RESUMO
In the present study, a novel configuration of liquid-phase microextraction was proposed, in which a magnetic stirrer with a groove was used as the extractant phase holder. It was termed as magnetic stirrer liquid-phase microextraction. In this way, the stability of the organic solvent was much improved under high stirring speed; the extraction efficiency was enhanced due to the enormously enlarged contact area between the organic solvent and aqueous phase. The extraction performance of the magnetic stirrer liquid-phase microextraction was studied using chlorobenzenes as the probe analytes. A wide linearity range (20 pg/mL to 200 ng/mL) with a satisfactory linearity coefficient (r(2) > 0.998) was obtained. Limits of detection ranged from 9.0 to 12.0 pg/mL. Good reproducibility was achieved with intra- and inter-day relative standard deviations <4.8%. The proposed magnetic stirrer liquid-phase microextraction was simple, environmentally friendly and efficient; compared to single-drop microextraction, it had obvious advantages in terms of reproducibility and extraction efficiency. It is a promising miniaturized liquid-phase technology for real applications.
RESUMO
Near-infrared reflectance spectroscopy (NIRS) is a simple, convenient and safe technology which is widely used in many industries. NIRS was employed to the rapid classification of coal in this study. The new method can be a replacement of the chemical analysis which is laborious and time consuming. Confidence machine was firstly applied to NIRS in this study which was used to evaluate the risk of the analysis. The near infrared reflectance spectrum of 199 coal samples including four types of coal (50 fat coal samples, 50 coking coal samples, 49 lean coal samples and 50 meager lean coal samples) from different mines in China were collected and classifiers based on the near infrared spectra of coal samples which were established by using machine learning methods to realize the rapid classification of coal samples. Confidence machine was introduced into the analysis technology based on NIRS in this paper. Confidence machine based on support vector machine (CM-SVM) was built and applied to the classification of coal samples via NIRS. Confidence machine is a probabilistic algorithm and instead of using hyper plane (SVM) to carry out the classification, using probability (CM-SVM) turned to be more effective which had 95.45% of the samples correctly grouped. Besides that, CM-SVM also estimated the confidence and credibility for each predicted sample. By setting different confidence levels, CM-SVM can perform region prediction whose error rate was predefined by the different confidence levels, which was very important for the control of product quality when NIRS was applied to the analysis of productions. Confidence machine is designed as an on-line learning method; new samples can be added to the training set one by one to improve the efficiency of the model and is very appropriate for industry on-line analysis. On-line CM-SVM models showed that the confidence of prediction would be raised as the samples increased, which was valuable for industry on-line analysis.
RESUMO
Nanostructured polyanilines (PANIs) are selected quite often as the matrix for the synthesis of inorganic/conductive polymer composites due to their excellent optical, electrical and magnetic properties. Herein both 2D lamellar PANI and the cor responding composite loading TiO2 species were successfully prepared from a microemulsion system, as composed by dodecyl benzenesulfonic acid (DBSA) and water. The composite was achieved through a simultaneous polymerization of aniline in the presence of ammonium persulfate and hydrolysis of tetrabutyl titanate. Scanning electron microscopy (SEM) images indicate clearly that 2D PANI lamella are formed through organization of small PANI sheets. The inter-lamellar distance of PANI and that of TiO2/polyaniline composite, as derived from X-ray diffraction (XRD), is about 3.4 nm (nearly twice the length of one DBS molecule), suggesting that PANI and double-layered DBSA species are arranged in an alternated way. FTIR spectrum displays that PANI chains exhibit quinonoid and benzenoid strutures while both Raman and X-ray photoelectron spectroscopy (XPS) indicate that rutile TiO2 is produced upon hydrolyzation of tetrabutyl titanate in the microemulsion system. Moreover, UV-Vis spectrum suggests that the electronic absorption behaviour of PANI species is influenced upon loading TiO2.
RESUMO
The zirconia-coated silica (ZrO2/SiO2) material was obtained by coupling layer-by-layer (LbL) self-assembly method and sol-gel technology, to take dual advantages of the suitable porous structure of SiO2 and basic resistance of ZrO2. Adenosine 5'-monophosphate (5'-AMP) was then self-assembled onto ZrO2/SiO2 via Lewis acid-base interaction, generating 5'-AMP-ZrO2/SiO2. The chromatographic properties of 5'-AMP-ZrO2/SiO2 were systemically studied by evaluating the effect of acetonitrile content, pH and buffer concentration in the mobile phase. The results demonstrated that the 5'-AMP-ZrO2/SiO2 possessed hydrophilic interaction chromatographic (HILIC) property comprising hydrophilic, hydrogen-bonding, electrostatic and ion-exchange interactions. For basic analytes, the column efficiency of ZrO2/SiO2 and 5'-AMP-ZrO2/SiO2 was superior to the bare ZrO2, and different selectivity was obtained after the introduction of 5'-AMP. For acidic analytes, good resolution was obtained on 5'-AMP-ZrO2/SiO2 while the analysis failed on the bare ZrO2 column owing to strong adsorption. Hence, the proposed 5'-AMP-ZrO2/SiO2 had great potential in analyzing acidic compounds in HILIC mode. It was an extended application of ZrO2 based SP.