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Novel titanium vanadate with superior Na^(+) transport kinetics for rapid charging and low-temperature sodium ion batteries

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Green Energy & Environment 2025年第2期10卷 374-381页

作者： Dan Lv Liehao Wei Cheng Wang Mingyue Wang Zhongchao Bai Yameng Fan Dongdong Wang Nana Wang Jian Yang Key Laboratory of Advanced Ceramics and Machining Technology(Ministry of Education) School of Materials Science and EngineeringTianjin UniversityTianjin300072China Key Laboratory of Colloid and Interface Chemistry Ministry of EducationSchool of Chemistry and Chemical EngineeringShandong UniversityJinan250100China Tianjin Key Lab of Indoor Air Environmental Quality Control School of Environmental Science and TechnologyTianjin UniversityTianjin300072China Institute for Superconducting and Electronic Materials University of WollongongWollongongAustralia Institute of Energy Materials Science(IEMS) University of Shanghai for Science and Technology516 Jungong RoadShanghai200093China

Sodium-ion batteries(SIBs)hold great promise for large-scale energy storage in the post-lithium-ion battery era due to their high rate performance and long lifespan,although their sluggish Na^(+) transformation kinetics still require *** by the excellent electrochemical performance of titanium-based anode materials,here,we present a novel titanium vanadate@carbon(TVO@C)material as anode for *** TVO@C material is synthesized via a facile coprecipitation method,with the following annealing process in an acetylene *** opened ion channel and the oxygen vacancies within TVO@C facilitate the diffusion of Na^(+) ions,reducing their diffusion ***,an ultrahigh rate of 100 A g^(-1)and long life of 10,000 cycles have been ***,the TVO@C electrode exhibits stable performance,not only at room temperature,but also at temperatures as low as 20 *** TVO@CjjNa_(3)V_(2)(PO_(4))_(3)@C full cells have also achieved stable discharge/charge for 500 *** is believed that this strategy provides new insight into the development of advanced electrodes and provides a new opportunity for constructing novel high rate electrodes.

关键词： Anode High rate Titanium vanadate Sodium ion batteries

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Influence Function Based Off-policy Q-learning control for Markov Jump Systems

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International Journal of control, Automation and Systems 2025年第5期23卷 1411-1420页

作者： Zou, Yuling Wen, Jiwei Xue, Huiwen Luan, Xiaoli Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) the School of Internet of Things Engineering Jiangnan University Wuxi China

This paper presents an off-policy Q-learning approach based on influence function for addressing H∞ control of Markov jump systems. Unlike existing literatures, the mode classification and parallel update method is developed to directly decouple the relationship among matrices across different modes, tackling the most challenging aspect of this issue. Subsequently, we utilize the off-policy algorithm to derive the optimal policy, which allows for efficient learning without the need to follow the current policy being improved. This approach is particularly advantageous as it enables the algorithm to explore and evaluate different policies from historical data, thus circumventing the limitations associated with specific forms of disturbance updates. Moreover, the influence function is employed for data cleansing during the learning process, thereby enabling a more efficient learning period. A numerical example and a DC motor model are presented to illustrate the validity of the proposed method.

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Differentially Private Opinion Dynamics of Influence Networks

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IEEE Transactions on control of Network Systems 2025年

作者： Wu, Guanglei Zhang, Wenbing Mao, Shuai Wu, Xiaotai Tang, Yang Yangzhou University School of Mathematical Sciences Jiangsu225002 China Nantong University Department of Electrical Engineering Nantong226019 China Anhui Polytechnic University Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment Ministry of Education Wuhu241000 China East China University of Science and Technology Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education Shanghai200237 China

In this paper, a unified influence networks model incorporating differential privacy mechanisms (DPMs), called the differentially private opinion dynamics (DPODs) model is proposed. In this model, each individual uses protected opinions rather than the private opinions of his/her neighbors to update his/her private opinions, where the protected opinion of an individual is a blend of private opinions and random noise following Laplace distribution. Building on stochastic analysis techniques and matrix theory, we show that the influence network under consideration converges under specific conditions governing individual sensitivities and interaction weights. In addition, the statistical properties related to convergence accuracy are established by utilizing the Markov inequality to estimate a lower bound on the probability of all individuals' final opinions converging to a neighborhood formed by their initial opinions' convex hull. We further conduct a differential privacy analysis to validate the efficacy of the proposed DPMs in safeguarding the private opinions of all individuals. Finally, two examples including one of the Karate-Club networks are provided to shed new light on the effectiveness of the theoretical results. © 2014 IEEE.

