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| 1 | Explicating the Role of Metal Centers in Porphyrin-Based MOFs of PCN-222(M) for Electrochemical Reduction of CO_(2)显示文摘The porphyrin-based MOFs formed by combining Zrclusters and porphyrin carboxylic acids with clear M-Nactive centers show unique advantages in electrocatalytic reduction of CO(CORR). However, its conductivity is still the bottleneck that limits its catalytic activity due to the electrical insulation of the Zr cluster. Therefore, the porphyrin-based MOFs of PCN-222(M)(M = Mn, Co, Ni, Zn) with explicit M-Ncoordination were combined with the highly conductive material carbon nanotube(CNT) for discussing the influence of metal centers on the CORR performance based on theoretical calculations and experimental observations. The results show that the PCN-222(Mn)/CNT, PCN-222(Co)/CNT, and PCN-222(Zn)/CNT all exhibit high selectivity to CO(FECO > 80%) in the range of-0.60 to-0.70 V vs. RHE. The FECOmax of PCN-222(Mn)/CNT(-0.60 V vs. RHE), PCN-222(Co)/CNT(-0.65 V vs. RHE), and PCN-222(Zn)/CNT(-0.70 V vs.RHE) are 88.5%, 89.3% and 92.5%, respectively. The high catalytic activity of PCN-222(Mn)/CNT and PCN-222(Co)/CNT comes from the excellent electron mobility of their porphyrin rings and their low ΔG*COOH(0.87 and 0.58 eV). It reveals that the strength of backbonding π of the transition metal and its influence on the electron mobility in the porphyrin ring can affect its CORR activity. | Mengjie Liu Mengting Peng Baoxia Dong Yunlei Teng Ligang Feng Qiang Xu | 2022 | Chinese Journal of Structural Chemistry2022，41，7： | 1 |
| 2 | Deep Learning Network for Energy Storage Scheduling in Power Market Environment Short-Term Load Forecasting Model显示文摘In the electricity market,fluctuations in real-time prices are unstable,and changes in short-term load are determined by many factors.By studying the timing of charging and discharging,as well as the economic benefits of energy storage in the process of participating in the power market,this paper takes energy storage scheduling as merely one factor affecting short-term power load,which affects short-term load time series along with time-of-use price,holidays,and temperature.A deep learning network is used to predict the short-term load,a convolutional neural network(CNN)is used to extract the features,and a long short-term memory(LSTM)network is used to learn the temporal characteristics of the load value,which can effectively improve prediction accuracy.Taking the load data of a certain region as an example,the CNN-LSTM prediction model is compared with the single LSTM prediction model.The experimental results show that the CNN-LSTM deep learning network with the participation of energy storage in dispatching can have high prediction accuracy for short-term power load forecasting. | Yunlei Zhang RuifengCao Danhuang Dong Sha Peng RuoyunDu Xiaomin Xu | 2022 | Energy Engineering2022，119，5： | 0 |
| 3 | Forecasting time series with optimal neural networks using multi-objective optimization algorithm based on AICc显示文摘In this letter,time series forecasting using optimal neural networks with optimal performance of generalization and stability is studied.After analyzing the reasons for over-fitting and instability of neural networks,in order to find the optimal NNs (neural networks)architecture,we consider minimizing three objective index:average training AICc (ATRAICc),average testing AICc (ATEAICc)and testing error variance AICc (VAAICc)based on Akaike information criterion theory.Then we built a multi-objective optimization model and proved the existence and uniqueness theorem of optimal solution.After determining the searching interval, a multi-objective optimization algorithm for optimal neural network architecture based on AICc (ONNAICc)with optimal generalization and stability is constructed to solve above model. | Muzhou HOU Yunlei YANG Taohua LIU Wenping PENG | 2018 | Frontiers of Computer Science2018，12，6： | 0 |
| 4 | An Empirical Study of the Influence of Migrant Workers' Individual Decisions concerning 'Change from Rural Residents to Urban Residents' in Chongqing City显示文摘This paper,from the city integration perspective,analyzes the main beneficiaries who benefit from the household registration system reform,and studies the influence of individual decisions about the transfer from agriculture to non-agriculture. Based on it,this paper makes an empirical research by using the survey data about migrant workers in Chongqing. The research findings are as follows:( i) The urban employment,the living condition and the rural connection have a significant impact on migrant workers' transfer decision;( ii) If the value of those factors( such as the working stability,the family income,the urban house condition and the urban social security) is higher,then the migrant workers who have no economic interest in rural areas are better able to integrate into the urban areas,therefore the inclination to transfer the household registration from agriculture to non-agriculture will be much stronger. It is proposed that we should do some significant things,such as enhancing the investment of security housing,bringing the migrant workers into the city housing accumulation fund system and giving them prior allocation right,perfecting land elastic exit mechanism,creating a harmonious employment environment,which are important strategies promoting migrant workers to integrate into the urban areas and affecting their individual decision about transferring from agriculture to nonagriculture. | Xiaoyang LI Yunlei PENG Junbo LIU | 2014 | Asian Agricultural Research2014，6，12： | 0 |
| 5 | Metallocorrole-based porous organic polymers as a heterogeneous catalytic nanoplatform for efficient carbon dioxide conversion显示文摘Metallocorrole macrocycles that represent a burgeoning class of attractive metal-complexes from the porphyrinoid family,have attracted great interest in recent years owing to their unique structure and excellent performance revealed in many fields,yet further functionalization through incorporating these motifs into porous nanomaterials employing the bottom-up approach is still scarce and remains synthetically challenging.Here,we report the targeted synthesis of porous organic polymers(POPs)constructed from custom-designed Mn and Fe-corrole complex building units,respectively denoted as CorPOP-1(Mn)and CorPOP-1(FeCl).Specifically,the robust CorPOP-1(Mn)bearing Mn-corrole active centers displays superior heterogeneous catalytic activity toward solvent-free cycloaddition of carbon dioxide(CO_(2))with epoxides to form cyclic carbonates under mild reaction conditions as compared with the homogeneous counterpart.CorPOP-1(Mn)can be easily recycled and does not show significant loss of reactivity after seven successive cycles.This work highlights the potential of metallocorrole-based porous solid catalysts for targeting CO_(2) transformations,and would provide a guide for the task-specific development of more corrole-based multifunctional materials for extended applications. | Yanming Zhao Yunlei Peng Chuan Shan Zhou Lu Lukasz Wojtas Zhenjie Zhang Bao Zhang Yaqing Feng Shengqian Ma | 2022 | Nano Research2022，15，2： | 0 |
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