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Deep learning from three-dimensional Lithium-ion battery multiphysics model Part II:Convolutional neural network and long short-term memory integration

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Energy and AI

Energy and AI 2024年第3期17卷 569-578页

作者： Yiheng Pang Anqi Dong Yun Wang Zhiqiang niu renewable Energy resources Lab(rErL) Department of Mechanical and Aerospace EngineeringUniversity of CaliforniaIrvineCaliforniaUSA92697-3975 College of Engineering School of System Design and Intelligent ManufacturingSouthern University of Science and TechnologyChina Department of Aeronautical and Automotive Engineering Loughborough UniversityUnited KingdomLE113TU

Lithium-ion (Li-ion) batteries have emerged as a cornerstone of electric vehicles (EVs), enabling the road transportation towards net zero. The success of electric vehicles largely hinges on the battery performance and safety. It is challenging to test and predict battery performance and safety issues by conventional methods, which are usually time-consuming and expensive, involving significant human and measurement errors. To enable the quick estimation of battery performance and safety, we developed three data-driven machine learning (ML) models, namely a convolutional neural network (CNN), a long short-term memory (LSTM), and a CNN-LSTM to predict battery discharge curves and local maximum temperature (hot spot) under various operating conditions. The developed ML models mitigated data scarcity by employing a three-dimensional multi-physics Li-ion battery model to generate enormous and diverse high-quality data. It was found the CNN-LSTM model outperforms the others and achieved high accuracy of 98.68% to learn discharge curves and battery maximum temperature, owing to the integration of spatial and sequential feature extraction. The battery safety can be improved by comparing the predicted maximum battery temperature against safe temperature threshold. The proposed data development and data-driven ML models are of great potential to provide digital tools for engineering high-performance and safe EVs.

关键词： Li-ion batteries CNN LSTM Integration Performance Hot spot

Investigation of FrP and SFrC Technologies for Efficient Tunnel reinforcement Using the Cohesive Zone Model

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Structural Durability & Health Monitoring 2024年第2期18卷 161-179页

作者： Gang niu Zhaoyang Jin Wei Zhang Yiqun Huang China Communications Construction Investment Development Co. Ltd.Fuzhou350000China rail Transit Branch of China Communications Construction Co. Ltd.Beijing101317China School of Civil Engineering Fujian University of TechnologyFuzhou350118China

Amid urbanization and the continuous expansion of transportation networks,the necessity for tunnel construction and maintenance has become *** this need requires the investigation of efficient,economical,and robust tunnel reinforcement *** paper explores fiber reinforced polymer(FrP)and steel fiber reinforced concrete(SFrC)technologies,which have emerged as viable solutions for enhancing tunnel *** is celebrated for its lightweight and high-strength attributes,effectively augmenting load-bearing capacity and seismic resistance,while SFrC’s notable crack resistance and longevity potentially enhance the performance of tunnel ***,current research predominantly focuses on experimental analysis,lacking comprehensive theoretical *** bridge this gap,the cohesive zone model(CZM),which utilizes cohesive elements to characterize the potential fracture surfaces of concrete/SFrC,the rebar-concrete interface,and the FrP-concrete interface,was employed.A modeling approach was subsequently proposed to construct a tunnel segment model reinforced with either SFrC or ***,the corresponding mixed-mode constitutive models,considering interfacial friction,were integrated into the proposed *** validation and numerical simulations corroborated the accuracy of the proposed ***,this study examined the reinforcement design of tunnel *** a numerical evaluation,the effectiveness of innovative reinforcement schemes,such as substituting concrete with SFrC and externally bonding FrP sheets,was assessed utilizing a case study from the Fuzhou Metro Shield Tunnel Construction Project.

关键词： Tunnel segment FrP SFrC cohesive zone model constitutive model fracture process

recent advances in multimodal sensing integration and decoupling strategies for tactile perception

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Materials Futures 2024年第2期3卷 85-103页

作者： Huijun Kong Weiyan Li Zhongqian Song Li niu School of Chemical Engineering and Technology Sun Yat-sen UniversityZhuhai 519082People’s Republic of China School of Chemistry and Pharmaceutical Engineering c/o College of Artificial Intelligence and Big Data for Medical SciencesShandong First Medical University&Shandong Academy of Medical SciencesJinan 250117People’s Republic of China

Human skin perceives external environmental stimulus by the synergies between the subcutaneous tactile *** electronics with multiple sensing capabilities by mimicking the function of human skin are of significance in health monitoring and artificial *** last decade has witnessed unprecedented development and convergence between multimodal tactile sensing devices and soft *** these advances,traditional flexible electronics achieve multimodal tactile sensing for pressure,strain,temperature,and humidity by integrating monomodal sensing devices *** strategy results in high energy consumption,limited integration,and complex manufacturing *** multimodal sensors and crosstalk-free sensing mechanisms have been proposed to bridge the gap between natural sensory system and artificial perceptual *** this review,we provide a comprehensive summary of tactile sensing mechanism,integration design principles,signal-decoupling strategies,and current applications for multimodal tactile ***,we highlight the current challenges and present the future perspectives to promote the development of multimodal tactile perception.

