Menthyl Grignard reagent 1 from either menthyl chloride (2) or neomenthyl chloride (3) consists of menthylmagnesium chloride (1a), neomenthylmagnesium chloride (1b), trans-p-menthane (4), 2-menthene (8), 3-menthene (9), and Wurtz coupling products including symmetrical bimenthyl 13. The diastereomeric ratio 1a/1b was determined in situ by 13 C NMR or after D 2 O quenching by 2 H NMR analysis. Hydrolysis of the C−Mg bond proceeds with retention of configuration at C-1. The kinetic ratio 1a/1b from Grignard reagent generation (dr 59:41 at 50 °C in THF) is close to the thermodynamic ratio (56:44 at 50 °C in THF). Carboxylation of 1 at −78 °C separates diastereomers 1a/b to give the anion of menthanecarboxylic acid (19) from 1a, which combines with unreactive 1b to give neomenthylmagnesium menthanecarboxylate (1b I ). The kinetics of epimerization for the menthyl/neomenthylmagnesium system was analyzed (ΔH ⧧ = 98.5 kJ/mol, ΔS ⧧ = −113 J/mol•K for 1b I → 1a I ). Reactions of 1 with phosphorus electrophiles proceed stereoconvergently at C-1 of 1a/b to give predominantly menthyl-configured substitution products: PCl 3 and 2 equiv of 1 give Men 2 PCl (6), which hydrolyzes to dimenthylphosphine P-oxide (7), whereas Ph 2 PCl with 1 equiv of 1 gave Pmenthyldiphenylphosphine oxide (27) after workup in air.

Hydrogen‐autotransfer alkylation (HAT or “borrowing‐hydrogen” alkylation) of heteroaromatic compounds has been studied with a range of substrates recently, but pyrroles have been largely absent from such studies. The conditions for HAT alkylations of pyrroles were investigated under a variety of conditions and were found to take place under basic alcoholic conditions (Hans Fischer alkylation) in the absence of transition‐metal catalysts; by means of a heterogeneous Pd/C catalyst in the presence of base; and finally by means of homogeneous transition‐metal catalysis combining a base and iridium pincer complexes generated in situ that have not previously been used in HAT alkylations of heterocycles.

Attaching di­(1R)-menthylphosphino fragments (menthyl = Men = 1R,2S,5R-2-isopropyl-5-methylcyclohex-1-yl) to molecular scaffolds turns them into homochiral, bulky, electron-rich phosphine ligands with proven and potential applications in coordination chemistry and transition-metal catalysis. Dimenthylphosphine P-oxide (Men2POH; 1) is established as a platform chemical toward dimenthylphosphino-containing targets via transformation to the known ligand precursors dimenthylchlorophosphine (4) and dimenthylphosphine (6). Transformations of 1 to dimenthylphosphinyl chloride (5) and dimenthylphosphinic acid (8) are elaborated. A phospha-Michael type 1,4-addition of 1 to p-benzo- or 1,4-naphthoquinone gives the corresponding o-hydroxyaryl­(dimenthyl)­phosphine oxides. Deprotonation of 1 with n-BuLi provides a phosphinyl nucleophile, whose reactions with alkyl halides or 1,n-dihaloalkanes provide tertiary alkyl dimenthylphosphine oxides or 1,n-bis­(dimenthylphosphino)­alkane bis­(P-oxides) 10a–c, respectively. As an example, oxide 10b was deoxygenated to the diphosphine Men2P­(CH2)3PMen2 (11) and characterized via the square-planar complex [(Men2P­(CH2)3PMen2)­PdCl2] (12). A selection of P-aryl dimenthylphosphines, including PhP­(Men)2 (19) and 2-ClC6H4P­(Men)2 (22), as well as the menthyl analogues Men-JohnPhos (21) and Men-SPhos (24), of the respective Buchwald ligands have been prepared. The combination of the secondary phosphine oxide (SPO) 1 with PdCl2 produces halide-bridged [(Men2POH)2Pd2Cl2] (25), mononuclear [(Men2POH)2PdCl2] (26), or the halide-bridged pseudochelate complex [(Men2PO···H···OPMen2)2Pd2Cl2] (27), depending on the reaction stoichiometry and conditions, all of which have been crystallographically characterized. The new ligands 1, 19, 21, 22, and 24 and complexes 25 and 26 have been evaluated in model palladium-catalyzed C–C- and C–N-fragment coupling reactions and found to display specific reactivity profiles due to the presence of the menthyl groups. Ligand 22 in particular catalyzed an asymmetric biaryl-forming coupling to give 2-methoxy-1,1′-binaphthalene with an er of up to 93:7.

Different components of the newly defined field of surgical data science have been under research at our groups for more than a decade now. In this paper, we describe our sensor-driven approaches to workflow recognition without the need for explicit models, and our current aim is to apply this knowledge to enable contextaware surgical assistance systems, such as a unified surgical display and robotic assistance systems. The methods we evaluated over time include dynamic time warping, hidden Markov models, random forests, and recently deep neural networks, specifically convolutional neural networks.