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Significantly Improving the Durability of Single-Chamber Solid Oxide Fuel Cells: A Highly Active CO₂-Resistant Perovskite Cathode

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ACS Applied Energy Materials 2018年第3期1卷 1337-1343页

作者： Zhang, Yuan Gao, Xuechao Sunarso, Jaka Liu, Bo Zhou, Wei Ni, Meng Shao, Zongping Jiangsu National Synergetic Innovation Center for Advanced Materials (SICAM) State Key Laboratory of Materials-Oriented Chemical Engineering Nanjing Tech University Nanjinga 210009 China College of Chemical Engineering Nanjing Tech University Nanjing 210009 China Research Centre for Sustainable Technologies Faculty of Engineering Computing and Science Swinburne University of Technology Jalan Simpang Tiga Kuching Sarawak 93350 Malaysia Department of Building and Real Estate Hong Kong Polytechnic University Hung Hom Kowloon Hong Kong 999077 Hong Kong Department of Chemical Engineering Curtin University Perth 6845 WA Australia

The single-chamber solid oxide fuel cell (SC-SOFC) represents an attractive alternative to batteries for micropower applications given its simplified stack design, easy gas management, lower operation temperature, and quicker start-up. Its stable operation over long duration relies on the availability of CO₂-resistant cathode materials with high oxygen reduction reaction (ORR) activity. Here, we reported a novel perovskite oxide cathode SrSc_0.075Ta_0.025Fe_0.9O_3-δ (SSTF75), which provides CO₂ resistance and high ORR activity. A peak power density of 1430 mW cm^-2 was achieved with the SSTF75/Sm_0.2Ce_0.8O_1.9 cathode at 650 °C with a methane and oxygen gas mixture (1:1 v/v ratio). It retained stable voltage performance at 600 °C for an over 90 h duration when discharged at a current density of 1000 mA cm^-2. This work not only represents an advancing step in the SC-SOFC field but also authenticates an effective codoping strategy for the design of a CO₂-resistant cathode for low-temperature applications. © 2018 American Chemical Society.

关键词： cathode oxygen reduction reaction perovskite single-chamber SOFC solid oxide fuel cells

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Mixed protonic-electronic conducting perovskite oxide as a robust oxygen evolution reaction catalyst

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Electrochimica Acta 2018年 282卷 324-330页

作者： Liu, Hong Yu, Jie Sunarso, Jaka Zhou, Chuan Liu, Bo Shen, Yujuan Zhou, Wei Shao, Zongping Jiangsu National Synergetic Innovation Center for Advanced Materials (SICAM) No. 5 Xinmofan Road Nanjing 210009 China State Key Laboratory of Materials-Oriented Chemical Engineering Nanjing Tech University No. 5 Xinmofan Road Nanjing 210009 China College of Chemical Engineering Nanjing Tech University No. 5 Xinmofan Road Nanjing 210009 China Research Centre for Sustainable Technologies Faculty of Engineering Computing and Science Swinburne University of Technology Jalan Simpang Tiga Kuching 93350 Sarawak Malaysia Department of Chemical Engineering Curtin University Perth 6845 Western Australia Australia

Large-scale utilization of hydro, solar, or wind-based electrochemical water splitting relies on the availability of low cost, highly active oxygen evolution reaction (OER) catalyst. Transition metal-containing perovskite oxide is attractive in this regard. The OER on such perovskite oxide in an alkaline solution is nonetheless often limited by proton transfer step. To overcome such limitation, here we apply mixed protonic-electronic conductor BaCo_0.8-xFe_xZr_0.1Y_0.1O₃ (x = 0, 0.2, and 0.4) as an OER catalyst. Among these three, BaCo_0.8Zr_0.1Y_0.1O₃ (BC_0.8ZY) in particular shows the lowest OER overpotential, the lowest Tafel slope, the highest OER mass activity, and the highest OER specific activity, which surpass those of Ba_0.5Sr_0.5Co_0.8Fe_0.2O_3-δ (BSCF) benchmark. Using O₂-temperature programmed desorption, impedance spectroscopy, and O1s X-ray photoelectron spectroscopy, we attribute such superior OER performance to the highest oxygen desorption capacity, the lowest charge transfer resistance, and the highest hydroxide species content for BC_0.8ZY. We also demonstrate that the OER current of BC_0.8ZY exhibits a first-reaction order dependence to the solution pH between 12.5 and 14, which confirms its proton transfer rate-determining step. © 2018 Elsevier Ltd