关键词： multimodal tactile sensing integration multifunctional materials and mechanisms signal decoupling applications of multimodal sensory system

Therapeutic potentials of peptide-derived nanoformulations in atherosclerosis:present status and future directions

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International Journal of Smart and Nano Materials 2024年第3期15卷 610-651页

作者： xue Liu Weijiao Wang Qiang Li Hongtao niu Weili Zhang Department of Cardiovascular Medicine Yantaishan HospitalYantaiChina Department of Otolaryngology Yantaishan HospitalYantaiChina Department of Geriatric Medicine Yantaishan HospitalYantaiChina

Atherosclerosis is a severe cardiovascular disease followed by the accumulation of atherosclerotic plaques within the lumen of blood vessels resulting in reduced blood flow thus initiating a series of *** therapies for atherosclerosis encounter multiple chal-lenges,especially difficulty in precisely concentrating in certain affected regions and the potential for unwanted side ***,scientists are focused on developing nanoformulations for atherosclerosis diagnosis and ***-based nanomedi-cines improve conventional therapies by offering improved structural and therapeutic stability and enabling target-specific *** inherent biocompatibility and biodegradability additionally render them desirable materials intended for in vivo *** review manu-script aims to provide an in-depth overview of peptide-based nano-medicines for atherosclerosis,focusing on targeted cells like endothelial cells,macrophages,and monocytes and their interaction with different plaque ***,the manuscript also highlights the latest progress in multimodal techniques and provides a comprehensive overview of limitations associated with their practical implementation.

关键词： Atherosclerosis anti-atherosclerotic drugs bioavailability peptide-based nanomedicines drug targeting

Efficient and robust CNN-LSTM prediction of flame temperature aided light field online tomography

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Science China(Technological Sciences) 2024年第1期67卷 271-284页

作者： niu ZhiTian QI Hong SUN AnTai rEN YaTao HE MingJian GAO BaoHai School of Energy Science and Engineering Harbin Institute of TechnologyHarbin 150001China Key Laboratory of Aerospace Thermophysics Ministry of Industry and Information TechnologyHarbin 150001China

Light field tomography,an optical combustion diagnostic technology,has recently attracted extensive attention due to its easy implementation and ***,the conventional iterative methods are high data throughput,low efficiency and time-consuming,and the existing machine learning models use the radiation spectrum information of the flame to realize the parameter field measurement at the current *** is still an offline measurement and cannot realize the online prediction of the instantaneous structure of the actual turbulent combustion *** this work,a novel online prediction model of flame temperature instantaneous structure based on deep convolutional neural network and long short-term memory(CNN-LSTM)is *** method uses the characteristics of local perception,shared weight,and pooling of CNN to extract the threedimensional(3D)features of flame temperature and outgoing radiation ***,the LSTM is used to comprehensively utilize the ten historical time series information of high dynamic combustion flame to accurately predict 3D temperature at three future moments.A chaotic time-series dataset based on the flame radiation forward model is built to train and validate the performance of the proposed CNN-LSTM *** is proven that the CNN-LSTM prediction model can successfully learn the evolution pattern of combustion flame and make accurate predictions.

关键词： temperature prediction convolutional neural network long short-term memory light field imaging online tomography

Liquid–liquid phase separation in plants:Advances and perspectives from model species to crops

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Plant Communications 2024年第1期5卷 24-40页

作者： Qianwen Liu Wenxuan Liu Yiding niu Tao Wang Jiangli Dong College of Biological Sciences China Agricultural UniversityBeijing 100193China College of Life Sciences Henan Agricultural UniversityZhengzhou 450002China Key Laboratory of Forage and Endemic Crop Biology Ministry of EducationSchool of Life SciencesInner Mongolia UniversityHohhot 010021China

Membraneless biomolecular condensates play important roles in both normal biological activities and re-sponses to environmental stimuli in living ***‒liquid phase separation(LLPS)is an organi-zational mechanism that has emerged in recent years to explain the formation of biomolecular *** the past decade,advances in LLPS research have contributed to breakthroughs in *** contrast,although LLPS research in plants has progressed over the past 5 years,it has been concentrated on the model plant Arabidopsis,which has limited relevance to agricultural *** this review,we provide an overview of recently reported advances in LLPS in plants,with a particular focus on photomorphogenesis,flowering,and abiotic and biotic stress *** propose that many potential LLPS proteins also exist in crops and may affect crop growth,development,and stress *** possibility presents a great challenge as well as an opportunity for rigorous scientific research on the biological functions and applications of LLPS in crops.

