Microtextures Induced by Nanosecond Laser on Ni–Co Alloy Coatings

Ni–Co alloys have a wide range of applications in various fields owning to their excellent physical, chemical, and mechanical properties. In this paper, we prepare Ni–Co alloy coatings on 316L stain steel surfaces by electroplating. We present a novel approach utilizing a nanosecond laser to induce microtextures on Ni–Co alloy coatings. We study experimentally the effects of laser power and scanning rate on the surface morphologies of Ni–Co alloy coatings. The results indicate that the shape and size of induced microtextures can be controlled by the laser power and scanning rate. The size of grains increases with increase in the work current of the laser (WCL) at a certain scanning rate. With the WCL constant, the size of grains decreases with increase in scanning rate while their average height increases. It is a simple and easily-controlled method for the fabrication of microstructures on Ni–Co alloy coatings, which has promising applications in investigations of the properties of microtextured surfaces, such as friction, adhesion, and wetting.     

Identifying anomalous Floquet edge modes via bulk-edge correspondence

Floquet engineering appears as a new protocol for designing topological states of matter,and features anomalous edge modes pinned at quasi-energy π/T with vanished topological index.We propose how to predict the anomalous edge modes via the bulk Hamiltonian in frequency space,and use Zak phase to quantitatively index the topological properties.The above methods are clarified by the example of time periodic Kitaev chain with chemical potential of harmonic driving and pulse driving,and topological phase transitions are manifested at different driving frequencies.     

Convergence of the viscosity solution of non-autonomous Hamilton-Jacobi equations

In this paper,we investigate the non-autonomous Hamilton-Jacobi equation ■ where H is 1-periodic with respect to t and M is a compact Riemannian manifold without boundary.We obtain the viscosity solution denoted by T_(t_0)~tφ(x) and show T_(t_0)~tφ(x) converges uniformly to a time-periodic viscosity solution u~*(x,t) of ?_tu+H(t,x,?_xu,u)=0.     

DFT mechanistic study of the H2‐assisted chain transfer copolymerization of propylene and p‐methylstyrene catalyzed by zirconocene complex

DFT computations have been performed to investigate the mechanism of H₂‐assisted chain transfer strategy to functionalize polypropylene via Zr‐catalyzed copolymerization of propylene and p‐methylstyrene (pMS). The study unveils the following: (i) propylene prefers 1,2‐insertion over 2,1‐insertion both kinetically and thermodynamically, explaining the observed 1,2‐insertion regioselectivity for propylene insertion. (ii) The 2,1‐inserion of pMS is kinetically less favorable but thermodynamically more favorable than 1,2‐insertion. The observation of 2,1‐insertion pMS at the end of polymer chain is due to thermodynamic control and that the barrier difference between the two insertion modes become smaller as the chain length becomes longer. (iii) The pMS insertion results in much higher barriers for subsequent either propylene or pMS insertion, which causes deactivation of the catalytic system. (iv) Small H₂ can react with the deactivated [Zr]?pMS?PP_n facilely, which displace functionalized pMS?PP_n chain and regenerate [Zr]? H active catalyst to continue copolymerization. The effects of counterions are also discussed. © 2014 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2015 , 53, 576–585     

Flame-retardant effect of cross-linked phosphazene derivatives and pentaerythritol derivatives on polypropylene

Journal of Thermal Analysis and Calorimetry - A phosphazene-based flame retardant (PBFA) was synthesized by hexachlorocyclotriphosphazene and N-aminoethylpiperazine. To improve the flame retardancy...     

A Photoactivated Cu–CeO2 Catalyst with Cu-[O]-Ce Active Species Designed through MOF Crystal Engineering

Fully utilizing solar energy for catalysis requires the integration of conversion mechanisms and therefore delicate design of catalyst structures and active species. Herein, a MOF crystal engineering method was developed to controllably synthesize a copper–ceria catalyst with well-dispersed photoactive Cu-[O]-Ce species. Using the preferential oxidation of CO as a model reaction, the catalyst showed remarkably efficient and stable photoactivated catalysis, which found practical application in feed gas treatment for fuel cell gas supply. The coexistence of photochemistry and thermochemistry effects contributes to the high efficiency. Our results demonstrate a catalyst design approach with atomic or molecular precision and a combinatorial photoactivation strategy for solar energy conversion.     

Origins of Boosted Charge Storage on Heteroatom-Doped Carbons

Although tremendous efforts have been devoted to understanding the origin of boosted charge storage on heteroatom-doped carbons, none of the present studies has shown a whole landscape. Herein, by both experimental evidence and theoretical simulation, it is demonstrated that heteroatom doping not only results in a broadened operating voltage, but also successfully promotes the specific capacitance in aqueous supercapacitors. In particular, the electrolyte cations adsorbed on heteroatom-doped carbon can effectively inhibit hydrogen evolution reaction, a key step of water decomposition during the charging process, which broadens the voltage window of aqueous electrolytes even beyond the thermodynamic limit of water (1.23 V). Furthermore, the reduced adsorption energy of heteroatom-doped carbon consequently leads to more stored cations on the heteroatom-doped carbon surface, thus yielding a boosted charge storage performance.     

An Improved Composite Multiscale Fuzzy Entropy for Feature Extraction of MI-EEG

Motor Imagery Electroencephalography (MI-EEG) has shown good prospects in neurorehabilitation, and the entropy-based nonlinear dynamic methods have been successfully applied to feature extraction of MI-EEG. Especially based on Multiscale Fuzzy Entropy (MFE), the fuzzy entropies of the τ coarse-grained sequences in τ scale are calculated and averaged to develop the Composite MFE (CMFE) with more feature information. However, the coarse-grained process fails to match the nonstationary characteristic of MI-EEG by a mean filtering algorithm. In this paper, CMFE is improved by assigning the different weight factors to the different sample points in the coarse-grained process, i.e., using the weighted mean filters instead of the original mean filters, which is conductive to signal filtering and feature extraction, and the resulting personalized Weighted CMFE (WCMFE) is more suitable to represent the nonstationary MI-EEG for different subjects. All the WCMFEs of multi-channel MI-EEG are fused in serial to construct the feature vector, which is evaluated by a back-propagation neural network. Based on a public dataset, extensive experiments are conducted, yielding a relatively higher classification accuracy by WCMFE, and the statistical significance is examined by two-sample t-test. The results suggest that WCMFE is superior to the other entropy-based and traditional feature extraction methods.