Thermal Degradation Kinetics and Modeling Study of Ultra High Molecular Weight Polyethylene (UHMWP)/Graphene Nanocomposite

The incorporation of nanofillers such as graphene into polymers has shown significant improvements in mechanical characteristics, thermal stability, and conductivity of resulting polymeric nanocomposites. To this aim, the influence of incorporation of graphene nanosheets into ultra-high molecular weight polyethylene (UHMWPE) on the thermal behavior and degradation kinetics of UHMWPE/graphene nanocomposites was investigated. Scanning electron microscopy (SEM) analysis revealed that graphene nanosheets were uniformly spread throughout the UHMWPE’s molecular chains. X-Ray Diffraction (XRD) data posited that the morphology of dispersed graphene sheets in UHMWPE was exfoliated. Non-isothermal differential scanning calorimetry (DSC) studies identified a more pronounced increase in melting temperatures and latent heat of fusions in nanocomposites compared to UHMWPE at lower concentrations of graphene. Thermogravimetric analysis (TGA) and derivative thermogravimetric (DTG) revealed that UHMWPE’s thermal stability has been improved via incorporating graphene nanosheets. Further, degradation kinetics of neat polymer and nanocomposites have been modeled using equations such as Friedman, Ozawa–Flynn–Wall (OFW), Kissinger, and Augis and Bennett’s. The "Model-Fitting Method” showed that the auto-catalytic nth-order mechanism provided a highly consistent and appropriate fit to describe the degradation mechanism of UHMWPE and its graphene nanocomposites. In addition, the calculated activation energy (E_a) of thermal degradation was enhanced by an increase in graphene concentration up to 2.1 wt.%, followed by a decrease in higher graphene content.     

Computing the throughput of Concatenation State Machines

Concatenation State Machine (CSM) is a labeled directed And–Or graph representing a deterministic push-down transducer. In the high-performance version of CSM, labels associated to edges are words (rather than letters) over the input alphabet. The throughput of a path p is defined as the sum of the lengths of the labels of the path, divided by the number of edges of p. The throughput of a CSM M is defined as the infimum of the throughput of all accepting paths of M. In this paper we give an $\mathrm{O}(nm\log (\frac{\mathit{max}-\mathit{min}}{\epsilon }))$ algorithm, computing an ε-approximation of the throughput of a CSM M, where n is the number of nodes, m is the number of edges, and max (min) is the maximum (respectively, minimum) of the lengths of the edge labels of M. While we have been interested in a particular case of an And–Or graph representing a transducer, we have actually solved the following problem: if a real weight function is defined on the edges of an And–Or graph G, we compute an ε-approximation of the infimum of the complete hyper-path mean weights of G. This problem, if restricted to digraphs, is strongly connected to the problem of finding the minimum cycle mean.     

Infrared spectroscopic and chemometric approach for identifying binding medium in Sukias mansion’s wall paintings

Abstract

This paper addresses the application of infrared spectroscopy in combination with chemometrics to identify wall painting’s binding medium while employing pattern recognition techniques to process FTIR data-set of complex samples. In this regard, based on the historical documents and previous researches, firstly 56 standard samples were prepared to represent strata of Persian wall paintings in the Safavid period in addition to real historic samples from the case study; Sukias mansion. Then, each sample was analysed by the means of FTIR and chemometrics. Finally, SIMCA was applied to the whole region of studied IR spectra which predicted egg yolk as the binding medium of Sukias mansion samples.     

Synthesis of bioactive magnetic nanoparticles spiro[indoline-3,4′-[1,3]dithiine]@Ni (NO3)2 supported on Fe3O4@SiO2@CPS as reusable nanocatalyst for the synthesis of functionalized 3,4-dihydro-2H-pyran

New bioactive magnetic nanoparticles of spiro[indoline-3,4′-[1,3]dithiine]@Ni (NO₃)₂ supported on Fe₃O₄@SiO₂@CPS were synthesized in five steps. The structure of synthesized magnetic nanoparticles was identified by using Energy-Dispersive X-ray spectroscopy (EDX), Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), X-Ray Diffraction (XRD), Thermal Gravimetric Analysis (TGA), Infrared spectroscopy (FT-IR), Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES), Vibrating Sample Magnetometer (VSM) and Brunauer Emmett Teller (BET) surface analysis. Antimicrobial activity of the synthesized magnetic nanoparticles based on MIC (Minimum Inhibitory Concentration) and MBC (Minimum Bactericidal Concentration) and MFC (Minimum Fungicidal Concentration) values were also examined. Furthermore, the synthesized magnetic nanoparticles exhibited appropriate catalytic properties in the synthesis of the 3,4-dihydro-2H- pyran derivatives.     

