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Enhancing through-plane thermal conductivity of fluoropolymer composite by developing in situ nano-urethane linkage at graphene–graphene interface

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Nano Research 2020年第10期13卷 2741-2748页

作者： Muhammad Maqbool Haichang Guo Akbar Bashir Ali Usman Adeel YAbid Guansong He Yanjuan Ren Zeeshan Ali Shulin Bai Department of Materials Science and Engineering Key Laboratory of High Eenergy Density Physics Simulation(HEDPS)Center of Applied Physics and Technology(CAPT)/Laboratory of Turbulence and Complex System(LTCS)Key Laboratory of Polymer Chemistry and Physics of Ministry of EducationCollege of EngineeringPeking UniversityBejing 100871China Institute of Chemical Materials Chinese Academy of Engineering Physics(CA EP)Mianyang 621900China School of Chemical and Materials Engineering(SCME) National University of Sciences and Technology(NUST)Islamabad 4000Pakistan

Attributed to the intense development and complexity in electronic devices,energy dissipation is becoming more essential *** carbonaceous materials particularly graphene(Gr)-based thermal interface materials(TIMs)are exceptional in heat ***,because of the anisotropic behavior of Gr in composites,the TIMs having outstanding through-plane thermal conductivity(┴TC)are needed to fulfill the upcoming innovation in numerous *** order to achieve this,herein,nano-urethane linkage-based modified Gr and carbon fibers architecture termed as nanourethane linkage(NUL)-Gr/carbon fibers(CFs)is ***,toluene diisocyanate is utilized to develop a novel but simple NUL to shape a new interface between graphene ***,the prepared composite of NUL-Gr/CFs with polyvinylidene fluoride matrix shows outstanding performance in heat *** to the unique structure of NUL-Gr/CFs,an unprecedented value of┴TC(~7.96 W·m^–1·K^–1)is achieved at a low filler fraction of 13.8 wt.%which translates into an improvement of^3,980%of pristine *** achieved outcomes elucidate the significance of the covalent interaction between graphene sheets as well as strong bonding among graphene and matrix in the composites and manifest the potential of proposed NUL-Gr/CFs architecture for practical applications.

关键词： graphene thermal interface materials polymer composites

Estimating the Lateral Motion States of an Underwater Robot by Propeller Wake Sensing Using an Artificial Lateral Line

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arXiv 2024年

作者： Wang, Jun Zhao, Dexin Zhao, Youxi Zhang, Feitian Shen, Tongsheng The Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing China The National Innovation Institute of Defense Technology Beijing China The Department of Mechanics and Engineering Science College of Engineering Peking University Beijing China The Department of Advanced Manufacturing and Robotics The State Key Laboratory of Turbulence and Complex Systems College of Engineering Peking University Beijing China

The artificial lateral line (ALL), comprising distributed flow sensors, has been successful in sensing motion states of bioinspired underwater robots like robotic fish. However, its application to robots driven by rotating propellers remains unexplored due to the complexity of propeller wake flow. This paper investigates the feasibility of using ALL to sense propeller wake for underwater robot leader-follower formation. To estimate the lateral motion states of a leader propeller, this paper designs a multi-output deep learning network that extracts temporal and spatial features from distributed pressure measurements of propeller wake. Extensive experiments are conducted on a designed testbed, the results of which validate the effectiveness of the proposed propeller wake sensing method. Copyright © 2024, The Authors. All rights reserved.

关键词： Wakes

Addressing Non-stationarity with Stochastic Trend in the Context of Limited Time Series Data: An Experimental Survey

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Research Square

Research Square 2025年

作者： Batoure Bamana, Apollinaire Sokdou Bila Lamou, Yannick Fotsa-Mbogne, David Jaures Shafiee Kamalabad, Mahdi Department of Computer Engineering University Institute of Technology The University of Ngaoundere Cameroon Department of Robotic and Industrial Computing School of Chemical Engineering and Mineral Industries The University of Ngaoundere Cameroon Department of Mathematics and Computer Science Faculty of Science The University of Ngaoundere Cameroon Laboratory of Mathematics Computer Science and Applications Department of Mathematics and Computer Science National Higher School of Agro-Industrial Sciences The University of Ngaoundéré Cameroon Laboratory of Mathematics and Computer Science Department of Mathematics Statistics and Computer Science Faculty of Science The University of Bertoua Cameroon Department of Methodology and Statistics Faculty of Social and Behavioural Sciences Utrecht University Utrecht Netherlands Centre for Complex Systems Studies Utrecht University Utrecht Netherlands

