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Network Embedding based on External Word Vectors

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Network Embedding based on External Word Vectors

IEEE International Performance computing and Communications Conference

作者： XiaoKun Zhang Yan Liu Jing Chen State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781538668092;9781538668085

Network embedding, which preserves network's sophisticated features, aims to effectively learn the low-dimensional embedding of vertices to lower the computing and storage costs. Content information network like Twitter is defined as network with rich text information. Most research about content information network are based on the information of the network itself. By introducing external word vectors into the modeling process, we can make use of the external syntactic and semantic features. In this paper, we propose NE-EWV (Network Embedding based on External Word Vectors), which preserves the feature fusion representation from both semantic feature space as well as structural feature space. Experiments are conducted in three real-world content information network datasets. In link predict task, the AUC increases 7% to 19% compared with the models which only considering the structural features, increases 1% to 12% compared with the model considering structural and text features in most cases.

关键词： Network embedding Content information network Auto-encoder External word vectors

Sparse representation of gaussian molecular surface

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arXiv 2019年

作者： Gui, Sheng Chen, Minxin Lu, Benzhuo STATE KEY LABORATORY of SCIENTIFIC and ENGINEERING COMPUTING NATIONAL CENTER for MATHEMATICS and INTERDISCIPLINARY SCIENCES ACADEMY of MATHEMATICS and SYSTEMS SCIENCE CHINESE ACADEMY of SCIENCES BEIJING100190 China SCHOOL of MATHEMATICAL SCIENCES UNIVERSITY of CHINESE ACADEMY of SCIENCES BEIJING100049 China DEPARTMENT of MATHEMATICS SOOCHOW UNIVERSITY SUZHOU215006 China

In this paper, we propose a model and algorithm for sparse representing Gaussian molecular surface. The original Gaussian molecular surface is approximated by a relatively small number of radial basis functions (RBFs) with rotational ellipsoid feature. The sparsity of the RBF representation is achieved by solving a nonlinear L1optimization problem. Experimental results demonstrate that the original Gaussian molecular surface is able to be represented with good accuracy by much fewer RBFs using our L1model and algorithm. The sparse representation of Gaussian molecular surface is useful in various applications, such as molecular structure alignment, calculating molecular areas and volumes, and the method in principle can be applied to sparse representation of general shapes and coarse-grained molecular modeling. Copyright © 2019, The Authors. All rights reserved.

关键词： Radial basis function networks

Photocurrent imaging of multi-memristive charge density wave switching in two-dimensional 1T-TaS2

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arXiv 2020年

作者： Patel, Tarun Okamoto, Junichi Dekker, Tina Yang, Bowen Gao, Jingjing Luo, Xuan Lu, Wenjian Sun, Yuping Tsen, Adam W. Institute for Quantum Computing Department of Physics and Astronomy Department of Electrical and Computer Engineering Department of Chemistry University of Waterloo WaterlooONN2L 3G1 Canada Institute of Physics University of Freiburg FreiburgD-79104 Germany Key Laboratory of Materials Physics Institute of Solid State Physics Chinese Academy of Sciences Hefei230031 China University of Science and Technology of China Hefei230026 China High Magnetic Field Laboratory Chinese Academy of Sciences Hefei230031 China Collaborative Innovation Centre of Advanced Microstructures Nanjing University Nanjing210093 China

Transport studies of atomically thin 1T-TaS2 have demonstrated the presence of intermediate resistance states across the nearly commensurate (NC) to commensurate (C) charge density wave (CDW) transition, which can be further switched electrically. While this presents exciting opportunities for the material in memristor applications, the switching mechanism has remained elusive and could be potentially attributed to the formation of inhomogeneous C and NC domains across the 1T-TaS2 flake. Here, we present simultaneous electrical driving and scanning photocurrent imaging of CDWs in ultrathin 1T-TaS2 using a vertical heterostructure geometry. While micron-sized CDW domains form upon changing temperature, electrically driven transitions result in largely uniform changes, indicating that states of intermediate resistance for the latter likely correspond to true metastable CDW states in between the NC and C phases, which we then explain by a free energy analysis. Additionally, we are able to perform repeatable and bidirectional switching across the multiple CDW states without changing sample temperature, demonstrating that atomically thin 1T-TaS2 can be further used as a robust and reversible multi-memristor material. Copyright © 2020, The Authors. All rights reserved.

