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Extending Ring-Chain Coupling Empirical Law to Lithium-Mediated Electrochemical Ammonia Synthesis

Angewandte Chemie 2023年第2期136卷

作者： Ya Li Zhenkang Wang Haoqing Ji Mengfan Wang Tao Qian Chenglin Yan Jianmei Lu Collaborative Innovation Center of Suzhou Nano Science and Technology College of Chemistry Chemical Engineering and Materials Science Soochow University 199 Ren'ai Road Suzhou 215123 P. R. China Contribution: Data curation (lead) Investigation (lead) Visualization (lead) Writing - original draft (lead) Key Laboratory of Core Technology of High Specific Energy Battery and Key Materials for Petroleum and Chemical Industry College of Energy Soochow University Suzhou Jiangsu 215006 P. R. China Contribution: Data curation (equal) Investigation (lead) Visualization (lead) Writing - original draft (lead) Contribution: Data curation (lead) Methodology (lead) Software (lead) Writing - original draft (lead) Writing - review & editing (equal) Contribution: Methodology (equal) Writing - review & editing (equal) College of Chemistry and Chemical Engineering Nantong University Nantong Jiangsu 226019 P. R. China Contribution: Funding acquisition (equal) Investigation (equal) Supervision (equal) Writing - review & editing (equal) School of Petrochemical Engineering Changzhou University Changzhou 213164 P. R. China Contribution: Conceptualization (lead) Formal analysis (lead) Funding acquisition (lead) Project administration (lead) Supervision (lead) Contribution: Funding acquisition (lead) Methodology (lead) Project administration (lead) Supervision (lead) Writing - review & editing (lead)

With its efficient nitrogen fixation kinetics, electrochemical lithium-mediated nitrogen reduction reaction (LMNRR) holds promise for replacing Haber–Bosch process and realizing sustainable and green ammonia production. However, the general interface problem in lithium electrochemistry seriously impedes the further enhancement of LMNRR performance. Inspired by the development history of lithium battery electrolytes, here, we extend the ring-chain solvents coupling law to LMNRR system to rationally optimize the interface during the reaction process, achieving nearly a two-fold Faradaic efficiency up to 54.78±1.60 %. Systematic theoretical simulations and experimental analysis jointly decipher that the anion-rich Li + solvation structure derived from ring tetrahydrofuran coupling with chain ether successfully suppresses the excessive passivation of electrolyte decomposition at the reaction interface, thus promoting the mass transfer of active species and enhancing the nitrogen fixation kinetics. This work offers a progressive insight into the electrolyte design of LMNRR system.

关键词： Electrochemical Synthesis Electrolyte Design Green Ammonia Lithium-Mediated Ring-Chain

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Moisture-Accelerated Precursor Crystallisation in Ambient Air for High-Performance Perovskite Solar Cells toward Mass Production

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Angewandte Chemie 2022年第42期134卷

作者： Weili Fan Dr. Kaimo Deng Ying Shen Prof. Yang Bai Prof. Liang Li Beijing Advanced Innovation Center for Materials Genome Engineering Institute for Advanced Materials and Technology University of Science and Technology Beijing 100083 P. R. China Contribution: Formal analysis (equal) Investigation (equal) Methodology (equal) Software (lead) Writing - original draft (equal) School of Physical Science and Technology Jiangsu Key Laboratory of Thin Films Soochow University Suzhou 215006 P. R. China Contribution: Data curation (equal) Funding acquisition (equal) Methodology (equal) Project administration (equal) Contribution: Methodology (equal) Software (equal) Contribution: Funding acquisition (equal) Methodology (equal) Project administration (equal) Contribution: Conceptualization (lead) Funding acquisition (lead) Project administration (lead)

Phase-pure crystallised perovskite is considered an excellent precursor for fabricating high-stability perovskite films with minimal defects. However, currently available protocols for synthesising crystallised perovskites must be conducted in an inert atmosphere or in the presence of an organic solvent as the reaction medium, which hinders mass production. Here, we report the fast synthesis of α-phase-crystallised perovskite powder assisted by moisture in ambient air. Moisture can promote the reaction between PbI 2 and organic salts and facilitate complete phase transition, as demonstrated in a joint experimental and theoretical study. Perovskite solar cells with a power conversion efficiency of 24.07 % were achieved using phase-pure crystallised perovskite powder as the precursor. This ambient-air-compatible method opens new vistas to reproducible high-quality precursors for large-scale photovoltaic applications.

