2-C-branched glycosides from 2'-carbonylalkyl 2-O-Ms(Ts)-C-glycosides. A tandem SN2-SN2 reaction via 1,2-cyclopropanated sugars

[reaction: see text] Under basic conditions, 2'-aldehydo (acetonyl) 2-O-Ms(Ts)-alpha-C-glycosides undergo an intramolecular S(N)2 reaction to form 1,2-cyclopropanated sugars, which react with nucleophiles (alcohols, thiols, and azide) at the anomeric carbon to give 2-C-branched glycosides. By way of contrast, the 1,2-cyclopropanes derived from 2'-ketones only react with thiols to give 2-C-branched thioglycosides.     

An Ethanol Biosensor Based on Simple Immobilization of Alcohol Dehydrogenase on Fe3O4@Au Nanoparticles

An ethanol biosensor based on alcohol dehydrogenase (ADH) attached to Au seeds decorated on magnetic nanoparticles (Fe₃O₄@Au NPs) is presented. ADH was immobilized on Fe₃O₄@Au NPs, which were subsequently fixed by a magnet on a carbon paste electrode modified with 5 % (m : m) MnO₂. Optimum conditions for the amperometric determination of ethanol with the biosensor were as follows: working potential +0.1 V (vs. Ag/AgCl); supporting electrolyte: 0.1 M phosphate buffer solution at pH 6.8 containing 0.25 mM of the coenzyme (NAD⁺); working electrode: carbon paste with magnetically attached Fe₃O₄@Au NPs (0.012 mg ? cm^?2 electrode area) with immobilized alcohol dehydrogenase (120 units per cm² of electrode area). Linearity between signal and concentration was found for the range from 0.1 to 2.0 M ethanol (r²=0.995) with a detection limit of 0.07 M, a sensitivity of 0.02 µA ? mM^?1 ? cm^?2, a reproducibility of 4.0 % RSD, and a repeatability of 2.7 % RSD. The results for the determination of ethanol in alcoholic beverages showed good agreement with gas chromatography (GC) with recovery of 96.0 – 108.8 %.     

1,2-migration of 2'-oxoalkyl group and concomitant synthesis of 2-C-branched O-, S-glycosides and glycosyl azides via 1,2-cyclopropanated sugars

Treatment of 2'-oxoalkyl 2-O-Ms(Ts)-alpha-C-mannosides (4, 5, and 6) with base resulted in 1,2-cyclopropanation via an intramolecular SN2 reaction due to their 1,2-trans-diaxial configurations. The 1,2-cyclopropanated sugars (10 and 13) were reacted with various alcohols, thiols, and sodium azide to produce 2-C-branched O- and S-glycosides and glycosyl azides (11, 14-28) in good to excellent yields. In contrast, 1,2-cis 2'-oxoalkyl 2-O-Ms(Ts)-alpha-C-glucoside 9 formed an acyclic conjugated aldehyde (31) under basic conditions, which occurred by 1'-enolation followed by beta-elimination. An intramolecular Michael addition from 31 produced 2-O-Ms-beta-C-glucoside 30 as a major product. However, due to the electron-withdrawing effect exerted by 2-O-Ms compound 31 also undergoes a C2 epimerization to form 32. Thereafter, the intramolecular Michael addition led to the formation of both 1,2-trans 2'-oxoalkyl 2-O-Ms-alpha-C-mannoside 4 and its beta-anomer (33). Because beta-elimination/Michael addition and C2 epimerization are reversible reactions, equilibriums among 9, 31, 30, 32, 33, and 4 were established, which included the transformation of 1,2-cis C-glucoside 9 into 1,2-trans C-mannoside 4. The subsequent 1,2-cyclopropanation of 4 was an irreversible reaction yielding 1,2-cyclopropanated 10 and further conversion to 1,2-migration products (11 and 12).     

Power oscillation suppression by robust SMES in power system with large wind power penetration

The large penetration of wind farm into interconnected power systems may cause the severe problem of tie-line power oscillations. To suppress power oscillations, the superconducting magnetic energy storage (SMES) which is able to control active and reactive powers simultaneously, can be applied. On the other hand, several generating and loading conditions, variation of system parameters, etc., cause uncertainties in the system. The SMES controller designed without considering system uncertainties may fail to suppress power oscillations. To enhance the robustness of SMES controller against system uncertainties, this paper proposes a robust control design of SMES by taking system uncertainties into account. The inverse additive perturbation is applied to represent the unstructured system uncertainties and included in power system modeling. The configuration of active and reactive power controllers is the first-order lead–lag compensator with single input feedback. To tune the controller parameters, the optimization problem is formulated based on the enhancement of robust stability margin. The particle swarm optimization is used to solve the problem and achieve the controller parameters. Simulation studies in the six-area interconnected power system with wind farms confirm the robustness of the proposed SMES under various operating conditions.