Stationarity in time series is a key property for practical data analysis, inferences, and predictions particularly in biosciences. Stationarity can be either deterministic or stochastic. If a time series data is not stationary, it can be rendered stationary through detrending or differentiation techniques. Differentiation can be performed in either an integer or fractional form. This paper investigates non-stationarity in time series data, focusing specifically on stochastic trends characterised by a unit root. It hypothesises that fractional differentiation can enhance forecast accuracy for datasets with limited volume. For experiments, 24 series corresponding to weekly Malaria and Typhoid Fever from Adamawa Region (Cameroon) are analysed and forecasted. Each series comprises 156 observations covering January 2021 to December 2023. After collecting, checking and classifying the data, four forecasting models, Auto Regressive Integrated Moving Average (ARIMA), Fractional ARIMA (ARFIMA), Long Short-Term Memory (LSTM), and the proposed Fractional Differencing and LSTM (FD-LSTM), are implemented. The models' performances are evaluated using Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Coefficient of determination (R2) metrics, which inform further analysis and recommendations. Results reveal that ARFIMA outperformed the ARIMA by 93% in training and 100% in testing. Similarly, FD-LSTM achieved a 100% improvement over LSTM in training and testing. These findings underscore the value of achieving stationarity through fractional differentiation, enhancing model performance and providing a robust framework for forecasting in datasets with limited observations. © 2025, CC BY.

关键词： Time series

Distributed Partial Quantum Consensus of Qubit Networks with Connected Topologies

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arXiv 2024年

作者： Jin, Xin Cao, Zhu Tang, Yang Kurths, Jürgen The Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China The Research Institute of Intelligent Complex Systems Fudan University Shanghai200433 China The Potsdam Institute for Climate Impact Research Potsdam14473 Germany Institute of Physics Humboldt University of Berlin Berlin12489 Germany

In this paper, we consider the partial quantum consensus problem of a qubit network in a distributed view. The local quantum operation is designed based on the Hamiltonian by using the local information of each quantum system in a network of qubits. We construct the unitary transformation for each quantum system to achieve the partial quantum consensus, i.e., the directions of the quantum states in the Bloch ball will reach an agreement. A simple case of two-qubit quantum systems is considered first, and a minimum completing time of reaching partial consensus is obtained based on the geometric configuration of each qubit. Furthermore, we extend the approaches to deal with the more general N-qubit networks. Two partial quantum consensus protocols, based on the Lyapunov method for chain graphs and the geometry method for connected graphs, are proposed. The geometry method can be utilized to deal with more general connected graphs, while for the Lyapunov method, the global consensus can be obtained. The numerical simulation over a qubit network is demonstrated to verify the validity and the effectiveness of the theoretical results. © 2024, CC BY.

关键词： Lyapunov methods

Fatigue-Resistant Adhesion Through High Energy Barriers

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SSRN

SSRN 2024年

作者： Li, Qi Ma, Chao He, Yunfeng Lv, Pengyu Duan, Huiling Hong, Wei Shenzhen Key Laboratory of Soft Mechanics & Smart Manufacturing Department of Mechanics and Aerospace Engineering Southern University of Science and Technology Guangdong Shenzhen518055 China State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science BIC-ESAT College of Engineering Peking University Beijing100871 China Shenyang Aircraft Corporation Liaoning Shenyang110850 China CAPT HEDPS and IFSA Collaborative Innovation Center of MoE Peking University Beijing100871 China

