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Boosting the Efficiency and Mechanical Stability of Organic Solar Cells Through a Polymer Acceptor by Reducing the Elastic Modulus

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Advanced Energy Materials 2025年第0期

作者： Wang, Yan Yu, Han Zhao, Dan Liu, Wei Liu, Baoze Wu, Xin Gao, Danpeng Zhang, Dong Zhang, Shoufeng Sun, Xianglang Zhang, Chunlei Zhao, Chaoyue Fu, Yuchen Song, Wei Gong, Shaokuan Fu, Yuang Kwok, Chung Hang Ge, Ziyi Lu, Xinhui Chen, Xihan Xiao, Shuang Wong, Wai-Yeung Chai, Yu Yan, He Zhu, Zonglong Department of Chemistry City University of Hong Kong Kowloon999077 Hong Kong Department of Chemistry Guangdong-Hong Kong-Macao Joint Laboratory of Optoelectronic and Magnetic Functional Materials Energy Institute and Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration & Reconstruction Hong Kong University of Science and Technology Clear Water Bay Kowloon999077 Hong Kong Department of Applied Biology and Chemical Technology and Research Institute for Smart Energy The Hong Kong Polytechnic University Hung Hom 999077 Hong Kong Hong Kong University of Science and Technology-Shenzhen Research Institute No. 9 Yuexing 1st RD Hi-tech Park Nanshan Guangdong Shenzhen518057 China School of Automation Engineering University of Electronic Science and Technology of China Sichuan Chengdu611731 China Department of Physics City University of Hong Kong Kowloon999077 Hong Kong Zhejiang Engineering Research Center for Energy Optoelectronic Materials and Devices Ningbo Institute of Materials Technology & Engineering Chinese Academy of Sciences Ningbo315201 China Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems SUSTech Energy Institute for Carbon Neutrality Department of Mechanical and Energy Engineering Southern University of Science and Technology Guangdong Shenzhen518055 China Department of Physics The Chinese University of Hong Kong Shatin999077 Hong Kong Center for Advanced Material Diagnostic Technology and College of Engineering Physics Shenzhen Technology University Guangdong Shenzhen518118 China Shenzhen Research Institute City University of Hong Kong Shenzhen518057 China

Organic solar cells (OSCs) are regarded as one of the most promising flexible power sources due to their lightweight and flexible properties, with the improvement of photovoltaic and mechanical performance. To improve the current density and power conversion efficiency (PCE), mPh4F-TS (TS) and PYSe2F-T (PA) are introduced into the binary host, PM6/mPh4F-TT (PM6/TT) as third components. It is demonstrated that the corresponding ternary devices, in both rigid and flexible devices, achieved superior efficiencies (19.6%/17.7% for PM6/TT+TS, and 19.2%/17.4% for PM6/TT+PA) outperform the binary counterparts (18.3%/16.4%). However, distinct differences in mechanical performance are observed between the polymer acceptor (PA) and small-molecular acceptor (TS). The PM6/TT+PA significantly improved the mechanical stability of flexible devices with a lower elastic modulus of 3.6 GPa, while the PM6/TT+TS resulted in the opposite effect with a higher elastic modulus of 5.5 GPa. Through in-depth investigation, a clear correlation between the elastic modulus, crack density, and mechanical stability of the active layer blends is successfully established, revealing the key role of reducing the elastic modulus in enhancing the mechanical stability of flexible OSCs. This study provides important guidance for the development of flexible photovoltaic devices with both high efficiency and mechanical robustness. © 2025 The Author(s). Advanced Energy Materials published by Wiley-VCH GmbH.

关键词： Organic solar cells

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Contact-Aware Controller Design for Complementarity systems

Contact-Aware Controller Design for Complementarity Systems

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IEEE International Conference on robotics and automation (ICRA)

作者： Alp Aydinoglu Victor M. Preciado Michael Posa Department of Electrical and Systems Engineering University of Pennsylvania Philadelphia PA USA General Robotics Automation Sensing and Perception (GRASP) Laboratory University of Pennsylvania Philadelphia PA USA

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

While many robotic tasks, like manipulation and locomotion, are fundamentally based in making and breaking contact with the environment, state-of-the-art control policies struggle to deal with the hybrid nature of multi-contact motion. Such controllers often rely heavily upon heuristics or, due to the combinatoric structure in the dynamics, are unsuitable for real-time control. Principled deployment of tactile sensors offers a promising mechanism for stable and robust control, but modern approaches often use this data in an ad hoc manner, for instance to guide guarded moves. In this work, by exploiting the complementarity structure of contact dynamics, we propose a control framework which can close the loop on rich, tactile sensors. Critically, this framework is non-combinatoric, enabling optimization algorithms to automatically synthesize provably stable control policies. We demonstrate this approach on three different underactuated, multi-contact robotics problems.

