Surface polarity of cellulose derivates observed by coumarin 151 and 153 as solvatochromic and fluorochromic probes

Solvent‐dependent ultraviolet–visible (UV–vis) absorption and Stokes shifts including strong hydrogen‐bond‐donating (HBD) solvents such as 2,2,2‐trifluoroethanol and 1,1,1,3,3,3‐hexafluoro‐2‐propanol of two coumarine dyes (Co 151 and Co 153) were analyzed with multiple‐square analyses of linear solvation energy relationships and the Kamlet–Taft solvent parameter set to α (HBD capacity), β (hydrogen‐bond‐accepting capacity), and π* (dipolarity/polarizability). The UV–vis absorption and emission spectra of Co 151 and Co 153 were measured when adsorbed on various polysaccharides such as different cellulose batches, carboxymethylcelluloses with different degrees of substitution, and chitine. As a result of this evaluation, Co 153 is recommended as an alternative UV–vis probe for evaluating the dipolarity/polarizability of cellulose and cellulose derivates. Multiple adsorption of Co 153 on Linters cellulose took place indicating a wide‐surface polarity distribution, which makes the determination of a rigid polarity parameter questionable. Thus, fluorescence measurements of adsorbed Co 153 are suitable to detect inhomogenities on a surface but not for the determination of empirical polarity parameters. © 2003 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 41: 1210–1218, 2003     

BonDNet: a graph neural network for the prediction of bond dissociation energies for charged molecules

A broad collection of technologies, including e.g. drug metabolism, biofuel combustion, photochemical decontamination of water, and interfacial passivation in energy production/storage systems rely on chemical processes that involve bond-breaking molecular reactions. In this context, a fundamental thermodynamic property of interest is the bond dissociation energy (BDE) which measures the strength of a chemical bond. Fast and accurate prediction of BDEs for arbitrary molecules would lay the groundwork for data-driven projections of complex reaction cascades and hence a deeper understanding of these critical chemical processes and, ultimately, how to reverse design them. In this paper, we propose a chemically inspired graph neural network machine learning model, BonDNet, for the rapid and accurate prediction of BDEs. BonDNet maps the difference between the molecular representations of the reactants and products to the reaction BDE. Because of the use of this difference representation and the introduction of global features, including molecular charge, it is the first machine learning model capable of predicting both homolytic and heterolytic BDEs for molecules of any charge. To test the model, we have constructed a dataset of both homolytic and heterolytic BDEs for neutral and charged (−1 and +1) molecules. BonDNet achieves a mean absolute error (MAE) of 0.022 eV for unseen test data, significantly below chemical accuracy (0.043 eV). Besides the ability to handle complex bond dissociation reactions that no previous model could consider, BonDNet distinguishes itself even in only predicting homolytic BDEs for neutral molecules; it achieves an MAE of 0.020 eV on the PubChem BDE dataset, a 20% improvement over the previous best performing model. We gain additional insight into the model''s predictions by analyzing the patterns in the features representing the molecules and the bond dissociation reactions, which are qualitatively consistent with chemical rules and intuition. BonDNet is just one application of our general approach to representing and learning chemical reactivity, and it could be easily extended to the prediction of other reaction properties in the future.

Prediction of bond dissociation energies for charged molecules with a graph neural network enabled by global molecular features and reaction difference features between products and reactants.     

Fluoride-facilitated deuterium exchange from DMSO-d6 to polyamide-based cryptands

Multiple deuterium exchange between DMSO-d6 and amide hydrogens in two hexaamido cryptand fluoride receptors has been verified by 19F and 2H NMR and FAB mass spectral studies. Structural results for one of the complexes indicate a tricapped trigonal prism hydrogen bond coordination geometry around an encapsulated fluoride, with hydrogen bonds from fluoride to six amide and three phenyl hydrogens.     

Capillary electrochromatography using polyelectrolyte multilayer coatings

This review covers recent progress in polyelectrolyte multilayer (PEM) coatings applied to analytical separations using open-tubular capillary electrochromatography (OT-CEC). The simple preparation procedure involved in the PEM approach has provided some attractive features over other modes of capillary electrophoresis-based separations including packed column capillary electrochromatography (PC-CEC) and micellar electrokinetic chromatography (MEKC). PEM coatings have been used to alleviate the adsorption of basic analytes, to improve separations, and to improve the stability of the electroosmotic flow. Fundamental aspects of PEM coatings on surfaces and analytical separation platforms are briefly outlined in this review. In addition, applications of PEM coatings to fused-silica capillaries or microchip separation devices for the separation of small achiral or chiral analytes, as well as large biomolecules, are discussed.     

