جستجوی مقالات مرتبط با کلیدواژه "glucose" در نشریات گروه "شیمی"

Nanostructured enzyme mimics are of great interest as promising alternatives to artificial enzymes for biomedical and catalytic applications. Studying the chemical interactions between antioxidants and nano-enzymes may result in a better understanding of the capability of antioxidants and may help improve the function of artificial enzymes to better mimic natural enzymes. In this study, using palladium nanoparticles (PdNPs) as peroxidase mimics to catalyze the oxidation of chromophoric substrates by H2O2, we developed a platform that acts as a biosensor for hydrogen peroxide and glucose and that can study the inhibitory effects of natural antioxidants on peroxidase mimics.The peroxidase-like activity of Butea monosperma reduced Palladium nanoparticles was assessed through using 3',3',5',5'-tetramethyl benzidine(TMB) as a chromogen in the presence of H2O2. Butea Monosperma reduced palladium nanoparticles BM-PdNPs catalytically oxidize TMB using H2O2, resulting in the production of a blue oxidation product. This product was measured and quantified using a UV-Vis spectrophotometer at a wavelength (λmax) of 652 nm. The pH, temperature, and nanoparticle concentration are crucial factors in investigating the catalytic activity of BM-PdNPs. The glucose oxidase enzyme catalyzes the production of gluconic acid, resulting in the release of H2O2 as a byproduct which can be subsequently be measured using BM-PdNPs. Under optimal conditions, the method exhibited a linear range of 1.5 µM to 1000 µM for glucose determination. The limit of detection (LOD) calculated using the equation 3σ/m, was found to be 0.78 μM. The authenticity of the results obtained from BM-PdNPs was confirmed through the use of UV-Vis, Fourier Transform Infrared Spectroscopy (FTIR) and Transmission Electron microscopy (TEM)

A novel non-enzymatic electrochemical sensor with high sensitivity for glucose determination was introduced herein with nickel pentacyanonitrosylferrate (NiPCNF)-modified multi-walled carbon nanotubes (MWCNTs) paste electrode and deposited nickel hydroxide onto paste electrode using NiSO4 solution and H2SO4 as the soft template. The NiO-modified electrode was scanned with cyclic voltammetry (CV) method in alkaline media to obtain Ni(OH)2/NiOOH particles as glucose electrocatalyst. The prepared nickel oxide was then mixed with the paste inside the tube. It was observed that introducing both NiPCNF and NiO could synergistically improve the activity toward electrocatalytic oxidation of glucose with an increase in the accessible active sites and promotion of the electron transport capability. Therefore, the modified electrode did not only exhibit an outstanding electrochemical behavior but also decreased the potential for electrochemical oxidation and enhanced the affinity of the electrode to glucose. Field emission scanning electron microscopy (FESEM) was applied to study the surface morphology of the electrode and prepared NiPCNF powder. After optimizing the condition, the chronoamperometry (CA) technique was applied for glucose determination. Porous-modified electrode, containing both nanomaterials of NiPCNF and NiO, exhibited a vast linear range from 5 µM to 1.95 mM (2.6 orders of magnitude) with a low limit of detection (LOD) of 2.35 × 10-7 ± 1.52×10-8 M (S/N=3) and high sensitivity (2.83 ± 0.17 mA mM-1 cm-2). Finally, the prepared sensor was utilized for glucose determination in the real samples successfully.

Several categories are usual ways for natural gas storage: Compressed Natural Gas (CNG), Adsorbed Natural Gas (ANG), and liquefied gas methods. The ANG technologies allow the natural gases to be absorbed via porous materials at high temperatures and low pressures, around 500 psig (3.5 MPa).  Via an accurate comparison, it has been exhibited those gases can be stored in a CNG tank at approximately 3,500 psig. Therefore, the ANG system appears to be prospective for any future activities. In this study, Glucose–Graphene hybrid based materials with hierarchical structures, tunable surfaces, chemical doping, and functionalization were simulated for gases with .... such as (H2, N2, O2) and ... for (CH4, CO2, NH3, NO2, H2S, SO2) and  for (He, Ne) sorption, storage, and separation. The scope of this work is to produce a new Nano-adsorbent, i.e., Hybrid -Glucose-Graphene, which can be introduced as a new candidate for that gas storage.

