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1st International Conference on science of Cyber Security, SciSec 2018

作者： Zhong, Xiang Yang, Lu-Xing Yang, Xiaofan Xiong, Qingyu Wen, Junhao Tang, Yuan Yan School of Big Data and Software Engineering Chongqing University Chongqing400044 China School of Information Technology Deakin University MelbourneVIC3125 Australia Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100083 China Department of Computer and Information Science The University of Macau China

ISBN: (纸本)9783030030254

advanced persistent threat (APT) as a new form of cyber attack has posed a severe threat to modern organizations. When an APT has been detected, the target organization has to develop a response resource allocation strategy to mitigate her potential loss. This paper suggests a risk management approach to solving this APT response problem. First, we present three state evolution models. Thereby we assess the organization’s potential loss. On this basis, we propose two kinds of game-theoretic models of the APT response problem. This work initiates the study of the APT response problem. © Springer Nature Switzerland AG 2018.

关键词： Game theory

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Residual Networks for Light Field Image Super-Resolution

Residual Networks for Light Field Image Super-Resolution

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IEEE/CVF Conference on Computer Vision and Pattern Recognition

作者： Shuo Zhang Youfang Lin Hao Sheng Beijing Key Lab of Traffic Data Analysis and Mining School of Computer and Information Technology Beijing Jiaotong University Key Laboratory of Intelligent Passenger Service of Civil Aviation CAAC State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University

Light field cameras are considered to have many potential applications since angular and spatial information is captured simultaneously. However, the limited spatial resolution has brought lots of difficulties in developing related applications and becomes the main bottleneck of light field cameras. In this paper, a learning-based method using residual convolutional networks is proposed to reconstruct light fields with higher spatial resolution. The view images in one light field are first grouped into different image stacks with consistent sub-pixel offsets and fed into different network branches to implicitly learn inherent corresponding relations. The residual information in different spatial directions is then calculated from each branch and further integrated to supplement high-frequency details for the view image. Finally, a flexible solution is proposed to super-resolve entire light field images with various angular resolutions. Experimental results on synthetic and real-world datasets demonstrate that the proposed method outperforms other state-of-the-art methods by a large margin in both visual and numerical evaluations. Furthermore, the proposed method shows good performances in preserving the inherent epipolar property in light field images.

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Why is the Winner the Best?

Why is the Winner the Best?

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： M. Eisenmann A. Reinke V. Weru M. D. Tizabi F. Isensee T. J. Adler S. Ali V. Andrearczyk M. Aubreville U. Baid S. Bakas N. Balu S. Bano J. Bernal S. Bodenstedt A. Casella V. Cheplygina M. Daum M. De Bruijne A. Depeursinge R. Dorent J. Egger D. G. Ellis S. Engelhardt M. Ganz N. Ghatwary G. Girard P. Godau A. Gupta L. Hansen K. Harada M. Heinrich N. Heller A. Hering A. Huaulmé P. Jannin A. E. Kavur O. Kodym M. Kozubek J. Li H. Li J. Ma C. Martín-Isla B. Menze A. Noble V. Oreiller N. Padoy S. Pati K. Payette T. Rädsch J. Rafael-Patiño V. Singh Bawa S. Speidel C. H. Sudre K. Van Wijnen M. Wagner D. Wei A. Yamlahi M. H. Yap C. Yuan M. Zenk A. Zia D. Zimmerer D. Aydogan B. Bhattarai L. Bloch R. Brüngel J. Cho C. Choi Q. Dou I. Ezhov C. M. Friedrich C. Fuller R. R. Gaire A. Galdran Á. García Faura M. Grammatikopoulou S. Hong M. Jahanifar I. Jang A. Kadkhodamohammadi I. Kang F. Kofler S. Kondo H. Kuijf M. Li M. Luu T. Martinčič P. Morais M. A. Naser B. Oliveira D. Owen S. Pang J. Park S. Park S. Płotka E. Puybareau N. Rajpoot K. Ryu N. Saeed A. Shephard P. Shi D. Štepec R. Subedi G. Tochon H. R. Torres H. Urien J. L. Vilaça K. A. Wahid H. Wang J. Wang L. Wang X. Wang B. Wiestler M. Wodzinski F. Xia J. Xie Z. Xiong S. Yang Y. Yang Z. Zhao K. Maier-Hein P. F. Jäger A. Kopp-Schneider L. Maier-Hein Division of Intelligent Medical Systems German Cancer Research Center (DKFZ) Heidelberg Germany Helmholtz Imaging German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Division of Biostatistics German Cancer Research Center (DKFZ) Heidelberg Germany Division of Medical Image Computing German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Engineering and Physical Sciences School of Computing University of Leeds Leeds UK Institute of Informatics School of Management HES-SO Valais-Wallis University of Applied Sciences and Arts Western Switzerland Sierre Switzerland Department of Nuclear Medicine and Molecular Imaging Lausanne University Hospital Lausanne Switzerland Technische Hochschule Ingolstadt Ingolstadt Germany Center for Artificial Intelligence and Data Science for Integrated Diagnostics (AI2D) and Center for Biomedical Image Computing and Analytics (CBICA) University of Pennsylvania Philadelphia PA USA Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Department of Radiology University of Washington Seattle WA USA Department of Computer Science Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS) University College London London UK Universitat Autònoma de Barcelona & Computer Vision Center Barcelona Spain Division of Translational Surgical Oncology National Center for Tumor Diseases (NCT/UCC) Dresden Dresden Germany Department of Advanced Robotics Istituto Italiano di Tecnologia Italy Department of Electronics Information and Bioengineering Politecnico di Milano Milan Italy IT University of Copenhagen Copenhagen Denmark Department of General Visceral and Transplantation Surgery Heidelberg University Hospital Heidelberg Germany Department of Radiology and Nuc