关键词： Lyapunov methods Control systems Force Dynamics Task analysis Tactile sensors

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Phase synchronization between two thermo-photoelectric neurons coupled through a Josephson Junction

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The European Physical Journal B 2022年第4期95卷 1-17页

作者： Fossi, Jules Tagne Deli, Vandi Edima, Hélène Carole Njitacke, Zeric Tabekoueng Kemwoue, Florent Feudjio Atangana, Jacques Laboratory of Energy-Electric and Electronic Systems Department of Physics Faculty of Science University of Yaoundé I Yaoundé Cameroon Centre d’Excellence Africain des Technologies de l’Information et de la Communication (CETIC) Université de Yaoundé I Yaoundé Cameroon Department of Pharmaceutical Sciences Faculty of Medicine and Pharmaceutical Sciences University of Douala Douala Cameroon National School of Agro-Industrial Sciences Food Microbiology and Biotechnology Laboratory University of Ngaoundéré Ngaoundéré Cameroon Department of Electrical and Electronic Engineering College of Technology (COT) University of Buea Buea Cameroon Department of Automation Biomechanics and Mechatronics Lodz University of Technology Lodz Poland Department of Physics Higher Teacher Training College Yaoundé University of Yaoundé I Yaoundé Cameroon

The transmission and encoding of information in the brain has been the subject of much research. The aim is to improve biophysical functions and to design reliable artificial synapses for the connection of several biological neurons. In this manuscript, it is coupled through a hybrid synapse two FitzHugh–Nagumo neural circuits driven simultaneously by a phototube and a thermistor. The hybrid synapse is based on an ideal Josephson Junction in parallel with a linear resistance. This configuration allows the evaluation of the external magnetic field in the neural circuit. Using the standard scale transformation on the physical variables and parameters, we obtain the mathematical model of the coupled neurons. A bifurcation analysis on the intrinsic parameters of the coupling channel is carried out to demonstrate the complete synchronization and phase synchronization. It can be seen a synchronization stability when the parameters of the coupling channel are well defined. To practically confirm these results, an electronic circuit is designed using discrete electronic components and multipliers. Thanks to the simulations in the PSpice software, we see that this circuit can well and well be used to estimate the effect of the external magnetic field on a coupled neural circuit and predict a stable synchronization.

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Optomechanical dissipative solitons (vol 600, pg 75, 2021)

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NATURE 2022年第7896期602卷 E24-E24页

作者： Zhang, Jing Peng, Bo Kim, Seunghwi Monifi, Faraz Jiang, Xuefeng Li, Yihang Yu, Peng Liu, Lianqing Liu, Yu-xi Alu, Andrea Yang, Lan Department of Electrical and Systems Engineering Washington University St. Louis MO USA Department of Automation Tsinghua University Beijing P. R. China Photonics Initiative Advanced Science Research Center City University of New York New York NY USA Physics Program Graduate Center City University of New York New York NY USA State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang P. R. China Institute of Microelectronics Tsinghua University Beijing P. R. China

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One to many: Adaptive instrument segmentation via meta learning and dynamic online adaptation in robotic surgical video

arXiv

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arXiv 2021年

作者： Zhao, Zixu Jin, Yueming Lu, Bo Ng, Chi-Fai Dou, Qi Liu, Yun-Hui Heng, Pheng-Ann The Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong The T Stone Robotics Institute The Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China The Department of Surgery The Chinese University of Hong Kong Hong Kong

Surgical instrument segmentation in robot-assisted surgery (RAS) - especially that using learning-based models - relies on the assumption that training and testing videos are sampled from the same domain. However, it is impractical and expensive to collect and annotate sufficient data from every new domain. To greatly increase the label efficiency, we explore a new problem, i.e., adaptive instrument segmentation, which is to effectively adapt one source model to new robotic surgical videos from multiple target domains, only given the annotated instruments in the first frame. We propose MDAL, a meta-learning based dynamic online adaptive learning scheme with a two-stage framework to fast adapt the model parameters on the first frame and partial subsequent frames while predicting the results. MDAL learns the general knowledge of instruments and the fast adaptation ability through the video-specific meta-learning paradigm. The added gradient gate excludes the noisy supervision from pseudo masks for dynamic online adaptation on target videos. We demonstrate empirically that MDAL outperforms other state-of-the-art methods on two datasets (including a real-world RAS dataset). The promising performance on ex-vivo scenes also benefits the downstream tasks such as robot-assisted suturing and camera control. Copyright © 2021, The Authors. All rights reserved.

