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Buried interface bridging for inverted cesium-formamidinium triiodide perovskite solar cells with long operational stability

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Science China Chemistry 2025年第1期68卷 163-173页

作者： Chenhui Zhang Chunjun Liang Fulin Sun Ting Zhu Xinghai Huang Yuzhu Guo Xinyu Guo Kunyang Ge Dan Li Fangtian You Zhiqun He Key Laboratory of Luminescence and Optical information Ministry of Education Institute of Optoelectronic TechnologyBeijing Jiaotong University Department of Physics School of Physical Science and Engineering Beijing Jiaotong University

In the field of perovskite solar cells(PSCs), the research on defects in the buried interface has been relatively limited due to its non-exposure; however, this interface significantly impacts the performance enhancement of inverted PSCs. This study employs phenylethylammonium chloride(PEACl) molecules as a buffer layer to modify the buried interface of p-i-n structured PSCs,aiming to enhance the uniformity of self-assembled monolayers(SAMs) and facilitate the uniform nucleation and growth of perovskite films on the substrate. Furthermore, the introduction of the PEACl buffer layer effectively passivates defects at the bottom of the perovskite layer and notably enhances the crystal quality of the perovskite film by mitigating residual stress,thereby reducing nonradiative recombination loss. Following these optimizations, the MA-free PSCs treated with PEACl achieve a power conversion efficiency(PCE) of 24.11%, with significant improvements in storage, thermal stability, and operational stability. Particularly noteworthy is the device's performance in an unencapsulated state, whereas after 1,500 hours of continuous light operation stability testing, it retains 97% of its original efficiency. This study not only enriches the systematic understanding of the characteristics of the buried interface in PSCs but also contributes significantly to advancing the commercial production of perovskite photovoltaic technology.

关键词： defect-induced recombination buried interfaces inverted perovskite solar cells crystallization lattice mismatch

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Domain generalization with semi-supervised learning for people-centric activity recognition

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Science China(information Sciences) 2025年第1期68卷 171-188页

作者： Jing LIU Wei ZHU Di LI Xing HU Liang SONG Academy for Engineering & Technology Fudan University Shanghai East-bund Research Institute on Networking Systems of AI school of optoelectronic information and Computer Engineering University of Shanghai for Science & Technology

People-centric activity recognition is one of the most critical technologies in a wide range of real-world applications,including intelligent transportation systems, healthcare services, and brain-computer interfaces. Large-scale data collection and annotation make the application of machine learning algorithms prohibitively expensive when adapting to new tasks. One way of circumventing this limitation is to train the model in a semi-supervised learning manner that utilizes a percentage of unlabeled data to reduce the labeling burden in prediction tasks. Despite their appeal, these models often assume that labeled and unlabeled data come from similar distributions, which leads to the domain shift problem caused by the presence of distribution gaps. To address these limitations, we propose herein a novel method for people-centric activity recognition,called domain generalization with semi-supervised learning(DGSSL), that effectively enhances the representation learning and domain alignment capabilities of a model. We first design a new autoregressive discriminator for adversarial training between unlabeled and labeled source domains, extracting domain-specific features to reduce the distribution gaps. Second, we introduce two reconstruction tasks to capture the task-specific features to avoid losing information related to representation learning while maintaining task-specific consistency. Finally, benefiting from the collaborative optimization of these two tasks, the model can accurately predict both the domain and category labels of the source domains for the classification task. We conduct extensive experiments on three real-world sensing datasets. The experimental results show that DGSSL surpasses the three state-of-the-art methods with better performance and generalization.

关键词： activity recognition deep learning domain generalization semi-supervised learning adversarial training

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Bifunctional bridging capping layer enables 24.5% efficiency of perovskite solar cells with polymer-based hole transport materials

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Science China Chemistry 2025年第1期68卷 350-359页

作者： Can Zhu Yiyang Wang Lei Meng Beibei Qiu Jing Li Shucheng Qin Ke Hu Xin Jiang Wenbin Lai Minchao Liu Zhe Liu Chenxing Lu Jinyuan Zhang Yongfang Li Beijing National Laboratory for Molecular Sciences CAS Key Laboratory of Organic Solids Institute of Chemistry Chinese Academy of Sciences school of Chemical Science University of Chinese Academy of Sciences Key Laboratory of Solid State optoelectronic Devices of Zhejiang Province College of Physics and Electronic Information Engineering Zhejiang Normal University Key Laboratory of Photochemical Conversion and optoelectronic Materials Technical Institute of Physics and ChemistryChinese Academy of Sciences Laboratory of Advanced optoelectronic Materials College of Chemistry Chemical Engineering and Materials ScienceSoochow University

