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RISS 인기검색어
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- 저자 : Chengliang Xiao (검색결과 3 건)
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Lanping Nong,Chengliang Xiao,Wei Jiang 한국화학공학회 2011 Korean Journal of Chemical Engineering Vol.28 No.3
Hydrotalcite (HTC), a typical layered compound, is a promising adsorbent for removal of organic pollutants. To partition azo dye from aqueous solution, Mg-Al HTCs intercalated with dodecanoic acid (DA) modifier, DAHTCs,were prepared by ion exchange and calcination-rehydration methods. The structures of HTCs and DAHTCs were characterized by powder XRD and FT-IR techniques. The introduction of DA broadened the spacing of interlayers and provided more space for ion exchange. The effects of pH value, contact time, adsorbent amount, temperature and different intercalated modifiers on the adsorption of azo dye onto HTCs and DAHTCs were determined. The optimum pH of uptake was around 3.0 and all the lower or higher pH values proved to decrease the adsorption properties. The pseudo-second-order model was found to best describe the adsorption dynamics of all adsorbents. Meanwhile, the size and polarity of intercalated modifiers might be crucial for adsorption of azo dye.
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Correction: The epoxy resin system: function and role of curing agents
Aziz Tariq,Haq Fazal,Farid Arshad,Chengliang Xiao,Chuah Lai Fatt,Bokhari Awais,Mubashir Muhammad,Tang Doris Ying Ying,Show Pau Loke 한국탄소학회 2024 Carbon Letters Vol.34 No.3
Curing agents are critical components of aqueous epoxy resin systems. Unfortunately, its uses and applications are restricted because of its low emulsifying yields. Epoxy resins are frequently used in electrical devices, castings, packaging, adhesive, corrosion resistance, and dip coating. In the presence of curing agents, epoxy resins become rigid and infusible. Eco-friendliness and mechanical functionality have emerged as vulcanization properties. Curing agents are used for surface modification, thermodynamic properties, functional approaches to therapeutic procedures, and recent advances in a variety of fields such as commercial and industrial levels. The curing agent has superior construction and mechanical properties when compared to the commercial one, which suggests that it has the potential for use as the architectural and industrial coatings. The thermal stability of cured products is good due to the presence of the imide group and the hydrogenated phenanthrene ring structure. Over the course of the projection period, it is anticipated that the global market for curing agents will continue to expand at a steady rate. The growth of the market is mainly driven by its expanding range in future applications such as adhesives, composites, construction, electrical, electronics, and wind energy. This review focused on the most recent advancements in curing techniques, emphasizing their thermal and mechanical properties. The review also presents a critical discussion of key aspects and bottleneck or research gap of the application of curing agents in the industrial areas.
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Chengjin Qin,Gang Shi,Jianfeng Tao,Honggan Yu,Yanrui Jin,Dengyu Xiao,Chengliang Liu 제어·로봇·시스템학회 2024 International Journal of Control, Automation, and Vol.22 No.2
During tunneling process, it is of critical importance to dynamically adjust operation parameters of shield machine due to changes of geological conditions. Cutterhead torque is one of the key load parameters, and its accurate prediction could adjust operational parameters including cutterhead rotational speed and tunneling speed in advance and avoid potential cutterhead jamming. Based on operation and state data collected by the monitoring system, we propose a residual-convolutional-LSTM neural network (RCLSTMNet) for forecasting cutter head torque in shield machine. On the basis of correlation analysis, parameters closely related to cutter head torque are selected as inputs by employing cosine similarity, which significantly reduces input dimension. Convolutional-LSTM neural network is fused and constructed for extracting deep useful features, while residual network module is utilized to avoid gradient disappearing and improve regression performance. Comparisons with recent data-driven cutterhead torque prediction methods are made on the actual engineering datasets, which demonstrate the presented RCLSTMNet outperforms the other data driven models in most cases. Moreover, the predicted curves of cutterhead torque using the proposed RCLSTMNet coincide with the actual curves much better than predicted curves using the other models. Meanwhile, the highest and average accuracy of RCLSTMNnet reach 98.1% and 95.6%, respectively.
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