关键词： Differential privacy

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Robustness of gross primary production estimation from long-term reconstructed solar-induced chlorophyll fluorescence varies with greenness on a global scale

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Journal of Applied Remote Sensing 2025年第1期19卷

作者： Fu, Lijiang Xia, Qian Tang, Hao Chen, Junqing Tan, Jinglu Guo, Ya Jiangnan University Ministry of Education Key Laboratory of Advanced Process Control for Light Industry Wuxi China Changshu Institute of Technology School of Electrical Engineering and Automation Changshu China University of Missouri Department of Chemical and Biomedical Engineering ColumbiaMO United States

Long-term reconstructed solar-induced chlorophyll fluorescence (SIF) derived from raw gridded SIF has been used for the estimation of gross primary production (GPP), but the robustness of the spatial relationship may vary from location to location. We examined the often-used linear relationship between GPP and SIF in terms of R2 values for varied locations globally using three GPP datasets (FLUXCOM, VPM, PML) and three long-term reconstructed monthly SIF datasets (CSIF, SIF005, and RTSIF). The results show that the R2 value is a concave function of vegetation greenness level (NDVI) on an annual or seasonal basis. The average R2 is over 0.8 in areas where the annual average NDVI is in the range of 0.4 to 0.6, whereas the R2 is much lower where the annual average NDVI is less than 0.2 or greater than 0.8. Prediction of GPP or SIF by three methods from five major environmental variables revealed greater uncertainties in GPP and/or SIF at low or high greenness levels as an apparent cause of the low R2. The results offer useful insights into how global GPP may be effectively estimated from multi-satellite measured SIF. © 2025 Society of Photo-Optical Instrumentation Engineers (SPIE).

关键词： Optical correlation

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Multi-scale feature fused stacked autoencoder and its application for soft sensor modeling

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Chinese Journal of chemical Engineering 2025年 81卷 241-254页

作者： Li, Zhi Xia, Yuchong Long, Jian Liu, Chensheng Zhang, Longfei State Key Laboratory of Industrial Control Technology East China University of Science and Technology Shanghai 200237 China Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China Huzhou Institute of Industrial Control Technology Huzhou313099 China Engineering Research Center of Process System Engineering Ministry of Education East China University of Science and Technology Shanghai200237 China

Deep Learning has been widely used to model soft sensors in modern industrial processes with nonlinear variables and uncertainty. Due to the outstanding ability for high-level feature extraction, stacked autoencoder (SAE) has been widely used to improve the model accuracy of soft sensors. However, with the increase of network layers, SAE may encounter serious information loss issues, which affect the modeling performance of soft sensors. Besides, there are typically very few labeled samples in the data set, which brings challenges to traditional neural networks to solve. In this paper, a multi-scale feature fused stacked autoencoder (MFF-SAE) is suggested for feature representation related to hierarchical output, where stacked autoencoder, mutual information (MI) and multi-scale feature fusion (MFF) strategies are integrated. Based on correlation analysis between output and input variables, critical hidden variables are extracted from the original variables in each autoencoder's input layer, which are correspondingly given varying weights. Besides, an integration strategy based on multi-scale feature fusion is adopted to mitigate the impact of information loss with the deepening of the network layers. Then, the MFF-SAE method is designed and stacked to form deep networks. Two practical industrial processes are utilized to evaluate the performance of MFF-SAE. Results from simulations indicate that in comparison to other cutting-edge techniques, the proposed method may considerably enhance the accuracy of soft sensor modeling, where the suggested method reduces the root mean square error (RMSE) by 71.8%, 17.1% and 64.7%, 15.1%, respectively. © 2025 chemical Industry and Engineering Society of China, and chemical Industry Press Co., Ltd.

