Fe3O4纳米颗粒固定化纤维素酶的酶学特性研究

试验研究了超顺磁性纳米颗粒直接固定纤维素酶的酶学特性.以化学共沉淀法合成出的纳米Fe3O4颗粒为载体,利用水溶性碳化二亚胺(EDC)活化将纤维素酶固定,探讨了不同酶量、交联剂、pH值等因素对固定化纤维素酶性能的影响,得出固定纤维素酶的最佳条件:酶浓度为9.0 mg/mL,EDC浓度为3.0 mg/mL,pH值为4.0.试验还研究了在不同温度和pH值条件下的固定化酶与游离酶的活性,酶固定后最佳水解温度为60℃,最适pH值向碱性迁移且范围有所增加.     

纳米Fe3O4催化UV-Fenton降解邻苯二酚的效能及自由基的鉴定

采用纳米Fe3O4催化UV-Fenton降解邻苯二酚,考察了溶液的初始pH值、H2O2投加量、催化剂的投加量和反应温度对邻苯二酚配水中COD的去除效果的影响.其结果表明,在邻苯二酚的浓度为100 mg/L、溶液初始pH为7、H2O2投加量为14.75 mmol/L、催化剂的投加量为0.50 g/L、反应温度30℃的条件...     

纳米Fe3O4固载聚苯乙烯球对甲烷水合物生成与分解的影响

为了提高甲烷水合物合成反应中的传热效率,选取纳米Fe3O4作为导热材料,将不同量的纳米Fe3O4固载在聚苯乙烯球(PSNS)上,通过乳液聚合法制备了20%Fe3O4/PSNS和40%Fe3O4/PSNS两种新型聚苯乙烯球,并研究了PSNS,20%Fe3O4/PSNS,40%Fe3O4/PSNS三种聚苯乙烯溶液和十二烷基硫酸钠(SDS)对甲烷水合物生成与分解的影响。实验结果表明:三种聚苯乙烯溶液生成的水合物储气倍数和分解后甲烷回收率均高于SDS的100V/V,72.50%;对比三种聚苯乙烯溶液的促进效果发现,Fe3O4的存在明显缩短了水合物反应平衡时间,随着Fe3O4含量的增加,反应平衡时间由18 h缩短到9 h;Fe3O4提高了甲烷回收率,以20%Fe3O4/PSNS和40%Fe3O4/PSNS为促进剂时,水合物分解后甲烷回收率分别为92.15%,89.80%,都高于PSNS的85.00%。     

聚N-异丙基丙烯酰胺磁性阿霉素纳米微球抗兔VX２肝肿瘤效果初步研究

目的观察应用聚N-异丙基丙烯酰胺磁性阿霉素纳米微球（ADM-PNIPAM-Fe ３ O ４ ）对兔VX２肝肿瘤的动脉化疗栓塞治疗作用。方法将肝脏已成功接种VX２肿瘤的新西兰大白兔随机分成４组，每组８只。A组为生理盐水对照组，肝动脉灌注生理盐水１０ml；B组为游离阿霉素组，肝动脉注入阿霉素（１mg／kg）；C组为ADM-PNIPAM组，肝动脉注入ADM-PNIPAM１．５mg／kg（约相当于阿霉素１mg／kg）；D组为ADM-PNIPAM-Fe ３ O ４ 并在瘤区外加磁场组，肝动脉注入ADM-PNIPAM-Fe ３ O ４ ２mg／kg（相当于阿霉素１mg／kg），同时在肿瘤表面加磁场。４组实验动物于介入术前１d，术后１４d行CT肝脏及肺部扫描，测量肿瘤大小，检查肺部转移灶；术后第１５天处死，全部实验动物均取肿瘤组织及肺脏作组织病理学检查，C组及D组取胃、脾、肾器官行病理学检查。结果术前１d各组动物肿瘤体积无明显统计学差异。至术后１４d时，A组平均肿瘤体积为（２３．８７±７．０２）cm ３ ；B组为（７．７０±１．５３）cm ３ ；C组为（４．２９±０．２５）cm ３ ；D组为（２．０５±０．１８）cm ３ 。B、C、D３组平均肿瘤体积均小于同期对照A组，B、C、D３组之间亦有差异，按术后肿瘤体积从大到小的顺序排列依次为B组＞C组＞D组，以ADM-PNIPAM-Fe ３ O ４ 并在瘤区外加磁场组最小。肺转移的发生率A、B、C、D组分别为１００％、６６．７％、３７．５％、１２．５％，C、D组肺转移率低于对照A组；与B组相比A组转移率无明显统计学差异，但病理学检查B组转移瘤数目比A组少；肿瘤坏死程度为D组＞C组＞B组＞A组。结论经动脉途径应用ADM-PNIPAM-Fe ３ O ４ 联合外加磁场治疗对兔VX２肝肿瘤生长有较明显的抑制作用。初步肯定ADM-PNIPAM-Fe ３ O ４ 是一种有效的介入化疗栓塞制剂。     

