Effect of hexagonal structure nanoparticles on the morphological performance of the ceramic scaffold using analytical oscillation response

Porous bony scaffolds are utilized to manage the growth and migration of cells from adjacent tissues to a defective position. In the current investigation, the effect of titanium oxide (TiO₂) nanoparticles on mechanical and physical properties of porous bony implants made of polymeric polycaprolactone (PCL) is studied. The bio-nanocomposite scaffolds are prepared with composition of nanocrystalline hydroxyapatite (HA) and TiO₂ powder using the freeze-drying technique for different weight fractions of TiO₂ (0 wt%, 5 wt%, 10 wt%, and 15 wt%). In order to identify the microstructure and morphology of the fabricated porous bio-nanocomposites, the X-ray diffraction (XRD), atomic force microscope (AFM) and scanning electron microscopy (SEM) are employed. Also, the biocompatibility and biodegradability of the manufactured scaffolds are examined by placing them in a simulated body fluid (SBF) for 21 days, their weight and pH changes are measured. The rate of degradation of the PCL-HA scaffold can be controlled by varying the percentage of its constituent components. Due to an increasing growth and activity of bone cells and the apatite formation on the free surface of the fabricated bio-nanocomposite implants as well as their reasonable mechanical properties, they have the potential to be used as a bone substitute. Additionally, with the aid of the experimentally extracted mechanical properties of the scaffolds, the vibrational characteristics of a beam-type implant made of the proposed porous bio-nanocomposites are explored. The results obtained from SEM image indicate that the scaffolds produced by the employed method have high total porosity (70%–85%) and effective porosity. The pore size is obtained between 60 and 200 μm, which is desirable for the growth and propagation of bone cells. Also, it is revealed that the addition of TiO₂ nanoparticles leads to reduce the rate of dissolution of the fabricated bio-nanocomposite scaffolds.     

A new hybrid chaotic atom search optimization based on tree-seed algorithm and Levy flight for solving optimization problems

Engineering with Computers - Optimizing the high computational real-world problems is a challenging task that has taken a great deal of efforts in the last decade. The meta-heuristic algorithms...     

Bimetallic PtPd nanoparticles relying on CoNiO2 and reduced graphene oxide as a most operative electrocatalyst toward ethanol fuel oxidation

Of late, fuel cells have drawn great attentions owing to high-energy demands, fossil fuel depletion and worldwide environmental pollution. Direct ethanol fuel cell (DEFC) constituted as one of the most promising sources of green energy, howbeit the ethanol oxidation reaction (EOR) sluggish kinetic is one of the essential challenges toward the commercialization of DEFCs. Herein, we introduce bimetallic catalyst on CoNiO₂ modified reduced graphene oxide (rGO) to completely exploit the advantages of nano-surface structures as well as the reduction of Pt and Pd loading in fuel cells. With the combined advantages of PtPd, CoNiO₂ and rGO, a significant enhancement in electrocatalytic behavior, stability and CO poisoning tolerance of PtPd have been observed. Regarding the implications, PtPd/CoNiO₂/rGO is greatly preferable than Pt/CoNiO₂/rGO and Pd/CoNiO₂/rGO in terms of high electroactive surface area (ECSA), electro-catalytic activity, and lower onset potential (E_ons) towards the EtOH oxidation in alkaline media. Furthermore, the chronoamperometry curve (CA) illustrated 77% after 3600 s which is dramatically soared compared with the other electrodes (≤40%), demonstrating the high stability of the PtPd bimetallic nanoparticle electrocatalyst. Ultimately, PtPd/CoNiO₂/rGO nanocomposite is found to be an excellent anode electrocatalyst for application in DEFCs.     

A Novel Approach for Prediction of Monthly Ground Water Level Using a Hybrid Wavelet and Non-Tuned Self-Adaptive Machine Learning Model

Water Resources Management - In recent decades, due to groundwater withdrawal in the Kabodarahang region, Iran, Hamadan, hazardous events such as sinkholes, droughts, water scarcity, etc., have...     

Prolonged drug release using PCL–TMZ nanofibers induce the apoptotic behavior of U87 glioma cells

In situ prolonged delivery of drugs at the site of tumor can be satisfactorily accelerated patient recovery. We compared the effect of temozolomide while incorporated by polycaprolactone nanofibers on the apoptotic behavior of U87 glioma cells. After biocompatibility evaluation of nanofibers by scanning electron microscope and 3-(4,5-dimethylthiazolyl-2)-2,5-diphenyltetrazolium bromide analysis, the apoptosis of U87 cells was evaluated using p53, Bcl2 and Bax genes expression. It was found that nanofiber-temozolomide group showed a greater ability to induce apoptosis as well as have a significantly diminished initial burst release of drug compared with other groups and have promising potential in treating cancer.     

A novel proposal for all optical 3 to 8 decoder based on nonlinear ring resonators

In this paper, a 3 to 8 optical decoder was proposed using nonlinear photonic crystal ring resonators. For realizing the 3 to 8 decoder, we combined seven 1 to 2 optical decoders. In the proposed structure, X, Y and Z serve as input ports. By combination of these ports, one can control which output port to be ON. The maximum time delay of the proposed structure is about 6?ps.     

Impact of Climate Change on Future Flood Susceptibility: an Evaluation Based on Deep Learning Algorithms and GCM Model

Floods are common and recurring natural hazards which damages is the destruction for society. Several regions of the world with different climatic conditions face the challenge of floods in different magnitudes. Here we estimate flood susceptibility based on Analytical neural network (ANN), Deep learning neural network (DLNN) and Deep boost (DB) algorithm approach. We also attempt to estimate the future rainfall scenario, using the General circulation model (GCM) with its ensemble. The Representative concentration pathway (RCP) scenario is employed for estimating the future rainfall in more an authentic way. The validation of all models was done with considering different indices and the results show that the DB model is most optimal as compared to the other models. According to the DB model, the spatial coverage of very low, low, moderate, high and very high flood prone region is 68.20%, 9.48%, 5.64%, 7.34% and 9.33% respectively. The approach and results in this research would be beneficial to take the decision in managing this natural hazard in a more efficient way.

     

A thermodynamically consistent framework for non-isothermal modelling of local heat generation and electromotive force in SOFC single electrodes

Mathematical models for single electrode reversible heat and non-isothermal electromotive force (EMF) of a solid oxide fuel cell (SOFC) are developed. These models estimate the volumetric reversible heat generation and EMF of electrochemical reactions, within each electrode at local conditions of temperature and pressure, based on entropy change of half reactions. The resulting equations are thermodynamically consistent. They inherently obey the conservation of energy law as the electrochemical energy released added to the heat of reactions at each electrode equate the enthalpy change of the reacted species. The equations are implemented to model electrodes in a tubular micro- solid oxide fuel cell (TμSOFC). The thermodynamic consistency of the model is numerically confirmed as the enthalpy of the reactants equates the electric energy released by the cell plus the sum of electrode heats plus electrolyte Ohmic heat. The effect of thermal gradients on the cell's overall EMF is found to be negligible. The reversible and irreversible heat generation of each electrode are distinguished. Overall, the anode is found to be endothermic, and the cathode exothermic.