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Polarization-Induced Proton Adsorption and Charge Separation in Pyrene-Based Conjugated Microporous Polymers Via Substituent Regulation for Efficient Photocatalytic Hydrogen Evolution

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SSRN 2023年

作者： Ren, Runtang Jiao, Zhengxu Li, Zhanfeng Tian, Yue Liu, Baoyou Yue, Gang Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province Taiyuan University of Technology Taiyuan030024 China Institute of Carbon Materials College of Materials Science and Engineering Taiyuan University of Technology Taiyuan030024 China Technology Innovation Center Ningxia Sinostar Display Material Co. Ltd. Yinchuan750003 China

Constructing photocatalysts with efficient light-harvesting abilities and charge separation properties is highly promising but still challenging for boosting photocatalytic hydrogen evolution from water. Herein, we report a simple and general polarization strategy through substituent regulation such as fluorination, chlorination and cyanation, to promote the photon capture and charge separation and unveil the latent structure–property–activity relationship in pyrene-based conjugated microporous polymers (CMPs). Notably, the introduction of fluorine, chlorine and cyano substituents onto the well-known full donor pyrene-benzene-based CMP network (Py-B) could induce a strong dipole along C–F/–Cl/–CN bonds and the backbone local polarization enhancement due to their strong electron-withdrawing ability, which afforded CMPs have a variety of superior effects such as narrowing band gaps, expanding optical absorption, improving interfacial wettability and solid-state morphology, and promoting charge separation inside organic photocatalysts. As a result, 1.73/2.50/4.69-fold increases of the hydrogen evolution rates of the –F/–Cl/–CN modified CMPs under visible light (λ > 420 nm) irradiation without Pt co-catalysts can be obtained in comparison with the counterpart Py-B (28.5/41.3/77.4 mmol g−1 h−1 vs 16.5 mmol g−1 h−1). Impressively, we find that the photocatalytic performance of this series of photocatalysts is linearly related to the dipole moment of polymers. Our studies reveal that the backbone local polarization enhancement induced by the substituent regulation could achieve high-performance organic photocatalysts toward solar-to-chemical energy conversion. © 2023, The Authors. All rights reserved.

关键词： Polarization

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A new safety theory: Concept, methodology, and application

A new safety theory: Concept, methodology, and application

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： M. Y. Cai C. J. Liu C. A. van Luttervelt J. W. Wang W. J. Zhang Y. Lin Complex and Intelligent System Research Center East China University of Science and Technology Shanghai China Industrial and Manufacturing Systems Engineering University of Hong Kong Hong Kong China Department of Mechanical and Industrial Engineering Northeastern University Boston USA Faculty of Mechanical Engineering Delft University of Technology Delft Netherlands Department of Mechanical Engineering University of Saskatchewan Saskatoon Canada

ISBN: (纸本)9781467386456

Critical systems are systems that have direct effects on human health and life. Large production systems are an example of the critical system. Safety is a concept that is ubiquitous in our life but has never been clearly defined. A common confusion with safety is that safety is viewed to be the same as reliability. In this paper, we revisit the concept of safety and propose a new approach for design and operation management of critical systems for safety. The new approach puts its foot on the threats to human health and life and an integrated consideration of reliability, robustness and resilience for safety. The new approach for safety is thus called 3R for safety.

关键词： Safety Resilience Robustness Reliability theory Accidents Reliability engineering

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A Subspace-Based Non-Dominated Subset Selection Method

A Subspace-Based Non-Dominated Subset Selection Method

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Congress on Evolutionary Computation

作者： Qingshan Tan Changhe Li Sanyou Zeng Shengxiang Yang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan China School of Computer Science and Informatics De Montfort University Leicester United Kingdom

Environmental selection is an important process in multi-objective evolutionary algorithms (MOEAs). As the evolution progresses, the number of non-dominated solutions increases. This paper is focused on selecting a subset from excess non-dominated solutions for evolutionary or the final output. However, traditional selection methods in classical MOEAs encounter difficulties when dealing with candidate solutions that possess irregular topologies. Although the distance-based subset selection methods are not sensitive to the topologies of the candidate points, they have significant room for reducing computational complexity. In order to address the above issues, a subspace selection method is proposed in this paper. It partitions the objective space into multiple subspaces that have comparable volumes and shapes. The maximal minimum distance of each solution is considered to ensure that the sparsest solution is always chosen first. To save computational costs, only the solutions in the neighboring subspaces are taken into account. The experimental results demonstrate that the proposed subspace selection method outperforms classical selection methods in solving problems with various shapes of the Pareto front.

