The combustion behavior of epoxy-based multifunctional electrolytes

Multifunctional or structural electrolytes are characterized by ionic conductivity high enough to be used in the electrochemical devices and mechanical performance suitable for the structural applications. Preliminary insights are provided into the combustion behavior of structural bi-continuous electrolytes based on bisphenol A diglycidyl ether (DGEBA), synthesized using the techniques of reaction induced phase separation and emulsion templating. The effect of the composition of the structural electrolytes and external heat flux on the behavior of the formulations were studied using a cone calorimeter with gases formed during testing analyzed using FTIR. The composition of the formulations investigated was changed by varying the type and amount of the ion conductive part of the bi-continuous electrolyte. Two ionic liquids, 1-ethyl-3-methylimidazolium bis(fluorosulfonyl)imide (EMIM-TFSI) and 1-butyl-3-methylimidazolium tetrafluoroborate (BMIM-BF₄), as well as a deep eutectic solvent (DES) based on ethylene glycol and choline chloride, were used. The results obtained confirm that time to ignition, heat release rate (HRR), total mass loss, as well as the composition of the gases released during tests depend on the composition of the formulations. Addition of liquid electrolyte is found to reduce the time to ignition by up to 10% and the burning time by between 28% and 60% with the added benefit of reducing the HRR by at least 34%. Gaseous products such as CO₂, CO, H₂O, CH₄, C₂H₂, N₂O, NO, and HCN were detected for all formulations with the gases SO₂, NH₃, HCl, C₂H₄, and NH₃ found to be for certain formulations only.     

An efficient decomposition and dual-stage multi-objective optimization method for water distribution systems with multiple supply sources

This paper proposes an efficient decomposition and dual-stage multi-objective optimization (DDMO) method for designing water distribution systems with multiple supply sources (WDS-MSSs). Three phases are involved in the proposed DDMO approach. In Phase 1, an optimal source partitioning cut-set is identified for a WDS-MSS, allowing the entire WDS-MSS to be decomposed into sub-networks. Then in Phase 2 a non-dominated sorting genetic algorithm (NSGA-II) is employed to optimize the sub-networks separately, thereby producing an optimal front for each sub-network. Finally in Phase 3, another NSGA-II implementation is used to drive the combined sub-network front (an approximate optimal front) towards the Pareto front for the original complete WDS-MSS. Four WDS-MSSs are used to demonstrate the effectiveness of the proposed approach. Results obtained show that the proposed DDMO significantly outperforms the NSGA-II that optimizes the entire network as a whole in terms of efficiently finding good quality optimal fronts.     

Coverage path planning for UAVs based on enhanced exact cellular decomposition method

In this paper, an enhanced exact cellular decomposition method to plan the coverage path of UAVs in a polygon area is proposed. To be more specific, the contributions of the paper are: firstly, the turning motion of UAVs is shown to be less efficient from the viewpoints of route length, duration and energy. Secondly, the problem of coverage Path Planning (CPP) in a convex polygon area is transformed to width calculation of the convex polygon, and a novel algorithm to calculate the widths of convex polygons with time complexity of O(n) is developed. The path of the least number of turns for an UAV based on the widths of convex polygons is devised. Thirdly, a convex decomposition algorithm for minimum width sum based on the greedy recursive method which revolves around decomposing the concave area into convex subregions is developed. It is proved that the algorithm is a polynomial time algorithm. To avoid unnecessary back and forth motion, some entirely adjacent subregions are combined. Finally, comparing different weights of two joint-points, a subregion connection algorithm based on minimum traversal of weighted undirected graph is proposed to connect the coverage paths of the subregions. Simulation results show that the proposed method is feasible and effective.     

Fluorescence Intrinsic Characterization of Excitation-Emission Matrix Using Multi-Dimensional Ensemble Empirical Mode Decomposition

Excitation-emission matrix (EEM) fluorescence spectroscopy is a noninvasive method for tissue diagnosis and has become important in clinical use. However, the intrinsic characterization of EEM fluorescence remains unclear. Photobleaching and the complexity of the chemical compounds make it difficult to distinguish individual compounds due to overlapping features. Conventional studies use principal component analysis (PCA) for EEM fluorescence analysis, and the relationship between the EEM features extracted by PCA and diseases has been examined. The spectral features of different tissue constituents are not fully separable or clearly defined. Recently, a non-stationary method called multi-dimensional ensemble empirical mode decomposition (MEEMD) was introduced; this method can extract the intrinsic oscillations on multiple spatial scales without loss of information. The aim of this study was to propose a fluorescence spectroscopy system for EEM measurements and to describe a method for extracting the intrinsic characteristics of EEM by MEEMD. The results indicate that, although PCA provides the principal factor for the spectral features associated with chemical compounds, MEEMD can provide additional intrinsic features with more reliable mapping of the chemical compounds. MEEMD has the potential to extract intrinsic fluorescence features and improve the detection of biochemical changes.     

An efficient simulation approach for multivariate nonstationary process: Hybrid of wavelet and spectral representation method

Currently, the classical spectral representation method (SRM) for nonstationary process simulation is widely used in the engineering community. Although this scheme has the higher accuracy, the time-dependent spectra results in unavailability of fast Fourier transform (FFT) and thus the simulation efficiency is lower. On the other hand, the approach based on stochastic decomposition can apply FFT in the simulation. However, the algorithm including the fitting procedure is relatively complicated and thus limits its use in practice.In this paper, the hybrid efficient simulation method is proposed for the vector-valued nonstationary process, which contains the spectra decomposition via wavelets and SRM. This method can take advantage of FFT and is also straightforward to engineering application. Numerical examples are employed to evaluate the proposed method. Results show that the method performs fairly well for the scalar process and vector-valued process with real coherence function. In the case of complex coherence function, the majority of the phase in the coherence function cannot be remained in the simulation. In addition, the validity of proper orthogonal decomposition (POD) in nonstationary process simulation via the decomposition of the time-dependent nonstationary spectra is studied. Analysis shows that the direct use of POD in nonstationary spectra decomposition may not be useful in nonstationary process simulations.     