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really generate scientific progress? What are common and successful participation strategies? What makes a solution superior to a competing method? To address this gap in the literature, we performed a multicenter study with all 80 competitions that were conducted in the scope of IEEE ISBI 2021 and MICCAI 2021. Statistical analyses performed based on comprehensive descriptions of the submitted algorithms linked to their rank as well as the underlying participation strategies revealed common characteristics of winning solutions. These typically include the use of multi-task learning (63%) and/or multi-stage pipelines (61%), and a focus on augmentation (100%), image preprocessing (97%), data curation (79%), and post-processing (66%). The “typical” lead of a winning team is a computer scientist with a doctoral degree, five years of experience in biomedical image analysis, and four years of experience in deep learning. Two core general development strategies stood out for highly-ranked teams: the reflection of the metrics in the method design and the focus on analyzing and handling failure cases. According to the organizers, 43% of the winning algorithms exceeded the state of the art but only 11% completely solved the respective domain problem. The insights of our study could help researchers (1) improve algorithm development strategies when approaching new problems, and (2) focus on open research questions revealed by this work.

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A Survey on Fresh Produce Grading Algorithms Using Machine Learning And Image Processing Techniques

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IOP Conference Series: Materials science and engineering 2020年第4期981卷

作者： Mrs. T K AmeethaJunaina Dr. B Ebenezer Abishek Dr. Vr Rajendren Dr. Shakir Mohammed Dr. P Sathish Kumar Research Student Electronics and Communication Engg. Vels Institute of Science Technology and Advanced Studies Assistant Professor Department of ECE KMCT College of Engineering NITC P.O Kozhikode 673601 Assistant Professor Electronics and Communication Engg. Vels Institute of Science Technology and Advanced Studies Chennai India Electronics and Communication Engg. Vels Institute of Science Technology and Advanced Studies Chennai India Senior Data Scientist White-box Analytics Sydney Australia

Agriculture has been the backbone of the Indian economy. Automation in the agriculture field helps to improve productivity and economic growth. The export market for fresh produce requires fast and reliable fruit and vegetable quality detection techniques. The traditional manual system of quality assessment is a time consuming and tedious task which is more prone to error. The goal of supply-chain management is to add product value by maintaining quality, reduce wastage of fresh produce, retain consumers by keeping customer satisfaction, and increase the profitability. Researches are going on in various domain to develop a fast and reliable automated fruit quality grading system which helps to meet the food value goals of supply-chain. This paper focuses on a detailed survey of the researches being carried out on various techniques used in post-harvest grading of fresh produces using computer vision, image processing and machine learning techniques. Few papers have been reviewed and discussed here pertaining to the above techniques. The advantages and shortcomings of various methods are also mentioned. This comprehensive paper will give researchers a deeper insight to the state of the art technologies in fresh produce grading system.

