Deep eutectic solvent based magnetic nanofluid in the development of stir bar sorptive dispersive microextraction: An efficient hyphenated sample preparation for ultra‐trace nitroaromatic explosives extraction in wastewater

A deep eutectic solvent based magnetic nanofluid was coupled with stir bar sorptive dispersive microextraction as a hyphenated sample preparation technique. The neodymium core magnetic stir bar was coated physically with nanofluid of magnetic carbon nanotube nanocomposites and deep eutectic solvents. The prepared nanofluid has magnetic and strong sorbing properties and is compatible with gas chromatography. In this nanofluid, the deep eutectic solvent acts simultaneously as both carrier and stabilizer for magnetic nanotubes. The predominant experimental variables affecting the extraction efficiency of nitroaromatic compounds were evaluated. Under the optimized conditions, the limit of detection and enrichment factor were in the range of 0.2–4.9 ng/L and 852–1480, respectively. The relative standard deviations were between 5.6 and 10.2% (n  = 6). Method validation was performed by both spiking–recovery method and comparison of results with other methods. Finally, the proposed method was successfully applied for the extraction and pre‐concentration of nitroaromatic explosives in water samples, followed by determination by gas chromatography with micro‐electron capture detection.     

Determination of the Heat Transfer Coefficient of Metal Oxide Based Water Nanofluids in a Laminar Flow Regime Using an Adaptive Neuro-Fuzzy Inference System

In order to enhance the thermal properties of turbine oil (TO), three different nanoparticles (CuO, Al₂O₃, and TiO₂) are loaded into the TO. To measure the thermal performance of nanoparticle-based TO nanofluids at laminar flow and under constant heat flux boundary conditions, an experimental setup was applied. The obtained data clearly demonstrate the positive effect of all nanoparticles on the heat transfer rate of TO. As the most important factor, the heat transfer coefficient of the abovementioned two-phase systems is increased upon increasing both the volume concentration and the flow rate. An adaptive neuro-fuzzy inference system (ANFIS) is applied for modeling the effect of critical parameters on the heat transfer coefficient of nanoparticle-TO based nanofluids numerically. The results are compared with experimental ones for training and test data. The results suggest that the developed model is valid enough and promising for predicting the extant of the heat transfer coefficient. R² and MSE values for all data were 0.990208751 and 108.1150734, respectively. Based on the results, it is obvious that our proposed modeling by ANFIS is efficient and valid, which can be expanded for more general states.     

基于基液连续假设的大体系Cu-H2O纳米流体输运特性的模拟研究

分子动力学模拟是研究纳米流体的输运特性的重要手段, 但计算量庞大. 为研究能体现流动传热过程的大体系纳米流体的输运特性, 本文对基液采用连续介质假设, 将基液的势能拟合在纳米团簇的势能中, 大幅度减小了计算量, 使得大体系输运特性的模拟成为可能, 且模拟结果与多组实验结果吻合较好. 采用此方法模拟研究了速度梯度剪切对Cu-H₂O纳米流体颗粒聚集过程和聚集特性的影响, 进而对Cu-H₂O纳米流体在流动传热过程中的热导率和黏度进行了模拟计算, 定量揭示了宏观流动传热过程中不同的速度梯度、速度、平均温度和温度梯度对于Cu-H₂O纳米流体热导率和黏度的影响.     

微细管碳纳米管悬浮液强制对流换热实验研究

测量了水平微细圆管内蒸馏水和不同质量浓度的水基多壁碳纳米管纳米流体在低雷诺数下的强制对流换热特性。实验结果表明,与蒸馏水相比,纳米流体的对流换热系数显著提高,且随质量浓度和管内雷诺数的增大而增大;并且研究了流体管内流动阻力特性,得到的泊肃叶数f·Re值随着雷诺数的变化不明显,但纳米流体的f·Re值要明显小于纯水。     

