Characterization of polyoxometalate/polymer photo-composites: A toolbox for the photodegradation of organic pollutants

Different inorganic/organic photocomposites based on polyoxometalate (POM) nanoparticles have been developed for photocatalytic applications. Currently, polyoxometalate nanoparticles have been successfully in-situ embedded into an acrylate polymer network by photopolymerization upon mild visible light irradiation at 405 nm. The proposed POM/polymer photocomposites have been characterized using complementary techniques for a better understanding of their photocatalytic activity. Interestingly, the obtained photocomposites exhibit high rigidity, excellent thermal stability, a non-negligible porosity and new functionalities such as light reactivity and redox properties. Moreover, developed composites showed efficient catalytic activity for the color removal of aqueous solutions of erythrosine and rose Bengal under Light Emitting Diodes LED@375 nm irradiation reaching 80 and 90% as a final color removal, respectively.     

Predicting retrosynthetic pathways using transformer-based models and a hyper-graph exploration strategy

We present an extension of our Molecular Transformer model combined with a hyper-graph exploration strategy for automatic retrosynthesis route planning without human intervention. The single-step retrosynthetic model sets a new state of the art for predicting reactants as well as reagents, solvents and catalysts for each retrosynthetic step. We introduce four metrics (coverage, class diversity, round-trip accuracy and Jensen–Shannon divergence) to evaluate the single-step retrosynthetic models, using the forward prediction and a reaction classification model always based on the transformer architecture. The hypergraph is constructed on the fly, and the nodes are filtered and further expanded based on a Bayesian-like probability. We critically assessed the end-to-end framework with several retrosynthesis examples from literature and academic exams. Overall, the frameworks have an excellent performance with few weaknesses related to the training data. The use of the introduced metrics opens up the possibility to optimize entire retrosynthetic frameworks by focusing on the performance of the single-step model only.

We present an extension of our Molecular Transformer model combined with a hyper-graph exploration strategy for automatic retrosynthesis route planning without human intervention.     

Rapid Discrimination of Crystal Handedness by X-ray Natural Circular Dichroism (XNCD) Mapping

An original method for determining the handedness of individual non-centrosymmetric crystals in a mixture using a tightly-focused, circularly polarized X-ray beam is presented. The X-ray natural circular dichroism (XNCD) spectra recorded at the metal K-edge on selected crystals of [Δ-M(en)₃](NO₃)₂ and [Λ-M(en)₃](NO₃)₂ (M=Co^II, Ni^II) show extrema at the metal pre-edge (7712 eV for Co, 8335 eV for Ni). A mapping of a collection of some 220 crystals was performed at the respective energies by using left and right circular polarizations. The difference in absorption for the two polarizations, being either negative or positive, directly yielded the handedness of the crystal volume probed by the beam. By using this technique, it was found that the addition of l -ascorbic acid during the synthesis of [Co(en)₃](NO₃)₂ resulted in an enantiomeric enrichment of the Λ-isomer of 67±13 %, whereas the Ni analogue was similarly, but conversely, enriched in the Δ-isomer (65±22 %).     

A stochastic analysis of a network with two levels of service

Queueing Systems - In this paper, a stochastic model of a call center with a two-level architecture is analyzed. A first-level pool of operators answers calls, identifies, and handles non-urgent...     

Aerodynamic optimization of the flat-plate leading edge for experimental studies of laminar and transitional boundary layers

This work is concerned with the design of a leading edge for a flat-plate model used to study laminar and transitional boundary layers. For this study, the flow over the complete boundary-layer model, including leading edge, flat section, and trailing-edge flap, is modeled. The effect of important geometrical features of the leading edge on the resulting pressure distribution, starting from the well-known symmetric modified super ellipse, is investigated. A minimal pressure gradient on the measurement side of the plate is achieved using an asymmetrical configuration of modified super ellipses, with a thickness ratio of 7/24. An aerodynamic shape optimization is performed to obtain a novel leading edge shape that greatly reduces the length of the non-zero pressure gradient region and the adverse pressure gradient region compared to geometries defined by ellipses. Wind tunnel testing is used to validate the numerical solutions.     