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Favoring CO Intermediate Stabilization and Protonation by Crown Ether for CO2Electromethanation in Acidic Media

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Angewandte Chemie 2023年第50期135卷

作者： Keqiang Xu Jinhan Li Fangming Liu Xijie Chen Tete Zhao Fangyi Cheng Key Laboratory of Advanced Energy Materials Chemistry (Ministry of Education) Engineering Research Center on High-Efficiency Energy Storage (Ministry of Education) Renewable Energy Conversion and Storage Center College of Chemistry Nankai University Tianjin 300071 China Contribution: Data curation (lead) Formal analysis (lead) Investigation (lead) Methodology (lead) Visualization (lead) Writing - original draft (equal) Contribution: Data curation (supporting) Formal analysis (equal) Investigation (supporting) Methodology (equal) Software (equal) Validation (equal) Frontiers Science Center for New Organic Matter Nankai University Tianjin 300071 China Contribution: Formal analysis (equal) Funding acquisition (supporting) Methodology (equal) Project administration (lead) Validation (supporting) Writing - review & editing (lead) Contribution: Data curation (supporting) Formal analysis (supporting) Investigation (supporting) Methodology (supporting) Validation (supporting) Contribution: Data curation (supporting) Formal analysis (supporting) Investigation (supporting) Visualization (supporting) Haihe Laboratory of Sustainable Chemical Transformations Tianjin 300192 China Contribution: Conceptualization (lead) Formal analysis (equal) Methodology (equal) Resources (lead) Supervision (lead) Writing - review & editing (equal)

The large-scale deployment of CO 2 electroreduction is hampered by deficient carbon utilization in neutral and alkaline electrolytes due to CO 2 loss into (bi)carbonates. Switching to acidic media mitigates carbonation, but suffers from low product selectivity because of hydrogen evolution. Here we report a crown ether decoration strategy on a Cu catalyst to enhance carbon utilization and selectivity of CO 2 methanation under acidic conditions. Macrocyclic 18-Crown-6 is found to enrich potassium cations near the Cu electrode surface, simultaneously enhancing the interfacial electric field to stabilize the *CO intermediate and accelerate water dissociation to boost *CO protonation. Remarkably, the mixture of 18-Crown-6 and Cu nanoparticles affords a CH 4 Faradaic efficiency of 51.2 % and a single pass carbon efficiency of 43.0 % toward CO 2 electroreduction in electrolyte with pH=2. This study provides a facile strategy to promote CH 4 selectivity and carbon utilization by modifying Cu catalysts with supramolecules.

关键词： CO2 Electroreduction Copper Catalyst Crown Ether Methanation Protonation

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Regulating the Mechanical and Optical Properties of Polymer-based Nanocomposites by Sub-Nanowires

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Angewandte Chemie 2022年第5期135卷

作者： Feng Yuan Dr. Chen Ouyang Minzheng Yang Prof. Wenxiong Shi Dr. Weibin Ren Prof. Yang Shen Prof. Yan Wei Prof. Xuliang Deng Prof. Xun Wang Institute of Medical Technology Peking University Health Science Center Beijing 100191 China Beijing Laboratory of Biomedical Materials Department of Geriatric Dentistry Peking University School and Hospital of Stomatology Beijing 100081 China Engineering Research Center of Advanced Rare Earth Materials Department of Chemistry Tsinghua University Beijing 100084 China Contribution: Data curation (lead) Formal analysis (lead) Investigation (lead) Writing - original draft (lead) Contribution: Data curation (supporting) Formal analysis (supporting) State Key Lab of New Ceramics and Fine Processing School of Materials Science and Engineering Tsinghua University Beijing 100084 China Institute for New Energy Materials and Low Carbon Technologies School of Materials Science and Engineering Tianjin University of Technology Tianjin 300384 China Contribution: Software (supporting) Contribution: Formal analysis (supporting) Contribution: Formal analysis (supporting) Supervision (supporting) Contribution: Conceptualization (equal) Formal analysis (lead) Supervision (lead) Contribution: Conceptualization (lead) Supervision (lead) Contribution: Conceptualization (lead) Data curation (lead) Investigation (lead) Methodology (lead) Project administration (lead) Supervision (lead) Validation (lead) Writing - review & editing (lead)

Sub-nanowires (SNWs) exhibit great potential applications in nanocomposites owing to their high specific surface area, high flexibility, and similarity to polymer chains in dimension, which are a good entry point to bridge inorganic materials and polymer materials. Herein, we synthesized hydroxyapatite sub-nanowires (HAP SNWs) and engineered hydroxyapatite sub-nanowires/polyimide (HSP) gels and films by simple mixing of HAP SNWs and polyimide (PI). Benefiting from the interactions between HAP SNWs and PI, these nanocomposites were a continuous hybrid network. As the increase of HAP SNWs contents, the viscosity and modulus of HSP gels were greatly improved by one or two orders of magnitude compared with PI gel. HSP films not only maintained high transparency but also gained high haze, as well as exhibited enhanced Young's modulus. Thus, both HSP gels and films developed in this work are promising for various applications in coatings and high-performance films.

