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Aims: Molecular insights into the analyte-bioreceptor interactions play a vital role in the efficacy of designing biosensors. Biosensors that utilize aptamers as bioreceptors are highly efficient with high specificity and reusability. Aptasensors can be used in a variety of conditions of in vivo or in vitro. The aim of this study was to study the changes in the solvent conditions of the binding of MUC1-G peptide and the anti-MUC1 aptamer.
Materials and Methods: The molecular dynamics simulation method has been used to investigate the change of molecular interactions due to selective variations in solvent conditions. The results can be used to reflect a variety of environments, in which the aptasensor utilizes anti-MUC1 S2.2 aptamer as a bioreceptor and MUC1–G peptide as a biomarker.
Findings: Based on the calculated binding energies, the medium containing 0.10M NaCl and anti-MUC1 S2.2 aptamer demonstrates the highest affinity toward the MUC1-G peptide among the studied concentrations of NaCl, and the arginine amino acid has a key role in the aptamer–peptide binding. Conclusion: The results of MD simulation indicated that the increase in the concentration of NaCl in the interaction environment leads to a decrease in binding energies; therefore, the binding affinity of the anti-MUC1 aptamer to MUC1-G peptide decreases. Insights from present modeling demonstrate the selectiveness and sensitivity to solvent conditions, which should be considered in the development of biosensors.

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Nanofluids are engineered by suspending nanoparticles with average sizes below 100 nm in traditional. The ever increasing of thermal loads in such applications requires advanced operational fluid characteristics, for example, high thermal conductivity dielectric oils in transformers and car radiators. These fluids require high thermal conduction, as long as electrical insulation. In the present work the thermophysical and rheological properties of the nanofluids such as thermal conductivity, viscosity and density are obtained from molecular dynamics simulations. These results served as initial data for computational fluid dynamics simulations to calculate heat transfer coefficient. The results show that, adding titanium oxide nanosheet in the base fluid enhanced the thermal conductivity and increased the viscosity and density of the base fluid. The theoretical calculations are confirmed the molecular dynamics simulation results and the simulation methods accuracy. The computational fluid dynamics results show that increasing the amount of titanium oxide nanosheet in the base fluid increases the heat transfer coefficient and increasing ethylene glycol ratio in base fluid leads to lower heat transfer coefficient. Also non-equilibirium molecular dynamics method can use as a effective and accurate method for nanofluids investigation. The coding which used to obtaine the thermal conductivity of nanofluid is a novel and modified type of non-equlibiruim molecular dynamics method. With using this coding the eror persentages of simulations is decreases. The other advantage of this code is reducing the simulation process, becous the molecular dynamics simulations need a long time for processing.

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The aim of present work is the investigation of polypropylene/graphene oxide nanocamposies. In this work, the reinforcing effects of the graphene oxide nanoparticles on the mechanical and thermal properties of the nonpolar polypropylene are examined. There is two main challenges to improve the properties of polypropylene by graphene oxide nanoparticles. First, the nanoparticles have not suitable dispersion in polymer matrix. Furthermore, there is not sufficient adhesion between nanoparticle and polymer chains. In this study, the graphene oxide (GO) surface is modified by a linear alkyl chain via a bimolecular nucleophilic substitution reaction between the oxygen groups of GO and reactants to promote the homogeneous dispersion of GO in the organic solvent and increasing the interfacial adhesion between the graphene oxide and polymer matrix. The presence of the alkyl groups on the surface of graphene oxide nanoparticles is characterized by FT-IR. To prevent the AGO aggregation in the polypropylene, the solution-blending method is used to prepare the nanocomposites with 0.1, 0.3, 0.5 wt% AGO. The SEM images confirmed the appropriate dispersion of the graphene oxide in the composites. The stress-strain analysis, dynamic-mechanical thermal analysis (DMTA), and thermal gravimetric analysis (TGA) are performed to investigate the mechanical and thermal properties of nanocomposites. The results demonstrated that the Young’s modulus of the polymer are improved by 20, 30 and 34% with adding 0.1, 0.3 and 0.5% AGO, respectively. Also the 10% mass loss temperature for 0.1, 0.3 and 0.5% AGO nanocomposites compared to neat polypropylene increased by 2, 8, 12 C0, respectively.