关键词： Electrocatalysts Electrolysis Oxygen evolution reaction Perovskite

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New Phosphorus-Doped Perovskite Oxide as an Oxygen Reduction Reaction Electrocatalyst in an Alkaline Solution

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Chemistry - A European Journal 2018年第27期24卷 6950-6957页

作者： Shen, Yujuan Zhu, Yinlong Sunarso, Jaka Guan, Daqin Liu, Bo Liu, Hong Zhou, Wei Shao, Zongping Jiangsu National Synergetic Innovation Center for Advanced Materials (SICAM) No. 5 Xin Mofan Road Nanjing 210009 China State Key Laboratory of Materials-Oriented Chemical Engineering Nanjing Tech University No.5 Xin Mofan Road Nanjing 210009 China College of Chemical Engineering Nanjing Tech University No. 5 Xin Mofan Road Nanjing 210009 China Research Centre for Sustainable Technologies Faculty of Engineering Computing and Science Swinburne University of Technology Jalan Simpang Tiga Kuching Sarawak 93350 Malaysia Department of Chemical Engineering Curtin University Perth 6845 WA Australia

Because of their structural and compositional flexibility, perovskite oxides represent an attractive alternative electrocatalyst class to precious metals for the oxygen reduction reaction (ORR);an important reaction in fuel cells and metal–air batteries. Partial replacement of the original metal cation with another cation, namely, doping, can be used to tailor the ORR activity of perovskite, for which a metal has been exclusively used as the dopant component in the past. Herein, phosphorus is proposed as a non-metal dopant for the cation site to develop a new perovskite family with the formula of La_0.8Sr_0.2Mn_1−xP_xO_3−δ (x=0, 0.02, 0.05, and 0.1;denoted as LSM, LSMP0.02, LSMP0.05, and LSMP0.1, respectively). Powder XRD patterns reveal that the solubility of phosphorus in the perovskite structure is around 0.05. Rotating ring-disk electrode experiments in the form of linear-sweep voltammetry scans demonstrated the best ORR performance for LSMP0.05, and also revealed close to a four-electron ORR pathway for all four compositions. A chronoamperometric test (9000 s) and 500 cycle accelerated durability test demonstrated higher durability for LSMP0.05 relative to that of LSM and the commercial 20 wt % Pt/C catalyst. The higher ORR activity for LSMP0.05 is attributed to the optimised average valence of Mn, as evidenced by combined X-ray photoelectron spectroscopy and soft X-ray absorption spectroscopy data. Doping phosphorus into perovskites is an effective way to develop high-performance electrocatalysts for ORR. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

关键词： cations doping electrochemistry perovskite phases phosphorus

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Network Coordinate System using Non-negative Matrix Factorization based on KL Divergence

Network Coordinate System using Non-negative Matrix Factoriz...

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International Conference on advanced Communication Technology

作者： Lixiang Chai Xiangyang Luo Fan Zhao Mingyue Li Siqi Liu The State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Information Science and Technology Institute Zhengzhou China

ISBN: (纸本)9781509048922

Network coordinate is used to predict the network delay between the network nodes, for the problem that the accuracy of predicting the network delay of the network coordinate system based on non-negative matrix factorization is low, proposing a new network coordinate system using non-negative matrix factorization based on KL divergence (KL-NMF). First, the advantages and disadvantages of classical algorithm for delay prediction of network coordinate system based on matrix factorization are analysed. Then, according to the characteristics of network link delay distributions, proposed a new network coordinate system based on KL-NMF algorithm and the algorithm flow. Experiment based on the four commonly used network delay matrix data set, and the results show that compared to the existing delay prediction algorithm based on NMF network coordinate system, the delay prediction algorithm based on KL-NMF network coordinate system not only reduce the error to reproduce delay matrix, but also improve the network node delay prediction accuracy.

