Investigation of the mechanical properties of a photocatalytic pseudo‐paint

Photocatalytic oxidative paints (e.g., a paint containing nano‐TiO₂) are used to break down volatile organic compounds to CO₂ by photooxidation reactions. In this research, a photocatalytic oxidative pseudo‐paint was made with acrylic–styrene copolymer latex, TiO₂ pigment, calcium carbonate extender, and TiO₂ nanoparticles as a photocatalyst. To investigate the effects of the pigment, extender, and nanoparticles on the mechanical properties of the samples and their relationship to their photocatalytic activity, different contents of the particles were dispersed in the paint formulation. The tensile strengths (TSs) of the samples were measured as the mechanical properties. The samples were characterized by scanning electron microscopy analysis. We found that up to 3% nano‐TiO₂ enhanced the mechanical properties of the pigmented resin, whereas beyond this, TS decreased. In samples containing 3% nanoparticles, the incorporation of 15% TiO₂ pigment caused optimized mechanical properties, and beyond that, TS decreased because of particle agglomeration. In the absence of nanoparticles, the samples showed improvements in the mechanical properties with up to a 40% loading of pigment. The results reveal that the samples containing nano‐TiO₂ and pigment showed the same trend for the mechanical and photocatalytic properties before the critical pigment volume concentration (CPVC). However, when the extender was incorporated or TiO₂ particles were loaded beyond CPVC, the mechanical and photocatalytic properties correlation was compromised, and they were not directly correlated. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 42885.     

A glutamic Acid-producing lactic Acid bacteria isolated from malaysian fermented foods

l-glutamaic acid is the principal excitatory neurotransmitter in the brain and an important intermediate in metabolism. In the present study, lactic acid bacteria (218) were isolated from six different fermented foods as potent sources of glutamic acid producers. The presumptive bacteria were tested for their ability to synthesize glutamic acid. Out of the 35 strains showing this capability, strain MNZ was determined as the highest glutamic-acid producer. Identification tests including 16S rRNA gene sequencing and sugar assimilation ability identified the strain MNZ as Lactobacillus plantarum. The characteristics of this microorganism related to its glutamic acid-producing ability, growth rate, glucose consumption and pH profile were studied. Results revealed that glutamic acid was formed inside the cell and excreted into the extracellular medium. Glutamic acid production was found to be growth-associated and glucose significantly enhanced glutamic acid production (1.032 mmol/L) compared to other carbon sources. A concentration of 0.7% ammonium nitrate as a nitrogen source effectively enhanced glutamic acid production. To the best of our knowledge this is the first report of glutamic acid production by lactic acid bacteria. The results of this study can be further applied for developing functional foods enriched in glutamic acid and subsequently γ-amino butyric acid (GABA) as a bioactive compound.     

Toward learning autonomous pallets by using fuzzy rules, applied in a Conwip system

Nowadays, material planning and control strategies are becoming continuously complex tasks spanning from individual plants to logistic networks. In fact, this is the consequence of increasing intricacy in product variants and their respective convolution in networks’ structures. Customers ask for specific products with individual characteristics that force companies for more clever performances by more flexibility. For doing so, the existing planning and control systems, which work based on central monitoring and controlling, show some limitations for organizing every operation on time or in the right time. Therefore, in the recent decade, a great attention is put on decentralized control and, to some extent, autonomy. This paper tries to investigate the possibility of combining this new research paradigm with existing strategies in production logistics, in order to improve material handling and control task according to material flow criteria. To show this, an exemplary plant after decoupling point out of a logistic network is considered for simulation and analysis. This combines Conwip system with learning autonomous pallets’ concept in a discrete event simulation model. Several decentralized control scenarios are experimented and compared together. Here, the learn methodology is brought to pallets based on fuzzy rules and advantage of closed loop systems.     

Prediction of fatigue life in cold expanded Al-alloy 2024-T3 plates used in double shear lap joints

To predict fatigue crack initiation and fatigue crack growth lives in cold expanded double shear lap joints a numerical method has been employed. The total estimated fatigue lives were compared with available experimental fatigue test results for plain hole and cold expanded hole specimens of Al 2024-T3 in double shear lap joints. Three-dimensional finite element simulations have been performed in order to obtain the created residual stresses field due to cold expansion and subsequent far field longitudinal loading in the double shear lap joint. The obtained stress and strain distributions from the finite element analyses were employed to predict stress concentration factors to calculate fatigue crack initiation and fatigue crack growth lives using AFGROW computer code. The predicted fatigue lives demonstrate that there is a good agreement between the proposed method and experimental fatigue test results.     

