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Parallel factor analysis (PARAFAC) was used to analyze data from the high throughput screening of an array of organometallic rhodium and iridium complexes as catalysts for the intramolecular hydroamination of 2-(2-phenylethynyl)aniline to give 2-phenylindole. The progress of the hydroamination reactions was monitored using UV-visible spectroscopy. The overlapped UV-visible spectra of the mixture of starting material, product and solvent in the samples taken at different times were deconvoluted using PARAFAC. Unique PARAFAC models led to close approximations of the actual UV-visible spectra of the compounds in the mixture. The performance of the catalysts was then compared by estimating the final concentration of the starting material and product using PARAFAC loadings. A library of 63 complexes generated in situwas examined in a single experiment using this methodology. The complexes were generated from combinations of seven ligands (bis(N-methyl2-imidazolyl)methane, bis(1-pyrazolyl)methane, 1,10-phenanthroline, N,N′-bis(p-tolyl)diazabutadiene, N,N′-bis(p-tolyl)1,2-dimethyldiazabutadiene, N,N′-bis(mesityl)1,2-dimethyldiazabutadiene and bis(2,4,6-trimethylphenylimino)acenapthene) and nine metal precursors ([Ir(COD)Cl]2(COD = 1,5-cyclooctadiene), [Ir(CO)2Cl]n, [Ir(COE)2Cl]2, [IrCp*Cl2]2(Cp* = 1,2,3,4,5-pentamethylcyclopentadiene), [Rh(COD)Cl]2, [Rh(CO)2Cl]2, [Rh(COE)2Cl]2, [RhCp*Cl2]2and [RhCpCl2]2) (Cp = cyclopentadiene)). The proposed method can be used for the fast screening of arrays of metal complexes for identifying effective catalysts, providing information that can augment traditional methods used for the analysis of catalyzed reactions. [ABSTRACT FROM AUTHOR]

Four comparison statistics (‘similarity indices’) for the identification of the source of a petroleum oil spill based on the ASTM standard test method D3414 were investigated. Namely, (1) first difference correlation coefficient squared and (2) correlation coefficient squared, (3) first difference Euclidean cosine squared and (4) Euclidean cosine squared. For numerical comparison, an FTIR spectrum is divided into three regions, described as: fingerprint (900–700 cm−1), generic (1350–900 cm−1) and supplementary (1770–1685 cm−1), which are the same as the three major regions recommended by the ASTM standard. For fresh oil samples, each similarity index was able to distinguish between replicate independent spectra of the same sample and between different samples. In general, the two first difference-based indices worked better than their parent indices. To provide samples to reveal relationships between weathered and fresh oils, a simple artificial weathering procedure was carried out. Euclidean cosine and correlation coefficients both worked well to maintain identification of a match in the fingerprint region and the two first difference indices were better in the generic region. Receiver operating characteristic curves (true positive rate versus false positive rate) for decisions on matching using the fingerprint region showed two samples could be matched when the difference in weathering time was up to 7 days. Beyond this time the true positive rate falls and samples cannot be reliably matched. However, artificial weathering of a fresh source sample can aid the matching of a weathered sample to its real source from a pool of very similar candidates. [ABSTRACT FROM AUTHOR]

The Guide to the Expression of Uncertainty in Measurement (GUM) requires that measurement results are corrected for all recognized systematic effects. Therefore the answer to the comment of Kadis is unequivocally ‘yes’, run bias does need to be accounted for. The approach which combines a properly determined repeatability standard deviation and the uncertainty of the assessment of bias is a valid basis of the estimation of uncertainty of a measurement result. This approach produces a realisitic estimate of measurement uncertainty rather than a ‘safe’ one. [ABSTRACT FROM AUTHOR]

Data analysis is central to understanding phenomena in host-guest chemistry. We describe here recent developments in this field starting with the revelation that the popular Job plot method is inappropriate for most problems in host-guest chemistry and that the focus should instead be on systematically fitting data and testing all reasonable binding models. We then discuss approaches for estimating uncertainties in binding studies using case studies and simulations to highlight key issues. Related to this is the need for ready access to data and transparency in the methodology or software used, and we demonstrate an example a webportal () that aims to address this issue. We conclude with a list of best-practice protocols for data analysis in supramolecular chemistry that could easily be translated to other related problems in chemistry including measuring rate constants or drug IC 50 values.