气泡流纳米流体的太阳能蒸腾特性研究

太阳能驱动水蒸发是光热利用的重要途径,光-热蒸汽转化可通过纳米流体吸收太阳能生成蒸汽。本文提出光散射气泡耦合光吸收纳米颗粒强化光能转换的新思路,在太阳能纳米流体蒸发体系中引入气泡群,这些动态气泡作为光能散射与传递中心,延长了入射光路径并倍增了光通量;同时提供了极大的气液界面完成气泡吸湿,以及破水而出的炸裂扰动加速蒸汽扩散,从而实现高效太阳能蒸发传质,蒸汽生成速率可达0.88 kg·m^-2·h^-1,为纯水蒸发速率的3.1倍。     

Investigation on rheological properties of carbon nanotube nanofluids

The effective viscosity of carbon nanotube nanofluids is strongly dependent on the temperature and concentration. The aggregation behaviour that carbon nanotubes exhibit in solution and the orientation variation of single carbon nanotube make rheological properties of nanofluids more complex. With the increase of shear rate, the degree of dispersion and orientation of carbon nanotubes will be improved. Based on previous studies and the fact mentioned above, a reasonable expression for viscosity of carbon nanotube nanofluids has been given, which is associated with the shear rate and aspect ratios of carbon nanotubes. The expression has been validated comparing with previous experimental data.     

Two numerical modelings of free convection heat transfer using nanofluids inside a square enclosure

This work describes the numerical simulation of natural convection heat transfer of Cu–water nanofluids in a square enclosure for Rayleigh numbers varying from 10³ up to 10⁵. Two different numerical approaches were used: the finite volume method and the finite element method. The nanofluids were assumed to be single-phase fluids with modified thermal properties obtained from experimental results and theoretical models. The results showed that the Nusselt number for nanofluids was basically the same as that obtained for the base fluid. Therefore, the enhancement observed in the heat transfer coefficient was significant due to the augmentation in the thermal conductivity.     

纳米流体液滴撞击壁面铺展动力学特性研究

纳米流体液滴撞击固体壁面的铺展动力学特性是基于液滴沉积实现高效传热传质过程的关键因素,然而由于纳米流体的非牛顿流变特性及液滴内微流动与纳米颗粒的耦合作用,目前对纳米流体液滴撞击固体壁面的铺展动力学行为缺乏足够的认识.本研究利用了两步法分别配制了分散有3种纳米颗粒的均匀稳定纳米流体(碳纳米管、石墨烯、纳米石墨粉),并对流体的流变特性进行了测量分析.利用显微高速数码摄像技术捕捉了液滴撞击固体壁面的动态过程,通过图像处理技术分析铺展过程中液滴的无量纲高度、铺展因子及动态接触角,探究了液滴在韦伯数约为200及800时撞击壁面后铺展沉积形态的演变规律.研究表明,3种不同纳米颗粒的加入均使基液表现出明显的剪切变稀特性,在液滴撞击壁面的铺展过程中,流体的剪切黏度起重要作用,液滴的无量纲高度和铺展因子的变化幅度随着纳米流体剪切黏度的增大而减小.纳米流体液滴撞击疏水表面时能更快的达到平衡状态,液滴的惯性力主导着液滴的初始铺展阶段,液滴的铺展范围和速度随撞击速度的增大而增大.开展该研究能够为基于液滴沉积的增益冷却技术以及微型高导热及导电材料的制造提供理论依据和技术指导.      

The role of interfacial layers in the enhanced thermal conductivity of nanofluids: A renovated Hamilton–Crosser model

We previously developed a renovated Maxwell model for the effective thermal conductivity of nanofluids and determined that the solid/liquid interfacial layers play an important role in the enhanced thermal conductivity of nanofluids. However, this renovated Maxwell model is limited to suspensions with spherical particles. Here, we extend the Hamilton--Crosser model for suspensions of nonspherical particles to include the effect of a solid/liquid interface. The solid/liquid interface is described as a confocal ellipsoid with a solid particle. The new model for the three-phase suspensions is mathematically expressed in terms of the equivalent thermal conductivity and equivalent volume fraction of anisotropic complex ellipsoids, as well as an empirical shape factor. With a generalized empirical shape factor, the renovated Hamilton--Crosser model correctly predicts the magnitude of the thermal conductivity of nanotube-in-oil nanofluids. At present, this new model is not able to predict the nonlinear behavior of the nanofluid thermal conductivity.