关键词： Moisture Perovskite Solar Cells Precursor Crystallization Stability

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Matching Consecutive Subpatterns Over Streaming Time Series

arXiv

引用

arXiv 2018年

作者： Kang, Rong Wang, Chen Wang, Peng Ding, Yuting Wang, Jianmin School of Software Tsinghua University Beijing China National Engineering Laboratory for Big Data Software China School of Computer Science Fudan University Shanghai China

Pattern matching of streaming time series with lower latency under limited computing resource comes to a critical problem, especially as the growth of Industry 4.0 and Industry Internet of Things. However, against traditional single pattern matching model, a pattern may contain multiple subpatterns representing different physical meanings in the real world. Hence, we formulate a new problem, called "consecutive subpatterns matching", which allows users to specify a pattern containing several consecutive subpatterns with various specified thresholds. We propose a novel representation Equal-Length Block (ELB) together with two efficient implementations, which work very well under all Lp-Norms without false dismissals. Extensive experiments are performed on synthetic and real-world datasets to illustrate that our approach outperforms the brute-force method and MSM, a multi-step filter mechanism over the multi-scaled representation by orders of magnitude. Copyright © 2018, The Authors. All rights reserved.

关键词： Time series

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Circularly and Linearly Polarized Luminescence from AIE Luminogens Induced by Super-Aligned Assemblies of Sub-1 nm Nanowires

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Angewandte Chemie 2022年第34期134卷

作者： Shujian Rong Prof. Wenxiong Shi Dr. Simin Zhang Prof. Dr. Xun Wang Key Lab of Organic Optoelectronics and Molecular Engineering Department of Chemistry Tsinghua University Beijing 100084 China Contribution: Investigation (lead) Methodology (lead) Writing - original draft (lead) Institute for New Energy Materials and Low Carbon Technologies School of Materials Science and Engineering Tianjin University of Technology Tianjin 300387 China Contribution: Data curation (lead) Formal analysis (lead) Software (lead) Contribution: Conceptualization (equal) Formal analysis (lead) Methodology (lead) Writing - review & editing (equal) Contribution: Conceptualization (lead) Data curation (lead) Formal analysis (lead) Funding acquisition (lead) Investigation (lead) Methodology (lead) Project administration (lead) Resources (lead) Supervision (lead) Validation (lead) Writing - review & editing (lead)

Sub-1 nm nanowires (SNWs) combine the properties of inorganic materials and polymers. They can be highly oriented through assembly, and can also be easily processed. Meanwhile, aggregation-induced emission luminogens (AIEgens) show high potential for optical applications, but they are usually hard to process. The combination of SNWs and AIEgens can enrich both of their applications. In this study, we report that the fluorescence emission intensity of the AIEgens–SNW dispersion is dramatically enhanced due to the flexibility of SNWs. Furthermore, we fabricate two kinds of functional films with circularly polarized luminescence (CPL) and linearly polarized luminescence (LPL) activities. The construction of CPL materials didn't require any chiral chemicals. The construction of LPL materials didn't require an additional stretching process. As a result, we endowed common achiral AIEgens with a high dissymmetry factor of 0.033 and a polarization ratio of 0.44, respectively.

