The effective calculation of static nonlinear optical properties requires a considerably high accuracy at a reasonable computational cost, to tackle challenging organic and inorganic systems acting ...as precursors and/or active layers of materials in (nano‐)devices. That trade‐off implies to obtain very accurate electronic energies in the presence of externally applied electric fields to consequently obtain static polarizabilities (αij) and hyper‐polarizabilities (βijk and γijkl). Density functional theory is known to provide an excellent compromise between accuracy and computational cost, which is however largely impeded for these properties without introducing range‐separation techniques. We thus explore here the ability of a modern (double‐hybrid and range‐separated) Range‐Separated eXchange Quadratic Integrand Double‐Hybrid exchange‐correlation functional to compete in accuracy with more costly and/or tuned methods, thanks to its robust and parameter‐free nature.
Background/Objectives: The diversity of the chemical structures of dietary polyphenols makes it difficult to estimate their total content in foods, and also to understand the role of polyphenols in ...health and the prevention of diseases. Global redox colorimetric assays have commonly been used to estimate the total polyphenol content in foods. However, these assays lack specificity. Contents of individual polyphenols have been determined by chromatography. These data, scattered in several hundred publications, have been compiled in the Phenol-Explorer database. The aim of this paper is to identify the 100 richest dietary sources of polyphenols using this database. Subjects/Methods: Advanced queries in the Phenol-Explorer database (www.phenol-explorer.eu) allowed retrieval of information on the content of 502 polyphenol glycosides, esters and aglycones in 452 foods. Total polyphenol content was calculated as the sum of the contents of all individual polyphenols. These content values were compared with the content of antioxidants estimated using the Folin assay method in the same foods. These values were also extracted from the same database. Amounts per serving were calculated using common serving sizes. Results: A list of the 100 richest dietary sources of polyphenols was produced, with contents varying from 15 000 mg per 100 g in cloves to 10 mg per 100 ml in rosé wine. The richest sources were various spices and dried herbs, cocoa products, some darkly coloured berries, some seeds (flaxseed) and nuts (chestnut, hazelnut) and some vegetables, including olive and globe artichoke heads. A list of the 89 foods and beverages providing more than 1 mg of total polyphenols per serving was established. A comparison of total polyphenol contents with antioxidant contents, as determined by the Folin assay, also showed that Folin values systematically exceed the total polyphenol content values. Conclusions: The comprehensive Phenol-Explorer data were used for the first time to identify the richest dietary sources of polyphenols and the foods contributing most significantly to polyphenol intake as inferred from their content per serving.
•Olive stone energetic properties and variability of these parameters.•Climate and geographical variability.•Variations between olive stone quality parameters supplied by both olive-oil mills and ...distribution companies.•A correlation between the ultimate analysis and higher heating values of olive stone.
In Andalusia, residual biomass produced in the olive sector results from the large amount of olive groves and olive oil manufacturers that generate byproducts with a potentially high energy content, suitable for thermal and electrical energy production. The main residue, olive stone, is an important solid biofuel and is widely generated and consumed. Consequently, olive stone quality parameters must be studied in order to achieve an optimum energetic efficiency. Therefore, the main objective of this study is to describe olive stone energetic properties and to evaluate variability of these parameters before consumption. For this purpose, mean values, normal distributions, intervals and deviations of these parameters have been obtained and studied. Concerning to statistical results, climate and geographical variability of quality parameters has been described. Furthermore, variations between olive stone physicochemical parameters supplied by both olive oil factories and distribution companies have been calculated. Finally, a correlation between the ultimate analysis and higher heating values (HHV) of olive stone has been determined. Results obtained show that olive stone pretreatments developed by distribution companies have a significant effect on quality parameters such as moisture content and low heating value. Moreover, olive stone properties dependence on factors such as rainfall or soil type has not been confirmed. Lastly, the calculated correlation based on ultimate analysis (i.e. HHV(MJ/kg)=0.401C−0.164H+0.493N+2.381S+0.791) has been developed and validated with olive stone samples with HHV range from 20 to 21MJ/kg (dry weight). Correlation has a mean absolute error (MAE) of 0.43% and a mean bias error (MBE) of −0.12% which indicate that it can be successfully used as a more economical and faster tool to accurately estimate olive stone HHV. The HHV prediction accuracies of 14 other correlations introduced by other researchers are also compared in this study.
We theoretically investigate here by means of DFT methods how the selective substitution in cyclic organic nanorings composed of pyrene units may promote semiconducting properties, analyzing the ...energy needed for a hole- or electron-transfer accommodation as a function of the substitution pattern and the system size (i.e., number of pyrene units). We choose to study both 3Cyclo-2,7-pyrenylene (3CPY) and 4Cyclo-2,7-pyrenylene (4CPY) compounds, the latter already synthesized, with substituents other than hydrogen acting in ipso and ortho positions, as well as the effect of the per-substitution. As substituents, we selected a set of electroactive halogen atoms (F, Cl, and Br) and groups (CN) to disclose structure–property relationships allowing thus to anticipate the use of these systems as organic molecular semiconductors.
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