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     

A new localization method in internet of things by improving beetle antenna search algorithm

Wireless Networks - Localization is regarded as one of the important challenges in the internet of things and Wireless Sensor Networks. The failure to localize sensors properly causes data loss and...     

Groundwater Model Calibration by Meta-Heuristic Algorithms

Groundwater models are computer models that simulate or predict aquifer conditions by using input data sets and hydraulic parameters. Commonly, hydraulic parameters are extracted by calibration, using observed and simulated aquifer conditions. The accuracy of calibration affects other modeling processes, especially the hydraulic head simulation. Meta-heuristic algorithms are good candidates to determine optimal/near-optimal parameters in groundwater models. In this paper, two meta-heuristic algorithms: (1) particle swarm optimization (PSO) and (2) pattern search (PS) are applied and compared in the Ghaen aquifer, by considering the sum of the squared deviation (SSD) between observed and simulated hydraulic heads and the sum of the absolute value of deviation (SAD) between observed and simulated hydraulic heads as the objective functions. Results show that obtained values of the objective function are enhanced significantly by using the PS algorithm. Accordingly, PS improves (decreases) the SSD and SAD by 0.20 and 2.36 percent, respectively, compared to results reported by using the PSO algorithm. Results also indicate that the proposed PS optimization tool is effective in the calibration of aquifer parameters.     

Fabrication and characterization of highly efficient three component CuBTC/graphene oxide/PSF membrane for gas separation application

Metal organic frameworks (MOFs) with marvelous properties have aroused enormous attention for different application especially gas adsorption and separation. In this regard, fabrication of MOF hybrids with carbon based materials is new strategy to upgrade MOF performance. In this study CuBTC (Copper benzene-1,3,5-tricarboxylic acid)/graphene oxide (GO) composite was synthesized and characterized by BET, SEM, TGA, XRD and FT-IR techniques. Then CuBTC and CuBTC/GO composite were incorporated into polysulfone (PSF) polymer to construct mixed matrix membranes (MMMs). The obtained membranes were characterized by SEM, TGA, XRD and tensile tests and their gas permeability was measured. The results were compared to those of CuBTC/PSF MMMs. It was revealed that CuBTC/GO composite as filler showed superior performance relative to CuBTC. For instance, 15 wt% loading of CuBTC/GO in PSF represented outstanding gas separation behavior while the same loading of CuBTC in PSF deteriorated performance of MMM. Well particle dispersion and favorable polymer-filler interaction were responsible for such observed difference. A high H₂/CH₄ and H₂/N₂ selectivity of 80.03 and 70.46 were recorded for CuBTC/GO in PSF (15 wt%) compared to 44.56 and 40.92 for CuBTC in PSF (15 wt%).     

Outlier accommodation in moving-horizon state estimation: A risk-averse performance-specified approach

This paper presents a novel state estimation approach for linear dynamic systems when measurements are corrupted by outliers. Since outliers can degrade the performance of state estimation, outlier accommodation is critical. The standard approach combines outlier detection utilizing Neyman-Pearson (NP) type tests with a Kalman filter (KF). This approach ignores all residuals greater than a designer-specified threshold. When measurements with outliers are used (ie, missed detections), both the state estimate and the error covariance matrix become corrupted. This corrupted state and covariance estimate are then the basis for all subsequent outlier decisions. When valid measurements are rejected (ie, false alarms), potentially using the corrupted state estimate and error covariance, measurement information is lost. Either using invalid information or discarding too much valid information can result in divergence of the KF. An alternative approach is moving-horizon (MH) state estimation, which maintains all recent measurement data within a moving window with a time horizon of length L. In MH approaches, the number of measurements available for state estimation is affected by both the number of measurements per time step and the number of time steps L over which measurements are retained. Risk-averse performance-specified (RAPS) state estimation works within an optimization setting to choose a set of measurements that achieves a performance specification with minimum risk of outlier inclusion. This paper derives and formulates the MH-RAPS solution for outlier accommodation. The paper also presents implementation results. The MH-RAPS application uses Global Navigation Satellite Systems measurements to estimate the state of a moving platform using a position, velocity, and acceleration model. In this application, MH-RAPS performance is compared with MH-NP state estimation.     

Synthesis of Janus/non-Janus hollow graphene oxide micro- and nanoparticles and the effects of their localization on the thermal conductivity of blend-based polymer composites

Journal of Materials Science - In this study, the effects of Janus, hydrophilic and hydrophobic hollow graphene oxide (HO) particles on the thermal conductivity of binary polymer blends were...     

