循环射流混合槽内液液两相混合特性数值模拟

循环射流混合槽作为一种高效的混合装置在化工过程强化处理技术中具有潜在的工业应用前景。由于缺乏对其内多相体系流动和混合行为的研究,制约了循环射流混合反应器的优化设计与工业化应用。本文选取水和二甲基硅油两相体系,采用计算流体力学软件ANSYS Fluent V16.1中Eulerian-Eulerian多相流模型和SST k-?湍流模型,对两种不同加料方式下循环射流混合槽内液液两相射流中心线速度、离析强度、拉伸率等参数进行研究。研究结果表明：分散相浓度（α_d）增大射流卷吸能耗增大,在l/s<0.4内α_d=1.80%和2.86%量纲为1的射流中心线速度衰减趋势与α_d=6.00%相比减弱51%和21%;在低分散相浓度时,量纲为1的射流中心线速度随Re的增大衰减趋势变化小,在l/s<0.24内Re=6346、9519和12692量纲为1的射流中心线速度衰减趋势与Re=3173相比分别减弱2.60%、2.87%和12.69%。离析强度随混合时间的增大而减小,随周向角度增大呈W形变化趋势。在相含率和雷诺数相同时,对称球状较圆柱状加料达到混合时间减少65.5%;不同喷嘴之间的拉伸率随迹线长度的增大而增大,jet1和jet9位置处的拉伸率与其余喷嘴相比较大;相同喷嘴之间拉伸率随Re的增大而增大,Re=6346、9519和12692的拉伸率与Re=3173相比分别提高289%~320%、418%~454%和607%~667%。     

Artificial Intelligence in Aptamer–Target Binding Prediction

Aptamers are short single-stranded DNA, RNA, or synthetic Xeno nucleic acids (XNA) molecules that can interact with corresponding targets with high affinity. Owing to their unique features, including low cost of production, easy chemical modification, high thermal stability, reproducibility, as well as low levels of immunogenicity and toxicity, aptamers can be used as an alternative to antibodies in diagnostics and therapeutics. Systematic evolution of ligands by exponential enrichment (SELEX), an experimental approach for aptamer screening, allows the selection and identification of in vitro aptamers with high affinity and specificity. However, the SELEX process is time consuming and characterization of the representative aptamer candidates from SELEX is rather laborious. Artificial intelligence (AI) could help to rapidly identify the potential aptamer candidates from a vast number of sequences. This review discusses the advancements of AI pipelines/methods, including structure-based and machine/deep learning-based methods, for predicting the binding ability of aptamers to targets. Structure-based methods are the most used in computer-aided drug design. For this part, we review the secondary and tertiary structure prediction methods for aptamers, molecular docking, as well as molecular dynamic simulation methods for aptamer–target binding. We also performed analysis to compare the accuracy of different secondary and tertiary structure prediction methods for aptamers. On the other hand, advanced machine-/deep-learning models have witnessed successes in predicting the binding abilities between targets and ligands in drug discovery and thus potentially offer a robust and accurate approach to predict the binding between aptamers and targets. The research utilizing machine-/deep-learning techniques for prediction of aptamer–target binding is limited currently. Therefore, perspectives for models, algorithms, and implementation strategies of machine/deep learning-based methods are discussed. This review could facilitate the development and application of high-throughput and less laborious in silico methods in aptamer selection and characterization.     

炭黑在橡胶中分散技术研究进展

对于炭黑补强橡胶复合材料,平衡生热、补强以及磨耗之间的关系是炭黑应用的瓶颈问题。炭黑在橡胶基体中的分散性是影响其补强的关键因素之一,从增强炭黑与橡胶之间的相互作用角度出发,炭黑在橡胶中分散技术的研究进展主要体现在炭黑改性、橡胶改性以及液相复合技术方面。重点阐述炭黑的表面改性、聚合物基体的功能化改性以及炭黑与橡胶湿法混炼制备母胶,旨在促进炭黑在橡胶中均匀纳米分散,提高炭黑对橡胶的补强作用,获得性能优异的炭黑/橡胶复合材料。     

沸石对海水拌合超高性能混凝土性能的影响

利用沸石部分或完全(体积分数为0%、50%、100%)取代海水拌合超高性能混凝土(UHPC)中的河砂,对比研究了沸石对海水拌合UHPC宏观和微观性能的影响。结果表明,海水拌合促进UHPC的水化,从而缩短UHPC的凝结时间,提高UHPC的抗压强度和自收缩,而沸石吸收氯离子会抑制氯离子的加速水化作用,使海水拌合UHPC的凝结时间延长,抗压强度降低。此外,沸石的内养护作用可以有效改善海水拌合UHPC的自收缩,且效果比在淡水拌合UHPC中更好,这主要是因为沸石在海水拌合UHPC中释水的时间更早且更长。由于多孔沸石的强度低于河砂,所以UHPC的早期抗压强度随着沸石含量的增多而逐渐降低,养护至28 d后,沸石的内养护作用优化了界面过渡区,从而促使后期硬化浆体进一步密实。     

