Strain‐rate‐dependent mechanical properties of polypropylene separator for lithium‐ion batteries

The mechanical integrity of battery separators is critical for battery safety and durability. A comprehensive study of strain‐rate‐dependent tensile and puncture properties of a polypropylene lithium‐ion battery separator is presented here with a new model. Due to anisotropy of the polymeric membrane, tensile testing was conducted for different directions. Results showed that tensile strength and elastic modulus were increased 1000% and 500%, respectively, for different directions. It was also demonstrated that tensile strength changed 10 to 25% with strain rate (1.67 × 10^?4 to 1.67 × 10^?1 s^?1) for different directions. An equation was obtained for the first time for flow stress versus strain rate at varied tensile directions with respect to machine direction. Moreover, puncture testing was performed and it was shown that puncture strength was increased 140% with increasing strain rate from 0.25 to 250 mm min^?1. Two failure modes were also observed in puncture samples. Finally, Eyring's model was used to calculate activation enthalpy of the porous polypropylene separator. © 2020 Society of Chemical Industry     

Synthesis of nanoporous Baghdadite by a modified sol-gel method and its structural and controlled release properties

In this research, a bimodal nanoporous Baghdadite (NB) (Ca3ZrSi2O9) was prepared by a modified sol-gel method using P123 as a surfactant. The effects of P123's contents on the structural and textural properties as well as the drug delivery behavior of NB were assessed in vitro. The usage of P123 offered a new route for the synthesis of NB. The synthesized NB samples with different amounts of P123 were studied through X-ray diffraction (XRD), Fourier transform infrared spectra (FTIR), N2 adsorption-desorption, field emission scanning electron microscopy (FESEM) equipped with energy-dispersive X-ray analysis spectroscopy (EDAX) and transmission electron microscopy (TEM). The results showed that a single-phase Baghdadite was obtained by this new method at the calcination temperature of 800?°C. It was found that an increase in P123's content up to 0.025?mol changed the morphology of NB samples from mountain-like to needle-like. The potential application of NB samples as drug delivery agents was assessed by estimating their release properties up to 240?h. This research revealed that the synthesized Baghdadite could be used as a potential nanoporous carrier with controlled release capability in bone tissue regeneration.     

Multiobjective invasive weed optimization: Application to analysis of Pareto improvement models in electricity markets

This paper presents a proposal for multiobjective Invasive Weed Optimization (IWO) based on nondominated sorting of the solutions. IWO is an ecologically inspired stochastic optimization algorithm which has shown successful results for global optimization. In the present work, performance of the proposed nondominated sorting IWO (NSIWO) algorithm is evaluated through a number of well-known benchmarks for multiobjective optimization. The simulation results of the test problems show that this algorithm is comparable with other multiobjective evolutionary algorithms and is also capable of finding better spread of solutions in some cases. Next, the proposed algorithm is employed to study the Pareto improvement model in two complex electricity markets. First, the Pareto improvement solution set is obtained for a three-player oligopolistic electricity market with a nonlinear demand function. Then, the IEEE 30-bus power system with transmission constraints is considered, and the Pareto improvement solutions are found for the model with deterministic cost functions. In addition, NSIWO algorithm is used to analyze this system with stochastic cost data in a risk management problem which maximizes the expected total profit but minimizes the profit risk in the market.     

Supplementing with L-Tryptophan Increases Medium Protein and Alters Expression of Genes and Proteins Involved in Milk Protein Synthesis and Energy Metabolism in Bovine Mammary Cells

The objective of this study was to investigate the effects of supplementing with L-tryptophan (L-Trp) on milk protein synthesis using an immortalized bovine mammary epithelial (MAC-T) cell line. Cells were treated with 0, 0.3, 0.6, 0.9, 1.2, and 1.5 mM of supplemental L-Trp, and the most efficient time for protein synthesis was determined by measuring cell, medium, and total protein at 0, 24, 48, 72, and 96 h. Time and dose tests showed that the 48 h incubation time and a 0.9 mM dose of L-Trp were the optimal values. The mechanism of milk protein synthesis was elucidated through proteomic analysis to identify the metabolic pathway involved. When L-Trp was supplemented, extracellular protein (medium protein) reached its peak at 48 h, whereas intracellular cell protein reached its peak at 96 h with all L-Trp doses. β-casein mRNA gene expression and genes related to milk protein synthesis, such as mammalian target of rapamycin (mTOR) and ribosomal protein 6 (RPS6) genes, were also stimulated (p < 0.05). Overall, there were 51 upregulated and 59 downregulated proteins, many of which are involved in protein synthesis. The results of protein pathway analysis showed that L-Trp stimulated glycolysis, the pentose phosphate pathway, and ATP synthesis, which are pathways involved in energy metabolism. Together, these results demonstrate that L-Trp supplementation, particularly at 0.9 mM, is an effective stimulus in β-casein synthesis by stimulating genes, proteins, and pathways related to protein and energy metabolism.     