关键词： Gels Nanocomposites Nanowires Thin Films

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The 2022 report of the Lancet Countdown on health and climate change: health at the mercy of fossil fuels (vol 400, pg 1619, 2022)

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LANCET 2022年第10365期400卷 1766-1766页

作者： Romanello, M. Di Napoli, C. Drummond, P. Institute for Global Health University College London London UK School of Agriculture Policy and Development University of Reading Reading UK Institute for Sustainable Resources University College London London UK Department of Global Health Centre for Health and the Global Environment University of Washington Seattle WA USA UCL Energy Institute University College London London UK Department of Health Sciences University of York York UK Department of Meteorology University of Reading Reading UK Institute for Risk and Disaster Reduction University College London London UK School of Earth and Environment University of Leeds Leeds UK Centre on Climate Change and Planetary Health London School of Hygiene & Tropical Medicine London UK School of Population Health University of Melbourne Melbourne VIC Australia Department of Earth System Science Tsinghua University Beijing China Mercator Research Institute on Global Commons and Climate Change Berlin Germany Department of Environment Climate Change and Health World Health Organization Geneva Switzerland Institute of Environmental Sciences University of Geneva Geneva Switzerland Cardiovascular Epidemiology Unit Department of Public Health & Primary Care University of Cambridge Cambridge UK School of Government University of Birmingham Birmingham UK Economic Analysis of Climate Impacts and Policy Division Centro Euro-Mediterraneo sui Cambiamenti Climatici Venice Italy Institute for Environmental Design and Engineering University College London London UK Natural Resources Institute University of Greenwich London UK Department of Environmental Health Sciences and Yale Center on Climate Change and Health Yale University New Haven CT USA Department of Civil and Environmental Engineering Northeastern University Boston MA USA Department of Fish and Wildlife Conservation Virginia Polytechnic Institute and State University Blacksburg VA USA Department of Geography University College London London UK NU

With advancements in the science of detection and attribution studies, the influence of climate change over many events has now been quantified. Because of the rapidly increasing temperatures, vulnerable populations (adults older than 65 years, and children younger than one year of age) were exposed to 3·7 billion more heatwave days in 2021 than annually in 1986–2005 (indicator 1.1.2), and heat-related deaths increased by 68% between 2000–04 and 2017–21 (indicator 1.1.5), a death toll that was significantly exacerbated by the confluence of the COVID-19 pandemic. Despite the local cooling and overall health benefits of urban greenspaces, only 277 (27%) of 1038 global urban centres were at least moderately green in 2021 (indicator 2.2.3), and the number of households with air conditioning increased by 66% from 2000 to 2020, a maladaptive response that worsens the energy crisis and further increases urban heat, air pollution, and greenhouse gas emissions. [...]millions of people do not have access to the energy needed to keep their homes at healthy temperatures, preserve food and medication, and meet the seventh Sustainable Development Goal (to ensure access to affordable, reliable, sustainable, and modern energy for all). Aggravating this situation even further, governments continue to incentivise fossil fuel production and consumption: 69 (80%) of 86 countries reviewed had net-negative carbon prices (ie, provided a net subsidy to fossil fuels) for a net total of US$400 billion

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Glucose-Responsive Charge-Switchable Lipid Nanoparticles for Insulin Delivery

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Angewandte Chemie 2023年第20期135卷

