Efficient Pd‐Catalyzed Allene Synthesis from Alkynes and Aryl Bromides through an Intramolecular Base‐Assisted Deprotonation (iBAD) Mechanism

An optimized ligand‐controlled palladium‐catalyzed allene synthesis starting from alkynes and aryl bromides giving rise to allene products in a simple and direct manner is described. The methodology is performed in an inter‐ and intramolecular fashion with unprecedented scope and excellent yields. Based on mechanistic investigations and on DFT calculations, the role played by the carboxylic additive (i.e., PivOH) in controlling the selectivity of the reaction is discussed, allowing us to propose an intramolecular base‐assisted deprotonation (iBAD) mechanism for this process.     

The potential of asymmetric flow field-flow fractionation hyphenated to multiple detectors for the quantification and size estimation of silica nanoparticles in a food matrix

This work represents a first systematic approach to the size-based elemental quantification and size estimation of metal(loid) oxide nanoparticles such as silica (SiO₂) in a real food matrix using asymmetric flow field-flow fractionation coupled online with inductively coupled plasma mass spectrometry (ICP-MS) and multi-angle light scattering (MALS) and offline with transmission electron microscopy (TEM) with energy-dispersive X-ray analysis (EDAX). Coffee creamer was selected as the model sample since it is known to contain silica as well as metal oxides such as titania at the milligramme per kilogramme levels. Optimisation of sample preparation conditions such as matrix-to-solvent ratio, defatting with organic solvents and sonication time that may affect nanoparticle size and size distribution in suspensions was investigated. Special attention was paid to the selection of conditions that minimise particle transformation during sample preparation and analysis. The coffee creamer matrix components were found to stabilise food grade SiO₂ particles in comparison with water suspensions whilst no significant effect of defatting using hexane was found. The use of sample preparation procedures that mimic food cooking in real life was also investigated regarding their effect on particle size and particle size distribution of silica nanoparticles in the investigated food matrix; no significant effect of the water temperature ranging from ambient temperature to 60 °C was observed. Field-flow fractionation coupled to inductively coupled plasma-mass spectrometry (FFF-ICP-MS) analysis of extracts of both unspiked coffee creamer and coffee creamer spiked with food grade silicon dioxide, using different approaches for size estimation, enabled determination of SiO₂ size-based speciation. Element-specific detection by ICP-MS and post-FFF calibration with elemental calibration standards was used to determine the elemental composition of size fractions separated online by FFF. Quantitative data on mass balance is provided for the size-based speciation of the investigated inorganic nano-objects in the complex matrix. The combination of FFF with offline fractionation by filtration and with detection by ICP-MS and TEM/EDAX has been proven essential to provide reliable information of nanoparticle size in the complex food matrix.

Harnessing the complexity of metabolomic data with chemometrics

Because of the ever‐increasing number of signals that can be measured within a single run by modern platforms in analytical chemistry, life sciences datasets become not only gradually larger but also more intricate in their structures. Challenges related to making use of this wealth of data include extracting relevant elements within massive amounts of signals possibly spread across different tables, reducing dimensionality, summarising dynamic information in a comprehensible way and displaying it for interpretation purposes. Metabolomics constitutes a representative example of fast‐moving research fields taking advantage of recent technological advances to provide extensive sample monitoring. Because of the wide chemical diversity of metabolites, several analytical setups are required to provide a broad coverage of complex samples. The integration and visualisation of multiple highly multivariate datasets constitute key issues for effective analysis leading to valuable biological or chemical knowledge. Additionally, high‐order data structures arise from experimental setups involving time‐resolved measurements. These data are intrinsically multiway, and classical statistical tools cannot be applied without altering their organisation with the risk of information loss. Dedicated modelling algorithms, able to cope with the inherent properties of these metabolomic datasets, are therefore mandatory for harnessing their complexity and provide relevant information. In that perspective, chemometrics has a central role to play. Copyright © 2013 John Wiley & Sons, Ltd.     

Continuous-time limit of repeated interactions for a system in a confining potential

We study the continuous-time limit of a class of Markov chains coming from the evolution of classical open systems undergoing repeated interactions. This repeated interaction model has been initially developed for dissipative quantum systems in Attal and Pautrat (2006) and was recently set up for the first time in Deschamps (2012) for classical dynamics. It was particularly shown in the latter that this scheme furnishes a new kind of Markovian evolutions based on Hamilton’s equations of motion. The system is also proved to evolve in the continuous-time limit with a stochastic differential equation. We here extend the convergence of the evolution of the system to more general dynamics, that is, to more general Hamiltonians and probability measures in the definition of the model. We also present a natural way to directly renormalize the initial Hamiltonian in order to obtain the relevant process in a study of the continuous-time limit. Then, even if Hamilton’s equations have no explicit solution in general, we obtain some bounds on the dynamics allowing us to prove the convergence in law of the Markov chain on the system to the solution of a stochastic differential equation, via the infinitesimal generators.     