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Reform and Practice in Experimental Teaching from the View of "Emerging Engineering": Case Study on the Field of Energy and Power Engineering

Reform and Practice in Experimental Teaching from the View o...

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Information Communication Technologies Conference (ICTC)

作者： He Tian Lijian Liu Miao Tian Shimin Zhou Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control National Demonstration Center for Experimental Mechanical and Electrical Engineering Education (Tianjin University of Technology) School of Mechanical Engineering Tianjin University of Technology Tianjin China Tianjin Academy of Educational Science Tianjin China Tianjin Newborn New Energy Technology Co. Ltd Tianjin China

According to the idea of "Emerging Engineering Education" talent training model of Ministry of Education, students should be trained to have "metaphysical" concept, connection, imagination, macro thinking. Project-driven experiment teaching focuses on a project, and the goal is the completion of the project; the student is the center of teaching activities, which is supported by the inquiry process. This study analyzes the significance of the project-driven method in experimental teaching. This paper describes the implementation process of experimental teaching in the field of energy and power engineering in terms of project design, teaching system construction and so on under the project-driven method. By analyzing the results of a questionnaire survey distributed to students of energy and power in the College of Mechanical Engineering at the Tianjin University of technology, it is found that the students are satisfied with the effects of project-driven experimental teaching, and the use of experimental teaching has greatly aroused the students' enthusiasm for learning. The ability of the students to engage in autonomous learning, engineering practice and innovation has been greatly improved, and a good teaching effect has been achieved.

关键词： Training Power engineering Technological innovation Education Solids Communications technology Mechanical engineering

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Role of Black Carbon in Modulating Aerosol Direct Effects Driven by Air Pollution controls During 2013-2017 in China

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SSRN 2022年

作者： Zhang, Fenfen Xing, Jia Ding, Dian Wang, Jiandong Zheng, Haotian Zhao, Bin Qi, Ling Wang, Shuxiao State Key Joint Laboratory of Environmental Simulation and Pollution Control School of Environment Tsinghua University Beijing100084 China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing100084 China Institute for Atmospheric and Earth System Research Faculty of Science University of Helsinki Helsinki00014 Finland School of Atmospheric Physics Nanjing University of Information Science and Technology Nanjing210044 China School of Energy and Environmental Engineering University of Science and Technology Beijing Beijing100083 China

Aerosol direct effects (ADEs) can modulate shortwave radiation as well as atmospheric dynamics and air quality. As the key absorbing component of aerosol, the black carbon (BC) largely determines the aerosol optical properties. Therefore, it is expected that BC emission controls might gain co-benefits from the simultaneous reduction of ADEs. To demonstrate such synergy, we quantified the ADEs changes and role of BC controls in China during 2013-2017 using a regional two-way coupled meteorology chemistry transport model. Results suggest that the control action effectively reduced wintertime PM2.5 concentration (-26.0 μg m-3) and associated ADEs. The influence of ADEs on surface shortwave radiation, 2-meter temperature, and planetary boundary layer height was weakened from -16.7 W m-2, -0.20°C, and -15.4 m in 2013 to -11.3 W m-2, -0.06°C, and -10.7 m in 2017, respectively. The enhancement of SO2, NO2, and PM2.5 concentrations due to ADEs was reduced from +3.1%, +5.2%, and +5.4% in 2013, to +2.6%, +4.5%, and +3.3% in 2017, respectively, demonstrating the extra benefit of air pollution controls by reducing ADEs. The BC emission reduced by 12.5% simultaneously along with the effective controls during 2013-2017. Such BC controls contributes 15.6-60.2% of such changes in the ADEs influence on meteorological variables, and 32.6-41.1% on air pollutants. More specially, the effectiveness of collaborative reduction of BC further reduced surface shortwave radiation in China by 3.6 W m-2 in January and 1.0 W m-2 in July, leading to a more weakened ADEs that bring extra benefits in reducing PM2.5 concentrations by 1.8 μg m-3 in January and 0.3 μg m-3 in July. Apparently, BC played a dominant role in modulating the ADEs and associated influences on meteorology and air quality, suggesting a wise control strategy by targeting absorbing component of PM2.5 reduction to address both air pollution and climate change in the future. © 2022, The Authors. All rights reserved.

