Rate and Computational Studies for Pd-NHC-Catalyzed Amination with Primary Alkylamines and Secondary Anilines: Rationalizing Selectivity for Monoarylation versus Diarylation with NHC Ligands

The relative rates of arylation of primary alkylamines with different Pd-NHC catalysts have been measured, as have the relative rates of arylation of the secondary aniline product in an attempt to understand the key ligand design features necessary to have high selectivity for the monoarylated amine product. As the substituents on the N-aryl ring of the NHC increase in size, selectivity for monoarylation increases and this is further enhanced by chlorinating the back of the NHC ring. Computations have been performed on the catalytic cycle of this transformation in order to understand the selectivity obtained with the different catalysts.     

Use of nanoporous Na+-montmorillonite sulfonic acid (SANM) as an eco-benign, efficient and reusable solid acid catalyst for the one-pot synthesis of 14-aryl-14-H-dibenzo[a,j]xanthenes and 1,8-dioxo-dodecahydroxanthene derivatives

Nanoporous Na⁺-montmorillonite sulfonic acid was found to be an efficient and green catalyst for the synthesis of various 14-aryl-14H-dibenzo[a,j]xanthenes and 1,8-dioxo-dodecahydroxanthene derivatives by the reaction of aldehydes with 2-naphthol and 1,3-cyclohexanedione, respectively. This novel synthetic method has the advantages of high yields, short reaction times and recyclability of the catalyst, simplicity and easy workup compared to the conventional methods reported in the literature.     

Regression and ANN models for estimating minimum value of machining performance

Surface roughness is one of the most common performance measurements in machining process and an effective parameter in representing the quality of machined surface. The minimization of the machining performance measurement such as surface roughness (R_a) must be formulated in the standard mathematical model. To predict the minimum R_a value, the process of modeling is taken in this study. The developed model deals with real experimental data of the R_a in the end milling machining process. Two modeling approaches, regression and Artificial Neural Network (ANN), are applied to predict the minimum R_a value. The results show that regression and ANN models have reduced the minimum R_a value of real experimental data by about 1.57% and 1.05%, respectively.     

Decorations of graphene oxide with cisplatin toward investigation of fluorescence quencher on regulatory sequence of BRCA1 and BRCA2

Journal of the Iranian Chemical Society - Herein, we investigated the interaction of cisplatin loaded on GO (GO@CDDP) with two regulatory sequences, BRCA1 and BRCA2, synthesized from ssDNA based on...     

Rice-husk-supported FeCl3 nano-particles: Introduction of a mild,efficient and reusable catalyst for some of the multi-component reactions

Rice-husk-supported FeCl₃ nano-particles (FeCl₃–RiH) were prepared and used as an environmentally friendly catalyst in the synthesis of β-amino carbonyl compounds, 1,8-dioxo-octahydro xanthenes, and bis-indolyl methanes from simple and readily available precursor molecules.