关键词： biomolecular condensates crops intrinsic disordered proteins LLPS potential prediction

A survey on the network models applied in the industrial network optimization

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Science China(Information Sciences) 2024年第2期67卷 85-103页

作者： Chao DONG xiaoxiong xIONG Qiulin xUE Zhengzhen ZHANG Kai niu Ping ZHANG Key Laboratory of Universal Wireless Communications Ministry of EducationBeijing University of Posts and Telecommunications Smart City College Beijing Union University

Network architecture design is critical for optimizing industrial networks. Network architectures can be classified into small-scale networks and large-scale networks based on scale. Graph theory is an efficient mathematical tool for network topology modeling. For small-scale networks, their structure often has regular topology. For large-scale ones, the current body of work mainly focuses on random characteristics of network nodes and edges. recently, widely used models include random networks, small-world networks,and scale-free networks. In this study, starting from the scale of the network, network modeling methods based on graph theory as well as their industrial applications, are summarized and analyzed. Moreover, a novel network performance metric, called system entropy, is proposed. From the perspective of mathematical properties, an analysis of its non-negativity and concavity is performed. The advantage of system entropy is that it can cover the existing regular networks, random networks, small-world networks, and scale-free networks, and has strong generality. The simulation results reveal that this proposed metric can achieve the comparison of various industrial networks under different models.

关键词： industrial network small-scale network large-scale network graph theory system entropy

Impact of Ni particle size on CO_(2)activation and CO formation during reforming process:A density functional theory study

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Frontiers in Energy 2024年第4期18卷 525-534页

作者： Juntian niu Shengzhuo CHEN xianrong ZHENG Haiyu LIU Yan JIN Jingyu rAN College of Electrical and Power Engineering Taiyuan University of TechnologyTaiyuan 030024China Key Laboratory of Low-grade Energy Utilization Technologies and Systems(Ministry of Education) Chongqing UniversityChongqing 400044China

In recent years,the dry reforming of methane(DrM)reaction has gained widespread attention due to its effective utilization of two major greenhouse *** Ni-based catalysts for DrM exhibit a strong dependence on particle size,however,the reaction mechanisms involved remain *** this work,the effect of metal particle size on CO_(2)activation and CO formation was explored in the DrM reaction using the density functional ***/MgO(x=13,25,37)was constructed to investigate the CO_(2)activation and the formation of CO during the DrM *** is found that CO_(2)is more inclined to undergo chemisorption on Nix/MgO before *** the variation in particle size,the main activation pathway of CO_(2)on the catalyst *** the smallest Ni13/MgO,CO_(2)tends to directly dissociate,while on the larger Ni25/MgO and Ni37/MgO,the hydrogenation dissociation of CO_(2)is more kinetically *** to Ni13/MgO and Ni37/MgO,the oxidation of surface C atoms and the oxidation of CH occur more readily on Ni25/*** indicates that C atoms are less likely to form on Ni25 particle and are more easily to be *** some extent,the results suggest that Ni25/MgO exhibits superior resistance to carbon formation.

关键词： particle size Ni/MgO catalyst CO_(2)activation CO formation

Facile Synthesis of Polyisothioureas via Alternating Copolymerization of Aziridines and Isothiocayanates

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Chinese Journal of Polymer Science 2024年第3期42卷 292-298,I0005页

作者： Hao-Tian Zhang Ming-xin niu Qi Zhang Chen-Yang Hu xuan Pang Key Laboratory of Polymer Ecomaterials Changchun Institute of Applied ChemistryChinese Academy of SciencesChangchun 130022China Department of Materials Science and Engineering Jilin UniversityChangchun 130025China School of Applied Chemistry and Engineering University of Science and Technology of ChinaHefei 230026China

Isothiourea is an important class of sulfur-containing molecules showing unique catalytic and biological activities. As such,polyisothiourea is envisioned to be an interesting type of polymer that potentially exhibits a number of interesting properties. However, there is no access to synthesizing well-defined polyisothiourea, and currently isothiourea-containing polymers are mainly prepared by immobilizing onto other polymer's side chain. Herein, we report the first facile synthesis of polyisothioureas via alternating copolymerization of aziridines and isothiocayanates. Mediated by the catalytic system of phosphazene superbases/alcohol, a broad scope of aziridines and isothiocayanates could be transformed into polyisothioureas with adjustable substitutions(11 examples). The structures of obtained polyisothioureas were fully characterized with ^(1)H-NMr, ^(13)C-NMr, and ^(1)H-^(13)C HMBC NMr. Moreover, the polyisothioureas show tunable thermal properties depending on substitutions on the isothiourea linkages. The novel structure of these polyisothioureas will enable a powerful platform for the discovery of nextgeneration functional plastics.

关键词： Polyisothioureas Alternative copolymer Aziridines Isothiocayanates