Electrocatalytic Reduction of CO2 to Ethylene by Molecular Cu‐Complex Immobilized on Graphitized Mesoporous Carbon

The electrochemical reduction of carbon dioxide (CO₂) to hydrocarbons is a challenging task because of the issues in controlling the efficiency and selectivity of the products. Among the various transition metals, copper has attracted attention as it yields more reduced and C2 products even while using mononuclear copper center as catalysts. In addition, it is found that reversible formation of copper nanoparticle acts as the real catalytically active site for the conversion of CO₂ to reduced products. Here, it is demonstrated that the dinuclear molecular copper complex immobilized over graphitized mesoporous carbon can act as catalysts for the conversion of CO₂ to hydrocarbons (methane and ethylene) up to 60%. Interestingly, high selectivity toward C2 product (40% faradaic efficiency) is achieved by a molecular complex based hybrid material from CO₂ in 0.1 m KCl. In addition, the role of local pH, porous structure, and carbon support in limiting the mass transport to achieve the highly reduced products is demonstrated. Although the spectroscopic analysis of the catalysts exhibits molecular nature of the complex after 2 h bulk electrolysis, morphological study reveals that the newly generated copper cluster is the real active site during the catalytic reactions.     

A Novel Beam Search to Improve Neural Machine Translation for English-Chinese

Neural Machine Translation (NMT) is an end-to-end learning approach for automated translation, overcoming the weaknesses of conventional phrase-based translation systems. Although NMT based systems have gained their popularity in commercial translation applications, there is still plenty of room for improvement. Being the most popular search algorithm in NMT, beam search is vital to the translation result. However, traditional beam search can produce duplicate or missing translation due to its target sequence selection strategy. Aiming to alleviate this problem, this paper proposed neural machine translation improvements based on a novel beam search evaluation function. And we use reinforcement learning to train a translation evaluation system to select better candidate words for generating translations. In the experiments, we conducted extensive experiments to evaluate our methods. CASIA corpus and the 1,000,000 pairs of bilingual corpora of NiuTrans are used in our experiments. The experiment results prove that the proposed methods can effectively improve the English to Chinese translation quality.     

Changes in phenolics,soluble solids,vitamin C,and antioxidant capacity of various cultivars of hardy kiwifruits during cold storage

Food Science and Biotechnology - Hardy kiwifruits (Actinidia arguta) contain various bioactive compounds such as vitamin C and phenolics and can withstand cold temperatures. Changes in soluble...     

Decorating surface charge of graphite nanoplate using an electrostatic coupling agent for 3-dimensional polymer nanocomposite

Here, we report a facile approach to electrostatically couple the surface charges of graphite nanoplate (GNP) fillers and poly(methyl methacrylate) (PMMA) polymer particles using ethylene maleic anhydride (EMA) copolymer as an electrostatic coupling agent. Our strategy involved switching the intrinsic repulsive electrostatic interactions between the directly exfoliated GNPs fillers and the PMMA particles to attractive electrostatic surface interactions for preparing core(PMMA)-shell (GNP) precursor in order to optimizing 3-dimensionally dispersed polymer nanocomposite. As a result, the electrical conductivity of the composites dramatically increased by a factor of 16.7 in the EMA-coupled GNP/PMMA composites compared with that of the EMA-free GNP/PMMA composites. In addition, the percolation threshold was also notably reduced from 0.32 to 0.159 vol% after electrostatic coupling of the GNPs fillers and PMMA particles. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48390.     

Effect of Initial Grain Size on Friction Stir Weldability for Rolled and Cast CoCrFeMnNi High-Entropy Alloys

Metals and Materials International - This study investigated the influence of the initial grain size on the plastic deformation and tunnel defects that occurred from friction stir welding of...     

A Distribution‐freeCUSUMChart for Monitoring Variability of AutocorrelatedProcesses

We present a distribution‐free tabular cumulative sum chart for monitoring the variability of an autocorrelated process. A quantity known as the asymptotic variance parameter is employed as a measure of the variability, and a distribution‐free tabular cumulative sum chart is applied to variance estimates calculated from batches of nonoverlapping samples. The proposed chart is applicable to a stationary process with a general marginal distribution and a general autocorrelation structure. It also determines control limits analytically without trial‐and‐error simulations. The performance of the proposed chart is tested on stationary processes with both normal and nonnormal marginals with various autocorrelation structures. Copyright © 2014 John Wiley & Sons, Ltd.     

A dynamic SVR–ARMA model with improved fruit fly algorithm for the nonlinear fiber stretching process

Natural Computing - The fiber stretching process plays the key role in the process of fiber production and its effects is measured by the stretching ratio. The stretching ratio is determined by the...     

High hydrostatic pressure extract of Siegesbeckia orientalis inhibits adipogenesis through the activation of the Wnt/β-catenin signaling pathway

Food Science and Biotechnology - St. Paul’s Wort (Siegesbeckia orientalis L.) confers anti-oxidative, anti-inflammatory, anti-allergic, anti-infertility, and immunosuppressive properties....     

Identification of the adverse effect of nitrate on the phosphate release rate and improvement of EBPR process models.

The adverse effect of nitrate on the phosphate release rate in the anaerobic phase was observed and was hardly explainable with conventional EBPR process models. Four possible mechanisms were proposed including substrate competition, reduced fermentation, parallel reaction and sequential reaction. Batch experiments were designed and conducted to identify the dominant mechanism. Results showed that the sequential reaction was the only possible mechanism where only denitrification occurred if any nitrate existed in the anaerobic phase. Then the phosphate release following after the nitrate was completely removed. Nitrate inhibition effect was added into the PHA storage rate to incorporate the sequential reaction in the conventional ASM3 plus EAWAG bio-P module (ASM3 + P). Nitrate inhibition coefficient, K(I,NO,PAO) was found to be as low as 0.05 mg/L. This correlated well with experimental observation where no also meant that the anaerobic compartment of a continuous flow reactor could be seriously affected by the residual nitrate contained in the sludge recycle flow. This phenomenon caused overestimation of the phosphate uptake rate and consequently underestimation of PO4(3-) -P concentration. This problem was resolved by incorporation of a nitrate inhibition term in the ASM3 + P for more accurate simulation of the EBPR process.