Mild and Phosphine-Free Iron-Catalyzed Cross-Coupling of Nonactivated Secondary Alkyl Halides with Alkynyl Grignard Reagents

A simple protocol for iron-catalyzed cross-coupling of nonactivated secondary alkyl bromides and iodides with alkynyl Grignard reagents at room temperature has been developed. A wide range of secondary alkyl halides and terminal alkynes are tolerated to afford the substituted alkynes in good yields. A slight modification of the reaction protocol also allows for cross-coupling with a variety of primary alkyl halides

Tri(1-adamantyl)phosphine: Expanding the Boundary of Electron-Releasing Character Available to Organophosphorus Compounds

We report here the remarkable properties of PAd₃, a crystalline air-stable solid accessible through a scalable S_N1 reaction. Spectroscopic data reveal that PAd₃, benefiting from the polarizability inherent to large hydrocarbyl groups, exhibits unexpected electron releasing character that exceeds other alkylphosphines and falls within a range dominated by N-heterocyclic carbenes. Dramatic effects in catalysis are also enabled by PAd₃ during Suzuki–Miyaura cross-coupling of chloro­(hetero)­arenes (40 examples) at low Pd loading, including the late-stage functionalization of commercial drugs. Exceptional space-time yields are demonstrated for the syntheses of industrial precursors to valsartan and boscalid from chloroarenes with ∼2 × 10⁴ turnovers in 10 min

Tri(1-adamantyl)phosphine: Expanding the Boundary of Electron-Releasing Character Available to Organophosphorus Compounds

We report here the remarkable properties of PAd₃, a crystalline air-stable solid accessible through a scalable S_N1 reaction. Spectroscopic data reveal that PAd₃, benefiting from the polarizability inherent to large hydrocarbyl groups, exhibits unexpected electron releasing character that exceeds other alkylphosphines and falls within a range dominated by N-heterocyclic carbenes. Dramatic effects in catalysis are also enabled by PAd₃ during Suzuki–Miyaura cross-coupling of chloro­(hetero)­arenes (40 examples) at low Pd loading, including the late-stage functionalization of commercial drugs. Exceptional space-time yields are demonstrated for the syntheses of industrial precursors to valsartan and boscalid from chloroarenes with ∼2 × 10⁴ turnovers in 10 min

Sea Surface Temperature Prediction With Memory Graph Convolutional Networks

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Segmenting Oil Spills from Blurry Images Based on Alternating Direction Method of Multipliers

We exploit the alternating direction method of multipliers (ADMM) for developing an oil spill segmentation method, which effectively detects oil spill regions in blurry synthetic aperture radar (SAR) images. We commence by constructing energy functionals for SAR image deblurring and oil spill segmentation separately. We then integrate the two energy functionals into one overall energy functional subject to a linear mapping constraint that correlates the deblurred image and the segmentation indicator. The overall energy functional along with the linear constraint follows the form of alternating direction method of multipliers and thus enables an effective augmented Lagrangian optimization. Furthermore, the iterative updates in the ADMM maintain information exchanges between the energy minimizations for SAR image deblurring and oil spill segmentation. Most existing blurry image segmentation strategies tend to consider deblurring and segmentation as two independent procedures with no interactions, and the operation of deblurring is thus not guided for obtaining accurate segmentation. In contrast, we integrate deblurring and segmentation into one overall energy minimization framework with information exchanges between the two procedures. Therefore, the deblurring procedure is inclined to operate in favor of more accurate oil spill segmentation. Experimental evaluations validate that our framework outperforms the separate deblurring and segmentation strategy for detecting oil spill regions in blurry SAR images

Copper-Catalyzed Alkylation of Benzoxazoles with Secondary Alkyl Halides

Copper-catalyzed direct alkylation of benzoxazoles using nonactivated secondary alkyl halides has been developed. The best catalyst is a new copper(I) complex (<b>1</b>), and the reactions are promoted by bis[2-(<i>N</i>,<i>N</i>-dimethylamino)ethyl] ether

Copper-Catalyzed Alkylation of Benzoxazoles with Secondary Alkyl Halides

Copper-catalyzed direct alkylation of benzoxazoles using nonactivated secondary alkyl halides has been developed. The best catalyst is a new copper(I) complex (<b>1</b>), and the reactions are promoted by bis[2-(<i>N</i>,<i>N</i>-dimethylamino)ethyl] ether

C–H Alkenylation of Heteroarenes: Mechanism, Rate, and Selectivity Changes Enabled by Thioether Ligands

Thioether ancillary ligands have been identified that can greatly accelerate the C–H alkenylation of <i>O</i>-, <i>S</i>-, and <i>N</i>-heteroarenes. Kinetic data suggest thioether–Pd-catalyzed reactions can be as much as 800× faster than classic ligandless systems. Furthermore, mechanistic studies revealed C–H bond cleavage as the turnover-limiting step, and that rate acceleration upon thioether coordination is correlated to a change from a neutral to a cationic pathway for this key step. The formation of a cationic, low-coordinate catalytic intermediate in these reactions may also account for unusual catalyst-controlled site selectivity wherein C–H alkenylation of five-atom heteroarenes can occur under electronic control with thioether ligands even when this necessarily involves reaction at a more hindered C–H bond. The thioether effect also enables short reaction times under mild conditions for many <i>O-</i>, <i>S</i>-, and <i>N</i>-heteroarenes (55 examples), including examples of late-stage drug derivatization

A benchmark image dataset for industrial tools

Robots and Artificial Intelligence (AI) play an increasingly important role in manufacture. One of the tasks is to identify tools in the scene so that the tools can be applied to different assembly purposes. In the AI community, many datasets have been generated and deployed to train robots to recognize individual items, however, these datasets are scene-specific and lack generic background. In this paper, we report our dataset contains photos of 8 objects types that would be easily recognized by qualified workers. This is achieved by gathering images of common tools in a typical factory. The ground truth categories of our dataset are manually labeled by experienced workers, which would be worthy evaluation tools for the intelligence industrial systems. The equipment used and the image collection process are discussed, along with the data format. The mean average precisions range from 64.37% to 78.20%, which bring the possibility for future improvement. The dataset is ideal to evaluate and benchmark view-point variant, vision-based control algorithm for industry robots. It is now public available from https://github.com/tools-dataset/Industrial-Tools-Detection-Dataset

Nickel-Catalyzed Diastereoselective Alkyl–Alkyl Kumada Coupling Reactions

A nickel pincer complex is found to catalyze alkyl–alkyl Kumada coupling reactions of 1,3- and 1,4-substituted cyclohexyl halides and tetrahydropyrans with an excellent diastereoselectivity. The mechanistic investigation of the coupling reactions provides evidence that the activation of alkyl halides is reversible