Lorestan University

About: Lorestan University is a education organization based out in Khorramabad, Iran. It is known for research contribution in the topics: Population & Adsorption. The organization has 1952 authors who have published 3329 publications receiving 38154 citations. The organization is also known as: LU.

Application of graphene nanoplatelets silica composite, prepared by sol-gel technology, as a novel sorbent in two microextraction techniques.

Abstract: In this study, the application of a novel nanomaterial composite was investigated in two microextraction techniques of solid-phase microextraction and a needle trap device in a variety of sampling conditions. The optimum sampling temperature and relative humidity were 10°C and 20%, respectively, for both techniques with two sorbents of graphene/silica composite and polydimethyl siloxane. The two microextraction techniques with the proposed sorbent showed recoveries of 95.2 and 94.6% after 7 days. For the needle trap device the optimums desorption time and temperature were 3 min at 290°C and for SPME these measures were 1 and 1.5 min at 240-250°C for the graphene/silica composite and polydimethyl siloxane, respectively. The relative standard division obtained in inter- and intra-day comparative studies were 3.3-14.3 and 5.1-25.4, respectively. For four sample the limit of detection was 0.021-0.25 ng/mL, and the limit of quantitation was 0.08-0.75 ng/mL. The results show that the graphene/silica composite is an appropriate extraction media for both techniques. Combining an appropriate sorbent with microextraction techniques, and using these in conjunction with a sensitive analytical instrument can introduce a strong method for sampling and analysis of occupational and environmental pollutants in air.

Anti-fouling polyethersulfone nanofiltration membranes aided by amine-functionalized boron nitride nanosheets with improved separation performance

Abstract: Nowadays, the implementation of a desirable membrane with high permeation and rejection properties in liquid and gas separation processes has become a competitive necessity in water purification and desalination. In this field, nanostructured membranes have enticed many researchers and industrialists to use them. Herein, an amine-functionalized boron nitride (BN) embedded microporous polyethersulfone (AFBN-PES) membrane was fabricated to examine the anti-fouling properties and separation performance of mixed matrix membranes (MMMs). Also, fouling parameters such as intrinsic resistance (Rm), pore resistance (Rp), cake resistance (Rc), and total resistance (Rt) were investigated, and a significant improvement in the anti-fouling characteristics of the fabricated MMMs was detected. Surprisingly, water permeation across AFBN-PES membrane increased two-fold compared to the bare PES, while its BSA and Reactive Blue 19 dye rejection capability remained over 99 %. Faster solvent-nonsolvent exchange during the preparation of polymeric membrane owing to the presence of AFBN nanosheets enhanced the hydrophilicity, changed the mean pore size, and decreased the surface roughness beyond the creation of larger microvoids in the sub-layer of MMMs.

Propagation of surface plasmon polaritons in monolayer graphene surrounded by nonlinear dielectric media

Abstract: The propagation of s-polarized surface plasmon polaritons (SPPs) was investigated in a monolayer graphene sheet surrounded by two dielectric media on each side, so that one or both sides of the media were linear or nonlinear with Kerr-type nonlinearity. The plasmonic properties including the wave propagation index n e f f, the penetration depth, the time-averaged power flow and the spatial profile of electric and magnetic fields were calculated for the following structures: Linear medium/Graphene/Linear medium (L/G/L), Nonlinear medium/G/L (NL/G/L) and NL/G/NL. The analysis of the nonlinear coefficient effect on the SPP properties showed that increasing the nonlinearity in NL/G/L enhanced n e f f. However, for a smaller difference between the nonlinearity of layers, n e f f decreased in NL/G/NL. By comparing between the proposed structures, it was found that while large values of n e f f can be obtained from L/G/L, its frequency confinement is smaller than that of NL/G/L and NL/G/NL. Furthermore, NL/G/L and NL/G/NL were able to support localized nonlinear modes, leading to enhanced frequency confinement of transverse electric (TE) waves in the presence of nonlinearity. Increasing the nonlinearity in NL/G/L confined the spatial profile of the electric field near the graphene interface, indicating the existence of surface plasmon solitons. The influence of the graphene chemical potential μ on the plasmonic properties of the structures was also investigated. In this case, it was found that the plasmonic properties can be controlled by μ. Our calculations may solve the difficulties in TE surface plasmons for application in optics and plasmonics.

The impact resistance and mechanical properties of fiber reinforced self-compacting concrete (SCC) containing nano-SiO2 and silica fume

Abstract: In this study, an extensive study including an experimental and analytical approach describes the effects of presence 1% nano-SiO2 and 7% silica fume on the key mechanical properties (compressive, tensile and flexural strength) and impact resistance of such compositions with inclusion of different fibre volume fractions of Polypropylene (PP) (.25, .5, .75 and 1%) and water-to-cement ratios (.27, .34, .41). The experimental tests have been implemented on two hundred and seventy specimens. Experimental results indicated that using both silica fume and nano-SiO2 instead of cement into the plain self-compacting concrete (SCC) leads to improved impact resistance and mechanical properties. This improvement was higher in terms of impact resistance compared to mechanical properties. Moreover, it was observed that using nano-SiO2 particles consequences to reduce the wall effect between PP fibre and its surrounding matrix. Reduction of this effect enhanced the impact resistance and mechanical properties of fibre-re...

Prediction of River Pipeline Scour Depth Using Multivariate Adaptive Regression Splines

Abstract: In this study, the multivariate adaptive regression splines (MARS) technique was applied to estimate scour depth around pipelines. To this purpose, 90 data sets related to effective dimensionless parameters on pipeline scouring phenomena were gathered from literature. A gamma test (GT) was used to define the most-effective parameters on scouring phenomena below pipelines. Performance of MARS model was compared with multilayer perceptron (MLP) neural network and empirical formulas. Results of the GT showed that e/D, τ*, and y/D are the most important parameters for scour depth. Results of MARS model with coefficient of determination (0.91) and root-mean square error (0.05) indicated that this model has suitable performance for predicting scour depth under pipelines and results of this model are more accurate compared to empirical formulas. Comparing results of MARS model and MLP showed that accuracy of MARS model is slightly lower than that of the MLP.