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Controlled synthesis of single cobalt atom catalysts via a facile one-pot pyrolysis for efficient oxygen reduction and hydrogen evolution reactions

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Science Bulletin 2019年第15期64卷 1095-1102页

作者： Yao Wang Linhui Chen zhanxin mao Lishan Peng Rui Xiang Xianyi Tang Jianghai Deng Zidong Wei Qiang Liao Chongqing Key Laboratory of Chemical Process for Clean Energy and Resource Utilization College of Chemistry and Chemical Engineering.Chongqing UniversityChongqing400044China Institute of New-Energy and Low-Carbon Technology Sichuan UniversityChengdu610065China Key Laboratory of Low-Grade Energy Utilization Technologies and Systems Chongqing UniversityChongqing400044China

Metal-nitrogen doped carbon catalysts(M-N/C) with abundantly accessible M-Nxsites, particularly single metal atom M-N/C(SAM-N/C), have been developed as a substitute for expensive Pt-based *** catalysts are used to increase the efficiency of otherwise sluggish oxygen reduction reactions(ORR) and hydrogen evolution reactions(HER). However, although the agglomerated metal nanoparticles are usually easy to form, they are very difficult to remove due to the protective surface-coating carbon layers, a factor that significantly hampers SAM-N/C fabrication. Herein, we report a one-step pyrolysis approach to successfully fabricate single cobalt atom Co-N/C(SACo-N/C) by using a Co2+-SCN-coordination compound as the metal precursor. Thanks to the decomposition of Co2+-SCN-compound at lower temperature than that of carbon layer deposition, Co-rich particles grow up to larger ones before carbon layers formation. Even though encapsulated by the carbon layers, it is difficult for the large Co-rich particle to be completely sealed. And thus, it makes the Co atoms possible to escape from incomplete carbon layer, to coordinate with nitrogen atoms, and to form SACo-N/C catalysts. This SACo-N/C exhibits excellent performances for both ORR(half-wave potential of 0.878 V) and HER(overpotential at 10 mA/cm2 of178 m V), and is thus a potential replacement for Pt-based catalysts. When SACo-N/C is integrated into a Zn-O2 battery, battery with high open-circuit voltage(1.536 V) has high peak power density(266 mW/cm2)and large gravimetric energy density(755 mA h/gZn) at current densities of 100 mA/cm2. Thus, we believe that this strategy may offer a new direction for the effective generation of SAM-N/C catalysts.

关键词： Carbon nanocomposites Single-atom catalysts H2 evolution O2 reduction Zn-O2 battery

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面向配用电侧负荷数据的深度端到端超分辨率感知方法

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电力系统自动化 2020年第24期44卷 28-35页

作者：刘国龙赵俊华文福拴毛一汝吴占昕薛禹胜香港中文大学(深圳)理工学院广东省深圳市518172 深圳市大数据研究院广东省深圳市518172 浙江大学电气工程学院浙江省杭州市310027 南瑞集团有限公司(国网电力科学研究院有限公司) 江苏省南京市211106

在智能电网中,精准的数据采集是整个系统安全与经济运行的基础。随着信息与物理系统融合的不断加深,各类大数据应用与实时控制等任务对采集高频数据的要求不断提高。然而,提高数据采样频率必然给系统造成更高的数据通信与存储负担。文... 详细信息

在智能电网中,精准的数据采集是整个系统安全与经济运行的基础。随着信息与物理系统融合的不断加深,各类大数据应用与实时控制等任务对采集高频数据的要求不断提高。然而,提高数据采样频率必然给系统造成更高的数据通信与存储负担。文中提出了一种基于深度学习的超分辨率感知技术,用于从低频采样的传感器数据中恢复精确的高频数据。具体地,提出了一种基于门控循环单元网络的深度端到端超分辨率感知方法,包括特征提取、关系推断、信息重建3个部分。特征提取部分采用一维卷积网络对低频数据进行特征提取;在关系推断部分应用门控循环单元网络对获得的特征进行学习,推断低频数据同高频数据间内在关系;在信息重建部分则使用全连接层对推断信息进行重建,获得对应的高频数据。采用所提方法对居民用户和工业用户功率数据及输电线电压数据进行超分辨率感知,同时使用恢复的高频数据进行负荷状态识别。算例结果表明所提方法能够精准有效地恢复低频数据的丢失信息并提升负荷识别等实际应用的准确性。

关键词：智能电网超分辨率感知深度学习负荷识别配电网

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