关键词： Aggregation-Induced Emission (AIE) Circularly Polarized Luminescence Linearly Polarized Luminescence Self-Assembly Sub-1 nm Nanowires

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In Situ Self-Assembly of Fluorogenic RNA Nanozipper Enables Real-Time Imaging of Single Viral mRNA Translation

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Angewandte Chemie 2023年第25期135卷

作者： Yu-Peng Zhang Prof. Zhi-Gang Wang Yi-Fan Tian Lin-Han Jiang Liang Zhao Prof. De-Ming Kong Prof. Xing Li Prof. Dai-Wen Pang Prof. Shu-Lin Liu State Key Laboratory of Medicinal Chemical Biology Tianjin Key Laboratory of Biosensing and Molecular Recognition Research Center for Analytical Sciences College of Chemistry and School of Medicine Nankai University Tianjin 300071 P. R. China Contribution: Conceptualization (equal) Data curation (lead) Formal analysis (equal) Investigation (lead) Methodology (lead) Writing - original draft (equal) Writing - review & editing (equal) Contribution: Data curation (supporting) Formal analysis (equal) Investigation (supporting) Contribution: Data curation (supporting) Formal analysis (supporting) Contribution: Investigation (supporting) Contribution: Resources (supporting) Writing - review & editing (supporting) Beijing Institutes of Life Science Chinese Academy of Science Beijing 100101 China Contribution: Methodology (equal) Resources (equal) Haihe Laboratory of Sustainable Chemical Transformations Tianjin 300192 China Contribution: Resources (supporting) Supervision (supporting) Engineering Research Center of Nano Geomaterials of Ministry of Education Faculty of Materials Science and Chemistry China University of Geosciences Wuhan 430074 P. R. China Contribution: Conceptualization (equal) Funding acquisition (lead) Methodology (equal) Project administration (equal) Software (lead) Writing - original draft (equal) Writing - review & editing (lead)

Real-time visualization of individual viral mRNA translation activities in live cells is essential to obtain critical details of viral mRNA dynamics and to detect its transient responses to environmental stress. Fluorogenic RNA aptamers are powerful tools for real-time imaging of mRNA in live cells, but monitoring the translation activity of individual mRNAs remains a challenge due to their intrinsic photophysical properties. Here, we develop a genetically encoded turn-on 3,5-difluoro-4-hydroxybenzylidene imidazolinone (DFHBI)-binding RNA nanozipper with superior brightness and high photostability by in situ self-assembly of multiple nanozippers along single mRNAs. The nanozipper enables real-time imaging of the mobility and dynamic translation of individual viral mRNAs in live cells, providing information on the spatial dynamics and translational elongation rate of viral mRNAs.

关键词： Aptamers Nanozippers Single mRNA Imaging Translation

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AI-skin: Skin disease recognition based on self-learning and wide data collection through a closed loop framework

arXiv

引用

arXiv 2019年

作者： Chen, Min Zhou, Ping Wu, Di Hu, Long Hassan, Mohammad Mehedi Alamri, Atif School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China School of Data and Computer Science Sun Yat-sen University Guangzhou China Guangdong Province Key Laboratory of Big Data Analysis and Processing Guangzhou China Chair of Pervasive and Mobile Computing Information Systems Department College of Computer and Information Sciences King Saud University Riyadh11543 Saudi Arabia Chair of Pervasive and Mobile Computing Software Engineering Department CCIS King Saud University Riyadh11543 Saudi Arabia

