Volume 97, Issue 7

This work summarizes the fundamentals of the description of molecular diffusion in liquid and gaseous non-electrolyte and electrolyte systems at constant temperature and pressure and in the absence of external fields. On the basis of Fick’s law and the theory of Maxwell and Stefan, the description of diffusive fluxes in commonly used reference frames and a recommendation for the terminology of the associated diffusion coefficients are given. For non-electrolyte systems, the corresponding equations for the diffusive fluxes are outlined for a general n -component mixture and are explicitly stated for binary and ternary mixtures. Additionally, the transformation of the component order is discussed for a general n -component mixture. For electrolyte mixtures, explicit equations for the diffusive fluxes are stated for binary mixtures consisting of a molecular solvent and a dissolved electrolyte component and binary mixtures consisting of two electrolyte components sharing a common ion. Furthermore, explicit equations for the diffusive fluxes are given for ternary systems consisting of one electrolyte component dissolved in two non-electrolyte solvents. For all the aforementioned systems, transformations of the diffusion coefficients between commonly used reference frames are included.

This Guide is intended for harmonization of interlaboratory comparisons of categorical − nominal (qualitative, i.e., non-quantitative) and ordinal (semi-quantitative) − characteristics of a substance, material, or object. It provides guidance for application of relevant methods of mathematical statistics for design of such interlaboratory comparisons and analysis of the obtained data, when the methods developed for continuous quantitative values (e.g., ANOVA − analysis of variance) cannot be used without violation of their basic assumptions. The proposed approach employs recently-developed two-way nominal analysis of variation CATANOVA and two-way ordinal analysis of variation ORDANOVA. The Guide also addresses correlation between the categorical characteristics, as well as correlation between these characteristics and the chemical composition of the material or object. A multisensory quality index of a product, combining information on its categorical characteristics, is detailed. It allows for comparison of the quality of the same material produced by different producers. The examples provided in the Guide are from the fields of macroscopic examination of weld imperfections, comparison of odor intensity of drinking water, and comparison of sensory (ordinal) characteristics of a sausage. A corresponding calculation tool with an Excel spreadsheet including macros, and programs written in the R environment, are available in the specified references.

A novel sensor has been developed for albumin recognition, using a Chitosan polymer film printed on the surface of ITO/Ag electrode. The electrode was fabricated through the deposition of an Ag film onto the ITO surface. Subsequently, MIP film was synthesized through Chitosan polymerization and cross-linked using glutaraldehyde. This polymer was used because it is more environmentally friendly and biocompatible. The formation of albumin binding sites on the MIP makes this sensor selective against other molecules. Meanwhile, Cyclic Voltammetry (CV) and Electric Impedance Spectroscopy (EIS) were used to analyze the performance of the sensor against albumin presence. Under optimal conditions, the ITO/Ag/MIP sensor showed high sensitivity with a value of 57.6 μA mM −1 cm −1 and 47,100 Ω mM −1  cm −1 for CV and EIS measurements. There was only a slight difference in sensitivity values, indicating that the electrode could be used in real serum. In addition, the limit of detection (LOD) was found to be very low at 7.00 × 10 −19  g dl −1 in the concentration range of 10 −19 to 10 −1  g/dl. The influence of other molecules was also investigated, and the sensor showed high selectivity, reproducibility, and stability. Moreover, molecular simulations show that the combination of hydrophobic and covalent interactions ensures that the MIP composition has the stability necessary for high sensitivity and the flexibility required for albumin binding.