Purification and characterization of membrane-bound polyphenoloxidase (mPPO) from Snake fruit [Salacca zalacca (Gaertn.) Voss]

Membrane-bound polyphenoloxidase (mPPO) an oxidative enzyme which is responsible for the undesirable browning reaction in Snake fruit (Salacca zalacca (Gaertn.) Voss) was investigated. The enzyme was extracted using a non-ionic detergent (Triton X-114), followed by temperature-induced phase partitioning technique which resulted in two separate layers (detergent-poor phase at the upper layer and detergent-rich phase at the lower layer). The upper detergent-poor phase extract was subsequently fractionated by 40–80% ammonium sulfate and chromatographed on HiTrap Phenyl Sepharose and Superdex 200 HR 10/30. The mPPO was purified to 14.1 folds with a recovery of 12.35%. A single prominent protein band appeared on native-PAGE and SDS–PAGE implying that the mPPO is a monomeric protein with estimated molecular weight of 38 kDa. Characterization study showed that mPPO from Snake fruit was optimally active at pH 6.5, temperature 30 °C and active towards diphenols as substrates. The K_m and V_max values were calculated to be 5.46 mM and 0.98 U/ml/min, respectively, when catechol was used as substrate. Among the chemical inhibitors tested, l-cysteine showed the best inhibitory effect, with an IC₅₀ of 1.3 ± 0.002 mM followed by ascorbic acid (1.5 ± 0.06 mM), glutathione (1.5 ± 0.07 mM), EDTA (100 ± 0.02 mM) and citric acid (186 ± 0.16 mM).     

New optimization method, the algorithms of changes, for heat exchanger design

Heat exchangers are widely used in the process engineering such as the chemical industries,the petroleum industries,and the HVAC applications etc.An optimally designed heat exchanger cannot only help the optimization of the equipment size but also the reduction of the power consumption.In this paper,a new optimization approach called algorithms of changes (AOC) is proposed for design and optimization of the shell-tube heat exchanger.This new optimization technique is developed based on the concept of the book of changes (I Ching) which is one of the oldest Chinese classic texts.In AOC,the hexagram operations in I Ching are generalized to binary string case and an iterative process,which imitates the I Ching inference,is defined.Before applying the AOC to the heat exchanger design problem,the new optimization method is examined by the benchmark optimization problems such as the global optimization test functions and the travelling salesman problem (TSP).Based on the TSP results,the AOC is shown to be superior to the genetic algorithms (GA).The AOC is then used in the optimal design of heat exchanger.The shell inside diameter,tube outside diameter,and baffles spacing are treated as the design (or optimized) variables.The cost of the heat exchanger is arranged as the objective function.For the heat exchanger design problem,the results show that the AOC is comparable to the GA method.Both methods can find the optimal solution in a short period of time.     

Experimental investigation and mathematical modeling of oxygen permeation through dense Ba0.5Sr0.5Co0.8Fe0.2O3−δ (BSCF) perovskite-type ceramic membranes

Ba_0.5Sr_0.5Co_0.8Fe_0.2O_3?δ (BSCF) perovskite powder was synthesized via EDTA/citrate complexation method. BSCF membranes were formed by pressing powder at 400 MPa and sintering at 1100 °C for 10 h. XRD patterns showed that a high pure powder with cubic structure was obtained. SEM micrographs revealed that the membranes are dense with large grains. Effects of temperature, feed and permeate side oxygen partial pressures, flow rates and membrane thickness on oxygen permeation flux were studied experimentally. A Nernst–Planck based mathematical model, including surface exchange kinetics and bulk diffusion, was developed to predict oxygen permeation flux. Considering non-elementary surface reactions and introducing system hydrodynamics into the model resulted in an excellent agreement (RMSD = 0.0617, AAD = 0.0487 and R² = 0.985) between predicted and measured fluxes. The results showed that oxygen permeation flux increases with temperature, feed side oxygen partial pressure and flow rates, however decreases with permeate side oxygen partial pressure and membrane thickness. Contribution of feed side surface exchange reactions, bulk diffusion and permeate side surface exchange reactions resistances in the total resistance are in the range of 8–32%, 10–81% and 11–59%, respectively. Permeation rate-limiting step was determined using the membrane dimensionless characteristic thickness.     

Highly Elastic Micropatterned Hydrogel for Engineering Functional Cardiac Tissue

Heart failure is a major international health issue. Myocardial mass loss and lack of contractility are precursors to heart failure. Surgical demand for effective myocardial repair is tempered by a paucity of appropriate biological materials. These materials should conveniently replicate natural human tissue components, convey persistent elasticity, promote cell attachment, growth and conformability to direct cell orientation and functional performance. Here, microfabrication techniques are applied to recombinant human tropoelastin, the resilience‐imparting protein found in all elastic human tissues, to generate photocrosslinked biological materials containing well‐defined micropatterns. These highly elastic substrates are then used to engineer biomimetic cardiac tissue constructs. The micropatterned hydrogels, produced through photocrosslinking of methacrylated tropoelastin (MeTro), promote the attachment, spreading, alignment, function, and intercellular communication of cardiomyocytes by providing an elastic mechanical support that mimics their dynamic mechanical properties in vivo. The fabricated MeTro hydrogels also support the synchronous beating of cardiomyocytes in response to electrical field stimulation. These novel engineered micropatterned elastic gels are designed to be amenable to 3D modular assembly and establish a versatile, adaptable foundation for the modeling and regeneration of functional cardiac tissue with potential for application to other elastic tissues.