关键词： Memristors

Improved Cryptanalysis of an ISO Standard Lightweight Block Cipher with Refined MILP Modelling 13th

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Improved Cryptanalysis of an ISO Standard Lightweight Block ...

13th International Conference on Information Securityand Cryptology, Inscrypt 2017

作者： Yin, Jun Ma, Chuyan Lyu, Lijun Song, Jian Zeng, Guang Ma, Chuangui Wei, Fushan State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China State Key Laboratory of Cryptology P.O. Box 5159 Beijing100878 China Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Data Assurance and Communication Security Research Center Chinese Academy of Sciences Beijing100093 China School of Cyber Security University of Chinese Academy of Sciences Beijing100049 China National University of Defense Technology Changsha410073 China Army Aviation Institute Beijing101116 China

ISBN: (纸本)9783319751597

Differential and linear cryptanalysis are two of the most effective attacks on block ciphers. Searching for (near) optimal differential or linear trails is not only useful for the security evaluation of block ciphers against these attacks, but also indispensable to the cryptanalysts who want to attack a cipher with these techniques. In recent years, searching for trails automatically with Mixed-Integer Linear Programming (MILP) gets a lot of attention. At first, Mouha et al. translated the problem of counting the minimum number of differentially active S-boxes into an MILP problem for word-oriented block ciphers. Subsequently, in Asiacrypt 2014, Sun et al. extended Mouha et al.’s method, and presented a technique which can find actual differential or linear characteristics of a block cipher in both the single-key and related-key models. In this paper, we refine the constraints of the 2-XOR operation in order to reduce the overall number of variables and constraints. Experimental results show that MILP models with the refined constraints can be solved more efficiently. We apply our method to HIGHT (an ISO standard), and we find differential (covering 11 rounds) or linear trails (covering 10 rounds) with higher probability or correlation. Moreover, we find so far the longest differential and linear distinguishers of HIGHT. © Springer International Publishing AG, part of Springer Nature 2018.

关键词： ISO Standards

MemNetAR: Memory Network with Adversative Relation for Target-Level Sentiment Classification

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MemNetAR: Memory Network with Adversative Relation for Targe...

2019 IEEE Global Communications Conference (GLOBECOM)

作者： Yiwei Gao Jianwei Niu Xuefeng Liu Kaili Mao Shui Yu State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing China Beijing Advanced Innovation Center for Big Data and Brain Computing (BDBC) Beihang University Hangzhou Innovation Research Institute Beihang University School of Computer Science and Cyber Engineering Guangzhou University Guangdong China

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

Target-level sentiment classification aims to identify the sentiment of multiple targets in a sentence. Although existing approaches based on neural network have achieved good performance in this task, we find that many approaches tend to give the same predictions for instances that have multiple targets, and this tendency can make a low accuracy for those instances that have different classes for different targets. Based on this observation, we propose MemNetAR, a memory network which can explicitly leverage the adversative relation among multiple targets in a sentence. Specifically, we add an adversative loss to the cross-entropy loss when there are adversative words between targets. The experimental results on public laptop and restaurant datasets prove that our model can improve 0.84% and 0.8% on total test dataset, and improve 2.97% and 2.68% on the dataset consisting of those instances with multiple targets but different classes by leveraging this new adversative information.

