Chemically modified nanocrystalline SnO2-based materials for nitrogen-containing gases detection using gas sensor array

International audienceThis study is devoted to creation of metal oxide semiconductor (MOS) materials for gas sensor array for determination of nitrogen oxides and ammonia traces in sub-Threshold Limit Value (TLV) concentrations in air, and to elaboration of data processing algorithms for identification and quantification of single gases. The array contained semiconductor sensors made from originally synthesized gas sensitive materials - chemically modified nanocrystalline SnO2. The modifiers were preliminarily chosen on the basis of an analysis of the target gas properties and experimental data obtained in the field of heterogeneous catalysis on the Platinum Group metals and d-metal oxides. A novel algorithm for data analysis of a semiconductor gas sensor array working in a dynamic temperature mode is used. The ability of the suggested algorithm, called EDMN+ (from Euclidian Distance Matrix Normalization), to solve the task of gases identification, and the ability of PLS (Projection to Latent Structures) algorithm combined with cross-validation approach to solve the task of gases quantification using a limited amount of data patterns available, are demonstrated. (C) 2016 Elsevier B.V. All rights reserved

Chemically modified nanocrystalline SnO2-based materials for nitrogen-containing gases detection using gas sensor array

International audienceThis study is devoted to creation of metal oxide semiconductor (MOS) materials for gas sensor array for determination of nitrogen oxides and ammonia traces in sub-Threshold Limit Value (TLV) concentrations in air, and to elaboration of data processing algorithms for identification and quantification of single gases. The array contained semiconductor sensors made from originally synthesized gas sensitive materials - chemically modified nanocrystalline SnO2. The modifiers were preliminarily chosen on the basis of an analysis of the target gas properties and experimental data obtained in the field of heterogeneous catalysis on the Platinum Group metals and d-metal oxides. A novel algorithm for data analysis of a semiconductor gas sensor array working in a dynamic temperature mode is used. The ability of the suggested algorithm, called EDMN+ (from Euclidian Distance Matrix Normalization), to solve the task of gases identification, and the ability of PLS (Projection to Latent Structures) algorithm combined with cross-validation approach to solve the task of gases quantification using a limited amount of data patterns available, are demonstrated. (C) 2016 Elsevier B.V. All rights reserved

Raman Spectroscopy of Water–Ethanol Solutions: The Estimation of Hydrogen Bonding Energy and the Appearance of Clathrate-like Structures in Solutions

The structure of aqueous alcohol solutions at the molecular level for many decades has remained an intriguing topic in numerous theoretical and practical investigations. The aberrant thermodynamic properties of water–alcohol mixtures are believed to be caused by the differences in energy of hydrogen bonding between water–water, alcohol–alcohol, and alcohol–water molecules. We present the Raman scattering spectra of water, ethanol, and water–ethanol solutions with 20 and 70 vol % of ethanol thoroughly measured and analyzed at temperatures varying from −10 to +70 °C. Application of the MCR-ALS method allowed for each spectrum to extract contributions of molecules with different strengths of hydrogen bonding. The energy (enthalpy) of formation/weakening of hydrogen bonds was calculated using the slope of Van’t Hoff plot. The energy of hydrogen bonding in 20 vol % of ethanol was found the highest among all the samples. This finding further supports appearance of clathrate-like structures in water–ethanol solutions with concentrations around 20 vol % of ethanol