关键词： Network Coordinate Non-negative Matrix Factorization KL Divergence Link Delay Distribution Node Delay Prediction

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Thermal generation, manipulation and detection of skyrmions

arXiv

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arXiv 2020年

作者： Wang, Zidong Guo, Minghua Zhou, Heng-An Zhao, Le Xu, Teng Tomasello, Riccardo Bai, Hao Dong, Yiqing Je, Soong Geun Chao, Weilun Han, Hee-Sung Lee, Suseok Lee, Ki-Suk Yao, Yunyan Han, Wei Song, Cheng Wu, Huaqiang Carpentieri, Mario Finocchio, Giovanni Im, Mi-Young Lin, Shi-Zeng Jiang, Wanjun State Key Laboratory of Low-Dimensional Quantum Physics Department of Physics Tsinghua University Beijing100084 China Frontier Science Center for Quantum Information Tsinghua University Beijing100084 China Institute of Microelectronics Tsinghua University Beijing100084 China Institute of Applied and Computational Mathematics FORTH Heraklion-CreteGR-70013 Greece Center for X-ray Optics Advanced Light Source Lawrence Berkeley National Laboratory Cyclotron Road BerkeleyCA94720 United States Department of Physics Chonnam National University Gwangju61186 Korea Republic of School of Materials Science and Engineering Ulsan National Institute of Science and Technology Ulsan44919 Korea Republic of Daegu Gyeongbuk Institute of Science and Technology Daegu711-873 Korea Republic of International Center for Quantum Materials School of Physics Peking University Beijing100871 China School of Materials Science and Engineering Tsinghua University Beijing100084 China Department of Electrical and Information Engineering Polytechnic of Bari Bari70125 Italy Department of Mathematical and Computer Sciences Physical Sciences and Earth Sciences University of Messina Messina98166 Italy Theoretical Division T-4 and CNLS Los Alamos National Laboratory Los AlamosNM87545 United States

Recent years have witnessed significant progresses in realizing skyrmions in chiral magnets1-4 and asymmetric magnetic multilayers5-13, as well as their electrical manipulation2,7,8,10. Equally important, thermal generation, manipulation and detection of skyrmions can be exploited for prototypical new architecture with integrated computation14 and energy harvesting15. It has yet to verify if skyrmions can be purely generated by heating16,17, and if their resultant direction of motion driven by temperature gradients follows the diffusion or, oppositely, the magnonic spin torque17-21. Here, we address these important issues in microstructured devices made of multilayers - [Ta/CoFeB/MgO]15, [Pt/CoFeB/MgO/Ta]15 and [Pt/Co/Ta]15 integrated with on-chip heaters, by using a full-field soft X-ray microscopy. The thermal generation of densely packed skyrmions is attributed to the low energy barrier at the device edge, together with the thermally induced morphological transition from stripe domains to skyrmions. The unidirectional diffusion of skyrmions from the hot region towards the cold region is experimentally observed. It can be theoretically explained by the combined contribution from repulsive forces between skyrmions, and thermal spin-orbit torques in competing with magnonic spin torques17,18,20,21 and entropic forces22. These thermally generated skyrmions can be further electrically detected by measuring the accompanied anomalous Nernst voltages23. The on-chip thermoelectric generation, manipulation and detection of skyrmions could open another exciting avenue for enabling skyrmionics, and promote interdisciplinary studies among spin caloritronics15, magnonics24 and skyrmionics3,4,12. Copyright © 2020, The Authors. All rights reserved.