Probing the surface polarity of native celluloses using genuine solvatochromic dyes

The surface polarity of native celluloses has been investigated by the following solvatochromic dyes: dicyano-bis (1,10)-phenanthroline iron (II) Fe(phen)2 (CN)2 (1), bis(4-N,N-dimethylamino)-benzophenone (2), and cou-marine 153 (3). Linear Solvation Energy (LSE) relationships and the UV/Vis data have been used to characterize the surface polarity of different native cellulose batches in terms of the empirical Kamlet–Taft polarity parameters (hydrogen bond acidity), (hydrogen bond basicity), and * (dipolarity/polarizability). , , *and calculated Reichardt's E T (30) values are reported for various native and regenerated cellulose samples with different degrees of crystallinity. The degree of crystallinity of the cellulose samples has been determined by X-ray. The microcrystalline environment of cellulose can be exactly parameterized in terms of the , and *values. It shows a fairly strong acidity and a low dipolarity/polarizability. For the amorphous sections smaller and larger * values are observed. The correspondence of the empirical polarity parameters determined has been discussed in relation to results from pyrene fluorescence and zetapotential measurements.     

An addition to the oxoacid family: H2B12(OH)12

The acid H(2)B(12)(OH)(12) can be isolated as a crystalline solid by protonation of the hydroxylated borane anion, B(12)(OH)(12)(2)(-). This acidic compound has low solubility in water, conducts protons in the solid state, and has thermal stability to a temperature of 400 degrees C. The conductivity mechanism is a Grotthuss mechanism with a low activation enthalpy (9-13 kcal/mol). This new acid represents an addition to the class of oxoacids, of which sulfuric and phosphoric acid are the most prominent examples.     

High-speed peak matching algorithm for retention time alignment of gas chromatographic data for chemometric analysis

A rapid retention time alignment algorithm was developed as a preprocessing utility to be used prior to chemometric analysis of large datasets of diesel fuel profiles obtained using gas chromatography (GC). Retention time variation from chromatogram-to-chromatogram has been a significant impediment against the use of chemometric techniques in the analysis of chromatographic data due to the inability of current chemometric techniques to correctly model information that shifts from variable to variable within a dataset. The alignment algorithm developed is shown to increase the efficacy of pattern recognition methods applied to diesel fuel chromatograms by retaining chemical selectivity while reducing chromatogram-to-chromatogram retention time variations and to do so on a time scale that makes analysis of large sets of chromatographic data practical. Two sets of diesel fuel gas chromatograms were studied using the novel alignment algorithm followed by principal component analysis (PCA). In the first study, retention times for corresponding chromatographic peaks in 60 chromatograms varied by as much as 300 ms between chromatograms before alignment. In the second study of 42 chromatograms, the retention time shifting exhibited was on the order of 10 s between corresponding chromatographic peaks, and required a coarse retention time correction prior to alignment with the algorithm. In both cases, an increase in retention time precision afforded by the algorithm was clearly visible in plots of overlaid chromatograms before and then after applying the retention time alignment algorithm. Using the alignment algorithm, the standard deviation for corresponding peak retention times following alignment was 17 ms throughout a given chromatogram, corresponding to a relative standard deviation of 0.003% at an average retention time of 8 min. This level of retention time precision is a 5-fold improvement over the retention time precision initially provided by a state-of-the-art GC instrument equipped with electronic pressure control and was critical to the performance of the chemometric analysis. This increase in retention time precision does not come at the expense of chemical selectivity, since the PCA results suggest that essentially all of the chemical selectivity is preserved. Cluster resolution between dissimilar groups of diesel fuel chromatograms in a two-dimensional scores space generated with PCA is shown to substantially increase after alignment. The alignment method is robust against missing or extra peaks relative to a target chromatogram used in the alignment, and operates at high speed, requiring roughly 1 s of computation time per GC chromatogram.     

A Water Molecule Triggers Guest Exchange at a Mono-Zinc Centre Confined in a Biomimetic Calixarene Pocket: a Model for Understanding Ligand Stability in Zn Proteins

In this study, the ligand exchange mechanism at a biomimetic Zn^II centre, embedded in a pocket mimicking the possible constrains induced by a proteic structure, is explored. The residence time of different guest ligands (dimethylformamide, acetonitrile and ethanol) inside the cavity of a calix[6]arene-based tris(imidazole) tetrahedral zinc complex was probed using 1D EXchange SpectroscopY NMR experiments. A strong dependence of residence time on water content was observed with no exchange occurring under anhydrous conditions, even in the presence of a large excess of guest ligand. These results advocate for an associative exchange mechanism involving the transient exo-coordination of a water molecule, giving rise to 5-coordinate Zn^II intermediates, and inversion of the pyramid at the Zn^II centre. Theoretical modelling by DFT confirmed that the associative mechanism is at stake. These results are particularly relevant in the context of the understanding of kinetic stability/lability in Zn proteins and highlight the key role that a single water molecule can play in catalysing ligand exchange and controlling the lability of Zn^II in proteins.