关键词： Task analysis Feature extraction Sentiment analysis Portable computers Machine learning Training Predictive models

Exploring Lorentz Invariance Violation from Ultrahigh-Energy γ Rays Observed by LHAASO

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Physical Review Letters 2022年第5期128卷 051102-051102页

作者： Zhen Cao 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 Zhe Cao J. Chang J. F. Chang B. M. Chen E. S. Chen J. Chen Liang Chen Long Chen M. J. Chen M. L. Chen Q. H. Chen S. H. Chen S. Z. Chen T. L. Chen X. L. Chen Y. Chen N. Cheng Y. D. Cheng S. W. Cui X. H. Cui Y. D. Cui B. D’Ettorre Piazzoli B. Z. Dai H. L. Dai Z. G. Dai Danzengluobu D. della Volpe X. J. Dong K. K. Duan J. H. Fan Y. Z. Fan Z. X. Fan J. Fang K. Fang C. F. Feng L. Feng S. H. Feng Y. L. Feng B. Gao C. D. Gao L. Q. Gao Q. Gao W. Gao M. M. Ge L. S. Geng G. H. Gong Q. B. Gou M. H. Gu F. L. Guo J. G. Guo X. L. Guo Y. Q. Guo Y. Y. Guo Y. A. Han H. H. He H. N. He J. C. He S. L. He X. B. He Y. He M. Heller Y. K. Hor C. Hou X. Hou H. B. Hu S. Hu S. C. Hu X. J. Hu D. H. Huang Q. L. Huang W. H. Huang X. T. Huang X. Y. Huang Z. C. Huang F. Ji X. L. Ji H. Y. Jia K. Jiang Z. J. Jiang C. Jin T. Ke D. Kuleshov K. Levochkin B. B. Li Cheng Li Cong Li F. Li H. B. Li H. C. Li H. Y. Li Jian Li Jie Li K. Li W. L. Li X. R. Li Xin Li Y. Li Y. Z. Li Zhe Li Zhuo Li E. W. Liang Y. F. Liang S. J. Lin B. Liu C. Liu D. Liu H. Liu H. D. Liu J. Liu J. L. Liu J. S. Liu J. Y. Liu M. Y. Liu R. Y. Liu S. M. Liu W. Liu Y. Liu Y. N. Liu Z. X. Liu W. J. Long R. Lu H. K. Lv B. Q. Ma L. L. Ma X. H. Ma J. R. Mao A. Masood Z. Min W. Mitthumsiri T. Montaruli Y. C. Nan B. Y. Pang P. Pattarakijwanich Z. Y. Pei M. Y. Qi Y. Q. Qi B. Q. Qiao J. J. Qin D. Ruffolo V. Rulev A. Sáiz L. Shao O. Shchegolev X. D. Sheng J. R. Shi H. C. Song Yu. V. Stenkin V. Stepanov Y. Su Q. N. Sun X. N. Sun Z. B. Sun P. H. T. Tam Z. B. Tang W. W. Tian B. D. Wang C. Wang H. Wang H. G. Wang J. C. Wang J. S. Wang L. P. Wang L. Y. Wang R. N. Wang W. Wang X. G. Wang X. J. Wang X. Y. Wang Y. Wang Y. D. Wang Y. J. Wang Y. P. Wang Z. H. Wang Z. X. Wang Zhen Wang Zheng Wang D. M. Wei J. J. Wei Y. J. Wei T. Wen C. Y. Wu H. R. Wu S. Wu W. X. Wu X. F. Wu S. Q. Xi J. Xia J. J. Xia G. M. Xiang D. X. Xiao G. Xiao H. B. Xiao G. G. Xin Y. L. Xin Y. Xing D. L. Xu R. X. Xu L. Xue Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center Institute of High Energy Physics Chinese Academy of Sciences 100049 Beijing China University of Chinese Academy of Sciences 100049 Beijing China TIANFU Cosmic Ray Research Center Chengdu 610000 Sichuan China Dublin Institute for Advanced Studies 31 Fitzwilliam Place 2 Dublin Ireland Max-Planck-Institut for Nuclear Physics P.O. Box 103980 69029 Heidelberg Germany State Key Laboratory of Particle Detection and Electronics 100049 Beijing China University of Science and Technology of China 230026 Hefei Anhui China School of Physical Science and Technology and School of Information Science and Technology Southwest Jiaotong University 610031 Chengdu Sichuan China College of Physics Sichuan University 610065 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 Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences 200030 Shanghai China Key Laboratory of Cosmic Rays (Tibet University) Ministry of Education 850000 Lhasa Tibet China National Astronomical Observatories Chinese Academy of Sciences 100101 Beijing China School of Physics and Astronomy and School of Physics (Guangzhou) Sun Yat-sen University 519000 Zhuhai Guangdong China Dipartimento di Fisica dell’Università di Napoli “Federico II ” Complesso Universitario di Monte Sant’Angelo via Cinthia 80126 Napoli Italy School of Physics and Astronomy Yunnan University 650091 Kunming Yunnan China Département de Physique Nucléaire et Corpusculaire Faculté de S

