In situ synthesis of poly(ethylene terephthalate-<Emphasis Type="Italic">co</Emphasis>-isophthalate)–SiO<Subscript>2</Subscript> nanocomposites and their optical properties

In this paper, poly(ethylene terephthalate-co-isophthalate) was prepared and a series of PETI/SiO₂ nanocomposites with different amounts of silica nanoparticles was synthesized by in situ polymerization. Optical properties of the resultant nanocomposites were investigated by WGW photoelectric haze meter and UV–Vis-NIR spectrophotometer. Chemical structure and its influence on spherulite size of nano-SiO₂ were characterized by Fourier transformed infrared spectra and polarized optical microscopy, respectively. The differential scanning calorimetry results reveal that the addition of nano-SiO₂ has an impact on the thermal performance of the nanocomposite. Different proportions of SiO₂ were compared and the degree of crystallinity was found to have influence on optical properties of as-prepared nanocomposites. In addition, the results indicate that the low loading levels of SiO₂ can improve the optical properties of the composite and an optimum content was selected. Possible reasons for this enhanced role might be the different combination structure of the nanocomposites when the amount of SiO₂ varied.     

A Sustainable Redox-Flow Battery with an Aluminum-Based,Deep-Eutectic-Solvent Anolyte

Nonaqueous redox-flow batteries are an emerging energy storage technology for grid storage systems, but the development of anolytes has lagged far behind that of catholytes due to the major limitations of the redox species, which exhibit relatively low solubility and inadequate redox potentials. Herein, an aluminum-based deep-eutectic-solvent is investigated as an anolyte for redox-flow batteries. The aluminum-based deep-eutectic solvent demonstrated a significantly enhanced concentration of circa 3.2 m in the anolyte and a relatively low redox potential of 2.2 V vs. Li⁺/Li. The electrochemical measurements highlight that a reversible volumetric capacity of 145 Ah L⁻¹ and an energy density of 189 Wh L⁻¹ or 165 Wh kg⁻¹ have been achieved when coupled with a I₃⁻/I⁻ catholyte. The prototype cell has also been extended to the use of a Br₂-based catholyte, exhibiting a higher cell voltage with a theoretical energy density of over 200 Wh L⁻¹. The synergy of highly abundant, dendrite-free, multi-electron-reaction aluminum anodes and environmentally benign deep-eutectic-solvent anolytes reveals great potential towards cost-effective, sustainable redox-flow batteries.     

An efficient multi-objective PSO algorithm assisted by Kriging metamodel for expensive black-box problems

The huge computational overhead is the main challenge in the application of community based optimization methods, such as multi-objective particle swarm optimization and multi-objective genetic algorithm, to deal with the multi-objective optimization involving costly simulations. This paper proposes a Kriging metamodel assisted multi-objective particle swarm optimization method to solve this kind of expensively black-box multi-objective optimization problems. On the basis of crowding distance based multi-objective particle swarm optimization algorithm, the new proposed method constructs Kriging metamodel for each expensive objective function adaptively, and then the non-dominated solutions of the metamodels are utilized to guide the update of particle population. To reduce the computational cost, the generalized expected improvements of each particle predicted by metamodels are presented to determine which particles need to perform actual function evaluations. The suggested method is tested on 12 benchmark functions and compared with the original crowding distance based multi-objective particle swarm optimization algorithm and non-dominated sorting genetic algorithm-II algorithm. The test results show that the application of Kriging metamodel improves the search ability and reduces the number of evaluations. Additionally, the new proposed method is applied to the optimal design of a cycloid gear pump and achieves desirable results.     

关于预不变凸函数的Hermite-Hadamard型不等式的一个注记

从预不变凸函数的定义和性质出发,用数学分析方法得到了由已有的预不变凸函数的Hermite-Hadamard型不等式的右端部分所决定的差函数的上界和下界.从而加细了预不变凸函数的Hermite-Hadamard型不等式.     

Generalized harmonic number summation formulae via hypergeometric series and digamma functions

By computing the derivatives of five classical hypergeometric summation theorems, and applying the related properties of the digamma function, we derive a large number of closed summation formulae for generalized harmonic numbers.     

New algebraic structures from Hermitian one-matrix model

Virasoro constraint is the operator algebra version of one-loop equation for a Hermitian one-matrix model, and it plays an important role in solving the model. We construct the realization of the Virasoro constraint from the Conformal Field Theory (CFT) method. From multi-loop equations of the one-matrix model, we get a more general constraint. It can be expressed in terms of the operator algebras, which is the Virasoro subalgebra with extra parameters. In this sense, we named as generalized Virasoro constraint. We enlarge this algebra with central extension, this is a new kind of algebra, and the usual Virasoro algebra is its subalgebra. And we give a bosonic realization of its subalgebra.     