Simultaneous determination of some components in detergent washing powder by mid-infrared spectrometry and artificial neural network

A method has been established for simultaneous determination of sodium sulfate, sodium carbonate, and sodium tripolyphosphate in detergent washing powder samples based on attenuated total reflectance Fourier transform IR spectrometry in the mid-IR spectral region (800-1550 cm(-1)). Genetic algorithm (GA) wavelength selection followed by feed forward back-propagation artificial neural network (BP-ANN) was the chemometric approach. Root mean square error of prediction for BP-ANN and GA-BP-ANN was 0.0051 and 0.0048, respectively. The proposed method is simple, with no tedious pretreatment step, for simultaneous determination of the above-mentioned components in commercial washing powder samples.     

Influence of the water molecules (n?=?1–6) on the interaction between Li+, Na+, K+ cations and indole molecule as tryptophan amino acid residue

Influence of the addition of water molecules (n = 1–6) on the interaction energy between Li⁺, Na⁺, K⁺ cations and indole molecule as tryptophan amino acid residue is considered at MP2(FULL)/6-311++G(d,p)//B3LYP/6-311++G(d,p) levels of theory. The calculations suggest that the size of cation and the number of water molecules are two important factors that affect the interaction energy between the hydrated metal cation and indole molecule. The strength of cation–π interactions get substantially reduced when the metal ion is solvated or the size of metal cation increases. Quantum theory of atoms in molecules analysis of cation–π interaction indicates that there is a correlation between the electron density (ρ(r)) in the cage critical points generated upon complexation and the distance between metal cation and centroid of phenyl ring in indole molecule.     

Determination of N-methylcarbamate insecticides in water samples using dispersive liquid–liquid microextraction and HPLC with the aid of experimental design and desirability function

A rapid and simple method for the extraction and preconcentration of N-methylcarbamates (NMCs) (carbofuran, carbaryl and promecarb) in water samples using dispersive liquid–liquid microextraction (DLLME) using chemometrics was developed. Influence variables such as volume of extracting (CHCl₃) and dispersing solvents (ACN), pH and ionic strength, extraction time and centrifugation time and speed were screened in a 2^7–4 Plackett–Burman design was investigated. The significant variables were optimized by using a central composite design (CCD) combined with desirability function (DF). At optimum conditions values of variables set as 126 μL chloroform, 1.5 mL acetonitrile, 1 min extraction time, 10 min centrifugation at 4000 rpm min⁻¹, natural pH, 4.7% (w/v) NaCl, the separation was reached in less than 14 min using a C₁₈ column and an isocratic binary mobile phase (acetonitrile: water (50:50, v/v)) with flow rate of 1.0 mL min⁻¹. At optimum conditions method has linear response over 0.001–10 μg mL⁻¹ with detection limit between 0.0001 and 0.0005 μg mL⁻¹ with relative standard deviations (RSDs) in the range 2.18–5.06% (n = 6).     

Influence of population and radius of cavity bubbles on size of sodium chloride crystals in ultrasound ablation

Crystal size distribution as a function of power in ultrasound ablation is simulated by using a theoretical method based on population and radius of bubbles. In this method, population and radius of bubbles are related to ultrasound power and Debye temperature of crystals. The best power for production of crystals with uniform size is obtained from the theory. In addition, it is shown that the population of bubbles effects the radius of the productions and the radius of bubbles influences the population of products. Results from the theory are supported by experimental results.     

A Comparison Between Full-COLD PCR/HRM and PCR Sequencing for Detection of Mutations in Exon 9 of PIK3CA in Breast Cancer Patients

Applied Biochemistry and Biotechnology - One of the most common somatic mutations in breast cancer is found in PIK3CA with a prevalence rate of 18–45%. Different variants of this gene are...