Recently, the LHAASO Collaboration published the detection of 12 ultrahigh-energy γ-ray sources above 100 TeV, with the highest energy photon reaching 1.4 PeV. The first detection of PeV γ rays from astrophysical sources may provide a very sensitive probe of the effect of the Lorentz invariance violation (LIV), which results in decay of high-energy γ rays in the superluminal scenario and hence a sharp cutoff of the energy spectrum. Two highest energy sources are studied in this work. No signature of the existence of the LIV is found in their energy spectra, and the lower limits on the LIV energy scale are derived. Our results show that the first-order LIV energy scale should be higher than about 105 times the Planck scale MPl and that the second-order LIV scale is >10−3MPl. Both limits improve by at least one order of magnitude the previous results.

关键词： Cosmic rays & astroparticles Gamma ray astronomy Lorentz symmetry

Demonstration of topological wireless power transfer

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arXiv 2020年

作者： Zhang Yang, Yihao Jiang, Zhao Chen, Qiaolu Yan, Qinghui Wu, Zhouyi Zhang, Baile Huangfu, Jiangtao Chen, Hongsheng Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China ZJU-Hangzhou Global Science and Technology Innovation Center Key Laboratory of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang Zhejiang University Hangzhou310027 China International Joint Innovation Center ZJU-UIUC Institute Zhejiang University Haining314400 China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University Singapore637371 Singapore Centre for Disruptive Photonic Technologies The Photonics Institute Nanyang Technological University Singapore639798 Singapore Zhejiang University Hangzhou310027 China

Recent advances in non-radiative wireless power transfer (WPT) technique essentially relying on magnetic resonance and near-field coupling have successfully enabled a wide range of applications. However, WPT systems based on double resonators are severely limited to short- or mid-range distance, due to the deteriorating efficiency and power with long transfer distance. WPT systems based on multi-relay resonators can overcome this problem, which, however, suffer from sensitivity to perturbations and fabrication imperfections. Here, we experimentally demonstrate a concept of topological wireless power transfer (TWPT), where energy is transferred efficiently via the near-field coupling between two topological edge states localized at the ends of a one-dimensional radiowave topological insulator. Such a TWPT system can be modelled as a parity-time-symmetric Su-Schrieffer-Heeger (SSH) chain with complex boundary potentials. Besides, the coil configurations are judiciously designed, which significantly suppress the unwanted cross-couplings between nonadjacent coils that could break the chiral symmetry of the SSH chain. By tuning the inter- and intra-cell coupling strengths, we theoretically and experimentally demonstrate high energy transfer efficiency near the exceptional point of the topological edge states, even in the presence of disorder. The combination of topological metamaterials, non-Hermitian physics, and WPT techniques could promise a variety of robust, efficient WPT applications over long distances in electronics, transportation, and industry. © 2020, CC BY.