关键词： Air quality

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An Electronic Nose for Harmful Gas Early Detection Based on a Hybrid Deep Learning Method H-Crnn

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SSRN 2023年

作者： Mao, Guosheng Zhang, Yanmei Xu, Yang Li, Xiaoyu Xu, Min Zhang, Yiyi Jia, Pengfei School of Electrical Engineering Guangxi University Nanning China Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment Guangxi University Nanning China College of Food Science and Bioengineering Xihua University Chengdu China Guangxi Key Laboratory of Power System Optimization and Energy Technology China

Among harmful gases, carbon monoxide (CO) has posed a significant threat to human safety due to its concealment and harmfulness. Therefore, it’s imperative for the preservation of human safety to implement early detection for CO concentration. However, traditional methods are plagued by the limitations of insufficient accuracy and the incapacity to make early prediction. To address this issue, a novel technique, namely H-CRNN, is presented for electronic nose (E-nose) to perform early prediction of CO concentration, leveraging the strengths of convolutional and recurrent neural network to efficiently capture long-term dependencies within data. Also, shortcut connection and gated attention mechanism is proposed to enhance the capacity to capture crucial features. Furthermore, a linear process unit has been incorporated to handle the scale insensitivity issue. The experimental results show that the proposed H-CRNN outperforms RNN with a notable average reduction of 50.51% in the root relative squared error and 53.8% in the relative absolute error, and exhibits varying degrees of improvement when compared to state-of-the-art algorithms (TCN, TPA-LSTM, STCN, LSTNet, LSTM). Additionally, the H-CRNN achieved an average accuracy rate of 96.42%, surpassing all other algorithms and demonstrating the highest level of performance. Therefore, our work substantiates the proposed H-CRNN as an applicable method for early prediction of CO concentration. © 2023, The Authors. All rights reserved.

关键词： Carbon monoxide

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An Empirical Evaluation of Meta Adaptive Residual Network for Classifying Sensor Drift Samples

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SSRN 2023年

作者： Zhu, Zhengyang Ling, Haikui Zhang, Yiyi Liu, Jiefeng Shuang, Feng Xu, Min Jia, Pengfei School of Electrical Engineering Guangxi University Nanning China Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment Guangxi University Nanning China College of Food Science and Bioengineering Xihua University Chengdu China Guangxi Key Laboratory of Power System Optimization and Energy Technology China

With the advancements in materials and pattern recognition algorithms, electronic nose (E-nose) has been continuously developing and finding increasingly widespread applications. However, due to factors including but not limited to variations in temperature and humidity, as well as chemical and physical interactions among analytes and gases, E-nose is prone to drift during practical usage, leading to decreased accuracy of pattern recognition algorithms. But now, this challenge can be overcome with the help of meta-learning. We applied the model-agnostic meta-learning (MAML) architecture from meta-learning and designed a residual classifier with learnable per-parameter learning rates. Leveraging the ability of ‘learning to learn’, our method do not require a large amount of target domain data and there is no need to repeat multiple training iterations when transferring to any other target domain compared to other unsupervised algorithms, resulting it highly deployable. Additionally, we present a Gini value-based approach to enhance the certainty of model output labels in a multi-task setting. Through the evaluation of multiple experiments, we demonstrate the feasibility of our approach and achieve very high classification accuracy on a publicly available long-term drift dataset compared with other methods. © 2023, The Authors. All rights reserved.