Excited states from range-separated density-functional perturbation theory

We explore the possibility of calculating electronic excited states by using perturbation theory along a range-separated adiabatic connection. Starting from the energies of a partially interacting Hamiltonian, a first-order correction is defined with two variants of perturbation theory: a straightforward perturbation theory and an extension of the Görling–Levy one that has the advantage of keeping the ground-state density constant at each order in the perturbation. Only the first, simpler, variant is tested here on the helium and beryllium atoms and on the hydrogen molecule. The first-order correction within this perturbation theory improves significantly the total ground- and excited-state energies of the different systems. However, the excitation energies mostly deteriorate with respect to the zeroth-order ones, which may be explained by the fact that the ionisation energy is no longer correct for all interaction strengths. The second (Görling–Levy) variant of the perturbation theory should improve these results but has not been tested yet along the range-separated adiabatic connection.     

Extent-based kinetic identification using spectroscopic measurements and multivariate calibration

Extent-based kinetic identification is a kinetic modeling technique that uses concentration measurements to compute extents and identify reaction kinetics by the integral method of parameter estimation. This article considers the case where spectroscopic data are used together with a calibration model to predict concentrations. The calibration set is assumed to be constructed from reacting data that include pairs of concentration and spectral data. Alternatively, one can use the concentration- and spectral contributions of the reactions and mass transfers, which are obtained by pretreatment in reaction- and mass-transfer-variant form. The extent-based kinetic identification using concentrations predicted from spectroscopic data is illustrated through the simulation of both a homogeneous and a gas–liquid reaction system.     

Gold(I) Complexes Nuclearity in Constrained Ferrocenyl Diphosphines: Dramatic Effect in Gold‐Catalyzed Enyne Cycloisomerization

Di‐tert‐butylated‐bis(phosphino)ferrocene ligands bearing phosphino substituents R (R=phenyl, cyclohexyl, iso‐propyl, mesityl, or furyl) allow tuning the selective formation of Au(I) halide complexes. Thus, dinuclear linear two‐coordinate, but also rare mononuclear trigonal three‐coordinate and tetrahedral four‐coordinate complexes were formed upon tuning of the conditions. Both Au(I) chloride and rarer Au(I) iodide complexes were synthesized, and their X‐ray diffraction analysis are reported. The significance of the control of structure and nuclearity in Au(I) complexes is further illustrated herein by its strong effect on the efficiency and selectivity of gold‐catalysed cycloisomerization. Cationic linear digold(I) bis(dicyclohexylphosphino) ferrocenes outperform other catalysts in the demanding regioselective cycloisomerization of enyne sulphonamides into cyclohexadienes. Conversely, tetrahedral and trigonal cationic monogold(I) complexes were found incompetent for enyne cycloaddition. We used the two‐coordinate linear electron‐rich Au(I) complex 2 b (R=Cy) to extend the scope of selective intramolecular cycloaddition of different 1,6‐enyne sulfonylamines with high activity and excellent selectivity to the endo cyclohexadiene products.     

Pulsed laser–deposited Li2TiO3 thin film electrodes for energy storage

Journal of Solid State Electrochemistry - Li2TiO3 (LTO) is a promising Ti-based material showing interesting electrochemical performance, good structural stability, cost-effectiveness, and...     

Total Synthesis of Tiacumicin B: Implementing Hydrogen Bond Directed Acceptor Delivery for Highly Selective β‐Glycosylations

A total synthesis of tiacumicin B, a natural macrolide whose remarkable antibiotic properties are used to treat severe intestinal infections, is reported. The strategy is in part based on the prior synthesis of the tiacumicin B aglycone, and on the decisive use of sulfoxides as anomeric leaving groups in hydrogen‐bond‐mediated aglycone delivery (HAD). This new HAD variant permitted highly β‐selective rhamnosylation and noviosylation. To increase convergence, the rhamnosylated C1–C3 fragment thus obtained was anchored to the C4–C19 aglycone fragment by adapting the Suzuki–Miyaura cross‐coupling used for the aglycone synthesis. Ring‐size‐selective macrolactonization provided a compound engaged directly in the noviolysation step with virtually total β selectivity. The final efficient removal of all the protecting groups provided synthetic tiacumicin B.     

RASS‐Enabled S/P−C and S−N Bond Formation for DEL Synthesis

DNA encoded libraries (DEL) have shown promise as a valuable technology for democratizing the hit discovery process. Although DEL provides relatively inexpensive access to libraries of unprecedented size, their production has been hampered by the idiosyncratic needs of the encoding DNA tag relegating DEL compatible chemistry to dilute aqueous environments. Recently reversible adsorption to solid support (RASS) has been demonstrated as a promising method to expand DEL reactivity using standard organic synthesis protocols. Here we demonstrate a suite of on‐DNA chemistries to incorporate medicinally relevant and C?S, C?P and N?S linkages into DELs, which are underrepresented in the canonical methods.