Unsupervised and semi-supervised extreme learning machine with wavelet kernel for high dimensional data

Extreme learning machine (ELM) not only is an effective classifier in supervised learning, but also can be applied on unsupervised learning and semi-supervised learning. The model structure of unsupervised extreme learning machine (US-ELM) and semi-supervised extreme learning machine (SS-ELM) are same as ELM, the difference between them is the cost function. We introduce kernel function to US-ELM and propose unsupervised extreme learning machine with kernel (US-KELM). And SS-KELM has been proposed. Wavelet analysis has the characteristics of multivariate interpolation and sparse change, and Wavelet kernel functions have been widely used in support vector machine. Therefore, to realize a combination of the wavelet kernel function, US-ELM, and SS-ELM, unsupervised extreme learning machine with wavelet kernel function (US-WKELM) and semi-supervised extreme learning machine with wavelet kernel function (SS-WKELM) are proposed in this paper. The experimental results show the feasibility and validity of US-WKELM and SS-WKELM in clustering and classification.     

Anion Storage Chemistry of Organic Cathodes for High-Energy and High-Power Density Divalent Metal Batteries

Multivalent batteries show promising prospects for next-generation sustainable energy storage applications. Herein, we report a polytriphenylamine (PTPAn) composite cathode capable of highly reversible storage of tetrakis(hexafluoroisopropyloxy) borate [B(hfip)₄] anions in both Magnesium (Mg) and calcium (Ca) battery systems. Spectroscopic and computational studies reveal the redox reaction mechanism of the PTPAn cathode material. The Mg and Ca cells exhibit a cell voltage >3 V, a high-power density of ∼∼3000 W kg⁻¹ and a high-energy density of ∼∼300 Wh kg⁻¹, respectively. Moreover, the combination of the PTPAn cathode with a calcium-tin (Ca−Sn) alloy anode could enable a long battery-life of 3000 cycles with a capacity retention of 60 %. The anion storage chemistry associated with dual-ion electrochemical concept demonstrates a new feasible pathway towards high-performance divalent ion batteries.     

A sensitive DNA biosensor based on the distance dependent quenching of Silica@Ru(bpy)32+-chitosan-GO electrochemiluminescence by Ferrocene@Gold nanoparticles

A sensitive electrochemiluminescence (ECL) biosensor for the specific DNA sequence of hepatitis C virus (HCV) was developed based on the efficient quenching effect of the ferrocene cluster functionalized gold nanoparticles (Fc@AuNPs) on the ECL of electrodeposited silica@Ru(bpy)₃²⁺-chitosan-graphene oxide nanocomposite (SiO₂@Ru−CS−GO). Graphene oxide (GO) can accelerate electron transfer rate, thus improving the ECL of Ru(bpy)₃²⁺ on electrode surface. The molecular beacons (MB) was fixed to SiO₂@Ru−CS−GO by glutaraldehyde (GA) using the Schiff reaction between amino groups of chitosan (CS) and MB. The ECL of SiO₂@Ru−CS−GO was depressed greatly by the Fc@AuNPs labelled at the end of MB, then, a stronger ECL was observed when the distance between Fc@AuNPs and SiO₂@Ru−CS−GO increased after the hybridization of target DNA with MB. Under optimum conditions, the restored ECL intensity increased linearly with the target DNA concentration in the range of 1.0×10⁻¹⁶∼1.0×10⁻¹⁰ mol ⋅ L⁻¹, and the limit of detection (LOD) is 1.4×10⁻¹⁷ mol ⋅ L⁻¹. The proposed method exhibits acceptable stability and reproducibility. In general, the constructed HCV biosensor can be used for the sensitive detection of HCV in human serum, suggesting potential application prospects in bioanalysis.     

A Triply Negatively Charged Nanographene Bilayer with Spin Frustration

We report on the largest open-shell graphenic bilayer and also the first example of triply negatively charged radical π-dimer. Upon three-electron reduction, bilayer nanographene fragment molecule (C₉₆H₂₄Ar₆)₂ (Ar=2,6-dimethylphenyl) ( 1 ₂) was transformed to a triply negatively charged species 1 ₂^3.−, which has been characterized by single-crystal X-ray diffraction, electron paramagnetic resonance (EPR) spectroscopy and magnetic properties on a superconducting quantum interference device (SQUID). 1 ₂^3.− features a 96-center-3-electron (96c/3e) pancake bond with a doublet ground state, which can be thermally excited to a quartet state. It consists of 34 π-fused rings with 96 conjugated sp² carbon atoms. Spin frustration is observed with the frustration parameter f>31.8 at low temperatures in 1 ₂^3.−, which indicates graphene upon reduction doping may behave as a quantum spin liquid.