Positive ground state solutions for Schrödinger–Poisson system with critical nonlocal term in ℝ3

This paper is dedicated to studying the following Schrödinger–Poisson system $$\left\{\begin{array}{ll}-\mathrm{\Delta }u+V(x)u-K(x)\varphi |u{|}^{3}u=a(x)f(u),& x\in {ℝ}^3,\\ -\mathrm{\Delta }\varphi =K(x)|u{|}^5,& x\in {ℝ}^3.\end{array}\right.$$ Under some different assumptions on functions V(x), K(x), a(x) and f(u), by using the variational approach, we establish the existence of positive ground state solutions.     

Simultaneous Removal of Antibiotics and Heavy Metals with Poly(Aspartic Acid)-Based Fenton Micromotors

The discharge of diverse pollutants has led to a complex water environment and posed a huge health threat to humans and animals. Self-propelled micromotors have recently attracted considerable attention for efficient water remediation due to their strong localized mass transfer effect. However, a single functionalized component is difficult to tackle with multiple contaminants and requires to combine different decontamination effects together. Here, we introduced a multifunctional micromotor to implement the adsorption and degradation roles simultaneously by integrating the poly(aspartic acid) (PASP) adsorbent with a MnO₂-based catalyst. The as-prepared micromotors are well propelled in contaminated waters by MnO₂ catalyzing hydrogen peroxide. In addition, the catalytic ramsdellite MnO₂(R-MnO₂) inner layer is decorated with Fe₂O₃ nanoparticles to improve their catalytic performance, contributing to an excellent degradation ability with 90% tetracycline (TC) removal in 50 minutes by enhanced Fenton-like reactions. Combining the attractive adsorption capability of poly (aspartic acid) (PASP), the composite micromotors offer an efficient removal of heavy metal ions in short time. Moreover, the designed micromotors are able to simultaneously remove antibiotic and heavy metals in mixed contaminants circumstance just in single treatment. This multifunctional micromotor with distinctive decontamination ability exhibits a promising prospective in treating multiple pollutants in the future.     

Photo-Controlled Macroscopic Self-Assembly Based on Photo-Switchable Hetero-Complementary Quadruple Hydrogen Bonds

A photo-switchable hetero-complementary quadruple H-bonding array, which consists of an azobenzene-derived ureidopyrimidinone (UPy) module ( Azo-UPy ) and a nonphotoactive diamidonaphthyridine (DAN) derivative ( Napy-1 ), is constructed based on a reversible photo-locking approach. Upon UV (390 nm)/Vis (460 nm) light irradiations, photo-switchable quadruple H-bonded dimerization between Azo-UPy and Napy-1 can be achieved with exhibiting 4.8×10⁴-fold differences in binding strength (ON/OFF ratios). Furthermore, smart polymeric gels with unique photo-controlled macroscopic self-assembly behavior can be fabricated by introducing such quadruple H-bonding array as photo-regulable noncovalent interfacial connections.     

80.5 MeV/u碳离子诱发铜靶的放射性剩余产物测量

高能重带电粒子能直接穿透靶原子核外电子层,与原子核发生直接碰撞,发生散裂反应,产生一系列具有放射性的剩余产物核.重带电粒子诱发靶材放射性剩余核与辐射防护和人员安全有着密切联系,当前,大部分剩余核产额主要依靠蒙特卡罗粒子输运程序进行模拟计算,其准确程度亟需通过实验测量进行准确评估.本文利用能量为80.5 MeV/u的(12)^C⁶⁺粒子对薄铜靶开展了辐照实验与伽玛射线测量,结合伽玛谱学分析方法,得出了辐照产生的18种放射性剩余产物的初始活度和产生截面值,并与PHITS模拟结果进行对比.结果表明,PHITS模拟程序对放射性剩余核种类的估计具有较高可靠性,在其绝对产额方面,与实验测量仍具有较大偏差.     

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.