关键词： Energy harvesting

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Observing geometry of quantum states in a three-level system

arXiv

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arXiv 2019年

作者： Xie, Jie Zhang, Aonan Cao, Ningping Xu, Huichao Zheng, Kaimin Poon, Yiu-Tung Sze, Nung-Sing Xu, Ping Zeng, Bei Zhang, Lijian National Laboratory of Solid State Microstructures College of Engineering and Applied Sciences School of Physics Nanjing University Nanjing210093 China Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing210093 China Center for Quantum Computing Peng Cheng Laboratory Shenzhen518055 China Department of Mathematics & Statistics University of Guelph GuelphONN1G 2W1 Canada Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada Department of Mathematics Iowa State University AmesIA50011 United States Department of Applied Mathematics Hong Kong Polytechnic University Hong Kong Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha410073 China Department of Physics Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong

Geometric characters of physical objects greatly facilitate our understanding of the world. Along with the founding of quantum mechanics, of particular interest is the geometry of quantum systems from which many non-classical behaviors arise and exotic properties of the system can be inferred. However, there is always the difficulty to illustrate geometry of quantum systems beyond the simplest quantum bit model. One approach is to project the state space of quantum systems to the familiar Euclidean space via measurements of observables on the system. Here we report the first experiment measuring the geometry of such projections beyond one quantum bit. Specifically, we observe the joint numerical ranges of a triple of observables in a three-level photonic system, providing complete classification of the geometric objects. We further show that the geometry of different classes reveals ground-state degeneracies of corresponding Hamiltonians, which is related to quantum phases in the thermodynamic limit. Our results offer a versatile geometric approach for exploring and utilizing the higher dimensional quantum systems. Copyright © 2019, The Authors. All rights reserved.

关键词： Quantum optics

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Optimal verification and fidelity estimation of maximally entangled states

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Physical Review A 2019年第5期99卷 052346-052346页

作者： Huangjun Zhu Masahito Hayashi Department of Physics and Center for Field Theory and Particle Physics Fudan University Shanghai 200433 China State Key Laboratory of Surface Physics Fudan University Shanghai 200433 China Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai 200433 China Collaborative Innovation Center of Advanced Microstructures Nanjing 210093 China Graduate School of Mathematics Nagoya University Nagoya 464-8602 Japan Shenzhen Institute for Quantum Science and Engineering Southern University of Science and Technology Shenzhen 518055 China Centre for Quantum Technologies National University of Singapore 3 Science Drive 2 117542 Singapore

We study the verification of maximally entangled states by virtue of the simplest measurement settings: local projective measurements without adaption. We show that optimal protocols are in one-to-one correspondence with complex projective 2-designs constructed from orthonormal bases. Optimal protocols with minimal measurement settings are in one-to-one correspondence with complete sets of mutually unbiased bases. Based on this observation, optimal protocols are constructed explicitly for any local dimension, which can also be applied to estimating the fidelity with the target state and to detecting entanglement. In addition, we show that incomplete sets of mutually unbiased bases are optimal for verifying maximally entangled states when the number of measurement settings is restricted. Moreover, we construct optimal protocols for the adversarial scenario in which state preparation is not trusted. The number of tests has the same scaling behavior as the counterpart for the nonadversarial scenario; the overhead is no more than three times. We also show that the entanglement of the maximally entangled state can be certified with any given significance level using only one test as long as the local dimension is large enough.

关键词： Quantum entanglement Quantum tomography

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Corrigendum to “Performance test of the electromagnetic particle detectors for the LHAASO experiment” [Nucl. Instrum. Methods Phys. Res. A 1001 (2021) 165193]

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Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 2022年 1022卷