pHEMA: An Overview for Biomedical Applications

Poly(2-hydroxyethyl methacrylate) (pHEMA) as a biomaterial with excellent biocompatibility and cytocompatibility elicits a minimal immunological response from host tissue making it desirable for different biomedical applications. This article seeks to provide an in-depth overview of the properties and biomedical applications of pHEMA for bone tissue regeneration, wound healing, cancer therapy (stimuli and non-stimuli responsive systems), and ophthalmic applications (contact lenses and ocular drug delivery). As this polymer has been widely applied in ophthalmic applications, a specific consideration has been devoted to this field. Pure pHEMA does not possess antimicrobial properties and the site where the biomedical device is employed may be susceptible to microbial infections. Therefore, antimicrobial strategies such as the use of silver nanoparticles, antibiotics, and antimicrobial agents can be utilized to protect against infections. Therefore, the antimicrobial strategies besides the drug delivery applications of pHEMA were covered. With continuous research and advancement in science and technology, the outlook of pHEMA is promising as it will most certainly be utilized in more biomedical applications in the near future. The aim of this review was to bring together state-of-the-art research on pHEMA and their applications.     

A NEW AGENT MATCHING SCHEME USING AN ORDERED FUZZY SIMILARITY MEASURE AND GAME THEORY

In this paper, an agent matching method for bilateral contracts in a multi-agent market is proposed. Each agent has a hierarchical representation of its trading commodity attributes by a tree structure of fuzzy attributes. Using this structure, the similarity between the trees of each pair of buyer and seller is computed using a new ordered fuzzy similarity algorithm. Then, using the concept of Stackelberg equilibrium in a leader–follower game, matchmaking is performed among the sellers and buyers. The fuzzy similarities of each agent with others in its personal viewpoint have been used as its payoffs in a bimatrix game. Through a case study for bilateral contracts of energy, the capabilities of the proposed agent-based system are illustrated.     

Multi agent architecture for dynamic incremental process planning in the flexible manufacturing system

Due to rapid changes of markets and pressures of competitions, industries are adopting their production ways to support diversity of customer’s needs and increase of new product developments. This paper deals with development of an agent-based architecture of dynamic systems for process planning in the manufacturing systems. In consideration of alternative manufacturing processes and machine tools, the process plans and the schedules of the manufacturing resources are generated incrementally and dynamically. A previously proposed negotiation protocol is customized and improved to generate suitable process plans for the target products real-timely and dynamically, based on the alternative manufacturing processes. The alternative manufacturing processes are presented by the process plan networks and the suitable process plans are searched and generated to cope with both the dynamic status and disturbances of the manufacturing systems. We initiatively combine the heuristic search algorithms of the process plan networks with the negotiation protocols, in order to generate suitable process plans.     

Decision making in dynamic stochastic Cournot games

In this paper, the Cournot competition is modeled as a stochastic dynamic game. In the proposed model, a stochastic market price function and stochastic dynamic decision functions of the rivals are considered. Since the optimal decision of a player needs the estimation of the unknown parameters of the market and rivals’ decisions, a combined estimation-optimization algorithm for decision making is proposed. The history of the rivals’ output quantities (supplies) and the market clearing price (MCP) are the only available information to the players. The convergence of the algorithm (for both estimation and decision making processes) is discussed. In addition, the stability conditions of the equilibrium points are analyzed using the converse Lyapunov theorem. Through the case studies, which are performed based on the California Independent System Operator (CA-ISO) historical public data, the theoretical results and the applicability of the proposed method are verified. Moreover, a comparative study among the agents using the proposed method, naïve expectation and adaptive expectation in the market is performed to show the effectiveness and applicability of the proposed method.     

Homotopy perturbation method for motion of a spherical solid particle in plane couette fluid flow

He’s homotopy perturbation method is applied to obtain exact analytical solutions for the motion of a spherical particle in a plane couette flow. It is demonstrated that the applied analytical method is very straightforward in comparison with existing techniques. Furthermore, it is decidedly effectual in terms of accuracy and rapid convergence. The formulation of the problem is presented in the text as well as the analytical and numerical procedures. The current results can be used in different areas of particulate flows.     

Algorithm for Increasing the Speed of Evolutionary Optimization and its Accuracy in Multi-objective Problems

Optimization algorithms are important tools for the solution of combinatorial management problems. Nowadays, many of those problems are addressed by using evolutionary algorithms (EAs) that move toward a near-optimal solution by repetitive simulations. Sometimes, such extensive simulations are not possible or are costly and time-consuming. Thus, in this study a method based on artificial neural networks (ANN) is proposed to reduce the number of simulations required in EAs. Specifically, an ANN simulator is used to reduce the number of simulations by the main simulator. The ANN is trained and updated only for required areas in the decision space. Performance of the proposed method is examined by integrating it with the non-dominated sorting genetic algorithm (NSGAII) in multi-objective problems. In terms of density and optimality of the Pareto front, the hybrid NSGAII-ANN is able to extract the Pareto front with much less simulation time compared to the sole use of the NSGAII algorithm. The proposed NSGAII-ANN methodology was examined using three standard test problems (FON, KUR, and ZDT1) and one real-world problem. The latter addresses the operation of a reservoir with two objectives (meeting demand and flood control). Thus, based on this study, use of the NSGAII-ANN integrative algorithm in problems with time-consuming simulators reduces the required time for optimization up to 50 times. Results of the real-world problem, despite lower computational-time requirements, show a performance similar to that achieved in the aforementioned test problems.