Synthesis and behavior ofAl-stabilized α-Ni（OH）2

Nano-fibrous Al-stabilized α-Ni(OH)2 was synthesized by the urea thermal decomposition method. The grain morphology, crystal structure, thermal stability, chemical composition and electrochemical performance of the Al-stabilized α-Ni(OH)2 were investigated. It is found that the urea thermal decomposition is an appropriate way to precipitate the Al-stabilized α-Ni(OH)2 with excellent performance. The fiber cluster TEM pattern shows that the synthesized α-Ni(OH)2 powder is composed of agglomerates of much smaller primary particles. The stabilized α-Ni(OH)2 powder with a 7.67 A c-axis distance and low thermal stabilities is obtained. The FTIR spectrum shows that the materials contain absorbed water molecules, and intercalated CO32- and SO42- anions. The experimental α-Ni(OH)2 electrode exhibits excellent electrochemical redox reversibility, high special capacity, good rate discharging performance and perfect cyclic stability. Moreover, the synthesized α-Ni(OH)2 electrode also shows high discharge capacity and cyclic stability at high temperature. The electrode specific capacity remains 290 mA-h/g at 60 ℃, which is only 15 mA-h/g lower than its ambient value, and the capacity loss is 0.9 mA-h/g per charge-discharge cycle.     

Comparison of Two-Level Preconditioners Derived from Deflation,Domain Decomposition and Multigrid Methods

For various applications, it is well-known that a multi-level, in particular two-level, preconditioned CG (PCG) method is an efficient method for solving large and sparse linear systems with a coefficient matrix that is symmetric positive definite. The corresponding two-level preconditioner combines traditional and projection-type preconditioners to get rid of the effect of both small and large eigenvalues of the coefficient matrix. In the literature, various two-level PCG methods are known, coming from the fields of deflation, domain decomposition and multigrid. Even though these two-level methods differ a lot in their specific components, it can be shown that from an abstract point of view they are closely related to each other. We investigate their equivalences, robustness, spectral and convergence properties, by accounting for their implementation, the effect of roundoff errors and their sensitivity to inexact coarse solves, severe termination criteria and perturbed starting vectors.     

亚磷酸盐臭氧化合物研究新进展

有关亚磷酸盐臭氧化合物的研究一直为人们所关注。这主要有三个方面的原因:(1)它是单重态氧气的重要化学来源,而单重态氧气可以作为氧碘化学激光的储能分子;(2)亚磷酸盐臭氧化合物的结构独特,一直为人们所关注;(3)它们的热分解以及催化分解的具体反应机理还不是很清楚,这也是目前研究的一个热点。本文主要从上述三个方面来综述亚磷酸盐臭氧化合物的相关研究。     

A new Lagrangian decomposition approach applied to the integration of refinery planning and crude-oil scheduling

The aim of this paper is to introduce a methodology to solve a large-scale mixed-integer nonlinear program (MINLP) integrating the two main optimization problems appearing in the oil refining industry: refinery planning and crude-oil operations scheduling. The proposed approach consists of using Lagrangian decomposition to efficiently integrate both problems. The main advantage of this technique is to solve each problem separately. A new hybrid dual problem is introduced to update the Lagrange multipliers. It uses the classical concepts of cutting planes, subgradient, and boxstep. The proposed approach is compared to a basic sequential approach and to standard MINLP solvers. The results obtained on a case study and a larger refinery problem show that the new Lagrangian decomposition algorithm is more robust than the other approaches and produces better solutions in reasonable times.     

Studies on spinel cobaltites,MCo2O4 (M = Mn,Zn, Fe,Ni and Co) and their functional properties

Optimization of electrodes for charge storage with appropriate processing conditions places significant challenges in the developments for high performance charge storage devices. In this article, metal cobaltite spinels of formula MCo₂O₄ (where M = Mn, Zn, Fe, Ni and Co) are synthesized by oxalate decomposition method followed by calcination at three typical temperatures, viz. 350, 550, and 750 °C and examined their performance variation when used as anodes in lithium ion batteries. Phase and structure of the materials are studied by powder x-ray diffraction (XRD) technique. Single phase MnCo2O4,ZnCo2O4 and Co3O4 are obtained for all different temperatures 350 °C, 550 °C and 750 °C; whereas FeCo₂O₄ and NiCo₂O₄ contained their constituent binary phases even after repeated calcination. Morphologies of the materials are studied via scanning electron microscopy (SEM): needle-shaped particles of MnCo₂O₄ and ZnCo₂O₄, submicron sized particles of FeCo₂O₄ and agglomerated submicron particle of NiCo₂O₄ are observed. Galvanostatic cycling has been conducted in the voltage range 0.005–3.0 V vs. Li at a current density of 60 mA g^?1 up to 50 cycles to study their Li storage capabilities. Highest observed charge capacities are: MnCo₂O₄ – 365 mA h g^?1 (750 °C); ZnCo₂O₄ – 516 mA h g^?1 (550 °C); FeCo₂O₄ – 480 mA h g^?1 (550 °C); NiCo₂O₄ – 384 mA h g^?1 (750 °C); and Co₃O₄ – 675 mA h g^?1 (350 °C). The Co₃O₄ showed the highest reversible capacity of 675 mA h g^?1; the NiO present in NiCo₂O₄ acts as a buffer layer that results in improved cycling stability; the ZnCo₂O₄ with long needle-like shows good cycling stability.