminobenzoic acid, <i>m</i>-aminobenzoic acid, and piroxicam as diprotic acids were studied. In addition, the acidity constants of the drugs were determined in the presence of Triton X-100 as an inert light-absorbing interference. The data for such systems, which are rank-deficient in nature, were successfully analyzed by the HS-NAS method. This method is based on changing the acidity constants of the drugs to maximize the correlation coefficient between the NAS vector obtained for one species of the reaction and the theoretical concentration profile of that species. Unlike existing methods, it needs neither previous information on the pure spectra of the species (as required for rank annihilation factor analysis) nor the hard models of all species contributing to the absorbance of the solution (as needed for the hard modeling method)

Prediction of <i>E</i>^T_N Polarity Scale of Ionic Liquids Using a QSPR Approach

A multiparameter quantitative model was developed to establish a relationship between structural descriptors of a set of 52 ionic liquids and their <i>E</i>^T_N polarity scale. Theoretical descriptors were extracted by Dragon software and the <i>E</i>^T_N model was obtained using multiple linear regression approach. After molecular modeling, four significant descriptors were identified which are related to the <i>E</i>^T_N values of the ionic liquids and demonstrates good fit statistics and accurate predictions. The stability and prediction ability of the <i>E</i>^T_N model was evaluated using various common statistical methods such as cross-validation, external validation, and Y-randomization test. As another indicator of model’s validity, the leverage and standardized residual confirmed the presence of almost all 52 ILs in the applicability domain of the proposed model

Assembly of cyclometalated platinum(II) complexes via 1,1′- bis(diphenylphosphino)ferrocene ligand: Kinetics and mechanisms.

The kinetics and mechanism of the reaction of the cyclometalated complexes [PtAr(C-N)(SMe2)], 1, in which Ar is Ph, p-MeC6H 4, or p-MeOC6H4, and C-N is either ppy (deprotonated 2-phenylpyridine) or bhq (deprotonated benzo[h]quinoline), with 1,1′-bis(diphenylphosphino)ferrocene, dppf, were studied using UV-visible and 31P NMR spectroscopies. When 0.5 equiv of dppf was added, the binuclear Pt(II) complex [Pt2Ar2(C-N)2(μ- dppf)], 2, was formed in a good yield. The complexes were fully characterized using multinuclear (1H, 31P, and 195Pt) NMR spectroscopy, and the structure of complex [Pt2(p-MeOC 6H4)2(bhq)2(μ-dppf)], 2c′•CH2Cl2, was further identified by X-ray crystallography. On the basis of low-temperature 31P NMR studies involving the starting complex [Pt(p-MeC6H4)(ppy)(SMe 2)], 1b, we suggest that dppf displaces the labile ligand SMe 2 to give an uncommon complex, [Pt(p-MeC6H 4)(ppy)(dppf-κ1P)], A, in which dppf- κ1P is a monodentate dppf ligand, which rapidly forms an equilibrium with the chelating dppf isomer complex [Pt(p-MeC6H 4)(dppf)(ppy-κ1C)], B, in which ppy- κ1C is the deprotonated ppy ligand that is C-ligated with the dangling N atom. In the second step, A is reacted with the remaining second half of starting complex 1b to give the final Pt(II)-Pt(II) binuclear complex [Pt2(p-MeC6H4)2(ppy) 2(μ-dppf)], 2b. A competitive-consecutive second-order reaction mechanism was suggested for the reaction using chemometric studies, and the rate constants at 5 °C for first and second steps were estimated as k 2 = 10.7 ± 0.2 L mol-1 s-1 and k 2′ = 0.68 ± 0.05 L mol-1 s-1, respectively. When the starting complex [Pt(p-MeC6H 4)(ppy)(SMe2)], 1b, was reacted with 1 equiv of dppf, similarly the complex A, in equilibrium with B, was formed first, with the rate constant at 5 °C being k2 = 10.5 ± 0.5 L mol-1 s-1, estimated using UV-visible spectroscopy. Subsequently, however, A and B would slowly and reversibly react with each other to form a new species, C, the structure of which, on the basis of 31P and 195Pt NMR spectra, was proposed to be [(p-MeC6H4)(ppy)Pt(μ- dppf)Pt(p-MeC6H4)(ppy-κ1C)(dppf- κ1P)]; the same results were obtained when more than 1, e.g., 2, equiv of dppf was used, with a similar rate constant of k2 = 10.6 ± 0.6 L mol-1 s-1. The complexes 1b and 2b were shown to have some interesting photophysical properties as investigated by absorption and electroluminescence spectroscopies