Effect of microstructure in mesoporous adsorbents on the adsorption of low concentrations of VOCs: An experimental and simulation study.

This study evaluated the adsorption of five volatile organic compounds (VOCs) on Opoka, precipitated silica, and palygorskite, to elucidate the effect of their pore size on VOCs adsorption. The adsorption capacity of these adsorbents is not only highly correlated with their surface area and pore volume, but also notably improved by the presence of micropores. The variation in adsorption capacity for different VOCs was primarily influenced by their boiling point and polarity. Palygorskite, which had the smallest total pore volume (0.357 cm3/g) but the largest micropore volume (0.043 cm3/g) among the three adsorbents, exhibited the highest adsorption capacity for all tested VOCs. Additionally, the study constructed slit pore models of palygorskite with micropores (0.5 and 1.5 nm) and mesopores (3.0 and 6.0 nm), calculated and discussed the heat of adsorption, concentration distribution, and interaction energy of VOCs adsorbed on different pore models. The results revealed that the adsorption heat, concentration distribution, total interaction energy, and van der Waals energy decrease with increasing pore size. The concentration of VOCs in 0.5 nm pore was nearly three times that in 6.0 nm pore. This work can also provide guidance for further research on using adsorbents with mixed microporous and mesoporous structures to control VOCs.

[Rapid Quantitative Detection of Bacterial in Water Based on Multi-Wavelength Scattering Spectra].

The structures of bacterial cells are analyzed in this paper. The scattering components of individual cell were divided into two parts including external structure and internal structure. The interpretation model of bacteria about scattering light is established. The model is used to analyze the scattering light of Escherichia coli in the region of 400~900 nm. The average size of external structure and the internal structure can be obtained, and the ratio of the two parts is also obtained. According to the relationship of the optical density of single cell and the overall measurement, the concentration of bacterial can be obtained quickly. The maximum difference in all the concentrations of the bacteria repeated measurements is 1.83%; compared with the plate culture method, the measurement results were in the same order of magnitude, with relative error of 3.43%. The scattering light of Escherichia coli and Klebsiella pneumoniae are analyzed in different growth stages, the curves of the concentration and the size of the two species bacteria over time are obtained. The results can provide a quick way for the study of bacterial growth and technical support for rapid detection of bacteria in the water.

[Study of Rapid Species Identification of Bacteria in Water].

Multi-wavelength ultraviolet visible (UV-Vis) transmission spectra of bacteria combined the forward scattering and absorption properties of microbes, contains substantial information on size, shape, and the other chemical, physiological character of bacterial cells, has the bacterial species specificity, which can be applied to rapid species identification of bacterial microbes. Four different kinds of bacteria including Escherichia coli, Staphylococcus aureus, Salmonella typhimurium and Klebsiella pneumonia which were commonly existed in water were researched in this paper. Their multi-wavelength UV-Vis transmission spectra were measured and analyzed. The rapid identification method and model of bacteria were built which were based on support vector machine (SVM) and multi-wavelength UV-Vis transmission spectra of the bacteria. Using the internal cross validation based on grid search method of the training set for obtaining the best penalty factor C and the kernel parameter g, which the model needed. Established the bacteria fast identification model according to the optimal parameters and one-against-one classification method included in LibSVM. Using different experimental bacteria strains of transmission spectra as a test set of classification accuracy verification of the model, the analysis results showed that the bacterial rapid identification model built in this paper can identification the four kinds bacterial which chosen in this paper as the accuracy was 100%, and the model also can identified different subspecies of E. coli test set as the accuracy was 100%, proved the model had a good stability in identification bacterial species. In this paper, the research results of this study not only can provide a method for rapid identification and early warning of bacterial microbial in drinking water sources, but also can be used as the microbes identified in biomedical a simple, rapid and accurate means.