Methyl orange degradation enhanced by hydrogen spillover onto platinum nanocatalyst surface

Following a thermal reduction method, platinum nanoparticles were synthesized and stabilized by polyvinylpyrrolidone. The colloidal platinum nanoparticles were stable for more than 3 months. The micrograph analysis unveiled that the colloidal platinum nanoparticles were well dispersed with an average size of 2.53 nm. The sol–gel‐based inverse micelle strategy was applied to synthesize mesoporous iron oxide material. The colloidal platinum nanoparticles were deposited on mesoporous iron oxide through the capillary inclusion method. The small‐angle X‐ray scattering analysis indicated that the dimension of platinum nanoparticles deposited on mesoporous iron oxide (Pt‐Fe₂O₃) was 2.64 nm. X‐ray photoelectron spectroscopy (XPS) data showed that the binding energy on Pt‐Fe₂O₃ surface decreased owing to mesoporous support–nanoparticle interaction. Both colloidal and deposited platinum nanocatalysts improved the degradation of methyl orange under reduction conditions. The activation energy on the deposited platinum nanocatalyst interface (2.66 kJ mol^?1) was significantly lowered compared with the one on the colloidal platinum nanocatalyst interface (40.63 ± 0.53 kJ mol^?1).     

Aryl Boronic Acid Catalysed Dehydrative Substitution of Benzylic Alcohols for C−O Bond Formation

A combination of pentafluorophenylboronic acid and oxalic acid catalyses the dehydrative substitution of benzylic alcohols with a second alcohol to form new C−O bonds. This method has been applied to the intermolecular substitution of benzylic alcohols to form symmetrical ethers, intramolecular cyclisations of diols to form aryl-substituted tetrahydrofuran and tetrahydropyran derivatives, and intermolecular crossed-etherification reactions between two different alcohols. Mechanistic control experiments have identified a potential catalytic intermediate formed between the aryl boronic acid and oxalic acid.     

Cascaded Plasma–Ozone Injection System: A Novel Approach for Controlling Total Hydrocarbon Emission in Diesel Exhaust

Plasma Chemistry and Plasma Processing - The hydrocarbons present in diesel exhaust, although treated as minor pollutants, are equivalent to some of the major pollutants in terms of toxicity,...     

Comparison of fast field-cycling magnetic resonance imaging methods and future perspectives

ABSTRACT

Fast field-cycling (FFC) nuclear magnetic resonance relaxometry is a well-established method to determine the relaxation rates as a function of magnetic field strength. This so-called nuclear magnetic relaxation dispersion gives insight into the underlying molecular dynamics of a wide range of complex systems and has gained interest especially in the characterisation of biological tissues and diseases. The combination of FFC techniques with magnetic resonance imaging (MRI) offers a high potential for new types of image contrast more specific to pathological molecular dynamics. This article reviews the progress in FFC-MRI over the last decade and gives an overview of the hardware systems currently in operation. We discuss limitations and error correction strategies specific to FFC-MRI such as field stability and homogeneity, signal-to-noise ratio, eddy currents and acquisition time. We also report potential applications with impact in biology and medicine. Finally, we discuss the challenges and future applications in transferring the underlying molecular dynamics into novel types of image contrast by exploiting the dispersive properties of biological tissue or MRI contrast agents.     

Intramolecular Hydroamination of Selenoalkynes to 2-Selenylindoles in the Absence of Catalyst

In this work, a series of 2-chalcogenylindoles was synthesized by an efficient methodology, starting from chalcogenoalkynes, including a previously unreported tellurium indole derivative. For the first time, these 2-substituted chalcogenylindoles were obtained in the absence of metal catalyst or base, under thermal conditions only. In addition, the results described herein represent a methodology with inverse regioselectivity for the chalcogen functionalization of indoles.     

The Landscape of the Spiked Tensor Model

We consider the problem of estimating a large rank-one tensor u ^⊗k ∈ (ℝⁿ)^⊗k , k ≥ 3 , in Gaussian noise. Earlier work characterized a critical signal-to-noise ratio λ  _Bayes = O(1) above which an ideal estimator achieves strictly positive correlation with the unknown vector of interest. Remarkably, no polynomial-time algorithm is known that achieved this goal unless λ ≥ Cn^{(k − 2)/4} , and even powerful semidefinite programming relaxations appear to fail for 1 ≪ λ ≪ n^{(k − 2)/4} . In order to elucidate this behavior, we consider the maximum likelihood estimator, which requires maximizing a degree-k homogeneous polynomial over the unit sphere in n dimensions. We compute the expected number of critical points and local maxima of this objective function and show that it is exponential in the dimensions n , and give exact formulas for the exponential growth rate. We show that (for λ larger than a constant) critical points are either very close to the unknown vector u or are confined in a band of width Θ(λ^{−1/(k − 1)}) around the maximum circle that is orthogonal to u . For local maxima, this band shrinks to be of size Θ(λ^{−1/(k − 2)}) . These “uninformative” local maxima are likely to cause the failure of optimization algorithms. © 2019 Wiley Periodicals, Inc.