Biaryl sulfonamides from O‐acetyl amidoximes: 1,2,4‐Oxadiazole cyclization under acidic conditions

A series of 4‐cyanobenzenesulfonamides ( 1a , 1b , 1c , 1d , 1e , 1f , 1g , 1h ) was converted to the corresponding O‐acetylated amidoximes ( 2a , 2b , 2c , 2d , 2e , 2f , 2g , 2h ). The reaction of 1a was exemplarily investigated with respect to the formation of a byproduct, which was identified as 1,2,4‐oxadiazole derivative 3a . This observation led to the development of an improved procedure for the preparation of 2a , 2b , 2c , 2d , 2e , 2f , 2g , 2h . Compounds 2 could be transformed to 1,2,4‐oxadiazoles 3a , 3b , 3c , 3d , 3e , 3f , 3g , 3h in high yields and purity upon heating in acetic acid. J. Heterocyclic Chem., (2011).     

Seeded dispersion polymerization of MMA using submicron PMMA particles as seed: a mechanistic study

Micron-size poly(methyl methacrylate) (PMMA) particles having a narrow particle size distribution were prepared by seeded dispersion polymerization of methyl methacrylate (MMA) using submicron PMMA particles as seed. The processes of particle aggregation and nucleation were controlled by the initial seed size, initial seed number, and initiator concentration, determining the formation of the mature particles and the number (N _(final)) and size of the final particles. It was found that N _(final) was equal to the number of particles produced in the absence of seed (N _{(ab initio)}) when the initial number of seed particles (N _(initial)) was less than N _{(ab initio)}. When N _(initial) was greater than N _{(ab initio)}, N _(final) was equal to k?×?N _(initial), where the value of k was a function of seed size and initiator concentration. k increased with seed size and was less than 1 at high initiator concentrations (0.52 and 1.00 %), while at low initiator concentrations (0.23 and 0.30 %), a maximum value of k was found for a 198 nm seed size. k could be greater than unity in some cases.     

Observation of two-neutrino double-beta decay in 136Xe with the EXO-200 detector

We report the observation of two-neutrino double-beta decay in (136)Xe with T(1/2) = 2.11 ± 0.04(stat) ± 0.21(syst) × 10(21) yr. This second-order process, predicted by the standard model, has been observed for several nuclei but not for (136)Xe. The observed decay rate provides new input to matrix element calculations and to the search for the more interesting neutrinoless double-beta decay, the most sensitive probe for the existence of Majorana particles and the measurement of the neutrino mass scale.     

Ligand Bite Angle‐Dependent Palladium‐Catalyzed Cyclization of Propargylic Carbonates to 2‐Alkynyl Azacycles or Cyclic Dienamides

The regioselectivity of the palladium‐catalyzed cyclization of propargylic carbonates with sulfonamide nucleophiles is critically dependent on the bite angle of the bidentate phosphine ligand. Ligands with small bite angles favor attack on the central carbon atom of an allenylpalladium intermediate to afford cyclic dienamide products, whereas the use of those with large bite angles leads to alkynyl azacycles, with high stereoselectivity. A computational analysis of the reaction pathway is also presented.     

Beam‐Induced Fe Nanopillars as Tunable Domain‐Wall Pinning Sites

Focused‐electron‐beam‐induced deposition (FEBID) is employed to create freestanding magnetic nanostructures. By growing Fe nanopillars on top of a perpendicular magnetic domain wall (DW) conduit, pinning of the DWs is observed due to the stray fields emanating from the nanopillar. Furthermore, a different DW pinning behavior is observed between the up and down magnetic states of the pillar, allowing to deduce the switching fields of the pillar in a novel way. The implications of these results are two‐fold: not only can 3‐dimensional nano‐objects be used to control DW motion in applications, it is also proposed that DW motion is a unique tool to probe the magnetic properties of nano‐objects.     

Derivation of monotone decision models from noisy data

Often, in economic decision problems such as credit loan approval or risk analysis, data mining models are required to be monotone with respect to the decision variables involved. If the model is obtained by a blind search through the data, it does mostly not have this property, even if the underlying database is monotone. In this correspondence, we present methods to enforce monotonicity of decision models. We propose measures to express the degree of monotonicity of the data and an algorithm to make data sets monotone. In addition, it is shown that decision trees derived from cleaned data perform better compared to trees derived from raw data.