关键词： Energy transfer

Very high energy gamma-ray emission beyond 10 TeV from GRB 221009A

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arXiv 2023年

作者： Cao, Zhen Aharonian, F. An, Q. Axikegu, A. Bai, Y.X. Bao, Y.W. Bastieri, D. Bi, X.J. Bi, Y.J. Cai, J.T. Cao, Q. Cao, W.Y. Cao, Zhe Chang, J. Chang, J.F. Chen, A.M. Chen, E.S. Chen, Liang Chen, Lin Chen, Long Chen, M.J. Chen, M.L. Chen, Q.H. Chen, S.H. Chen, S.Z. Chen, T.L. Chen, Y. Cheng, N. Cheng, Y.D. Cui, M.Y. Cui, S.W. Cui, X.H. Cui, Y.D. Dai, B.Z. Dai, H.L. Dai, Z.G. Danzengluobu della Volpe, D. Dong, X.Q. Duan, K.K. Fan, J.H. Fan, Y.Z. Fang, J. Fang, K. Feng, C.F. Feng, L. Feng, S.H. Feng, X.T. Feng, Y.L. Gabici, S. Gao, B. Gao, C.D. Gao, L.Q. Gao, Q. Gao, W. Gao, W.K. Ge, M.M. Geng, L.S. Giacinti, G. Gong, G.H. Gou, Q.B. Gu, M.H. Guo, F.L. Guo, X.L. Guo, Y.Q. Guo, Y.Y. Han, Y.A. He, H.H. He, H.N. He, J.Y. He, X.B. He, Y. Heller, M. Hor, Y.K. Hou, B.W. Hou, C. Hou, X. Hu, H.B. Hu, Q. Hu, S.C. Huang, D.H. Huang, T.Q. Huang, W.J. Huang, X.T. Huang, X.Y. Huang, Y. Huang, Z.C. Ji, X.L. Jia, H.Y. Jia, K. Jiang, K. Jiang, X.W. Jiang, Z.J. Jin, M. Kang, M.M. Ke, T. Kuleshov, D. Kurinov, K. Li, B.B. Li, Cheng Li, Cong Li, D. Li, F. Li, H.B. Li, H.C. Li, H.Y. Li, J. Li, Jian Li, Jie Li, K. Li, W.L. Li, W.L. Li, X.R. Li, Xin Li, Y.Z. Li, Zhe Li, Zhuo Liang, E.W. Liang, Y.F. Lin, S.J. Liu, B. Liu, C. Liu, D. Liu, H. Liu, H.D. Liu, J. Liu, J.L. Liu, J.Y. Liu, M.Y. Liu, R.Y. Liu, S.M. Liu, W. Liu, Y. Liu, Y.N. Lu, R. Luo, Q. Lv, H.K. Ma, B.Q. Ma, L.L. Ma, X.H. Mao, J.R. Min, Z. Mitthumsiri, W. Mu, H.J. Nan, Y.C. Neronov, A. Ou, Z.W. Pang, B.Y. Pattarakijwanich, P. Pei, Z.Y. Qi, M.Y. Qi, Y.Q. Qiao, B.Q. Qin, J.J. Ruffolo, D. Sáiz, A. Semikoz, D. Shao, C.Y. Shao, L. Shchegolev, O. Sheng, X.D. Shu, F.W. Song, H.C. Stenkin, Yu.V. Stepanov, V. Su, Y. Sun, Q.N. Sun, X.N. Sun, Z.B. Tam, P.H.T. Tang, Q.W. Tang, Z.B. Key Laboratory of Particle Astrophysics & Experimental Physics Division & Computing Center Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China University of Chinese Academy of Sciences Beijing100049 China TIANFU Cosmic Ray Research Center Sichuan Chengdu China Dublin Institute for Advanced Studies 31 Fitzwilliam Place 2 Dublin Ireland Max-Planck-Institut for Nuclear Physics P.O. Box 103980 Heidelberg69029 Germany State Key Laboratory of Particle Detection and Electronics China University of Science and Technology of China Anhui Hefei230026 China School of Physical Science and Technology School of Information Science and Technology Southwest Jiaotong University Sichuan Chengdu610031 China School of Astronomy and Space Science Nanjing University Jiangsu Nanjing210023 China Center for Astrophysics Guangzhou University Guangdong Guangzhou510006 China Hebei Normal University Hebei Shijiazhuang050024 China Key Laboratory of Dark Matter and Space Astronomy Key Laboratory of Radio Astronomy Purple Mountain Observatory Chinese Academy of Sciences Jiangsu Nanjing210023 China Tsung-Dao Lee Institute School of Physics and Astronomy Shanghai Jiao Tong University Shanghai200240 China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai200030 China Ministry of Education Tibet Lhasa850000 China National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China Sun Yat-sen University Guangdong Zhuhai Guangzhou519000 510275 China School of Physics and Astronomy Yunnan University Yunnan Kunming650091 China Département de Physique Nucléaire et Corpusculaire Faculté de Sciences Université de Genève 24 Quai Ernest Ansermet Geneva1211 Switzerland Institute of Frontier and Interdisciplinary Science Shandong University Shandong Qingdao266237 China APC Université Paris Cité CNRS IN2P3 CEA IRFU Observatoire de Paris 119 Par