关键词： Surgical equipment

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Distributed Observer-Based Time-Varying Formation Control Under Switching Topologies

Distributed Observer-Based Time-Varying Formation Control Un...

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European Control Conference (ECC)

作者： Sandeep Kumar Soni Garima Soni Siyuan Wang Driss Boutat Mohamed Djemai Sorin Olaru Johann Reger Daniel Geha INSA Centre Val de Loire University d’Orleans PRISME EA 4229 Bourges Cedex France Department of Electrical and Electronics Engineering BIT Raipur Chhattisgarh India Université Polytechnique Hauts-de-France LAMIH CNRS UMR 8201 Valenciennes Cedex 9 France QUARTZ Laboratory EA 7393 ENSEA Cergy 6 Avenue du Ponceau Cergy France Laboratoire des Signaux et Systèmes CentraleSupélec Université Paris Saclay 3 rue Joliot Curie Gif-sur-Yvette France Control Engineering Group Technische Universität Ilmenau Ilmenau Germany Industrial Automation Robotics 1 Chemin de la Bourellerie Thenioux France

This paper proposes the distributed observer-based control approach to achieve time-varying formation of second-order autonomous unmanned systems (AUSs) under switching topologies. It is assumed that each AUS has access only to the positions of its neighbouring AUS agents. An observer is then designed to estimate the velocity of neighbouring AUS agents. Furthermore, a distributed control for the AUSs is designed using information of position and estimated velocity. A common Lyapunov function is employed in order to establish sufficient conditions for the stability of closed-loop systems. In order to address the effect of switching topologies, a dwell-time condition is has been considered. Moreover, the observer-based time-varying formation controller satisfies the separation principle. Finally, simulation results are presented to illustrate the effectiveness of the proposed approach.

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Quantization of Acoustic Modes in Dumbbell Nanoparticles

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Physical Review Letters 2022年第4期128卷 048003-048003页

作者： Zuyuan Wang Hojin Kim Maria Secchi Maurizio Montagna Eric M. Furst Bahram Djafari-Rouhani George Fytas Max Planck Institute for Polymer Research Ackermannweg 10 Mainz 55128 Germany Institute for Measurement and Automation Division of Sensor Technology and Measurement Systems Bundeswehr University Munich Werner Heisenberg Weg 39 85579 Neubiberg Germany Department of Chemical & Biomolecular Engineering Allan P. Colburn Laboratory University of Delaware Newark Delaware 19716 USA Department of Industrial Engineering University of Trento via Sommarive 9 I-38123 Trento Italy Dipartimento di Fisica Universitá di Trento via Sommarive 14 I-38123 Trento Italy Institut d’Électronique de Microélectronique et de Nanotechnologie (IEMN) UMRCNRS 8520 Department of Physics University of Lille Villeneuve d’Ascq 59655 France

The vibrational eigenmodes of dumbbell-shaped polystyrene nanoparticles are recorded by Brillouin light spectroscopy (BLS), and the full experimental spectra are calculated theoretically. Different from spheres with a degeneracy of (2l+1), with l being the angular momentum quantum number, the eigenmodes of dumbbells are either singly or doubly degenerate owing to their axial symmetry. The BLS spectrum reveals a new, low-frequency peak, which is attributed to the out-of-phase vibration of the two lobes of the dumbbell. The quantization of acoustic modes in these molecule-shaped dumbbell particles evolves from the primary colloidal spheres as the separation between the two lobes increases.