The applications of soft materials in various fields often require interfacial adhesion to sustain prolonged static or cyclic loads, whereas most existing adhesives are susceptible to fatigue failure. Unlike in a quasistatic debonding process, which depends more on the average resistance, the key to preventing fatigue crack propagation is to build up high energy barriers locally. Herein, we invoke three types of structural designs to induce large energy barriers at the interface to achieve fatigue-resistant adhesion. By varying the local bending stiffness of the backing layer, locally altering the fracture mode through kirigami patterns, or hindering crack initiation with simple edge notches, we enhanced the fatigue thresholds of various adhesives against peeling by several orders of magnitude, reaching record-breaking values. To verify the proposed mechanism and reveal the details of these remarkable enhancements, we develop theoretical models to study the peeling processes. Based entirely on structural design, the proposed mechanism is non-material-specific and universally applicable to various intermolecular interactions under any harsh environment, such as high temperature, high humidity, and physiological environments. We envision that the strategy and methodologies presented can pave the avenue of future adhesion designs for both durability and reliability. © 2024, The Authors. All rights reserved.

关键词： Adhesion

An integrated framework for accelerating reactive flow simulation using GPU and machine learning models

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arXiv 2023年

作者： Mao, Runze Wang, Yingrui Zhang, Min Li, Han Xu, Jiayang Dong, Xinyu Zhang, Yan Chen, Zhi X. State Key Laboratory of Turbulence and Complex Systems Aeronautics and Astronautics College of Engineering Peking University Beijing100871 China Beijing100080 China Shanghai SenseTime Intelligent Technology Co. LTD Shanghai200233 China CAEP Software Center for High Performance Numerical Simulation Beijing100088 China Institute of Applied Physics and Computational Mathematics Beijing100088 China

Recent progress in artificial intelligence (AI) and high-performance computing (HPC) have brought potentially game-changing opportunities in accelerating reactive flow simulations. In this study, we introduce an open-source computational fluid dynamics (CFD) framework that integrates the strengths of machine learning (ML) and graphics processing unit (GPU) to demonstrate their combined capability. Within this framework, all computational operations are solely executed on GPU, including ML-accelerated chemistry integration, fully-implicit solving of PDEs, and computation of thermal and transport properties, thereby eliminating the CPU-GPU memory copy overhead. Optimisations both within the kernel functions and during the kernel launch process are conducted to enhance computational performance. Strategies such as static data reorganisation and dynamic data allocation are adopted to reduce the GPU memory footprint. The computational performance is evaluated in two turbulent flame benchmarks using quasi-DNS and LES modelling, respectively. Remarkably, while maintaining a similar level of accuracy to the conventional CPU/CVODE-based solver, the GPU/ML-accelerated approach shows an overall speedup of over two orders of magnitude for both cases. This result highlights that high-fidelity turbulent combustion simulation with finite-rate chemistry that requires normally hundreds of CPUs can now be performed on portable devices such as laptops with a medium-end GPU. © 2023, CC BY.

关键词： Graphics processing unit

ScatterFormer: Locally-Invariant Scattering Transformer for Patient-Independent Multispectral Detection of Epileptiform Discharges

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arXiv 2023年

作者： Zheng, Ruizhe Li, Jun Wang, Yi Luo, Tian Yu, Yuguo Research Institute of Intelligent and Complex Systems Fudan University China State Key Laboratory of Medical Neurobiology Fudan University China MOE Frontiers Center for Brain Science Fudan University China Institutes of Brain Science Fudan University China Institute of Science and Technology for Brain-Inspired Intelligence Fudan University China Shanghai Artificial Intelligence Laboratory China Department of Neurology Children's Hospital of Fudan University China

Patient-independent detection of epileptic activities based on visual spectral representation of continuous EEG (cEEG) has been widely used for diagnosing epilepsy. However, precise detection remains a considerable challenge due to subtle variabilities across subjects, channels and time points. Thus, capturing fine-grained, discriminative features of EEG patterns, which is associated with high-frequency textural information, is yet to be resolved. In this work, we propose Scattering Transformer (ScatterFormer), an invariant scattering transform-based hierarchical Transformer that specifically pays attention to subtle features. In particular, the disentangled frequency-aware attention (FAA) enables the Transformer to capture clinically informative high-frequency components, offering a novel clinical explainability based on visual encoding of multichannel EEG signals. Evaluations on two distinct tasks of epileptiform detection demonstrate the effectiveness our method. Our proposed model achieves median AUCROC and accuracy of 98.14%, 96.39% in patients with Rolandic epilepsy. On a neonatal seizure detection benchmark, it outperforms the state-of-the-art by 9% in terms of average AUCROC. Copyright © 2023, The Authors. All rights reserved.