Platinum–nickel electrocatalysts supported on the modified carbon paper (MCP) were prepared by electrodeposition. Here, various procedures were applied for the electrodeposition of nickel and platinum particles, separately or simultaneously, on the surface of the MCP as an anode electrode for glucose alkaline fuel cells. The establishment of the best procedure for this fabrication is the main goal of this work. The obtained electrocatalysts were characterized by cyclic voltammetry, linear sweep voltammetry, electrochemical impedance spectroscopy (EIS), scanning electron microscopy (SEM), and X-ray photoelectron spectroscopy (XPS). The results showed that the Pt/Ni electrocatalyst, electrodeposited from two separate solutions containing Ni and then Pt ions, has excellent electrocatalytic activity for the glucose oxidation reaction (GOR). On the other hand, the Pt/Ni/MCP electrode showed satisfactory repeatability when subjected to continuous cycling and less concentration polarization in the oxidation region of GOR (from -1 to 0.6 V vs. SCE). Also, the Pt/Ni/MCP electrode showed a significant increase in the exchange current density (0.95 mA cm-2) that accelerates the kinetics of the glucose oxidation reaction.These results indicate that modification of the catalyst layer structure in the present work is the most promising approach to achieve low-cost and efficient catalysts for use in glucose alkaline fuel cells.

Graphene-modified Cu2O nanocomposite was synthesized under facile microwave irradiation of an aqueous solution and has been investigated as an enzyme-free glucose biosensor. Morphology and crystal structure of the graphene-modified Cu2O nanocomposite were investigated by using electron microscopy and X-Ray Diffraction (XRD) analyses. Also, the electrochemical performance of the graphene-modified Cu2O nanocomposite for the measurement of glucose concentration in alkaline media was evaluated by using cyclic voltammetry and chronoamperometric measurements. The electrochemical studies revealed that the graphene-modified nanocomposite electrode exhibited a high performance for non-enzymatic oxidation of glucose with a desirable sensitivity. Also, the fabricated graphene-modified biosensor exhibited a wide linear response for glucose detection in the concentrations ranges from 2 µM to 12 mM and a desirable detection limit of 2 µM. Also, the graphene-modified Cu2O nanocomposite provided an appropriate selective response for glucose detection in the presence of high concentrations of ascorbic acid and dopamine.

This paper describes the performance of Granular Activated Carbon (GAC) to adsorb and separate glucose and maltose solutes from the industrial effluents by adsorption process. In this study, the capability of Granular Activated Carbon (GAC) to adsorb glucose and maltose were experimentally examined. Commercial GAC (mesh 12-20), supplied by Sigma Aldrich company in the UK was used in this work. The parameters affecting the sorbate adsorption such as the pH of the solution, initial solution concentration, shaking time and speed, sorbent dose and temperature were tested. Additionally, the adsorption equilibrium isotherm was also tested using the common isotherm modules; Langmuir and Freundlich. GAC exhibited a capability to adsorb glucose and maltose from the industrial effluent. Also, the glucose adsorption process was physical and in good agreement with the Freundlich isotherm model, while, the maltose adsorption process was a physical and the adsorption data can be adequately described by the Freundlich and Langmuir models.

In the present work, a fast, green and simple synthesis method for the production of silver nanoparticles (AgNPs) is introduced. Silver nanoparticles are currently among the most widely used man-made nano materials, present in a wide range of consumer products. Green chemistry is characterized by careful planning of chemical synthesis of silver nanoparticles to reduce adverse outcomes. Synthesis of AgNPs was carried out at 100 ◦C temperature using glucose as reducing agent and starch as capping agent. Prepared AgNPs were characterized using transmission electron microscopy, UV-Vis spectrophotometry, Dynamic Light Scattering (DLS) and X-ray Diffraction (XRD) patterns. It was found that the synthesized AgNPs have an average diameter size of 50 nm. Further experiments showed that silver nanoparticles have good antibacterial properties and their production process is capable to scaling up. Due to the using of natural and low-cost materials, the production process is also environmental and eco-friendly.

The active cauliflower-like LiFePO4 (LFP/Cin) material was synthesized with hydrothermal process in the presence of glucose and then calcined at 600 °C. The physical properties, particle size and morphology of obtained samples were investigated with the Xray diffraction (XRD), Scanning Electron Microscope (SEM) and Transmission Electron Microscope (TEM). The electrochemical performance of nano-composites was studied by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS) and galvanostatic cycling performance. The CV curves show that LFP/Cin has higher electrochemical reactivity for lithium insertion and extraction than the LFP conventional cathode material. EIS measurements demonstrated that Rct for LFP/Cin is 70 and 50 percent lower compared to LFP and LFP/Cex respectively. The initial discharge capacity of LiFePO4/Cin cathode material delivers about 133.92 mAh g−1 (82% of theoretical capacity) at 0.1 C and cycling stability with 96.3% of capacity retention after 40 cycles at 0.1 C. Electrochemical tests demonstrate that in-situ carbon coating play an important role in the improvement of battery performance with increasing the conductivity, reduce the particles size and unique structure.