关键词： Light-matter interaction Scattering theory Soft colloids Brillouin scattering & spectroscopy Finite-element method Inelastic light scattering

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HybrUR: A Hybrid Physical-Neural Solution for Unsupervised Underwater Image Restoration

arXiv

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arXiv 2021年

作者： Yan, Shuaizheng Chen, Xingyu Wu, Zhengxing Tan, Min Yu, Junzhi The Laboratory of Cognitive and Decision Intelligence for Complex System Institute of Automation Chinese Academy of Sciences Beijing100190 China The Department of Mechanical Engineering Fuzhou University Fuzhou350000 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China Xiaobing.AI Beijing100080 China The State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing100871 China

Robust vision restoration of underwater images remains a challenge. Owing to the lack of well-matched underwater and in-air images, unsupervised methods based on the cyclic generative adversarial framework have been widely investigated in recent years. However, when using an end-to-end unsupervised approach with only unpaired image data, mode collapse could occur, and the color correction of the restored images is usually poor. In this paper, we propose a data- and physics-driven unsupervised architecture to perform underwater image restoration from unpaired underwater and in-air images. For effective color correction and quality enhancement, an underwater image degeneration model must be explicitly constructed based on the optically unambiguous physics law. Thus, we employ the Jaffe-McGlamery degeneration theory to design a generator and use neural networks to model the process of underwater visual degeneration. Furthermore, we impose physical constraints on the scene depth and degeneration factors for backscattering estimation to avoid the vanishing gradient problem during the training of the hybrid physical-neural model. Experimental results show that the proposed method can be used to perform high-quality restoration of unconstrained underwater images without supervision. On multiple benchmarks, the proposed method outperforms several state-of-the-art supervised and unsupervised approaches. We demonstrate that our method yields encouraging results in real-world applications. © 2021, CC BY-NC-ND.

关键词： Image reconstruction

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衰亡链揭示互利共生生态系统中安全与崩溃的中间阶段（英文）

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engineering 2024年第12期 89-98页

作者：王光炜刘雪明肖颖袁烨潘林强管晓宏高建喜张海涛 The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems State Key Laboratory of Digital Manufacturing Equipment and Technology School of Artificial Intelligence and Automation Huazhong University of Science and Technology Guangdong HUST Industrial Technology Research Institute Huazhong University of Science and Technology Guangdong Provincial Engineering Technology Center of Autonomous Unmanned Vessels MOE Key Laboratory of Intelligent Networks and Network Security&State Key Laboratory of Manufacturing Systems Xi'an Jiaotong University Tsinghua National Laboratory of Information Science and Technology Department of Automation Tsinghua University Department of Computer Science Rensselaer Polytechnic Institute

Ecosystems are undergoing unprecedented persistent deterioration due to unsustainable anthropogenic human activities, such as overfishing and deforestation, and the effects of such damage on ecological stability are uncertain. Despite recent advances in experimental and theoretical studies on regime shifts and tipping points, theoretical tools for understanding the extinction chain, which is the sequence of species extinctions resulting from overexploitation, are still lacking, especially for large-scale nonlinear networked systems. In this study, we developed a mathematical tool to predict regime shifts and extinction chains in ecosystems under multiple exploitation situations and verified it in 26 real-world mutualistic networks of various sizes and densities. We discovered five phases during the exploitation process: safe,partial extinction, bistable, tristable, and collapse, which enabled the optimal design of restoration strategies for degraded or collapsed systems. We validated our approach using a 20-year dataset from an eelgrass restoration project. Counterintuitively, we also found a specific region in the diagram spanning exploitation rates and competition intensities, where exploiting more species helps increase *** computational tool provides insights into harvesting, fishing, exploitation, or deforestation plans while conserving or restoring the biodiversity of mutualistic ecosystems.

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Atomic force microscopy studies on cellular elastic and viscoelastic properties

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Science China(Life Sciences) 2018年第1期61卷 57-67页

作者： Mi Li Lianqing Liu Ning Xi Yuechao Wang State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 China Department of Industrial and Manufacturing Systems Engineering The University of Hong Kong Hong Kong China

In this work, a method based on atomic force microscopy (AFM) approach-reside-retract experiments was established to simultaneously quantify the elastic and viscoelastic properties of single cells. First, the elastic and viscoelastic properties of normal breast cells and cancerous breast cells were measured, showing significant differences in Young’s modulus and relaxation times between normal and cancerous breast cells. Remarkable differences in cellular topography between normal and cancerous breast cells were also revealed by AFM imaging. Next, the elastic and viscoelasitc properties of three other types of cell lines and primary normal B lymphocytes were measured; results demonstrated the potential of cellular viscoelastic properties in complementing cellular Young’s modulus for discerning different states of cells. This research provides a novel way to quantify the mechanical properties of cells by AFM, which allows investigation of the biomechanical behaviors of single cells from multiple aspects.

关键词： atomic force microscopy cell mechanical properties viscoelastic properties Young＇s modulus relaxation time

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