Effect of hybrid nanoparticles MgO and Al2O3 added water-in-diesel emulsion fueled diesel engine using hybrid deep neural network-based spotted hyena optimization

The automotive sector is one of the top energy consumers globally compared with any other sector where oil plays the main role. According to statista.com (an online platform that displays the stats on oil consumption and reserves), in 2016, the demand for crude oil was about 85.3 million barrels per day worldwide. In 2019, the demand almost reached 100 barrels per day, and then it was reduced to 91 million per day during the 2020 global COVID-19 crisis. However, it was predicted that the global crude oil requirements will exceed 100 million barrels per day by 2023 and will continue to raise. Also, geographically, not all countries worldwide have the oil reservoirs or the technology to extract oil from the reservoirs. Although the oil demand worldwide is increasing every year, researchers have estimated that there are only 47 years of oil left on the planet earth if the current oil consumption will raise this way. Researchers are looking for finding alternative fuels, such as electrochemical energy (electric vehicles), biodiesel, electricity, ethanol, hydrogen, natural gas, propane, emerging fuels, or the use of such fuels in the existing engines to minimize the use of nonrenewable energy resources. However, researchers are also looking more at fuels based on hybrid nanoparticles added to emulsified fuels. Due to the limitations of utilizing electrochemical energy or biofuels include high charging time, limited millage, harmful exhaust emissions, complicated production process, engine efficiency, the cost of fuel, and the advantages over hybrid nanoparticles added emulsified fuels than biofuels. Hence, after going through numerous researches, in this present experimentation, “hybrid nanoparticles (MgO and Al₂O₃) added water-in-diesel emulsion” are formulated to enhance the quality of emission and improve the performance of the compression ignition engine. The best combination of diesel, MgO, and Al₂O₃, a water-in-diesel (W/D) emulsion blend, is proposed. The results were further validated using deep neural network-based spotted hyena optimization (DNN-SHO) prediction and compared with traditional machine learning approaches artificial neural network (ANN), convolution neural network (CNN), regression-based network (RBN), recurrent neural network (RNN), and DNN. As a result, the best proportions of the proposed nanoparticles added into the W/D bend are identified to be 10% W/D, 50 ppm of MgO, and 50 ppm of Al₂O in terms of engine performance and emission characteristics brake thermal efficiency 30.7%, brake-specific fuel consumption 0.29 kg/kW-h, CO 0.027 vol%, NO_x 855 ppm vol, and HC 12 ppm vol. Besides this, the DNN-SHO-based validated outcomes are in good agreement with the experimental values and outperformed other traditional approaches ANN, CNN, RBN, RNN, and DNN used in this study.     