作者： F. Aharonian Q. An Axikegu L.X. Bai Y.X. Bai Y.W. Bao D. Bastieri X.J. Bi Y.J. Bi H. Cai J.T. Cai Z. Cao J. Chang J.F. Chang X.C. Chang B.M. Chen J. Chen X. Zuo University of Chinese Academy of Sciences 100049 Beijing China Department of Engineering Physics Tsinghua University 100084 Beijing China Dublin Institute for Advanced Studies 31 Fitzwilliam Place 2 Dublin Ireland National Astronomical Observatories Chinese Academy of Sciences 100101 Beijing China Max–Planck-Institut for Nuclear Physics P.O. Box 103980 69029 Heidelberg Germany State Key Laboratory of Particle Detection and Electronics China University of Science and Technology of China 230026 Hefei Anhui China School of Physical Science and Technology & School of Information Science and Technology Southwest Jiaotong University 610031 Chengdu Sichuan China Key Laboratory of Particle Astrophysics & Experimental Physics Division & Computing Center Institute of High Energy Physics Chinese Academy of Sciences 100049 Beijing China College of Physics Sichuan University 610065 Chengdu Sichuan China TIANFU Cosmic Ray Research Center Chengdu Sichuan China School of Astronomy and Space Science Nanjing University 210023 Nanjing Jiangsu China Center for Astrophysics Guangzhou University 510006 Guangzhou Guangdong China School of Physics and Technology Wuhan University 430072 Wuhan Hubei China Key Laboratory of Dark Matter and Space Astronomy Purple Mountain Observatory Chinese Academy of Sciences 210023 Nanjing Jiangsu China Hebei Normal University 050024 Shijiazhuang Hebei China

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Understanding adversarial attacks on deep learning based medical image analysis systems

arXiv

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arXiv 2019年

作者： Ma, Xingjun Niu, Yuhao Gu, Lin Wang, Yisen Zhao, Yitian Bailey, James Lu, Feng State Key Laboratory of VR Technology and Systems School of CSE Beihang University Beijing China School of Computing and Information Systems The University of Melbourne ParkvilleVIC3010 Australia Beijing Advanced Innovation Center for Big Data-Based Precision Medicine Beihang University Beijing China National Institute of Informatics Tokyo101-8430 Japan Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Cixi Instuitue of Biomedical Engineering Ningbo Institute of Industrial Technology Chinese Academy of Sciences Ningbo China

Deep neural networks (DNNs) have become popular for medical image analysis tasks like cancer diagnosis and lesion detection. However, a recent study demonstrates that medical deep learning systems can be compromised by carefully-engineered adversarial examples/attacks with small imperceptible perturbations. This raises safety concerns about the deployment of these systems in clinical settings. In this paper, we provide a deeper understanding of adversarial examples in the context of medical images. We find that medical DNN models can be more vulnerable to adversarial attacks compared to models for natural images, according to two different viewpoints. Surprisingly, we also find that medical adversarial attacks can be easily detected, i.e., simple detectors can achieve over 98% detection AUC against state-of-the-art attacks, due to fundamental feature differences compared to normal examples. We believe these findings may be a useful basis to approach the design of more explainable and secure medical deep learning systems. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep neural networks

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Attentive relational networks for mapping images to scene graphs

arXiv

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arXiv 2018年

作者： Qi, Mengshi Li, Weijian Yang, Zhengyuan Wang, Yunhong Luo, Jiebo State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University China Beijing Advanced Innovation Center for Big Data and Brain Computing Department of Computer Science University of Rochester United States

Scene graph generation refers to the task of automatically mapping an image into a semantic structural graph, which requires correctly labeling each extracted object and their interaction relationships. Despite the recent success in object detection using deep learning techniques, inferring complex contextual relationships and structured graph representations from visual data remains a challenging topic. In this study, we propose a novel Attentive Relational Network that consists of two key modules with an object detection backbone to approach this problem. The first module is a semantic transformation module utilized to capture semantic embedded relation features, by translating visual features and linguistic features into a common semantic space. The other module is a graph self-attention module introduced to embed a joint graph representation through assigning various importance weights to neighboring nodes. Finally, accurate scene graphs are produced by the relation inference module to recognize all entities and the corresponding relations. We evaluate our proposed method on the widely-adopted Visual Genome Dataset, and the results demonstrate the effectiveness and superiority of our model. Copyright © 2018, The Authors. All rights reserved.

关键词： Semantics

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