Synthesis of Heat-resistant Polymers by Thiol–Ene Reaction of N-Allylmaleimide Copolymers Using Glycoluril Crosslinkers with Rigid Molecular Structures

We carried out the thermal curing of the copolymers of N-allylmaleimide (AMI) and 2-ethylhexyl acrylate (2EHA) using 1,3,4,6-tetra(2-mercaproethyl)glycoluril ( G1 ), 1,3,4,6-tetra(3-mercaptopropyl)glycoluril ( G2 ), 1,3,4,6-tetraallylglycoluril ( G3 ), triallylisocyanurate (TAIC), and pentaerythritol tetrakis(3-mercaptobutyrate) (PEMB) as the crosslinkers. Based on the results for the analysis of thiol–ene reactions monitored by IR spectroscopy, it was confirmed that the curing rate significantly depended on the combination of the used crosslinkers. The insoluble fraction after curing was more than 90% for the systems using the glycoluril crosslinkers, while the conversion of the allyl groups was suppressed due to the rigid structure of these crosslinkers. The heat resistance and the mechanical properties of the crosslinked polymers were investigated by thermogravimetric analysis, differential scanning calorimetry, dynamic mechanical analysis, and mechanical tensile tests. For the products cured using the glycoluril crosslinkers, the glass transition temperature (T_g) and the maximum temperature of thermal decomposition (T_max) were 54–59 °C and 395–409 °C, respectively, being higher than those for the cured product prepared with PEMB and TAIC as the conventional crosslinkers. The elasticity (75–139 MPa), the maximum strength (3.0–4.1 MPa), and the adhesion strength (6.7–10.7 MPa) for the polymers cured with the glycoluril crosslinkers, determined by the mechanical tensile and single lap-shear adhesion tests, were higher than those for cured materials produced with PEMB. Thus, the thermal and mechanical properties of the maleimide copolymers were efficiently enhanced by crosslinking using the rigid glycoluril compounds. © 2020 Wiley Periodicals, Inc. J. Polym. Sci. 2020 , 58, 923–931     

Highly stretchable,self-adhesive,and self-healable double network hydrogel based on alginate/polyacrylamide with tunable mechanical properties

A number of synthetic hydrogels suffer from low mechanical strength. Despite of the recent advances in the fabrication of tough hydrogels, it is still a great challenge to simultaneously construct high stretchability, and self-adhesive and self-healing capability in a hydrogel. Herein, a new type of double network hydrogel was prepared based on irreversible cross-linking of polyacrylamide chains and Schiff-base reversible cross-linking between glycidyl methacrylate-grafted ethylenediamine and oxidized sodium alginate (OSA). The combination of both cross-linkings and their synergistic effect provided a novel hydrogel with high strength, stretchable, rapid self-healing, and self-adhesiveness to different material. Besides, the hydrogels with diverse OSA content could maintain their original shapes after loading–unloading tensile test. The resulting hydrogel has a great potential in various fields for supporting and load-bearing substance.     

A post curing strategy toward the feasible covalent adaptable networks in polyacrylate latex films

The implementation of covalent adaptable networks (CANs) in general resin system is becoming attractive. In this work, we propose a simple post-curing strategy based on the core-shell structured acrylate latex for the achievement on both the improved general performance and the CANs characteristics in latex films. The building to the CANs was relied on the introduction of 4,4′-diaminophenyl disulfide as the curing agent, which cured the acetoacetoxy decorated shell polymer through the ketoamine reaction. The metathesis reaction of aromatic disulfides in the crosslinking segments enabled the thermally induced dynamic behavior of the network as revealed in the stress relaxation tests by comparison with other diamine crosslinking agents without the incorporation of disulfide. The synergism of the dynamic crosslinking of the shell polymer and static crosslinking in the core polymer contributed to the improved mechanical strength (15 MPa, strain% = 250%) and the suppressed water adsorption (~1% in 24 h of soaking) of the latex film, which exhibited above 90% of recovery in both strength and strain from a cut-off film damage within 1 h at 80°C. Moreover, the cured latex film could be recycled, and 75% of the mechanical performance was regained after three fragmentation-hot-pressing cycles. These, in addition with the feasible and environmental friendly characteristics, suggest a sustainable paradigm toward the smart thermosetting latex polymers.     