作者： Yun Liu Yanfang Wang Yuejun Yao Juan Zhang Wei Liu Kangfan Ji Xinwei Wei Yuanwu Wang Prof. Xiangsheng Liu Prof. Shiming Zhang Prof. Jinqiang Wang Prof. Zhen Gu Key Laboratory of Advanced Drug Delivery Systems of Zhejiang Province College of Pharmaceutical Sciences Zhejiang University 310058 Hangzhou China Jinhua Institute of Zhejiang University 321299 Jinhua China Contribution: Data curation (lead) Formal analysis (lead) Investigation (lead) Methodology (lead) Software (lead) Validation (lead) Visualization (lead) Writing - original draft (lead) Writing - review & editing (lead) Contribution: Data curation (supporting) Investigation (supporting) Visualization (supporting) Contribution: Data curation (supporting) Formal analysis (supporting) Investigation (supporting) Contribution: Formal analysis (supporting) Investigation (supporting) Methodology (supporting) Contribution: Formal analysis (supporting) Investigation (supporting) Contribution: Writing - review & editing (supporting) Contribution: Investigation (supporting) Zhejiang Cancer Hospital Hangzhou Institute of Medicine (HIM) Chinese Academy of Sciences 310022 Hangzhou China Department of Electrical and Electronic Engineering The University of Hong Kong 999077 Hong Kong SAR China Second Affiliated Hospital Zhejiang University School of Medicine 310009 Hangzhou China Contribution: Conceptualization (lead) Data curation (equal) Formal analysis (equal) Funding acquisition (lead) Investigation (lead) Methodology (equal) Project administration (lead) Resources (lead) Software (lead) Supervision (lead) Validation (supporting) Visualization (supporting) Writing - review & editing (lead) Department of General Surgery Sir Run Run Shaw Hospital School of Medicine Zhejiang University 310009 Hangzhou China Zhejiang Laboratory of Systems & Precision Medicine Zhejiang University Medical Center 310009 Hangzhou China MOE Key Laboratory of Macromolecular Synthesis and Functionalization Department of Polymer Science and Engineering Zhejiang University 310009 Hangzhou China Contribution: Funding acquisition (lead) Project administration (lead) Resources (lead) Softwar

Lipid nanoparticle-based drug delivery systems have a profound clinical impact on nucleic acid-based therapy and vaccination. Recombinant human insulin, a negatively-charged biomolecule like mRNA, may also be delivered by rationally-designed positively-charged lipid nanoparticles with glucose-sensing elements and be released in a glucose-responsive manner. Herein, we have designed phenylboronic acid-based quaternary amine-type cationic lipids that can self-assemble into spherical lipid nanoparticles in an aqueous solution. Upon mixing insulin and the lipid nanoparticles, a heterostructured insulin complex is formed immediately arising from the electrostatic attraction. In a hyperglycemia-relevant glucose solution, lipid nanoparticles become less positively charged over time, leading to reduced attraction and subsequent insulin release. Compared with native insulin, this lipid nanoparticle-based glucose-responsive insulin shows prolonged blood glucose regulation ability and blood glucose-triggered insulin release in a type 1 diabetic mouse model.

关键词： Diabetes Drug Delivery Glucose-Responsive Insulin Delivery Lipid Nanoparticles

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Evolutionary Algorithm Directed Synthesis of Mixed Anion Compounds LaF2X (X=Br, I) and LaFI2

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Angewandte Chemie 2023年第30期135卷

作者： Dr. Daichi Kato Dr. Peng Song Dr. Hiroki Ubukata Haruki Taguro Dr. Cédric Tassel Dr. Kohei Miyazaki Prof. Takeshi Abe Dr. Kousuke Nakano Prof. Kenta Hongo Prof. Ryo Maezono Prof. Hiroshi Kageyama Department of Energy and Hydrocarbon Chemistry Graduate School of Engineering Kyoto University Nishikyo-ku Kyoto 615-8510 Japan PRESTO Japan Science and Technology Agency (JST) Kawaguchi Saitama 332-0012 Japan Contribution: Data curation (lead) Formal analysis (lead) Funding acquisition (lead) Investigation (lead) Methodology (lead) Project administration (lead) Resources (supporting) Supervision (lead) Validation (equal) Visualization (equal) Writing - original draft (lead) Writing - review & editing (lead) School of Information Science JAIST Asahidai 1-1 Nomi Ishikawa 923-1292 Japan Contribution: Data curation (supporting) Formal analysis (supporting) Funding acquisition (supporting) Methodology (supporting) Software (supporting) Validation (supporting) Writing - original draft (supporting) Contribution: Formal analysis (supporting) Writing - original draft (supporting) Contribution: Data curation (supporting) Contribution: Data curation (supporting) Formal analysis (supporting) Writing - original draft (supporting) Contribution: Funding acquisition (supporting) Resources (supporting) Writing - original draft (supporting) Center for Basic Research on Materials (CBRM) National Institute for Materials Science (NIMS) 1-2-1 Sengen Tsukuba Ibaraki 305-0047 Japan Contribution: Writing - original draft (supporting) Research Center for Advanced Computing Infrastructure JAIST Asahidai 1-1 Nomi Ishikawa 923-1292 Japan Contribution: Conceptualization (lead) Funding acquisition (lead) Project administration (lead) Resources (lead) Supervision (lead) Validation (lead) Writing - original draft (supporting)

