Novel electrospun polymer electrolytes incorporated with Keggin‐type hetero polyoxometalate fillers as solvent‐free electrolytes for lithium ion batteries

In this study, solvent‐free nanofibrous electrolytes were fabricated through an electrospinning method. Polyethylene oxide (PEO), lithium perchlorate and ethylene carbonate were used as polymer matrix, salt and plasticizer respectively in the electrolyte structures. Keggin‐type hetero polyoxometalate (Cu‐POM@Ru‐rGO, Ni‐POM@Ru‐rGO and Co‐POM@Ru‐rGO (POM, polyoxometalate; rGO, reduced graphene oxide)) nanoparticles were synthesized and inserted into the PEO‐based nanofibrous electrolytes. TEM and SEM analyses were carried out for further evaluation of the synthesized filler structures and the electrospun nanofibre morphologies. The fractions of free ions and crystalline phases of the as‐spun electrolytes were estimated by obtaining Fourier transform infrared and XRD spectra, respectively. The results showed a significant improvement in the ionic conductivity of the nanofibrous electrolytes by increasing filler concentrations. The highest ionic conductivity of 0.28 mS cm^?1 was obtained by the introduction of 0.49 wt% Co‐POM@Ru‐rGO into the electrospun electrolyte at ambient temperature. Compared with solution‐cast polymeric electrolytes, the electrospun electrolytes present superior ionic conductivity. Moreover, the cycle stability of the as‐spun electrolytes was clearly improved by the addition of fillers. Furthermore, the mechanical strength was enhanced with the insertion of 0.07 wt% fillers to the electrospun electrolytes. The results implied that the prepared nanofibres are good candidates as solvent‐free electrolytes for lithium ion batteries. © 2020 Society of Chemical Industry     

An inverse solution methodology for estimating the diffusion coefficient of gases in Athabasca bitumen from pressure-decay data

An inverse solution methodology is developed for the estimation of diffusion coefficient of gases in highly viscous, oil-sands bitumens from isothermal, pressure-decay measurements. The approach involves modeling the rate of change in pressure using the diffusion equation for the liquid phase coupled with a mass balance equation for the gas phase. The inverse solution framework is utilized to arrive at two graphical techniques for estimating the diffusion coefficient. Both techniques involve the determination of the slope of a straight line resulting from plotting the experimental data in accordance with the developed model. An advantage of the proposed techniques is that the diffusion coefficient is estimated directly, i.e. without making it an adjustable parameter. The novelty of the proposed method is in its simplicity as well as its ability to isolate portions of the pressure-decay data affected by experimental fluctuations. The effect of the initial pressure on the predicted diffusion coefficient and pressure-decay profile was also investigated. The diffusion coefficients of CO₂, CH₄, C₂H₆ and N₂ in Athabasca bitumen at 50–90 °C and about 8 MPa were estimated and compared with literature values.     

Bayesian estimation based on vague lifetime data

In Classical Bayesian approach, estimation of lifetime data usually is dealing with precise information. However, in real world, some informations about an underlying system might be imprecise and represented in the form of vague quantities. In these situations, we need to generalize classical methods to vague environment for studying and analyzing the systems of interest. In this paper, we propose the Bayesian estimation of failure rate and mean time to failure based on vague set theory in the case of complete and censored data sets. To employ the Bayesian approach, model parameters are assumed to be vague random variables with vague prior distributions. This approach will be used to induce the vague Bayes estimate of failure rate and mean time to failure by introducing and applying a theorem called “Resolution Identity” for vague sets. In order to evaluate the membership degrees of vague Bayesian estimate for these quantities, a computational procedure is investigated. In the proposed method, the original problem is transformed into a nonlinear programming problem which is then divided into eight subproblems to simplifying computations.     

Using plasmonic cloaking method on infinite cylindrical structures and its applications

Journal of Computational Electronics - In recent years, cloaking using materials with negative electric permittivity or magnetic permeability has been studied and researched. It has been...     