关键词： Frequency estimation

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Error Bounds Revisited, and How to Use Bayesian Statistics While Remaining a Frequentist

Error Bounds Revisited, and How to Use Bayesian Statistics W...

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Ning Xu Christopher M. Foster Jonathan H. Manton Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) School of Internet of Things Engineering Jiangnan University Wuxi PR China Department of Electrical and Electronic Engineering The University of Melbourne Parkville Australia

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Signal processing makes extensive use of point estimators and accompanying error bounds. These work well up until the likelihood function has two or more high peaks. When it is important for an estimator to remain reliable, it becomes necessary to consider alternatives, such as set estimators. An obvious first choice might be confidence intervals or confidence regions, but there can be difficulties in computing and interpreting them (and sometimes they might still be blind to multiple peaks in the likelihood). Bayesians seize on this to argue for replacing confidence regions with credible regions. Yet Bayesian statistics require a prior, which is not always a natural part of the problem formulation. This paper demonstrates how a reinterpretation of the prior as a weighting function makes an otherwise Bayesian estimator meaningful in the frequentist context. The weighting function interpretation also serves as a reminder that an estimator should always be designed in the context of its intended application; unlike a prior which ostensibly depends on prior knowledge, a weighting function depends on the intended application. This paper uses the time-of-arrival (TOA) problem to illustrate all these points. It also derives a basic theory of region-based estimators distinct from confidence regions.

关键词： Accuracy Buildings Signal processing Acoustics Bayes methods Reliability Speech processing Guidelines

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A production planning benchmark for real-world refinery-petrochemical complexes

arXiv

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arXiv 2025年

作者： Du, Wenli Wang, Chuan Fan, Chen Li, Zhi Zhong, Yeke Kang, Tianao Liang, Ziting Yang, Minglei Qian, Feng Dai, Xin State Key Laboratory of Industrial Control Technology East China University of Science and Technology Shanghai200237 China Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China

To achieve digital intelligence transformation and carbon neutrality, effective production planning is crucial for integrated refinery-petrochemical complexes. Modern refinery planning relies on advanced optimization techniques, whose development requires reproducible benchmark problems. However, existing benchmarks lack practical context or impose oversimplified assumptions, limiting their applicability to enterprise-wide optimization. To bridge the substantial gap between theoretical research and industrial applications, this paper introduces the first open-source, demand-driven benchmark for industrial-scale refinery-petrochemical complexes with transparent model formulations and comprehensive input parameters. The benchmark incorporates a novel port-stream hybrid superstructure for modular modeling and broad generalizability. key secondary processing units are represented using the delta-base approach grounded in historical data. Three real-world cases have been constructed to encompass distinct scenario characteristics, respectively addressing (1) a stand-alone refinery without integer variables, (2) chemical site integration with inventory-related integer variables, and (3) multi-period planning. All model parameters are fully accessible. Additionally, this paper provides an analysis of computational performance, ablation experiments on delta-base modeling, and application scenarios for the proposed benchmark. © 2025, CC BY-NC-SA.

关键词： Refining

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Scatter Search Based Particle Swarm optimization Algorithm for Earliness/Tardiness Flowshop Scheduling with Uncertainty

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International Journal of Automation and computing 2016年第3期13卷 285-295页

作者： Jia-Can Geng Zhe Cui Xing-Sheng Gu Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of EducationEast China University of Science and Technology

Considering the imprecise nature of the data in real-world problems, the earliness/tardiness （E/T） fiowshop scheduling problem with uncertain processing time and distinct due windows is concerned in this paper. A fuzzy scheduling model is established and then transformed into a deterministic one by employing the method of maximizing the membership function of middle value. Moreover, an effective scatter search based particle swarm optimization （SSPSO） algorithm is proposed to minimize the sum of total earliness and tardiness penalties. The proposed SSPSO algorithm incorporates the scatter search （SS） algorithm into the frame of particle swarm optimization （PSO） algorithm and gives full play to their characteristics of fast convergence and high diversity. Besides, a differential evolution （DE） scheme is used to generate solutions in the SS. In addition, the dynamic update strategy and critical conditions are adopted to improve the performance of SSPSO. The simulation results indicate the superiority of SSPSO in terms of effectiveness and efficiency.