Three-dimensional tilted hydromagnetic natural double-diffusive convection in a rectangular cuboid filled with nanofluids based on magnetic nanoparticles

In this article, we use magnetic nanoparticles to explore the three-dimensional natural upward force flow within a quadrangular cuboid under the influence of a sloping magnetic flux. We consider three forms of thermic conditions on the bottom surface of the cavity, such as uniform surface temperature, constant heat flux, and temperature varied parabolically in space. The Galerkin-type finite element method is used to solve the unitless leading equations of implicit physical systems. Ferrite-water nanofluid is the default, used to study the flow field, thermal field, and concentration field other than the regular Nusselt number. We examined the influence of many model parameters, especially the thermal Rayleigh number, volumetric nanoparticles fraction, the Hartmann number, nanoparticles formation, and the predisposition of magnetic flux. The influence of the position of the thermal flux on the lower surface of the thermal field cavity is also studied. The heat transfer rate of various magnetic nanofluids is compared. Our simulated data echoed nicely with the available experimental one. The results show that Mn-Zn ferrite-kerosene nanofluid exhibits advanced heat transportation more than the other nanofluids studied. For lower dimensions of aspect ratio and nanoparticle diameter, higher heat transfer is obtained. Compared with other boundary conditions studied, the uniform temperature on the bottom surface of the cuboid provides a higher heat transfer rate.     

The preparation of Fe3O4/nanocellulose aerogel nanocomposite as anodes for lithium-ion batteries and electrochemical performance

纤维素因其环境友好、价格低廉等优点受到研究者的广泛关注,近年来作为碳材料广泛应用于电化学研究中。采用碳化后的纳米纤维素气凝胶为载体,六水合氯化铁为铁源,通过溶液热法合成了四氧化三铁/纳米纤维素气凝胶复合材料。通过XRD和SEM对产物进行了结构表征和微观形貌分析,并将其作为锂离子电池的负极材料,测试了一系列电化学性能,并与纯Fe₃O₄纳米颗粒的进行对比。结果表明,碳化后的纳米纤维素气凝胶保持着疏松多孔的三维网络结构,尺寸均一的Fe₃O₄纳米粒子均匀的分布于其中。该复合材料表现出优异的循环稳定性,在100 mA/g的电流密度下,首次放电比容量为1064 mA·h/g,100次循环后仍稳定在847 mA·h/g。相比于纯Fe₃O₄纳米颗粒,材料的电化学性能得到大幅度提高。本文有助于推动纤维素基碳材料在电化学领域中的进一步应用,为复合电极材料的发展提供一定的实验依据。     

Effects of Newtonian heating and thermal radiation on micropolar ferrofluid flow past a stretching surface: Spectral quasi‐linearization method

This study article addressesthe flow and heat transfer characteristics of a magnetite Fe₃O₄ micropolar ferrofluid flow past a stretching sheet. For practical interest, thermal radiation, Newtonian heating, and a heat source or sink are considered in this investigation. A useful Tiwari‐Das nanofluid model is considered to analyze the microstructure and inertial characteristics of the water‐based nanofluids containing iron oxide. The dimensionless nonlinear ordinary differential equations are solved by employing suitable similarity variables. The resulting nonlinear system is solved by the spectral quasi‐linearization method. The effects of different nondimensional parameters on various profiles are shown graphically and explored in detail. It is found that the micropolar ferrofluid exhibits a higher energy distribution than that of a classical micropolar fluid. Compared to the classical micropolar liquid, local skin‐friction is more significant for the micropolar magnetite ferrofluid. In the presence of Newtonian heating, the thermal behavior of the micropolar nanofluid is remarkably better than that of the classical micropolar fluid.     

The heating of magnetic nanoparticles in a rotating magnetic field

ABSTRACT

The specific absorption rate of magnetic nanoparticles in a rotating magnetic field has been calculated taking into account both thermal fluctuations of the particle magnetic moments and strong magneto-dipole interactions in nanoparticle clusters with various filling factors. For an assembly of interacting superparamagnetic nanoparticles, the maximal values of the specific absorption rate in a rotating magnetic field are found to be 30–40% greater than that in alternating magnetic field. In addition, for the given filling factor and magnetic field amplitude in rotating magnetic field the nanoparticles in a wider range of diameters can effectively contribute to the energy absorption process. Therefore, the use of rotating magnetic field seems preferable in magnetic nanoparticle hyperthermia.     

