As volatile organic compounds (VOCs) are a major group of air pollutants, development of materials for efficient adsorption and removal of VOCs is of great significance in both environmental and analytical sciences. Here we report metal-organic frameworks (MOFs) MIL-101 for the effective adsorption of VOCs at atmospheric pressure. A simple device was designed for quartz crystal microbalance (QCM), and six VOCs with various functional groups and polarities, i.e., n-hexane, toluene, methanol, butanone, dichloromethane, and n-butylamine, were chosen as targets to probe the adsorption properties of MIL-101. The developed device allows measurement of the adsorption isotherms and monitoring of the dynamic process for the adsorption of VOCs on MOFs, and also provides a useful tool for characterization of MOFs. The adsorption isotherms of the VOCs on MIL-101 followed the Dubinin-Astakhov equation with the characteristic energy from 5.70 (methanol) to 9.13 kJ mol(-1) (n-butylamine), Astakhov exponent from 0.50 (n-butylamine) to 3.03 (n-hexane), and the limiting adsorption capacity from 0.08 (n-hexane) to 12.8 (n-butylamine) mmol g(-1). MIL-101 exhibited the strongest affinity to n-butylamine, but the weakest affinity to n-hexane. The determined Astakhov exponents and the isosteric heats of adsorption revealed the energetic heterogeneity of MIL-101. MIL-101 showed the most energetically homogeneous for n-hexane, but the most energetically heterogeneous for n-butylamine. The dynamic process of adsorption monitored by the QCM system demonstrated the distribution of the sorption sites within MIL-101. The metal sites within the MIL-101 were vital in adsorption process. MIL-101 gave much higher affinity and bigger adsorption capacity to VOCs than activated carbon, offering great potential for real applications in the adsorption and removal of VOCs.

In this paper, a unique approach for road extraction utilizing pixel spectral information for classification and image segmentation-derived object features was developed. In this approach, road extraction was performed in two steps. In the first step, support vector machine (SVM) was employed merely to classify the image into two groups of categories: a road group and a non-road group. For this classification, support vector machine (SVM) achieved higher accuracy than Gaussian maximum likelihood (GML). In the second step, the road group image was segmented into geometrically homogeneous objects using a region growing technique based on a similarity criterion, with higher weighting on shape factors over spectral criteria. A simple thresholding on the shape index and density features derived from these objects was performed to extract road features, which were further processed by thinning and vectorization to obtain road centerlines. The experiment showed the proposed approach worked well with images comprised by both rural and urban area features.

No abstract

No abstract

An electrothermal vaporization-inductively coupled plasma-mass spectrometric (ETV-ICP-MS) method based on selective volatilization of cesium with KSCN as modifier has been developed for determination of radiocesium, i.e. 135Cs and 137Cs, in the presence of isobaric barium. A 10,000 times excess of barium, which was volatilized at a temperature of 1,100 degrees C, resulted only in a 1% signal increase in the signal of mass 135 amu. The recommended concentration of KSCN is 0.3 mM, and pretreatment and volatilization temperatures are 400 degrees C and 1,100 degrees C, respectively. A ramp time of 1 s is recommeded for the volatilization step. The achieved limit of detection for 135Cs is 0.2 pg/mL (10 microBq/mL) and 4 fg (0.2 microBq) absolute for a sample volume of 20 microL. This means a limit of detection for 137Cs of 0.2 pg/mL (0.6 Bq/mL) and of 4 fg (0.01 Bq) absolute. Signal variations of 135Cs and 137Cs, respectively, in spiked samples with various matrices were investigated.