关键词： Earliness/tardiness (E/T) scheduling fuzzy modeling scatter search (SS) particle swarm optimization (PSO).

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Interfacial Polarization-Enabled High Anti-Interference for Fiber Pressure Sensors

SSRN

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SSRN 2025年

作者： Liu, Lu Huang, Xin Zhao, Kezheng Jiang, Gaoming Cong, Honglian Ramakrishna, Seeram He, Haijun Engineering Research Center for Knitting Technology Ministry of Education Jiangnan University Wuxi214122 China Key Laboratory of Advanced Process Control for Light Industry Ministry of Education Jiangnan University Wuxi214122 China Faculty of Engineering Department of Mechanical Engineering National University of Singapore Singapore117574 Singapore

Fiber pressure sensors possess the ability to be integrated into intelligent fabrics or garments due to their flexible one-dimensional (1D) size, thus playing a crucial role in wearable electronics and robotics. However, due to the proximity effect, the signal accuracy of the reported capacitive sensors is inevitably degraded by interference from the surrounding environment. Therefore, minimizing interference while maintaining excellent sensing performance is a challenge for fiber capacitive sensors. One straightforward method to enhance anti-interference capability involves raising the initial capacitance. Based on it, this study proposed an anti-interference fiber capacitive sensor by enhancing the interfacial polarization effect between the nanofiller and the matrix. The modified CNTs@PDA with a core-shell structure increased the polarization interface as well as the charge storage capacity of the composite dielectric layer by improving the nanofillers’ dispersion, thereby significantly increasing the sensor’ initial capacitance to 1.6 times. This enables the sensor an ideal signal-to-noise ratio (SNR), reflecting negligible capacitive signal fluctuations when electromagnetic interference and proximity to objects are present. Moreover, with the synergy of interfacial polarization effect and excellent elastic recovery, the sensor achieved a linear response with high sensitivity in the ultra-high pressure range of 3500 kPa and long-term stability over 5000 cycles. With the flexible 1D structure, it was easily knitted into sensing textiles, and a 2D pressure recognization fabric and a traditional Chinese medicine (TCM) foot massage sock system were prepared by circuit integration. This demonstrates the potential application of high anti-interference fiber flexible pressure sensors in wearable electronic textiles. © 2025, The Authors. All rights reserved.

关键词： Flexible electronics

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MOFs-based porous liquids for CO2 capture and utilization

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Green Energy and Environment 2025年

作者： Wang, Xun Liu, Yuxi Dai, Hongxing Wei, Zhen Xie, Shaohua Deng, Jiguang Beijing Key Laboratory for Green Catalysis and Separation Key Laboratory of Beijing on Regional Air Pollution Control Key Laboratory of Advanced Functional Materials Education Ministry of China College of Materials Science and Engineering Beijing University of Technology Beijing100124 China Department of Chemical and Environmental Engineering University of California RiversideCA92521 United States

Due to the greenhouse effect caused by carbon dioxide (CO2) emission, much attention has been paid for the removal of CO2. Porous liquids (PLs), as new type of liquid materials, have obvious advantages in mass and heat transfer, which are widely used in gas adsorption and separation. Metal–organic frameworks (MOFs) with the merit like large surface area, inherent porous structure and adjustable topology have been considered as one of the best candidates for PLs construction. This review presents the state-of-the-art status on the fabrication strategy of MOFs-based PLs and their CO2 absorption and utilization performance, and the positive effects of porosity and functional modification on the absorption-desorption property, selectivity of target product, and regeneration ability are well summarized. Finally, the challenges and prospects for MOFs-based PLs in the optimization of preparation, the coupling of multiple removal techniques, the in situ characterization methods, the regeneration and cycle stability, the environmental impact as well as expansion of application are proposed. © 2025 Institute of process Engineering, Chinese Academy of Sciences

关键词： Carbon capture and utilization

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