关键词： Diagnosis

PPSS: A Privacy-Preserving Supervision Scheme Based on Blockchain

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PPSS: A Privacy-Preserving Supervision Scheme Based on Block...

IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Ming Chen Peichang Shi Xiang Fu Feng Jiang Fei Gao Penghui Ma Jinzhu Kong National Key Laboratory of Parallel and Distributed Processing College of Computer Science National University of Defense Technology Changsha China Key Laboratory of Software Engineering for Complex Systems College of Computer Science National University of Defense Technology Changsha China Kylin Software Co.LTD Changsha China Zhejiang Lab Hangzhou China

In JointCloud Computing, multi-party participation introduces complexity and uncertainty. For all participants in JointCloud Computing, both continuous supervision and necessary privacy protection are required. Traditional supervision methods usually adopt the centralized information interaction mode, which has such defects as collusion of interests, single point of failure, privacy disclosure, etc. Building a decentralized supervision mechanism has become a new research direction. In this paper, we propose PPSS, a privacy-preserving supervision scheme based on blockchain, which decentralizes the supervision of the participants in JointCloud Computing, and combines the “double encryptions” and “threshold encryption” technologies to provide privacy protection. While making full use of the decentralization of the blockchain, a committee is established to carry out the analysis and decision-making tasks in terms of supervision and privacy protection. Experimental results indicate that PPSS can balance performance and security by reasonably configuring the committee.

关键词： Privacy Uncertainty Decision making Buildings Reliability engineering Blockchains complexity theory

Ionic liquids for CO_(2) electrochemical reduction

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Chinese Journal of Chemical Engineering 2021年第3期34卷 75-93页

作者： Fangfang Li Francesca Mocci Xiangping Zhang Xiaoyan Ji Aatto Laaksonen Energy Engineering Division of Energy ScienceLuleåUniversity of TechnologyLuleå97187Sweden Department of Chemical and Geological Sciences University of CagliariMonserrato 09042Italy CAS Key Laboratory of Green Process and Engineering Beijing Key Laboratory of Ionic Liquids Clean ProcessState Key Laboratory of Multiphase Complex SystemsInstitute of Process EngineeringChinese Academy of SciencesBeijing 100190China Division of Physical Chemistry Department of Materials and Environmental ChemistryArrhenius LaboratoryStockholm UniversityStockholm 10691Sweden Center of Advanced Research in Bionanocojugates and Biopolymers “Petru Poni”Institute of Macromolecular ChemistryIasi 700469Romania State Key Laboratory of Materials-Oriented and Chemical Engineering Nanjing Tech UniversityNanjing 211816China

Electrochemical reduction of CO_(2) is a novel research field towards a CO_(2)-neutral global economy and combating fast accelerating and disastrous climate changes while finding new solutions to store renewable energy in value-added chemicals and *** liquids(ILs),as medium and catalysts(or supporting part of catalysts)have been given wide attention in the electrochemical CO_(2) reduction reaction(CO_(2) RR)due to their unique advantages in lowering overpotential and improving the product selectivity,as well as their designable and tunable *** this review,we have summarized the recent progress of CO_(2) electro-reduction in IL-based electrolytes to produce higher-value *** then have highlighted the unique enhancing effect of ILs on CO_(2) RR as templates,precursors,and surface functional moieties of electrocatalytic ***,computational chemistry tools utilized to understand how the ILs facilitate the CO_(2) RR or to propose the reaction mechanisms,generated intermediates and products have been discussed.

关键词： Carbon dioxide Ionic liquids Electro-reduction Electrolyte Electrocatalytic material Computer simulation