Using the genetic algorithm to enhance nonnegative matrix factorization initialization

Nonnegative matrix factorization (NMF) algorithms have been utilized in a wide range of real applications; however, the performance of NMF is highly dependent on three factors including: (1) choosing a problem dependent cost function; (2) using an effective initialization method to start the updating procedure from a near‐optimal point; and (3) determining the rank of factorized matrices prior to decomposition. Due to the nonconvex nature of the NMF cost function, finding an analytical‐based optimal solution is impossible. This paper is aimed at proposing an efficient initialization method to modify the NMF performance. To widely explore the search space for initializing the factorized matrices in NMF, the island genetic algorithm (IGA) is employed as a diverse multiagent search scheme. To adapt IGA for NMF initialization, we present a specific mutation operator. To assess how the proposed IGA initialization method efficiently enhances NMF performance, we have implemented state‐of‐the‐art initialization methods and applied to the Japanese Female Facial Expression dataset to recognize the facial expression states. Experimental results demonstrate the superiority of the proposed approach to the compared methods in terms of relative error and fast convergence.     

Surface modification of ultra‐high‐molecular‐weight polyethylene. II. Effect on the physicomechanical and tribological properties of ultra‐high‐molecular‐weight polyethylene/poly(ethylene terephthalate) composites

We performed surface modification of ultra‐high‐molecular‐weight polyethylene (UHMWPE) through chromic acid etching, with the aim of improving the performance of its composites with poly(ethylene terephthalate) (PET) fibers. In this article, we report on the morphology and physicomechanical and tribological properties of modified UHMWPE/PET composites. Composites containing chemically modified UHMWPE had higher impact properties than those based on unmodified UHMWPE because of improved interfacial bonding between the polymer matrix and the fibers and better dispersion of the fibers within the modified UHMWPE matrix. Chemical modification of UHMWPE before the introduction of PET fibers resulted in composites exhibiting improved wear resistance compared to the base material and compared to unmodified UHMWPE/PET composites. On the basis of the morphological studies of worn samples, microploughing and fatigue failure associated with microcracking were identified as the principle wear mechanisms. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci, 2006     

Centroid index: Cluster level similarity measure

In clustering algorithm, one of the main challenges is to solve the global allocation of the clusters instead of just local tuning of the partition borders. Despite this, all external cluster validity indexes calculate only point-level differences of two partitions without any direct information about how similar their cluster-level structures are. In this paper, we introduce a cluster level index called centroid index. The measure is intuitive, simple to implement, fast to compute and applicable in case of model mismatch as well. To a certain extent, we expect it to generalize other clustering models beyond the centroid-based k-means as well.     

A low order,torsion deformable spatial beam element based on the absolute nodal coordinate formulation and Bishop frame

Multibody System Dynamics - Heretofore, the Serret–Frenet frame has been the ubiquitous choice for analyzing the elastic deformations of beam elements. It is well-known that this frame is...     

A bio-inspired gelatin-based pH- and thermal-sensitive magnetic hydrogel for in vitro chemo/hyperthermia treatment of breast cancer cells

Gelatin (Gel)-based pH- and thermal-responsive magnetic hydrogels (MH-1 and MH-2) were designed and developed as novel drug delivery systems (DDSs) for cancer chemo/hyperthermia therapy. For this goal, Gel was functionalized with methacrylic anhydride (GelMA), and then copolymerized with (2-dimethylaminoethyl) methacrylate (DMAEMA) monomer in the presence of methacrylate-end capped magnetic nanoparticles (MNPs) as well as triethylene glycol dimethacrylate (TEGDMA; as crosslinker). Afterward, a thiol-end capped poly(N-isopropylacrylamide) (PNIPAAm-SH) was synthesized through an atom transfer radical polymerization technique, and then attached onto the hydrogel through “thiol-ene” click grafting. The preliminary performances of developed MHs for chemo/hyperthermia therapy of human breast cancer was investigated through the loading of doxorubicin hydrochloride (Dox) as an anticancer agent followed by cytotoxicity measurement of drug-loaded DDSs using MTT assay by both chemo- and chemo/hyperthermia-therapies. Owing to porous morphologies of the fabricated magnetic hydrogels according to scanning electron microscopy images and strong physicochemical interactions (e.g., hydrogen bonding) the drug loading capacities of the MH-1 and MH-2 were obtained as 72 ± 1.4 and 77 ± 1.8, respectively. The DDSs exhibited acceptable pH- and thermal-triggered drug release behaviors. The MTT assay results revealed that the combination of hyperthermia therapy and chemotherapy has synergic effect on the anticancer activities of the developed DDSs.