Determination of 5-nitroindazole using silver solid amalgam electrode

Monatshefte für Chemie - Chemical Monthly - The voltammetric behavior of 5-nitroindazole was investigated at polished (p-AgSAE) and at mercury meniscus-modified (m-AgSAE) silver solid amalgam...     

Formation of porous polymer morphology by microsyneresis during divinylbenzene polymerization

This article describes the investigation of the importance of various reaction conditions on microsyneretic pore formation during polymerization of divinylbenzene (DVB) under so‐called “solvothermal” conditions. To induce microsyneretic pore formation, the most important parameter is an unusually high dilution of monomers with a “good” porogen solvating the polymer chains. High dilution and solvation of the growing poly(DVB) chains promote the prolongation of the polymer chains rather than their interconnection by crosslinking. Consequently, when the polymer gel density reaches the point where syneresis starts, the polymer network is geometrically too extensive to be broken up into precipitating entities and, instead, porogen droplets are formed within the continuous polymer gel. The pore geometry created by microsyneresis offers high surface area in wide mesopores and hence, high capacity for supporting functional groups or reactions with much better accessibility than narrow pores between polymer microspheres produced by macrosyneresis in conventional styrenic polymer supports. © 2015 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2015 , 53, 774–781     

Prediction of chromatographic retention of metal complexes from stability constants measured by ion chromatography

Chromatographia - A theoretical model is used to predict retention times of divalent metal cations in single-column ion chromatography using one or more ligands in the eluent. Stability constants...     

Some remarks to multivariate regression model

Some remarks to problems of point and interval estimation, testing and problems of outliers are presented in the case of multivariate regression model. This work was supported by the Council of Czech Government J14/98:153100011.