Isomer separation enabled by a micro circulatory gas chromatography system

Investigation of Physicochemical Characteristics of Aspergillus niger Biomass and Examination of Its Ability to Separate Butyl Acetate Isomers

Aspergillus niger is a species of fungus that is widely found in natural ecosystems and has an important role in various industrial fields and is readily available. To study the adhesion of microbial cells to solid substrates and to improve their properties, physicochemical characterization of microorganisms is extremely important. For this purpose, in this study, the surface properties of A. niger biomass were determined at low cost and with high accuracy by inverse gas chromatography (IGC), a physicochemical characterization technique. IGC experiments were conducted between 303.2 and 328.2 K at infinite dilution. Among these temperatures, various organic solvent vapors were passed over the A. niger biomass considered as stationary phase and their retention behavior was studied. Using the raw data, net retention volumes were calculated and retention diagrams were drawn. From the linear retention diagrams, the dispersive surface energy was calculated according to Dorris-Gray (48.73-46.09 mJ/m2), Donnet-Park (47.12-44.50 mJ/m2), Schultz (46.88-42.45 mJ/m2), and Hamieh (76.42-64.06 mJ/m2) methods. With the IGC method, the acidity-basicity parameters of A. niger biomass were determined and it was found that the surface was basic (K D / K A = 4.871 ). In the second part of this study, the butyl acetate isomer series, which are difficult to be separated by conventional methods, were effectively separated by the IGC method using A. niger stationary phase.

Real-time gas mass spectroscopy by multivariate analysis

Early and significant results for a real-time, column-free miniaturized gas mass spectrometer in detecting target species with partial overlapping spectra are reported. The achievements have been made using both nanoscale holes as a nanofluidic sampling inlet system and a robust statistical technique. Even if the presented physical implementation could be used with gas chromatography columns, the aim of high miniaturization requires investigating its detection performance with no aid. As a study case, in the first experiment, dichloromethane (CH₂Cl₂) and cyclohexane (C₆H₁₂) with concentrations in the 6-93 ppm range in single and compound mixtures were used. The nano-orifice column-free approach acquired raw spectra in 60 s with correlation coefficients of 0.525 and 0.578 to the NIST reference database, respectively. Then, we built a calibration dataset on 320 raw spectra of 10 known different blends of these two compounds using partial least square regression (PLSR) for statistical data inference. The model showed a normalized full-scale root-mean-square deviation (NRMSD) accuracy of [Formula: see text] and [Formula: see text] for each species, respectively, even in combined mixtures. A second experiment was conducted on mixes containing two other gasses, Xylene and Limonene, acting as interferents. Further 256 spectra were acquired on 8 new mixes, from which two models were developed to predict CH₂Cl₂ and C₆H₁₂, obtaining NRMSD values of 6.4% and 13.9%, respectively.