There are a lot of hidden dangers in the change of human skin conditions, such as the sunburn caused by long-time exposure to ultraviolet radiation, which not only has aesthetic impact causing psychological depression and lack of selfconfidence, but also may even be life-threatening due to skin canceration. Current skin disease researches adopt the auto-classification system for improving the accuracy rate of skin disease classification. However, the excessive dependence on the image sample database is unable to provide individualized diagnosis service for different population groups. To overcome this problem, a medical AI framework based on data width evolution and self-learning is put forward in this paper to provide skin disease medical service meeting the requirement of real time, extendibility and individualization. First, the wide collection of data in the close-loop information flow of user and remote medical data center is discussed. Next, a data set filter algorithm based on information entropy is given, to lighten the load of edge node and meanwhile improve the learning ability of remote cloud analysis model. In addition, the framework provides an external algorithm load module, which can be compatible with the application requirements according to the model selected. Three kinds of deep learning model, i.e. LeNet-5, AlexNet and VGG16, are loaded and compared, which have verified the universality of the algorithm load module. The experiment platform for the proposed real-time, individualized and extensible skin disease recognition system is built. And the system's computation and communication delay under the interaction scenario between tester and remote data center are analyzed. It is demonstrated that the system we put forward is reliable and effective. Copyright © 2019, The Authors. All rights reserved.

关键词： data acquisition

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Partial adversarial domain adaptation

arXiv

引用

arXiv 2018年

作者： Cao, Zhangjie Ma, Lijia Long, Mingsheng Wang, Jianmin School of Software Tsinghua University China National Engineering Laboratory for Big Data Software Beijing National Research Center for Information Science and Technology

Domain adversarial learning aligns the feature distributions across the source and target domains in a two-player minimax game. Existing domain adversarial networks generally assume identical label space across different domains. In the presence of big data, there is strong motivation of transferring deep models from existing big domains to unknown small domains. This paper introduces partial domain adaptation as a new domain adaptation scenario, which relaxes the fully shared label space assumption to that the source label space subsumes the target label space. Previous methods typically match the whole source domain to the target domain, which are vulnerable to negative transfer for the partial domain adaptation problem due to the large mismatch between label spaces. We present Partial Adversarial Domain Adaptation (PADA), which simultaneously alleviates negative transfer by down-weighing the data of outlier source classes for training both source classifier and domain adversary, and promotes positive transfer by matching the feature distributions in the shared label space. Experiments show that PADA exceeds state-of-the-art results for partial domain adaptation tasks on several datasets. Copyright © 2018, The Authors. All rights reserved.

关键词： Machine learning

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Carbazole-Dendronized Luminescent Radicals

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Angewandte Chemie 2023年第28期135卷

作者： Rui Xiaotian Wataru Ota Prof. Tohru Sato Minori Furukori Prof. Yasuo Nakayama Prof. Takuya Hosokai Eri Hisamura Kazuhiro Nakamura Kenshiro Matsuda Dr. Kohei Nakao Prof. Andrew P. Monkman Prof. Ken Albrecht Department of Applied Science for Electronics and Materials Interdisciplinary Graduate School of Engineering Sciences Kyushu University 6-1 Kasuga-Koen Kasuga-shi Fukuoka 816-8580 Japan Contribution: Conceptualization (supporting) Data curation (lead) Formal analysis (lead) Funding acquisition (supporting) Investigation (equal) Visualization (equal) Writing - original draft (lead) MOLFEX Inc. Takano Nishibiraki-cho 34–4 Sakyo-ku Kyoto 606-8103 Japan Contribution: Conceptualization (supporting) Data curation (equal) Formal analysis (equal) Investigation (equal) Methodology (equal) Resources (supporting) Software (supporting) Visualization (supporting) Writing - original draft (supporting) Fukui Institute for Fundamental Chemistry Kyoto University Takano Nishibiraki-cho 34–4 Sakyo-ku Kyoto 606-8103 Japan Department of Molecular Engineering Graduate School of Engineering Kyoto University Nishikyo-ku Kyoto 615-8510 Japan Elements Strategy Initiative for Catalysts & Batteries (ESICB) Kyoto University Kyotodaigaku Katsura Nishikyo-ku Kyoto 615-8245 Japan Contribution: Conceptualization (supporting) Software (supporting) Supervision (equal) Validation (supporting) Writing - review & editing (supporting) Department of Pure and Applied Chemistry Graduate School of Science and Technology Tokyo University of Science 2641 Yamazaki Noda Chiba 278-8510 Japan National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba Central 5 1-1-1 Higashi Tsukuba Ibaraki 305-8565 Japan Contribution: Data curation (supporting) Formal analysis (supporting) Investigation (supporting) Contribution: Supervision (supporting) Writing - review & editing (supporting) Contribution: Conceptualization (supporting) Data curation (supporting) Formal analysis (supporting) Funding acquisition (supporting) Supervision (equal) Writing - review & editing (equal) Institute for Materials Chemistry and Engineering Kyushu University 6-1 Kasuga-Koen Kasuga-shi Fukuoka 816-8580 J