Glucose, as the major energy source in cellular metabolism, plays an important role in the natural growth of cells. Herein, a simple, rapid and low-cost method for the glucose determination by utilizing glucose oxidase and CdTe/thioglycolic acid (TGA) quantum dots (QDs) on a thin layer chromatography (TLC) plate has been described. The detection was based on the combination of the glucose enzymatic reaction and the quenching effect of H2O2 on the CdTe/TGA quantum dots photoluminescence. This QDs-based assay exhibits several advantages. Enzyme immobilization and QDs modification process are not required and the high stability of the QDs towards photobleaching is beneficial to this sensing system. The proposed method is linear in concentration range of 1.00 × 10-1-3.00 × 10-5 M of glucose and has a detection limit of 1.25 × 10-8 M. The results of real sample analysis show that the glucose oxidase CdTe/TGA QDs system would be a promising glucose-biosensing system.

Carbon Spheres were fabricated by hydrothermal method and their structural properties were investigated. Carbon Spheres with average sizes around of 230, 320 and 430 nm were synthesized in different concentration of glucose aqueous solution and different hydrothermal reaction time. The temperature of 180 °C by a hydrothermal reaction was fixed in all of glucose concentration and hydrothermal reaction time. The result showed that the spherical shape of Carbon Spheres was formed in the special concentration of glucose aqueous solution and hydrothermal reaction time.The product obtained was characterized by X-ray diffraction(XRD); Fourier transforms infrared (FTIR) spectra, which have inferred the Carbonic nature of the product. Further,SEM images have revealed the spheres having quite spherical morphology.

2,4-dinitrophenylhydrazanomethylphenol (DNPHMP) was immobilized onto silicate rice husk ash to form a heterogeneous catalyst denoted as RHDNPH. The elemental and EDX analysis of RHDNPH showed the nitrogen is incorporated into silica. The RHDNPH had 154.6 m2g-1 as a specific surface area. The FT-IR clearly showed the appearance of –NH and C=N absorption band at the expected range. The TGA curve shows that the RHDNPH was stable at the temperature of less than 200 °C. Hydrolysis experiments of cellulose were conducted in liquid face reaction at 140 °C, and 150 mg of catalyst mass in 11 h. The maximum hydrolysis of cellulose was 84 % with 100 % selectivity of glucose over the catalyst. The catalyst was simple in its preparation, stable during the cellulose hydrolysis in addition to repeatedly without a significant loss of its catalytic activity.

In this study, we developed a hybrid biosensor based on sulfite oxidase and glucose oxidase for determination of sulfite and glucose. The principle of the measurements was based on the determination of the decrease in the differentiation of oxygen level which had been caused by the catalytic reactions of the enzymes in the bioactive layer of the biosensor. The biosensor showed a linear response for an interval of sulfite concentration between 1×10-4 and 1.75×10-3 M and for glucose concentrations between 2.5×10-5 and 1.25×10-3 M. After some optimum and characterization studies, the proposed biosensor was applied to the determination of sulfite and glucose in certain real samples, blood and pickle water.

Production of several yeast products occur in presence of mixtures of monosaccharides. To study effect of xylose and glucose mixtures with system aeration and nitrogen source as the other two operative variables on xylitol production by Pichia guilliermondii, the present work was defined. Artificial Neural Network (ANN) strategy was used to mathematically show interplay between these three controllable factors and the xylitol productivity response. In the first stage, model fitting was performed using Response Surface Methodology (RSM) and the appropriate fraction of this design then was applied for the ANN training step (Levenberg Marquardt ‘LM’ algorithm). The best ANN model configuration with the three test input variables composed of six neurons in the hidden layer and tangent sigmoid (TANSIG) and linear transfer function (PURELIN) were used as the activation functions for the data processing from inputs to the hidden layer and from the constructed neurons to the output nodes. The network performance was evaluated by Mean Squared Error (MSE) and the regression coefficient of determination (R2). These values respectively, for the RSM model fitting were 2.327× 10-4 and 0.9817, and for the ANN training data were 2.29 × 10-8 and 0.9999. While MSE and R2 values for the other two steps of ANN were 4.56 × 10-3 and 0.9741 (validating step) and1.52× 10-3 and 0.9325 (testing step), respectively. Positive synergism of ANN with RSM was confirmed.