Cyclometallated 1,2,3-triazol-5-ylidene iridium(III) complexes: synthesis,structure, and photoluminescence properties

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Synthesis of Supported Heterogeneous Catalysts by Laser Ablation of Metallic Palladium in Supercritical Carbon Dioxide Medium

To obtain a supported heterogeneous catalyst, laser ablation of metallic palladium in supercritical carbon dioxide was performed in the presence of a carrier, microparticles of γ-alumina. The influence of the ablation process conditions—including supercritical fluid density, ablation, mixing time of the mixture, and laser wavelength—on the completeness and efficiency of the deposition of palladium particles on the surface of the carrier was studied. The obtained composites were investigated by scanning and transmission electron microscopy using energy dispersive spectroscopy. We found that palladium particles were nanosized and had a narrow size distribution (2–8 nm). The synthesized composites revealed high activity as catalysts in the liquid-phase hydrogenation of diphenylacetylene.     

MgFe2O4@SiO2–SO3H: an efficient,reusable catalyst for the microwave-assisted synthesis of benzoxazinone and benzthioxazinone via multicomponent reaction under solvent free condition

Research on Chemical Intermediates - We report the synthesis of sulfuric acid-functionalized silica-coated magnetic nanoparticles (MgFe2O4@SiO2–SO3H) as a catalyst for the microwave-assisted...     

Isotropy of unitary involutions

We prove the so-called unitary isotropy theorem, a result on isotropy of a unitary involution. The analogous previously known results on isotropy of orthogonal and symplectic involutions as well as on hyperbolicity of orthogonal, symplectic, and unitary involutions are formal consequences of this theorem. A component of the proof is a detailed study of the quasi-split unitary grassmannians.     

A Planar‐Chiral Rhodium(III) Catalyst with a Sterically Demanding Cyclopentadienyl Ligand and Its Application in the Enantioselective Synthesis of Dihydroisoquinolones

The rapid development of enantioselective C?H activation reactions has created a demand for new types of catalysts. Herein, we report the synthesis of a novel planar‐chiral rhodium catalyst [(C₅H₂^tBu₂CH₂^tBu)RhI₂]₂ in two steps from commercially available [(cod)RhCl]₂ and tert‐butylacetylene. Pure enantiomers of the catalyst were obtained through separation of its diastereomeric adducts with natural (S)‐proline. The catalyst promoted enantioselective reactions of aryl hydroxamic acids with strained alkenes to give dihydroisoquinolones in high yields (up to 97 %) and with good stereoselectivity (up to 95 % ee).     

Support vector machines in water quality management

Support vector classification (SVC) and regression (SVR) models were constructed and applied to the surface water quality data to optimize the monitoring program. The data set comprised of 1500 water samples representing 10 different sites monitored for 15 years. The objectives of the study were to classify the sampling sites (spatial) and months (temporal) to group the similar ones in terms of water quality with a view to reduce their number; and to develop a suitable SVR model for predicting the biochemical oxygen demand (BOD) of water using a set of variables. The spatial and temporal SVC models rendered grouping of 10 monitoring sites and 12 sampling months into the clusters of 3 each with misclassification rates of 12.39% and 17.61% in training, 17.70% and 26.38% in validation, and 14.86% and 31.41% in test sets, respectively. The SVR model predicted water BOD values in training, validation, and test sets with reasonably high correlation (0.952, 0.909, and 0.907) with the measured values, and low root mean squared errors of 1.53, 1.44, and 1.32, respectively. The values of the performance criteria parameters suggested for the adequacy of the constructed models and their good predictive capabilities. The SVC model achieved a data reduction of 92.5% for redesigning the future monitoring program and the SVR model provided a tool for the prediction of the water BOD using set of a few measurable variables. The performance of the nonlinear models (SVM, KDA, KPLS) was comparable and these performed relatively better than the corresponding linear methods (DA, PLS) of classification and regression modeling.