Non-Newtonian blood flow with magnetic nanoparticles in a W-shaped stenosed arterial segment: A numerical study

Flow of blood, infused with magnetic nanoparticles, in a W-shaped stenosed human arterial segment is studied numerically using a realistic non-Newtonian blood rheology model. It is observed that the Newtonian model predicts less time to reach a steady state than the non-Newtonian blood rheology model. An increased drug retention time at the target site with an increase in nanoparticle concentration is predicted. Detailed simulations further reveal that the skin friction coefficient does not increase significantly with the increase in nanoparticle concentration. Hence, it is anticipated from our study that the infusion of drug-carrying nanoparticles in blood flow does not excessively enhance wall shear stress that may lead to arterial wall damage. An overall increase in heat transfer rates and wall shear stress at the stenosed section is seen with an increase in Reynolds number. The present study provides valuable information for designing computer-assisted drug delivery systems.     

Synthesis and application of Fe3O4@nanocellulose/TiCl as a nanofiller for high performance of quasisolid‐based dye‐sensitized solar cells

In this research, to optimize the surface of the photoanode, two different types of surface coatings were used and their effects on the photovoltaic parameters were investigated. Also, to compare the two different electrolytic systems based on liquid and gel‐state electrolyte, the novel magnetic core‐shell nanocellulose/titanium chloride (Fe₃O₄@)NCs/TiCl) nanocomposite was introduced into a polymeric system as a nanofiller to decrease the crystallinity of the polymer and enhance the diffusion of triiodide ions in quasisolid‐state dye‐sensitized solar cells (QS‐DSSCs). For this purpose, Fe₃O₄@)NCs/TiCl was synthesized by coprecipitation of Fe³⁺ and Fe²⁺ ions in the presence of nanocellulose and then used as magnetic support for bonding TiCl₄ to prepare QS‐DSSCs. Containing a 10.0 wt% magnetic nanocomposite, it displayed a higher apparent diffusion coefficient (D_app) for I₃^? ions (4.10 × 10^?6 cm²/s) than the gel polymeric electrolyte (GPE) did (1.35 × 10^?6 cm²/s). GPEs were characterized using various techniques including current density‐voltage curves, AC impedance measurements, and linear sweep voltammetry (LSV). The photovoltaic values for the short‐circuit current density (J_sc), open‐circuit voltage (V_OC), and fill factor (FF) and the energy conversion efficiency (η) of the novel Fe₃O₄@NCs/TiCl nanocomposite–based QS‐DSSCs were 14.90 mA cm^?2, 0.757 V, 64%, and 7.22%, respectively.     

Enhanced performance of alpha‐Fe2O3 nanoparticles with optimized graphene coated layer as anodes for lithium‐ion batteries

A series of different α‐Fe₂O₃ nanoparticles composites containing different amounts of graphene coatings have been successfully prepared using a simple electrostatic self‐assembly (ESA) method. The structure and electrochemical properties of these α‐Fe₂O₃@graphene composites have been investigated. The α‐Fe₂O₃ nanoparticles composite containing 40 wt% graphene coating exhibits the highest specific capacity (385 mAh g^?1) under 1000 mA g^?1, resulting in superior cycle stability with no downward trend after 500 cycles. These results demonstrate that graphene coatings can be used to enhance the electrochemical properties and morphological stability of α‐Fe₂O₃ nanoparticles as anodic materials for high performance lithium‐ion batteries (LIBs). The low‐energy self‐assembly method employed in the paper has good potential for the broad‐scale preparation of other graphene‐modified materials because of its simplicity and the relatively low temperature conditions.     

Study on Aerodynamic Design Optimization of Turbomachinery Blades

This paper describes the study on aerodynamics design optimization of turbomachinery blading developed by the authors at the Institute of Engineering Thermophysics, Chinese Academy of Sciences, during the recent few years. The present paper describes the aspects mainly on how to use a rapid approach of profiling a 3D blading and of grid generation for computation, a fast and accurate viscous computation method and an appropriate optimization methodology including a blade parameterization algorithm to optimize turbomachinery blading aerodynamically. Any blade configuration can be expressed by three curves, they are the camber lines, the thickness distributions and the radial stacking line, and then the blade geometry can be easily parameterized by a number of parameters with three polynomials. A gradient-based parameterization analytical method and a response surface method were applied herein for blade optimization. It was found that the optimization process provides reliable design for turbomachinery with reasonable computing time.