超声波湿法混炼炭黑/天然橡胶复合材料的性能研究

利用超声波的乳化均质作用,将经水湿润的炭黑与稀释的天然胶乳混合均匀,然后采用蒸发成膜法和胶凝成膜法制备胶膜(炭黑/天然橡胶复合材料),探究制膜方法及超声波处理时间和功率对胶膜性能的影响。结果表明:蒸发成膜法成膜时间过长,打开的炭黑二次结构重新团聚,胶膜中炭黑分散性差,胶膜的拉伸强度较小,而胶凝成膜法稳定性更高,胶膜中炭黑分散性好;超声波处理时间为90 s、功率为840~960 W时,超声波的乳化均质效果最好,炭黑二次结构打开程度更高,此时采用胶凝成膜法制备胶膜,成膜速度快,炭黑来不及团聚,胶膜中炭黑分散性较好和结合橡胶较多,胶膜的拉伸强度较大。     

Chaotic mixing behavior of non-Newtonian fluid intensified by multilayer rigid-flexible impeller induced flow field interface instability

The traditional multilayer rigid impeller has large dead zone for the mixing of pseudoplastic non-Newtonian fluid, stable flow field interface and low mixing efficiency. A method for enhancing the chaotic mixing of non-Newtonian fluid by multilayer rigid-flexible impeller induced flow field interface instability was proposed. In the experiment, sodium carboxymethylcellulose was used as the non-Newtonian fluid system. The power characteristics were measured by the torque sensor. The mixing time was determined by the acid-base neutralization and decolorization method. The largest Lyapunov exponents were calculated by using Matlab software programming. The chaotic characteristics and mixing performance in the mixing process are analyzed. The results show that when the combination mode was RF-(PBTD+PBTD+DT), the impeller arrangement mode θ=60°, and the flexible sheet length installation ratio r=0.8, 1.2, the degree of chaos was higher and the mixing performance was better. Multilayer rigid-flexible impeller can generate multiple spiral flows, and realize the flow field interface instability under the disturbance frequency difference of the flexible sheet between the layers, the stirring dead zone was reduced, and the system enters a chaotic state at a lower speed (when the multilayer rigid-flexible impeller system N>88 r/min, LLE>0; when the multilayer rigid impeller system N>125 r/min, LLE>0). At the same speed, the mixing rate and power per unit volume of the multilayer rigid-flexible combined impeller are higher than that of the multilayer rigid impeller, but the mixing energy per unit volume is approximately the same.     

基于BP神经网络电子评标方法的研究和应用

为了解决招投标中评标环节专家评审法随意性大的问题,针对建设工程的不同特点,对评标内容进行分类剖析.利用人工神经网络的智能识别功能,建立基于神经网络的电子评标方法.结合人工神经网络的自适应功能、良好的容错能力以及非线性数据处理特点,科学地评价多因素建设工程投标方案,使招标商从众多的投标商中选出最佳的中标单位.     

Effect of particle size on flow and mixing in a bladed granular mixer

A number of studies have modeled flow and mixing of granular materials using the discrete element method (DEM). In an attempt to reduce computational costs, many of these DEM studies model particles larger than the actual particle size without investigating the implications of this assumption. Using DEM, the influence of the modeled particle size on flow and mixing in a bladed granular mixer is studied. The predicted flow microdynamics, including mixing rates, are strongly dependent on the particle diameter. The effect of particle size on macroscopic advective flow also is significant, particularly for dilute flow regions. These results suggest that the influence of particle size needs to be taken into consideration when using larger particles in DEM mixing simulations. To guide scale‐up efforts, particle‐size‐based scaling relationships for several key flow measurements are presented. © 2014 American Institute of Chemical Engineers AIChE J, 61: 46–57, 2015     

Modeling segregation of bidisperse granular materials using physical control parameters in the quasi‐2D bounded heap

Quantitatively predicting segregation of size‐disperse granular materials is of potential value in many industrial applications. We consider granular segregation of size‐bidisperse particles in quasi‐2D bounded heaps, a canonical granular flow, using an advection‐diffusion transport equation with an additional term to account for particle segregation. The equation is characterized by two dimensionless parameters that are functions of control parameters (flow rate, system size, and particle sizes) and kinematic parameters (flowing layer depth, diffusion coefficient, and percolation length scale). As the kinematic parameters are usually difficult to measure in practice, their dependence on the control parameters is determined directly from discrete element method simulations. Using these relationships, it is possible to determine which values of the control parameters result in a mixed or segregated heap. The approach used here is broadly applicable to a wide range of other flow geometries and particle systems. © 2015 American Institute of Chemical Engineers AIChE J, 61: 1524–1534, 2015     

SSM一步法炼胶工艺对胎面气孔率的影响

试验研究SSM一步法炼胶工艺对半钢子午线轮胎胎面气孔率的影响。结果表明,与传统胎面四段炼胶工艺相比,SSM一步法炼胶工艺生产的胎面胶料的炭黑分散度等级和分散性指数均较高,胶料的流动性提高,物理性能提升,可降低挤出胎面的断面气孔率,最终提升成品轮胎的胎面稳定性、外观质量及耐磨性能。