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Selected papers from the latest issue:
Recent advances in dispersive liquid-liquid microextraction using organic solvents lighter than water: A review
11 December 2011, 02:04:35
Publication year: 2011
Source: Microchemical Journal, Available online 9 December 2011
Lívia Kocúrová, Ioseph S. Balogh, Jana Šandrejová, Vasil Andruch
Dispersive liquid–liquid microextraction (DLLME) has in the very short time since its invention in 2006 grabbed the attention of researchers and become very popular among analytical chemists. Like other analytical methods, however, DLLME also has its drawbacks, which result mainly from requirements related to the extraction solvent and disperser solvent. To overcome these various drawbacks, researchers have recently attempted to use solvents with a density lower than that of water and to perform the extraction without using a disperser solvent and without the need for centrifugation. We offer an overview of what in our opinion are some of the most interesting solutions published recently, those which could possibly expand the applicability of DLLME.
Source: Microchemical Journal, Available online 9 December 2011
Lívia Kocúrová, Ioseph S. Balogh, Jana Šandrejová, Vasil Andruch
Dispersive liquid–liquid microextraction (DLLME) has in the very short time since its invention in 2006 grabbed the attention of researchers and become very popular among analytical chemists. Like other analytical methods, however, DLLME also has its drawbacks, which result mainly from requirements related to the extraction solvent and disperser solvent. To overcome these various drawbacks, researchers have recently attempted to use solvents with a density lower than that of water and to perform the extraction without using a disperser solvent and without the need for centrifugation. We offer an overview of what in our opinion are some of the most interesting solutions published recently, those which could possibly expand the applicability of DLLME.
Highlights
►Methods utilizing special devices►DLLME based on solidification of a floating organic drop►Low-density solvent-based solvent demulsification DLLME►Methods based on the adjustment of the solvents mixture density ► Automation of DLLME using sequential injection analysisMulti-walled carbon nanotubes – solid phase extraction for isolating marine dissolved organic matter before characterization by size exclusion chromatography
11 December 2011, 02:04:35
Publication year: 2011
Source: Microchemical Journal, Available online 9 December 2011
Juan Sánchez-González, Natalia García-Otero, Antonio Moreda-Piñeiro, Pilar Bermejo-Barrera
The feasibility of multi-walled carbon nanotubes (MWCNTs) for extracting dissolved organic matter (DOM) from seawater has been investigated. Solid phase extraction (SPE) operating in column and batch modes was used as an extractive technique, and the latter mode offered better performance. DOM adsorption was achieved using 60 mg of MWCNTs per each 250 mL of seawater subsample, working at pH 1.0 and under an orbital-horizontal shaking at 180 rpm and 25 °C for 4 hours. DOM desorption from the MWCNTs support implied an orbital–horizontal shaking (180 rpm and 25 °C) for 2 hours using 10 mL of a 0.1 M sodium hydroxide solution (DOM determination), or using 20 mL of alkaline methanol (pH 10.0) for DOM fractionation by size exclusion chromatography (SEC) with UV detection at 205 nm. A Total Organic Carbon (TOC) analyzer with wet DOM oxidation (30% (m/v) potassium peroxodisulphate in 6.0 M phosphoric acid) under super critical conditions and with Non-Dispersive Infra Red (NDIR) for CO2detection was used for DOM measurements. Calibration covered TOC concentrations within the 0.13–1000 mg Lrange. The percentage of DOM retained in the MWCNTs support was dependent on the seawater sample, and it varied from 34 to 81%. This means that only the DOM of certain molecular weights is capable to interact with the SPE support. Various SEC columns, ranging from 100 to 7000 and from 500 to 15000 Da (optimum separation range for peptides), were therefore used for DOM fractionation. Results have shown that DOM of low molecular weight is retained in the MWCNTs (fractions within the ranges of 125–1102 Da and 6.88–125 Da).