Developing a bridge capping layer between perovskite and hole transport layer materials（HTMs） in the n-i-p perovskite solar cells（pero-SCs） is an effective approach to modify the morphology of HTMs and passivate the perovskite ***, we select the quinoxaline-based bifunctional passivation agent, quinoxalin-6-yl-methylamine hydrochloride（Qx MACl）,as the bridging layer, and a D-A copolymer PBQ12 containing the same quinoxaline unit as an HTM for the n-i-p pero-SCs. Due to the π-π stacking among the common quinoxaline units in the bridge layer and HTM, Qx MACl induces the π-π stacking of the PBQ12 film and improves the film morphology of HTMs with better conductivity. Additionally, Qx MACl can effectively passivate the perovskite surface, and PBQ12 possesses appropriate energy levels and high hole mobility. The pero-SCs based on FAPbI3with PBQ12/Qx MACl treatment showed a higher power conversion efficiency（PCE） of 24.05% and outstanding stability, maintaining 95.4% and 92.1% of its initial PCE after 750 h of storage and after over 800 h of thermal annealing at 85 °C, respectively. To further enhance the PCE of the PBQ12/Qx MACl-based devices, we developed a non-metal ion dopant for the PBQ12 HTM. Through trace doping of PBQ12 HTM by the non-metal ion dopant, the PCE of the PBQ12/Qx MACl-based devices reached 25.24%（the calibrated PCE of 24.55% by the National Institute of Metrology, China）.

关键词： D-A copolymer, hole transport materials, bifunctional bridge capping layer, passivation perovskite solar cells

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Turbulent Agglomeration of Microparticles in a Cylinder Wake Flow Using LES-DEM:Focusing on the Effect of the Reynolds Number

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Journal of Thermal Science 2025年第1期34卷 34-49页

作者： WANG Shuang MU Lin LI Xue XIE Jun DONG Ming school of Energy and Power Engineering Dalian University of Technology school of Optical information and Energy Engineering Wuhan Institute of Technology school of Energy and Environment Shenyang Aerospace University

Turbulent agglomeration is viewed as a promising technology for enhancing fine particle removal *** better understand particle transport,agglomeration behaviors,and fluid-particle interactions,we numerically explored these phenomena under cylindrical vortex wake influence using a coupled large eddy simulation and discrete element method（LES-DEM） *** validity of the LES approach was verified by comparison with available direct numerical simulation（DNS） *** adopted the Johnson-Kendall-Roberts（JKR） contact model for particle-particle *** particle dispersion and agglomeration characteristics of particles with different diameters（dp=2-20 μm） in the laminar and transition of shear layer（TrSL） flow regimes were *** particles were concentrated at the vortex centers,while larger particles accumulated around the *** agglomeration efficiency exhibited an M-shaped profile spanwise（y-direction）.With increasing Reynolds number,the agglomeration efficiency and turbulence intensity *** particle agglomeration efficiency peaks at a certain Reynolds ***,at higher Reynolds numbers,reducing the residence time of particles in the flow field decreases the agglomeration efficiency.

关键词： discrete element method large eddy simulation microparticle particle agglomeration

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Multi-receptive field interaction network for shape from polarization

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Science China(information Sciences) 2025年第1期68卷 394-395页

作者： Yini PENG Rui LIU Zhiyuan ZHANG Zhongyuan WANG Jiayi MA Xin TIAN Electronic information school Wuhan University Computer Science school Wuhan University Wuhan Institute of Quantum Technology

Shape from polarization (SfP) method can use the polarization information in reflected light to estimate the surface normal of the target,which can further reconstruct the shape of the *** a simple image capture process,it can use low-cost equipment to meet a high precision imaging requirement,which can be used in remote scenes and other applications.

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IDSSCNN-XgBoost:Improved Dual-Stream Shallow Convolutional Neural Network Based on Extreme Gradient Boosting Algorithm for Micro Expression Recognition

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Computers, Materials & Continua 2025年第1期82卷 729-749页

作者： Adnan Ahmad Zhao Li Irfan Tariq Zhengran He school of information Science and Engineering Southeast UniversityNanjing210016China

Micro-expressions(ME)recognition is a complex task that requires advanced techniques to extract informative features fromfacial *** deep neural networks(DNNs)with convolutional structures have been ***,unlike DNNs,shallow convolutional neural networks often outperform deeper models in mitigating overfitting,particularly with small ***,many of these methods rely on a single feature for recognition,resulting in an insufficient ability to extract highly effective *** address this limitation,in this paper,an Improved Dual-stream Shallow Convolutional Neural Network based on an Extreme Gradient Boosting Algorithm(IDSSCNN-XgBoost)is introduced for ME *** proposed method utilizes a dual-stream architecture where motion vectors(temporal features)are extracted using Optical Flow TV-L1 and amplify subtle changes(spatial features)via EulerianVideoMagnification(EVM).These features are processed by IDSSCNN,with an attention mechanism applied to refine the extracted effective *** outputs are then fused,concatenated,and classified using the XgBoost *** comprehensive approach significantly improves recognition accuracy by leveraging the strengths of both temporal and spatial information,supported by the robust classification power of *** proposed method is evaluated on three publicly available ME databases named Chinese Academy of Sciences Micro-expression Database(CASMEII),Spontaneous Micro-Expression Database(SMICHS),and Spontaneous Actions and Micro-Movements(SAMM).Experimental results indicate that the proposed model can achieve outstanding results compared to recent *** accuracy results are 79.01%,69.22%,and 68.99%on CASMEII,SMIC-HS,and SAMM,and the F1-score are 75.47%,68.91%,and 63.84%,*** proposed method has the advantage of operational efficiency and less computational time.