关键词： Electronic nose

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Supervised Drift Sensor Sample Classification Method Based on Meta-Learning

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SSRN 2023年

With the advancements in materials and pattern recognition algorithms, electronic nose (E-nose) has been continuously developing and finding increasingly widespread applications. However, due to factors including but not limited to variations in temperature and humidity, as well as chemical and physical interactions among analytes and gases, E-nose is prone to drift during practical usage, leading to decreased accuracy of pattern recognition algorithms. Currently, the primary methods for addressing the issue of sensor drift in sample classification are semi-supervised learning and unsupervised learning. Supervised learning has been limited in the past due to the need for large amounts of up-to-date samples to retrain the models. But now, this challenge can be overcome with the help of meta-learning. Meta-learning, also known as "learning to learn", aims to equip models with the ability to acquire a learning capability and automatically learn some meta-knowledge. To tackle the challenge of few-shot learning, we applied the model-agnostic meta-learning (MAML) architecture from meta-learning and designed a residual classifier with learnable per-parameter learning rates. Additionally, we present a Gini value-based approach to enhance the certainty of model output labels in a multi-task setting. As a result, we achieved high classification accuracy on a publicly available long-term drift dataset. © 2023, The Authors. All rights reserved.

关键词： Electronic nose

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Lightweight Vision Transformer for Small Data Sets

Lightweight Vision Transformer for Small Data Sets

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Wenxing Fang Yanxu Su Institutes of Physical Science and Information Technology Anhui University Hefei China School of Artificial Intelligence Anhui University Hefei P. R. China Key Laboratory of Measurement and Control of Complex System of Engineering Ministry of Education Southeast University Nanjing P. R. China

With the rapid development of Transformers in the field of computer vision, models based on Transformers have become highly competitive architectures in the area. Although variants of Transformer models have achieved increasing accuracy on image classification tasks, the size of the training set and the number of parameters required by the models have increased dramatically. When dealing with small datasets, such models face problems such as overfitting and undergeneralization, leading to poor accuracy on the test set. We propose a new lightweight vision transformer (LVT) to address these issues. We reconstructed the backbone network, which learns the relationship between pixels through local window self-attention and global self-attention computation. We also use the attention pooling approach to fuse the token sequences generated by the backbone network more meticulously. We trained on the CIFAR-10 and CIFAR-100 datasets from scratch and compared them with a modern convolutional neural network. The experimental results show that LVT outperforms the modern convolutional neural network in terms of accuracy and efficiency. On the test set of CIFAR-10, we have obtained an accuracy of 96.83%, which indicates that our model can effectively solve the problems facing the training of small datasets and has a wide range of application prospects.

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A process simulation-based quantitative HAZOP analysis method

A process simulation-based quantitative HAZOP analysis metho...

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IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Jianlong Chen Xiwei Liu Sifeng Jing Gang Xiong Xiuqin Shang Changjian Cheng The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Chemical Engineering and the Environment Beijing Institute of Technology Beijing China Institute of Smart Education Systems Qingdao Academy of Intelligent Industries Qingdao China Cloud Computing Center Chinese Academy of Sciences Dongguan China Beijing Engineering Research Center for Intelligent Systems and Technology Chinese Academy of Science Beijing China

ISBN: (纸本)9781509029280

Hazard and operability (HAZOP) methodology is an important Process Hazard Analysis (PHA) technique for ensuring safety production in chemical industry. Due to the lacks of accuracy and reliability in manual HAZOP analysis, the quantitative HAZOP analysis has gained more and more attention. In this work, a process simulation-based HAZOP analysis method and its flow chart are proposed. And the proposed method is applied to a steam generation subsystem in an ethylene pyrolysis unit on a dynamic process simulation platform. All deviation parameters of system can be calculated and described quantitatively. The case study shows the proposed method is useful for the effective risk prevention and control measures in a chemical process.

关键词： Analytical models Hazards Manuals Process control Boilers

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