Novel organometallic chalcones functionalized with a crown ether fragment as optical ion chemosensors

We previously reported the synthesis and characterization of new organometallic chalcones derived from ferrocene, cyrhetrene and cymantrene functionalized with a benzo‐15‐crown‐5 fragment. The ferrocene and cyrhetrene chalcones have been investigated as chemosensors for metal ions with optical response in acetonitrile. Several metal ions were selected considering the diameter of the cavity and the charge‐to‐radius ratio of the cation. The stoichiometry of the complexes was determined using Job's method. It was found that Na⁺ and Ca²⁺ complexes have a 1:1 stoichiometry while a 2:1 (metaloligand‐to‐cation) stoichiometry was determined for Ba²⁺ and Pb²⁺ complexes. The association constants were calculated according to the stoichiometry of the complex and the results showed that they are directly affected by the electron‐withdrawing nature of the organometallic fragment. Moreover, complexes of ferrocenyl chalcone have larger association constants than those of the cyrhetrenyl analogue. This experimental observation is consistent with the electronic properties of the ferrocenyl fragment.     

gem-Heteroatom-Substituted Fluoroalkenes as Mimics of Amide Derivatives or Phosphates: A Comprehensive Review

gem-Heteroatom-substituted fluoroalkenes have received little attention despite their great potential in medicinal chemistry or in fine chemistry. Indeed, due to the electronic and steric similarity between the fluoroalkene moiety and the amide bond as well as the high strength of the carbon-fluorine bond, these gem-heteroatom-substituted fluoroalkenes could be envisioned as stable mimics of various important organic functions, such as phosphates, carbamates, S-thiocarbamates and ureas. We present herein an overview describing the syntheses over the last decade of heteroatom-substituted fluoroalkenes in geminal position. This review will be divided into several sections covering each the common following heteroatom: oxygen-, nitrogen-, sulfur-, phosphorus-, boron- and silicon-substituted fluoroalkenes.     

Numerically stable,scalable formulas for parallel and online computation of higher-order multivariate central moments with arbitrary weights

Formulas for incremental or parallel computation of second order central moments have long been known, and recent extensions of these formulas to univariate and multivariate moments of arbitrary order have been developed. Such formulas are of key importance in scenarios where incremental results are required and in parallel and distributed systems where communication costs are high. We survey these recent results, and improve them with arbitrary-order, numerically stable one-pass formulas which we further extend with weighted and compound variants. We also develop a generalized correction factor for standard two-pass algorithms that enables the maintenance of accuracy over nearly the full representable range of the input, avoiding the need for extended-precision arithmetic. We then empirically examine algorithm correctness for pairwise update formulas up to order four as well as condition number and relative error bounds for eight different central moment formulas, each up to degree six, to address the trade-offs between numerical accuracy and speed of the various algorithms. Finally, we demonstrate the use of the most elaborate among the above mentioned formulas, with the utilization of the compound moments for a practical large-scale scientific application.     

Physical complexity of variable length symbolic sequences

A measure called physical complexity is established and calculated for a population of sequences, based on statistical physics, automata theory, and information theory. It is a measure of the quantity of information in an organism’s genome. It is based on Shannon’s entropy, measuring the information in a population evolved in its environment, by using entropy to estimate the randomness in the genome. It is calculated from the difference between the maximal entropy of the population and the actual entropy of the population when in its environment, estimated by counting the number of fixed loci in the sequences of a population. Up until now, physical complexity has only been formulated for populations of sequences with the same length. Here, we investigate an extension to support variable length populations. We then build upon this to construct a measure for the efficiency of information storage, which we later use in understanding clustering within populations. Finally, we investigate our extended physical complexity through simulations, showing it to be consistent with the original.