Source: Microchemical Journal, Available online 9 December 2011
Juan Sánchez-González, Natalia García-Otero, Antonio Moreda-Piñeiro, Pilar Bermejo-Barrera
The feasibility of multi-walled carbon nanotubes (MWCNTs) for extracting dissolved organic matter (DOM) from seawater has been investigated. Solid phase extraction (SPE) operating in column and batch modes was used as an extractive technique, and the latter mode offered better performance. DOM adsorption was achieved using 60 mg of MWCNTs per each 250 mL of seawater subsample, working at pH 1.0 and under an orbital-horizontal shaking at 180 rpm and 25 °C for 4 hours. DOM desorption from the MWCNTs support implied an orbital–horizontal shaking (180 rpm and 25 °C) for 2 hours using 10 mL of a 0.1 M sodium hydroxide solution (DOM determination), or using 20 mL of alkaline methanol (pH 10.0) for DOM fractionation by size exclusion chromatography (SEC) with UV detection at 205 nm. A Total Organic Carbon (TOC) analyzer with wet DOM oxidation (30% (m/v) potassium peroxodisulphate in 6.0 M phosphoric acid) under super critical conditions and with Non-Dispersive Infra Red (NDIR) for CO2detection was used for DOM measurements. Calibration covered TOC concentrations within the 0.13–1000 mg Lrange. The percentage of DOM retained in the MWCNTs support was dependent on the seawater sample, and it varied from 34 to 81%. This means that only the DOM of certain molecular weights is capable to interact with the SPE support. Various SEC columns, ranging from 100 to 7000 and from 500 to 15000 Da (optimum separation range for peptides), were therefore used for DOM fractionation. Results have shown that DOM of low molecular weight is retained in the MWCNTs (fractions within the ranges of 125–1102 Da and 6.88–125 Da).
Highlights
► Multi-walled carbon nanotubes (MWCNTs) for isolating marine dissolved organic matter (DOM) ► Effect of the saline matrix and the solid phase extraction mode on the retained DOM ratio ► Size exclusion chromatography for characterizing the retained DOM ► Retained DOM onto MWCNTs is in low molecular weight (within the 125 – 1102 Da range)Monitoring of solid-state fermentation of wheat straw in a pilot scale using FT-NIR spectroscopy and support vector data description
11 December 2011, 02:04:35
Publication year: 2011
Source: Microchemical Journal, Available online 9 December 2011
Hui Jiang, Guohai Liu, Xiahong Xiao, Congli Mei, Yuhang Ding, ...
Fourier transform near-infrared (FT-NIR) spectroscopy coupled with support vector data description (SVDD) as an ideal tool was attempted to rapidly and accurately monitor physical and chemical changes in solid-state fermentation (SSF) of crop straws without the need for chemical analysis. Raw spectra of fermented samples were acquired with wavelength range of 10,000-4,000 cm. SVDD algorithm was employed to build a one-class classification model, and some parameters of SVDD algorithm were optimized by cross-validation in calibrating model. Simultaneously, four traditional two-class classification approaches (i.e., linear discriminant analysis, LDA;K-nearest neighbor, KNN; back propagation neural networks, BPNN; support vector machine, SVM) were comparatively utilized for monitoring time-related changes that occur during SSF. Compared to the four models, SVDD model revealed its incomparable superiority in handling the problem of imbalance training sets. The discrimination rate of SVDD model was 90% in the validation set when the ratio of samples from stationary stage to those from other stages was one to eight. This study demonstrates that FT-NIR spectroscopy combined with SVDD is an efficient method to develop one-class classification model for the rapid monitoring of SSF.
Source: Microchemical Journal, Available online 9 December 2011
Hui Jiang, Guohai Liu, Xiahong Xiao, Congli Mei, Yuhang Ding, ...
Fourier transform near-infrared (FT-NIR) spectroscopy coupled with support vector data description (SVDD) as an ideal tool was attempted to rapidly and accurately monitor physical and chemical changes in solid-state fermentation (SSF) of crop straws without the need for chemical analysis. Raw spectra of fermented samples were acquired with wavelength range of 10,000-4,000 cm. SVDD algorithm was employed to build a one-class classification model, and some parameters of SVDD algorithm were optimized by cross-validation in calibrating model. Simultaneously, four traditional two-class classification approaches (i.e., linear discriminant analysis, LDA;K-nearest neighbor, KNN; back propagation neural networks, BPNN; support vector machine, SVM) were comparatively utilized for monitoring time-related changes that occur during SSF. Compared to the four models, SVDD model revealed its incomparable superiority in handling the problem of imbalance training sets. The discrimination rate of SVDD model was 90% in the validation set when the ratio of samples from stationary stage to those from other stages was one to eight. This study demonstrates that FT-NIR spectroscopy combined with SVDD is an efficient method to develop one-class classification model for the rapid monitoring of SSF.
