http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Xia Lv,Xueqin Li,Lu Huang,Siyuan Ding,Yin Lv,Jinli Zhang 한국화학공학회 2022 Korean Journal of Chemical Engineering Vol.39 No.3
Pebax® MH 1657 (Pebax)-based blend membranes with different polyether-amine (PEA) loadings were designed and fabricated for efficient CO2 separation. The CO2 separation performance of Pebax/PEA blend membranes was greatly improved in comparison with that of pure membranes. This was mainly because the introduced PEA tailored the physical and chemical microenvironments in blend membranes. Specifically, PEA was a liquid-like additive, which was beneficial to reduce the mass transfer resistance of gases and increase CO2 permeability. Meanwhile, PEA contained amino groups that acted as mobile carriers to tailor the chemical microenvironment in blend membranes. The mobile carriers preferentially reacted reversibly with CO2 molecules, facilitating CO2 transport in membranes. Compared with CO2/CH4 separation performance of pure Pebax membrane, CO2 permeability and CO2/CH4 separation factor of Pebax/PEA-3 increased by 144.8% and 29.4%, respectively. This study suggests that PEA is a promising membrane material for tailoring the physical and chemical microenvironments in blend membranes for efficient CO2 separation.
Microgrid Fault Diagnosis Based on Whale Algorithm Optimizing Extreme Learning Machine
Wu Zhongqiang,Lu Xueqin 대한전기학회 2024 Journal of Electrical Engineering & Technology Vol.19 No.3
A microgrid fault diagnosis method based on whale algorithm optimizing extreme learning machine (ELM) is proposed. Firstly, the three-phase fault voltage is analyzed by wavelet packet decomposition, and the feature vector composed of wavelet packet energy entropy is calculated as data samples. Then, a whale algorithm is used to optimize the extreme learning machine to establish a diagnostic model to identify and diagnose the fault type of microgrid. The whale algorithm has the characteristics of simple parameter setting, fast learning speed, and strong global optimization ability. The whale algorithm is used to optimize the input weights and hidden layer neuron thresholds of the extreme learning machine, which solves the problem that the random initialization of the input weights and hidden layer neuron thresholds easily afects the network performance, which can further improve the learning speed and generalization ability of the network, and beneft to global optimization. Simulation results show that compared with BP neural network, RBF neural network and ELM, the fault diagnosis model based on whale algorithm optimization extreme learning machine has faster learning speed, stronger generalization ability and higher recognition accuracy
Construction of amphiphilic networks in blend membranes for CO2 separation
Jiangnan Wang,Xia Lv,Lu Huang,Long Li,Xueqin Li,Jinli Zhang 한국화학공학회 2023 Korean Journal of Chemical Engineering Vol.40 No.1
Blend membranes have attracted great attention because they can combine the advantages of different polymers. To investigate the effect of amphiphilic polymer on the separation performance of blend membranes, a series of blend membranes were designed and fabricated by blending an amphiphilic polymer of poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) into poly(ether-block-amide) (Pebax) polymer for CO2 separation. For the as-prepared Pebax/PEDOT:PSS blend membranes, the interconnected CO2-philic networks were constructed by hydrophilic anionic chains of PSS− for accelerating CO2 transport. Meanwhile, non-CO2-philic networks were constructed by the hydrophobic cationic chains of PEDOT+, which distributed around the PSS− chains to provide low friction diffusion for CO2. Therefore, the amphiphilic polymer of PEDOT:PSS was an excellent material for improving CO2 separation performance of blend membranes. The results showed that the Pebax/PEDOT:PSS blend membranes were endowed with excellent CO2 separation performance. Pebax/PEDOT:PSS blend membrane demonstrated the optimal separation performance with a CO2 permeability of 440.2±3.3 Barrer and a CO2/CH4 separation factor of 28±0.6. This study indicates that introducing the amphiphilic polymer into the blend membranes is an efficient strategy for gas separation.