The highest energy gamma-rays from gamma-ray bursts (GRBs) have important implications for their radiation mechanism. Here we report for the first time the detection of gamma-rays up to 13 TeV from the brightest GRB 221009A by the Large High Altitude Air-shower Observatory (LHAASO). The LHAASO-KM2A detector registered more than 140 gamma-rays with energies above 3 TeV during 230−900s after the trigger. The intrinsic energy spectrum of gamma-rays can be described by a power-law after correcting for extragalactic background light (EBL) absorption. Such a hard spectrum challenges the synchrotron self-Compton (SSC) scenario of relativistic electrons for the afterglow emission above several TeV. Observations of gamma-rays up to 13 TeV from a source with a measured redshift of z=0.151 hints more transparency in intergalactic space than previously expected. Alternatively, one may invoke new physics such as Lorentz Invariance Violation (LIV) or an axion origin of very high energy (VHE) signals. © 2023, CC BY.

关键词： Gamma rays

A Ce-UiO-66 Metal–Organic Framework-Based Graphene-Embedded Photocatalyst with Controllable Activation for Solar Ammonia Fertilizer Production

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Angewandte Chemie 2022年第37期134卷

作者： Dr. Sixiao Liu Dr. Zhenyuan Teng Dr. Hang Liu Dr. Tianyi Wang Prof. Guoxiu Wang Prof. Qiang Xu Prof. Xiuyun Zhang Prof. Min Jiang Prof. Chengyin Wang Prof. Wei Huang Prof. Huan Pang College of Chemistry and Chemical Engineering Yangzhou University Yangzhou 225002 P. R. China Department of Applied Chemistry Faculty of Engineering Kyushu Institute of Technology Kitakyushu 804-8550 Japan School of Mathematical and Physical Science University of Technology Sydney Sydney NSW 2007 Australia College of Physical Science and Technology Yangzhou University Yangzhou 225002 P. R. China College of Agriculture Yangzhou University Yangzhou 225002 P. R. China State Key Laboratory of Organic Electronics and Information Displays & Institute of Advanced Materials (IAM) Nanjing University of Posts & Telecommunications Nanjing 210023 P R. China Frontiers Science Center for Flexible Electronics (FSCFE) MIIT Key Laboratory of Flexible Electronics (KLoFE) Northwestern Polytechnical University Xi'an 710072 P. R. China

Currently, nitrogen fertilizers feed half of the global population, but their use is limited by energy consumption and transportation. Therefore, it is important to study photocatalysts for use in solar nitrogen fertilizers. Herein, a new type of graphene-embedded Ce-based UiO-66 (Ce-UiO-66) photocatalyst (GSCe) is investigated. Ce-UiO-66 is activated by the breakage of benzene-C bonds and the formation of active sites by ultraviolet light in water. Moreover, embedding graphene effectively controls activation and improves nitrogen fixation. GSCe exhibited a remarkable apparent quantum efficiency (AQE) of 9.25 % and stability under 365 nm light with solar-level intensity. GSCe also performed well as a solar ammonia fertilizer for crop cultivation. This investigation opens up opportunities for nitrogen fixation photocatalysts to be used as environmentally friendly solar nitrogen fertilizers.

关键词： Ammonia Graphene Metal–Organic Frameworks Photocatalysis Sustainable Chemistry