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The prenyl group is present in numerous biologically active small molecule drugs and natural products. We introduce benzylic C-H alkenylation of substrates Ar-CH3 with alkenylboronic esters (CH2)3O2B-CH=CMe2 as a pathway to form prenyl functionalized arenes Ar-CH2CH=CMe2. Mechanistic studies of this radical relay catalytic protocol reveal diverse reactivity pathways exhibited by the copper(II) vinyl intermediate [CuII]-CH=CMe2 that involve radical capture, bimolecular C-C bond formation, and hydrogen atom transfer (HAT). 

The methyl moiety is a key functional group that can result in major improvements in the potency and selectivity of pharmaceutical agents. We present a radical relay C–H methylation methodology that employs a β-diketiminate copper catalyst capable of methylating unactivated C(sp3)–H bonds. Taking advantage of the bench-stable DABAL-Me3, an amine-stabilized trimethylaluminum reagent, methylation of a range of substrates possessing both activated and unactivated C(sp3)–H bonds proceeds with a minimal amount of overmethylation. Mechanistic studies supported by both experiment and computation suggest the intermediacy of a copper(II) methyl intermediate reactive toward both the loss of the methyl radical as well capture of radicals R• to form R–Me bonds. 

Abstract α‐substituted ketones are important chemical targets as synthetic intermediates as well as functionalities in natural products and pharmaceuticals. We report the α‐acetylation of C(sp³)−H substrates R−H with arylmethyl ketones ArC(O)Me to provide α‐alkylated ketones ArC(O)CH₂R at RT with^tBuOO^tBu as oxidant via copper(I) ‐diketiminato catalysts. Proceeding via alkyl radicals R•, this method enables α‐substitution with bulky substituents without competing elimination that occurs in more traditional alkylation reactions between enolates and alkyl electrophiles. DFT studies suggest the intermediacy of copper(II) enolates [Cu^II](CH₂C(O)Ar) that capture alkyl radicals R• to give R−CH₂C(O)Ar outcompeting dimerization of the copper(II) enolate to give the 1,4‐diketone ArC(O)CH₂CH₂C(O)Ar. 

Our computational developments and analyses on experimental images are designed to evaluate the effectiveness of chemical spraying via unmanned aerial vehicle (UAV). Our evaluations are in accord with the two perspectives of color-complexity: color variety within a color system and color distributional geometry on an image. First, by working within RGB and HSV color systems, we develop a new color-identification algorithm relying on highly associative relations among three color-coordinates to lead us to exhaustively identify all targeted color-pixels. A color-dot is then identified as one isolated network of connected color-pixel. All identified color-dots vary in shapes and sizes within each image. Such a pixel-based computing algorithm is shown robustly and efficiently accommodating heterogeneity due to shaded regions and lighting conditions. Secondly, all color-dots with varying sizes are categorized into three categories. Since the number of small color-dot is rather large, we spatially divide the entire image into a 2D lattice of rectangular. As such, each rectangle becomes a collective of color-dots of various sizes and is classified with respect to its color-dots intensity. We progressively construct a series of minimum spanning trees (MST) as multiscale 2D distributional spatial geometries in a decreasing-intensity fashion. We extract the distributions of distances among connected rectangle-nodes in the observed MST and simulated MSTs generated under the spatial uniformness assumption. We devise a new algorithm for testing 2D spatial uniformness based on a Hierarchical clustering tree upon all involving MSTs. This new tree-based p -value evaluation has the capacity to become exact.