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Delong Hou,Songhang Wang,Jinming Chang,Zhou Xu,Qi Zeng,Zhonghui Wang,Yongcheng Yang,Jun Yan,Yi Chen 한국섬유공학회 2020 Fibers and polymers Vol.21 No.8
Plasticizers that enable flexible polyvinyl chloride (PVC) are usually combustible, restricting the application ofPVC in fire-prone scenarios. In this context, intrinsically flame-retardant plasticizers displaying dual function continue to bethe focus of intensive research. Despite their efficiency, the majority of these dual-functional plasticizers previously reportedcontain halogen elements, which, once ignited, emanate toxic and potentially carcinogenic substances, along with toxic gasesand smoke, polluting the environment, damaging the biota, and threatening human health. Here, we report a strategy to obtaina halogen-free, intrinsically flame-retardant PVC bio-plasticizer that harnesses the phenolic hydroxyl of naturally occurringcardanol and covalent attachment of an organophosphate moiety. When combined with di-(2-ethylhexyl) phthalate (DOP),the organophosphate-containing cardanol is qualified as a co-plasticizer, while endowing the PVC materials with flameretardancy. Unlike inorganic flame-retardants, the engineered cardanol is compatible with PVC such that the mechanicalproperties of the PVC materials are not compromised. The rationale underlying the present effort may provide guidance fordeveloping sustainable alternatives to halogen-containing plasticizers to address the sustainability challenge now confrontingPVC industry.
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Chen Zexi,Zhang Delong,Jiang Haoran,Wang Longze,Chen Yongcong,Xiao Yang,Liu Jinxin,Zhang Yan,Li Meicheng 대한전기학회 2021 Journal of Electrical Engineering & Technology Vol.16 No.5
With the complete implementation of the “Replacement of Coal with Electricity” policy, electric loads borne by urban power systems have achieved explosive growth. The traditional load forecasting method based on “similar days” only applies to the power systems with stable load levels and fails to show adequate accuracy. Therefore, a novel load forecasting approach based on long short-term memory (LSTM) was proposed in this paper. The structure of LSTM and the procedure are introduced firstly. The following factors have been fully considered in this model: time-series characteristics of electric loads; weather, temperature, and wind force. In addition, an experimental verification was performed for “Replacement of Coal with Electricity” data. The accuracy of load forecasting was elevated from 83.2 to 95%. The results indicate that the model promptly and accurately reveals the load capacity of grid power systems in the real application, which has proved instrumental to early warning and emergency management of power system faults. With the complete implementation of the “Replacement of Coal with Electricity” policy, electric loads borne by urban power systems have achieved explosive growth. The traditional load forecasting method based on “similar days” only applies to the power systems with stable load levels and fails to show adequate accuracy. Therefore, a novel load forecasting approach based on long short-term memory (LSTM) was proposed in this paper. The structure of LSTM and the procedure are introduced fi rstly. The following factors have been fully considered in this model: time-series characteristics of electric loads; weather, temperature, and wind force. In addition, an experimental verifi cation was performed for “Replacement of Coal with Electricity” data. The accuracy of load forecasting was elevated from 83.2 to 95%. The results indicate that the model promptly and accurately reveals the load capacity of grid power systems in the real application, which has proved instrumental to early warning and emergency management of power system faults.
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