Surface modification of cellulose nanocrystals towards new materials development

Cellulose nanocrystals (CNCs) are a kind of sustainable nanoparticle from biomass, which are widely used as reinforcing filler and assembly building block for high-performance composites and function materials including biomaterial, optics, and so forth. Here, their unique advantages in material applications were reviewed based on their rod-like morphology, crystalline structure, dimension-related effects, and multi-level order structure. Then, we focused on the molecular engineering of CNCs, including the structure and physicochemical properties of their surface, along with surface modification methods and steric effects. We further discussed the performance-improvement and functionalization methods based on multi-component complex systems, together with the effects of surface molecular engineering on the performance and functions. Meanwhile, methods of optimizing orientation in uniaxial arrays were discussed along with those of enhancing photoluminescence efficiency via surface chemical modification and substance coordination. In the end, we prospected the design, development, and construction methods of new CNCs materials.     

5G-oriented Virtual Augmented Reality Scene Construction and Business Information Flow Demonstration

Mobile Networks and Applications - Aiming at the problems of large data volume, long calculation time, and information feedback speed in traditional virtual augmented reality-based scenes, this...     

Using “intercalation bridging” to effectively improve the electrothermal properties of sheet graphite / ultrafine carbon powder conductive paste for screen printing

Electrothermal materials can easily and controllably convert electric energy into heat energy, and are widely used in many electrothermal fields. In this paper, a series of conductive pastes were simply prepared by ball milling, and their rheological and electrothermal properties were studied. Phenolic resin was used as curing agent of epoxy resin and rheological modifier, which could make the paste have very good printing applicability. Ultrafine carbon(UC) powder has excellent dispersion effect. Sheet carbon materials such as graphite powder(GP), graphite nanosheet(GS) and graphene(GE) would improve the performance of paste using only UC as conductive filler. It was proved that GE with the smallest thickness has the most obvious lifting effect. UC was gathered around the graphene sheet, as a bridge between graphene sheets. GE could also be connected with each other to build a more effective and denser conductive path. The electrothermal film could reach 199°C under 30 V voltage, increasing by 254.7% compared with the electrothermal film with only UC as conductive filler. The electrothermal film had a short response time, good recyclability and excellent flexibility. The electrothermal film also had certain electromagnetic shielding efficiency. The electromagnetic shielding efficiency SE could reach about 20 dB at 30–1500 MHz, and the ratio of field strength before and after attenuation SE_% could reach 97%?+?. This electrothermal film has simple preparation process, good printing applicability, controllable film resistance, excellent flexibility, fast response speed and good recyclability. It is suitable for large-scale preparation and has broad application prospects in many scenarios.

     

Atomistic insight into the lubrication of glycerol aqueous solution: The role of the solid interface-induced microstructure of fluid molecules

Molecular dynamics simulations are performed to investigate the solid surface-induced microstructure and friction coefficient of glycerol aqueous solutions with different water contents confined in graphene and FeO nanoslits. Results show that the friction coefficient of glycerol aqueous solutions confined in both nanoslits presents similar nonlinear variation tendencies with increasing water content, but their lowest value and the corresponding water contents differ. Distinctive microstructures of the near-surface liquid layer induced by surfaces with different hydrophilicity are responsible for their difference in lubrication. The sliding primarily occurs at the solid–liquid interface for the hydrophobic graphene nanoslit owing to almost the same velocity difference in fluid molecules. By contrast, the sliding mainly occurs at the liquid–liquid interface for the hydrophilic FeO nanoslit because of the large velocity difference in fluid molecules. The weaker the interaction force at the sliding position, the lower the friction coefficient.     

Anthocyanin-fortified konjac glucomannan/sodium alginate composite edible boba: characteristics of texture,microstructure, in vitro release behaviour and antioxidant capacity

Konjac glucomannan/sodium alginate composite edible boba (KGM/SA-boba) with good taste is very popular in China, and it is an outstanding carrier for health potential ingredients. In this work, KGM/SA-boba were fortified with 0.25, 0.50, 0.75 and 1.00% purple sweet potato anthocyanin (PSPA), then characterised by the water distribution, texture, microstructure, in vitro release property of PSPA and antioxidant capacity. LF-NMR analysis demonstrated that the free water of KGM/SA-boba could transfer to tightly bound water with the addition of PSPA that made it with better water-binding ability, higher springiness and lower hardness. And the results of SEM and rheology showed that PSPA could stabilise the microstructure of KGM/SA-boba by forming more amorphous regions and hydrogen bonds proved by the results of DSC and FT-IR. Furthermore, 50% of PSPA in PSPA-fortified KGM/SA-boba can be released at the first hour in a simulated gastrointestinal environment. And the scavenging capacity of DPPH and ABTS of the PSPA-fortified KGM/SA-boba after digestion was higher than that of PSPA alone. Generally, PSPA could improve the texture while KGM/SA-boba in turn would make PSPA more stable in the gastrointestinal digestive system.     

CDBN‑IKELM的轴承变工况故障诊断方法

针对现有方法在轴承变工况方面存在的诊断精度低、人工提取特征不充分等问题，提出了基于卷积深度置信网络（convolutional deep belief network，简称CDBN）与改进核极限学习机 （improved Kernel?based extreme learning machine，简称IKELM）的滚动轴承故障智能识别方法。首先，由卷积深度置信网络对原始信号内的故障特征进行深层自适应提取；其次，利用等距特征映射对提取的多维特征进行降维，去除冗余特征信息；然后，采用改进的核极限学习机对特征进行分类，使用粒子群（particle swarm optimization， 简称PSO）对模型重要参数进行优化，实现滚动轴承变工况下的故障识别；最后，将所提方法应用于不同工况下多种轴承故障的诊断。实验结果表明，该方法能够智能有效地识别变工况的轴承故障，诊断结果优于已有的智能故障诊断方法。