关键词： ME recognition dual stream shallow convolutional neural network euler video magnification TV-L1 XgBoost

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Experimental demonstration of 220-GHz terahertz signals wireless transmission over 4.6 km

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Science China(information Sciences) 2025年第1期68卷 386-388页

作者： Yi WEI Jianjun YU Mingxu WANG Xiongwei YANG Qiutong ZHANG Jingwen TAN Bing ZHANG Ying WU Yang HAN Peng TIAN Wen ZHOU Kaihui WANG Feng ZHAO State Key Laboratory of ASIC and System Key Laboratory for Information Science of Electromagnetic Waves (MoE)School of Information Science and Technology Fudan University school of Electronic Engineering Xi'an University of Posts and Telecommunications

The advancement of terahertz (THz) communication technology drives the evolution of wireless communication systems,offering novel pathways and technical means for the development of future 6G communication *** wireless communication systems are often constrained by bandwidth limitations of electronic devices in high frequency ***,THz communication technology leverages the characteristics of electromagnetic waves to transcend these limitations,enabling communication athigher frequencies and wider bandwidths.

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Federated local causal structure learning

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Science China(information Sciences) 2025年

作者： Kui YU Chen RONG Hao WANG Fuyuan CAO Jiye LIANG school of Computer and information Hefei University of Technology school of Computer and information Technology Shanxi University

Local causal structure learning (LCS) efficiently identifies a set of direct neighbors of a specified variable from observational data. Additionally, it distinguishes direct causes and direct effects of this variable without learning the entire causal structure. While many LCS algorithms have been proposed, they do not consider the data privacy-preserving problem,which has attracted extensive attention from academia and industry. To address this issue, we propose a federated local causal structure learning (FedLCS) algorithm to learn local causal structures in privacy-preserving data in a federated ***, FedLCS introduces a layer-wise federated local skeleton learning algorithm to construct the local skeleton. Based on this skeleton, it introduces a federated local skeleton orientation algorithm and an extension-and-backtracking orientation algorithm to orient the edges. Finally, FedLCS uses a federated local extension-and-backtracking orientation algorithm to orient the remaining edges. Extensive experiments on benchmark, synthetic, and real datasets demonstrate that FedLCS can learn the local causal structure of a given variable in a federated setting.

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Collaborative Trajectory Planning for Stereoscopic Agricultural Multi-UAVs Driven by the Aquila Optimizer

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Computers, Materials & Continua 2025年第1期82卷 1349-1376页

作者： Xinyu Liu Longfei Wang Yuxin Ma Peng Shao school of Computer and information Engineering Jiangxi Agricultural UniversityNanchang330045China

Stereoscopic agriculture,as an advanced method of agricultural production,poses new challenges for multi-task trajectory planning of unmanned aerial vehicles(UAVs).To address the need for UAVs to perform multi-task trajectory planning in stereoscopic agriculture,a multi-task trajectory planning model and algorithm(IEP-AO)that synthesizes flight safety and flight efficiency is *** on the requirements of stereoscopic agricultural geomorphological features and operational characteristics,the multi-task trajectory planning model is ensured by constructing targeted constraints at five aspects,including the path,slope,altitude,corner,energy and obstacle threat,to improve the effectiveness of the trajectory planning *** combined with the path optimization algorithm,an Aquila optimizer(IEP-AO)based on the interference-enhanced combination model is proposed,which can help UAVs to improve the trajectory search capability in complex operation space and large-scale operation tasks,and jump out of the locally optimal trajectory path region timely,to generate the optimal trajectory planning plan that can adapt to the diversity of the tasks and the flight ***,four simulated flights with different operation scales and different scene constraints were conducted under the constructed real 3Dimension scene,and the experimental results can show that the proposedmulti-task trajectory planning method canmeet themulti-task requirements in stereoscopic agriculture and improve the mission execution efficiency and agricultural production effect of UAV.

关键词： Stereoscopic agriculture unmanned aerial vehicle multi-task interference model Aquila optimizer

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Remaining Life Prediction Method for Photovoltaic Modules Based on Two-Stage Wiener Process

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Energy Engineering 2025年第1期122卷 331-347页

作者： Jie Lin Hongchi Shen Tingting Pei Yan Wu school of Electrical Engineering and information Engineering Lanzhou University of TechnologyLanzhou730050China

Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation *** service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental *** cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.

关键词： Photovoltaic modules degradation stochastic processes lifetime prediction

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