Novel NGR anchored pullulan micelles for controlled and targeted delivery of doxorubicin to HeLa cancerous cells

Doxorubicin (DOX) is used to treat different kinds of cancers, including cervix carcinoma. However, it has various side effects such as cardiotoxicity. Nano-sized controlled releasing carriers such as polymeric micelles are of interesting approaches to overcome these side effects of doxorubicin in cancer chemotherapy. Regarding the up-regulation of CD13/APN receptors on the cervix carcinoma cells, which can bind to peptide sequences specially NGR (asparagine–glycine–arginine) with high affinity, peptide sequence (NGR) targeted micelles would lead to effective treatment of this carcinoma. In this study, the NGR peptide sequence was synthesized using the solution-phase strategy from asparagine, glycine, and arginine residues. The pullulan–retinoic acid conjugate and pullulan–retinoic acid–NGR conjugate were prepared by the amide and ester bond formation between the hydroxyl groups of pullulan and carboxylic acid groups of retinoic acid and peptide sequence. Pullulan–retinoic acid–NGR micelles were prepared by the direct dissolution method. The optimized micelles, according to their particle size (124.5 nm), zeta potential (? 3.65 mV), entrapment efficiency (85%), and release of DOX (70%, within 72 h) were assessed for their cytotoxicity on HeLa cells using MTT assay. NGR-targeted pullulan/retinoic acid micelles had higher cytotoxicity than the free DOX in cell culture studies on the HeLa cell line, and this can be a promising result in the treatment of cervix carcinoma.     

Evaluation of Real-Time Operation Rules in Reservoir Systems Operation

Reservoir operation rules are logical or mathematical equations that take into account system variables to calculate water release from a reservoir based on inflow and storage volume values. In fact, previous experiences of the system are used to balance reservoir system parameters in each operational period. Commonly, reservoir operation rules have been considered to be linear decision rules (LDRs) and constant coefficients developed by using various optimization procedures. This paper addresses the application of real-time operation rules on a reservoir system whose purpose is to supply total downstream demand. Those rules include standard operation policy (SOP), stochastic dynamic programming (SDP), LDR, and nonlinear decision rule (NLDR) with various orders of inflow and reservoir storage volume. Also, a multi-attribute decision method, elimination and choice expressing reality (ELECTRE)-I, with a combination of indices, objective functions, and reservoir performance criteria (reliability, resiliency, and vulnerability) are used to rank the aforementioned rules. The ranking method employs two combinations of indices: (1) performance criteria and (2) objective function and performance criteria by using the same weights for all criteria. Results show that the NLDR gives an appropriate rule for real-time operation. Moreover, NLDR validation is presented by testing predefined curves for dry, normal, and wet years.     

The influence of depressive symptoms on experimental smoking and intention to smoke in a diverse youth sample.

Numerous studies have shown associations between smoking and depression, but the generalizability of the relationship across ethnic groups remains unknown. The present study assessed the association between depression and smoking intention and experimentation among adolescents from four ethnic groups in the Los Angeles area-Chinese/Chinese American, Latino/Hispanic, Persian/Iranian, and White. Over 800 7th graders in the Los Angeles area completed measures of depressive symptoms, experimentation with smoking, intention to smoke, and sociodemographic covariates. Chinese/Chinese American students had the lowest levels of depressive symptoms, whereas Latinos/Hispanics had the highest levels. Latinos/Hispanics also were the most likely to intend to smoke in the next year and were the most likely to have started experimenting with cigarette smoking. Depressive symptoms were significantly associated with intention to smoke even after controlling for language use acculturation, socioeconomic status, gender, and ethnicity. The association between depressive symptoms and intention to smoke did not vary significantly across ethnic groups. These results indicate that the association between depressive symptoms and adolescent smoking generalizes across diverse ethnic groups.     

PEG-PLA-PCL based electrospun yarns with curcumin control release property as suture

This work presents an interesting method using an electrospinning process to fabricate suture yarns loaded with curcumin to achieve reasonable mechanical properties as well as tunable drug release behavior. Different structures including different yarn counts and twists as well as core-sheath structures were used to adjust drug release properties along with improving the yarn's mechanical properties. The core parts were made of polycaprolactone and the sheath parts were made of polyethylene glycol, polylactic acid, and polycaprolactone. Drugs can be incorporated in both parts based on the required condition and application. Electrospun yarns were compared using both structural properties and their drug release profiles as metrics. The results of comparing drug release profiles of six electrospun yarns with different yarn counts and twists showed that yarns with finer fiber diameters in the core part have more drug release as well as more initial release. Overall evaluations showed that core-sheath drugloaded yarn with appropriate physical and mechanical properties can be a useful material as a drug delivery system to the site of damaged tissue. It can also be concluded that the amount and duration of drug release can be controlled using the structural parameters of electrospun yarns as an engineering tool for designing suture yarns with required properties.