A series of carbazole-dendronized tris(2,4,6-trichlorophenyl)methyl (TTM) radicals have been synthesized. The photophysical properties of dendronized radicals up to the fourth generation were compared systematically to understand how structure–property relationships evolve with generation. The photoluminescence quantum yield (PLQY) was found to increase with the increasing generation, and the fourth generation (G4TTM) in cyclohexane solution showed a PLQY as high as 63 % at a wavelength of 627 nm (in the deep-red region) from the doublet state. The dendron modification strategy also showed a blue-shift of the emission on increasing the generation number, and the photostability was also increased compared to the bare TTM radical.

关键词： Carbazoles Dendrimers Excited Doublet State Luminescencent Materials Stable Radicals

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A Wide Residual Network for Sentiment Classification 18

A Wide Residual Network for Sentiment Classification

引用

2nd International Conference on Deep Learning Technologies, ICDLT 2018

作者： Wen, Yang Xu, An Liu, Wei Chen, Leiting Key Laboratory of Digital Media Technology of Sichuan Province Chengdu China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Dongguan Data Science Software Technology Co. Ltd Dongguan China Chengdu Vocational and Technical College of Industry Chengdu China Institute of Electronic and Information Engineering UESTC in Guangdong Dongguan China

ISBN: (纸本)9781450364737

Recurrent neural network (RNN) is a popular deep learning model for sentiment classification. Most RNN models benefit from the power of the depth of the deep learning network. However, training a sufficiently deep RNN using one word-embedding vector has a problem of feature reuse. In addition, deeper neural networks are more difficult to train. To overcome these problems, in this paper, we describe a sentiment classification model that combines a wide word embedding network architecture and a residual RNN. Firstly, more than one word-embedding vectors are pre-trained to obtain a larger feature space;Secondly, extend the RNN to be a deeper architecture, then employ a residual learning to ease the deep training of networks. Finally, experimental evaluations are conducted on two benchmarks, the results of the proposed networks demonstrate a good applicability for the sentiment classification problem. © 2018 ACM.

关键词： Recurrent neural networks

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GAN-based semi-supervised for imbalanced data classification

GAN-based semi-supervised for imbalanced data classification

引用

International Conference on Information Management (ICIM)

作者： Tingting Zhou Wei Liu Congyu Zhou Leiting Chen School of Computer Science and Engineering Dongguan Data Science software Technology Co. Ltd Dongguan China Chengdu Vocational and Technical College of Industry Dongguan Data Science software Technology Co. Ltd Dongguan China School of Computer Science and Engineering Institute of Electronic and Information Engineering UESTC in Guangdong Dongguan China

Most of the traditional classification algorithms are based on the premise that the datasets are uniformly distributed or roughly equivalent. Once the sample dataset is not balanced , the classification performance drops sharply. To efficiently deal with the imbalance of data, an improved generative adversarial network (GAN) algorithm is proposed in this work . Firstly, we construct artificial samples so that more minority-class's data can be obtained via optimizing GAN loss function. Secondly, we build a fully-connected network for structured data classification. Finally, experimental evaluations are conducted on two open structured-datasets and the results of the proposed algorithm demonstrate a good applicability for the classification of structured data.

关键词： Gallium nitride Generators Classification algorithms Training data models Feature extraction Radio frequency

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