基于流量测点的热网变动阻力系数优化辨识

随着供热计量系统的普及，系统可以根据负荷的变化进行调整，管网的阻力系数随即发生变化。对变动阻力系数进行优化辨识是了解供热管网实时运行状况的有效手段。提出一种基于流量监测数据的供热管网变动阻力系数优化辨识方法，并利用遗传算法进行求解。对洛阳市某小区供暖季管网实际运行数据进行验证，辨识结果的相对误差在5%以内。结果表明：该方法可以在只有流量观测数据时得到精度较高的供热管网变动阻力系数，为供热系统的运行调节提供指导。     

An artificial hummingbird algorithm based localization with reduced number of reference nodes for wireless sensor networks

Wireless Sensor Networks (WSN) are widely used in recent years due to the advancements in wireless and sensor technologies. Many of these applications require to know the location information of nodes. This information is useful to understand the collected data and to act on them. Existing localization algorithms make use of a few reference nodes for estimating the locations of sensor nodes. But, the positioning and utilization of reference nodes increase the cost and complexity of the network. To reduce the dependency on reference nodes, in this paper, we have developed a novel optimization based localization method using only two reference nodes for the localization of the entire network. This is achieved by reference nodes identifying a few more nodes as reference nodes by the analysis of the connectivity information. The sensor nodes then use the reference nodes to identify their locations in a distributive manner using Artificial Hummingbird Algorithm (AHA). We have observed that the localization performance of the reported algorithm at a lower reference node ratio is comparable with other algorithms at higher reference node ratios.     

Prediction of Concrete Meso-Model Stress-Strain Curves Based on GoogLeNet北大核心CSCD

非均质复合材料的宏观力学性能往往取决于细观组分的分布方式和力学性能，但是建立明确的关系表达式极其困难。为了应对这一挑战，以混凝土为研究对象，提出了一种基于深度学习的策略，能够高效、准确地通过细观模型图像信息获取应力-应变曲线。首先，使用基于卷积神经网络（convolutional neural network，CNN）的GoogLeNet模型进行图像信息识别和提取，并针对应力-应变曲线的复杂性特点，进行了数据预处理操作，并且设计了相应的多任务损失函数。数据集中的细观模型图像采用基于Monte-Carlo的随机骨料模型生成，并且使用数值模拟试验获取对应细观模型的单轴压缩应力-应变曲线。最后，通过对神经网络的训练和测试评估了所提出方法的可行性。结果表明，GoogLeNet模型训练效率和预测精度均优于AlexNet和ResNet模型，具有良好的泛化能力和鲁棒性。     

Design consideration and modelling studies of ultrasound and ultraviolet combined approach for shelf-life enhancement of pine apple juice

Although both ultraviolet (UV) radiation and ultrasound (US) treatment have their capabilities in microbial inactivation, applying any one method alone may require a high dose for complete inactivation, which may affect the sensory and nutritional properties of pineapple juice. Hence, this study was intended to analyse and optimise the effect of combined US and UV treatments on microbial inactivation without affecting the selected quality parameters of pineapple juice. US treatment (33 kHz) was done at three different time intervals, viz. 10 min, 20 min and 30 min., after which, juice samples were subjected to UV treatment for 10 min at three UV dosage levels, viz. 1 J/cm², 1.3 J/cm², and 1.6 J/cm². The samples were evaluated for total colour difference, pH, total soluble solids (TSS), titrable acidity (TA), and ascorbic acid content; total bacterial count and total yeast count; and the standardization of process parameters was done using Response Surface Methodology and Artificial Neural Network. The results showed that the individual, as well as combined treatments, did not significantly impact the physicochemical properties while retaining the quality characteristics. It was observed that combined treatment resulted in 5 log cycle reduction in bacterial and yeast populations while the individual treatment failed. From the optimization studies, it was found that combined US and UV treatments with 22.95 min and1.577 J/cm² ensured a microbiologically safe product while retaining organoleptic quality close to that of fresh juice.     

Highly Sensitive Electrochemical Immunosensor Based on Mesoporous PdPt Nanoparticles Anchored on a Three-dimensional PANI@CNTs Network as Nanozyme Labels

In this study, a novel strategy to amplify electrochemical signals by mesoporous PdPt nanoparticles with core-shell structures anchored on a three-dimensional PANI@CNTs network as nanozyme labels (PdPt/PANI@CNTs) was proposed for the sensitive monitoring of α-fetoprotein (AFP, Ag). First, the mesoporous PdPt nanoparticles prepared by a facile chemical reduction method had excellent biocompatibility with biomolecules, which could capture a large amount of AFP-Ab₂ (Ab₂) and exhibit plentiful pores to entrap more thionine (Thi) into mesoporous PdPt nanoparticles with enhanced loading and abundant active sites. Furthermore, the resulting mesoporous PdPt nanoparticles were abundantly dotted on the surface of a three-dimensional PANI@CNTs network with excellent conductivity and a high specific surface area through the bonding of the amino group to form PdPt/PANI@CNTs nanozyme labels. Most importantly, the as-prepared PdPt/PANI@CNTs nanozyme labels exhibited unexpected enzyme-like activity towards the reduction of hydrogen peroxide owing to the highly indexed facets, enhancing the current response to realize signal amplification. In view of the advantages of nanozyme labels and the involvement of gold nanoparticles (AuNPs, which behave as electrode materials) for the sensitive determination of AFP, the as-developed immunosensor could obtain a dynamic working range of 0.001 ng mL^−1–100.0 ng mL⁻¹ at a detection limit of 0.33 pg mL⁻¹ via DPV (at 3σ). Furthermore, the nanozyme-based electrochemical immunosensor exhibited remarkable analytical performance, which brought about feasible ideas for disease diagnosis in the future.