Mixed-anion compounds have attracted growing attentions, but their synthesis is challenging, making a rational search desirable. Here, we explored LaF 3 -LaX 3 (X=Cl, Br, I) system using ab initio structure searches based on evolutionary algorithms, and predicted LaF 2 X and LaFX 2 (X=Br, I), which are respectively isostructural with LaHBr 2 and YH 2 I, consisting of layered La-F blocks with single and double ordered honeycomb lattices, separated by van der Waals gaps. We successfully synthesized these compounds: LaF 2 Br and LaFI 2 crystallize in the predicted structure, while LaF 2 I is similar to the predicted one but with different layer stacking. LaF 2 I exhibits fluoride ion conductivity comparable to that of non-doped LaF 3 , and has the potential to show better ionic conductivity upon appropriate doping, given the theoretically lower diffusion energy barrier and the presence of soft iodine anions. This study shows the structure prediction using evolutionary algorithms will accelerate the discovery of mixed-anion compounds in future, in particular those with an ordered anion arrangement.

关键词： Evolutionary Algorithm Fluoride Ion Conductor Mixed Anion

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Amorphous Mo-doped NiS0.5Se0.5Nanosheets@Crystalline NiS0.5Se0.5Nanorods for High Current-density Electrocatalytic Water Splitting in Neutral Media

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Angewandte Chemie 2022年第6期135卷

作者： Dr. Yang Wang Dr. Xiaopeng Li Dr. Zhong Huang Dr. Haozhi Wang Dr. Zelin Chen Dr. Jinfeng Zhang Prof. Xuerong Zheng Prof. Yida Deng Prof. Wenbin Hu State Key Laboratory of Marine Resource Utilization in South China Sea School of Materials Science and Engineering Hainan University Haikou 570228 P. R. China Contribution: Data curation (lead) Investigation (lead) Methodology (lead) Validation (lead) Writing - original draft (lead) School of Materials Science and Engineering Tianjin Key Laboratory of Building Green Functional Materials Tianjin Chengjian University Tianjin 300384 China Contribution: Formal analysis (equal) State Key Laboratory of Marine Resource Utilization in South China Sea College of Information and Communication Engineering Hainan University Haikou 570228 P. R. China Contribution: Methodology (equal) Software (equal) Validation (equal) Contribution: Methodology (equal) Software (equal) School of Materials Science and Engineering Tianjin Key Laboratory of Composite and Functional Materials Key Laboratory of Advanced Ceramics and Machining Technology of Ministry of Education Tianjin University Tianjin 300072 P. R. China Contribution: Methodology (equal) Contribution: Conceptualization (equal) Investigation (equal) Supervision (equal) Contribution: Funding acquisition (lead) Supervision (equal) Contribution: Funding acquisition (supporting)

It is vitally important to develop highly active, robust and low-cost transition metal-based electrocatalysts for overall water splitting in neutral solution especially at large current density. In this work, amorphous Mo-doped NiS 0.5 Se 0.5 nanosheets@crystalline NiS 0.5 Se 0.5 nanorods (Am−Mo−NiS 0.5 Se 0.5 ) was synthesized using a facil one-step strategy. In phosphate buffer saline solution, the Am−Mo−NiS 0.5 Se 0.5 shows tiny overpotentials of 48 and 209 mV for hydrogen evolution reaction (HER), 238 and 514 mV for oxygen evolution reaction (OER) at 10 and 1000 mA cm −2 , respectively. Moreover, Am−Mo−NiS 0.5 Se 0.5 delivers excellent stability for at least 300 h without obvious degradation. Theoretical calculations revealed that the Ni sites in the defect-rich amorphous structure of Am−Mo−NiS 0.5 Se 0.5 owns higher electron state density and strengthened the binding energy of H 2 O, which will optimize H adsorption/desorption energy barriers and reduce the adsorption energy of OER determining step.

关键词： Amorphous Crystalline High-Current-Density Neutral Environment Water Splitting

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