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2D Ruddlesden-Popper Perovskites/PVDF-TrFE Photodetector for Anti-Interference Vision system Derived from Ferroelectric Polarization Modulation

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ADVANCED FUNCTIONAL MATERIALS 2025年第0期

作者： Zhang, Xinglong Hong, Enliu Tan, Xiaojun Liu, Jie Jiang, Anquan Fang, Xiaosheng Fudan Univ Dept Mat Sci State Key Lab Mol Engn Polymers Shanghai 200433 Peoples R China Shaoxin Lab Shaoxing 312000 Peoples R China Fudan Univ Sch Microelect State Key Lab ASIC&System Shanghai 200433 Peoples R China

2D Ruddlesden-Popper (RP) perovskites have garnered increasing attention for their excellent photoresponse, characterized by high carrier mobility, tunable bandgaps, high optical absorption, and molecular asymmetry. Herein, centimeter scale single crystal 2D hybrid perovskites, BA2PbBr4 (BPB) is synthesized, using quasi-static cooling method and composited with ferroelectric PVDF-TrFE(PT) film to construct a multi-field coupling photodetector (PD) via van der Waals force contact. Ferroelectric tests show that the PT film exhibits a saturated polarization strength of 3.6 mu C cm-2, allowing the ferroelectric localized field to modulate the band structure of PT and enhance the photocurrent. The Heterojunction systems exhibit ultra-high responsivity (15.3 A W-1) and detectivity (1.99 x 1013 Jones) under 390 nm illumination at 3 V bias, with a performance improvement of over 102 times compared to BPB PDs. Furthermore, the hybrid PDs exhibit highly stable I-t curve with a photocurrent retention rate of 97.4%. Leveraging this feature, a large-area imaging device is designed at the centimeter level scale, enabling multifunctional vision applications accurate letter imaging process and anti-interference number detection. The work presents a valuable insight in design of future autonomous driving vision systems.

关键词： 2D Ruddlesden-Popper perovskites ferroelectric photodetector PVDF-TrFE single-crystal

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Automated Design of Complex Analog Circuits with Multiagent Based Reinforcement Learning 23

Automated Design of Complex Analog Circuits with Multiagent ...

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Proceedings of the 60th Annual ACM/IEEE Design Automation Conference

作者： Jinxin Zhang Jiarui Bao Zhangcheng Huang Xuan Zeng Ye Lu State Key Lab. of ASIC & System School of Information Science and Technology Frontier Institute of Chip and System State Key Lab. of ASIC & System Microelectronics Department Fudan University Shanghai China

ISBN: (纸本)9798350323481

Despite the effort of analog circuit design automation, currently complex analog circuit design still requires extensive manual iterations, making it lab.r intensive and time-consuming. Recently, reinforcement learning (RL) algorithms have been demonstrated successfully for the analog circuit design optimization. However, a robust and highly efficient RL method to design analog circuits with complex design space has not been fully explored yet. In this work, inspired by multiagent planning theory as well as human expert design practice, we propose a multiagent based RL (MA-RL) framework to tackle this issue. Particularly, we (i) partition the complex analog circuits into several sub-blocks based on topology information and effectively reduce the complexity of design search space; (ii) leverage MA-RL for the circuit optimization, where each agent corresponds to a single sub-block, and the interactions between agents delicately mimic the best design tradeoffs between circuit sub-blocks by human experts; (iii) introduce the multiagent twin-delayed techniques to further boost training stability and accomplish higher performances. Experiments on two different analog circuit topologies and knowledge transfers between two technology nodes are demonstrated. It's shown that MA-RL framework can achieve the best FoM for complex analog circuits design. This work shines the light for future large scale analog circuit system design automation.

关键词： complex analog circuits

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Synthesizing Invariants for Polynomial Programs by Semidefinite Programming

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ACM Transactions on Programming Languages and systems 2025年第1期47卷 1-35页

作者： Wu, Hao Wang, Qiuye Xue, Bai Zhan, Naijun Zhi, Lihong Yang, Zhi-Hong State Key Lab. of Computer Sciences Institute of Software Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Fermat Labs Huawei Inc. Dongguan China Key Lab. of System Software and State Key Lab. of Computer Science Institute of Software Chinese Academy of Sciences Beijing China Key Laboratory of High Confidence Software Technology School of Computer Science Peking University Beijing China School of Mathematics and Statistics Central South University Changsha China

Constraint-solving-based program invariant synthesis takes a parametric invariant template and encodes the (inductive) invariant conditions into constraints. The problem of characterizing the set of all valid parameter assignments is referred to as the strong invariant synthesis problem, while the problem of finding a concrete valid parameter assignment is called the weak invariant synthesis problem. For both problems, the challenge lies in solving or reducing the encoded constraints, which are generally non-convex and lack efficient solvers. In this article, we propose two novel algorithms for synthesizing invariants of polynomial programs using semidefinite programming (SDP): (1) The Cluster algorithm targets the strong invariant synthesis problem for polynomial invariant templates. Leveraging robust optimization techniques, it solves a series of SDP relaxations and yields a sequence of increasingly precise under-approximations of the set of valid parameter assignments. We prove the algorithm’s soundness, convergence, and weak completeness under a specific robustness assumption on templates. Moreover, the outputs can simplify the weak invariant synthesis problem. (2) The Mask algorithm addresses the weak invariant synthesis problem in scenarios where the aforementioned robustness assumption does not hold, rendering the Cluster algorithm ineffective. It identifies a specific subclass of invariant templates, termed masked templates, involving parameterized polynomial equalities and known inequalities. By applying variable substitution, the algorithm transforms constraints into an equivalent form amenable to SDP relaxations. Both algorithms have been implemented and demonstrated superior performance compared to state-of-the-art methods in our empirical evaluation. © 2025 Copyright held by the owner/author(s).

关键词： Polynomial approximation

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Routability-Driven Macro Placement Engine for Modern FPGAs With Complex Cascade Shape and Region Constraints

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IEEE Transactions on Computer-Aided Design of Integrated Circuits and systems 2025年

作者： Gu, Hao Gu, Jian Peng, keyu Chen, Jianli Yang, Jun Zhu, Ziran Southeast University National ASIC System Engineering Research Center School of Integrated Circuits Nanjing210096 China Fudan University State Key Lab of ASIC and System Shanghai200433 China

Field-programmable gate array (FPGA) macro placement holds a crucial role within the FPGA physical design flow since it substantially influences the subsequent stages of cell placement and routing. With the increasing number of macros and the complex cascade shape and region constraints imposed by modern FPGAs, the routability and macro placement have become much more challenging. In this paper, we propose an effective and efficient routability-driven macro placement algorithm for modern FPGAs with cascade shape and region constraints. To reserve adequate space for cell placement and guarantee routability, we first develop a routability-driven mixed-size analytical global placement that evenly distributes both macros and cells while considering cascade shape and region constraints. Particularly, the proposed global placement engine integrates a well-trained congestion prediction model, targeting benchmarks with high routing congestion to enhance overall routability. Then, we propose an integer linear programming (ILP)-based cascade shape legalization followed by matching-based macro legalization to remove macro overlaps while satisfying the region constraints. Finally, a routability-driven detailed macro placement is proposed to refine the solution. Compared with the winners of the MLCAD 2023 FPGA macro placement contest and state-of-the-art works, experimental results show that our algorithm achieves the best overall score and routability. © 1982-2012 IEEE.

关键词： Electronic design automation

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Research on 1050 nm high-power narrow linewidth fiber laser based on tapered ytterbium-doped fiber 7

Research on 1050 nm high-power narrow linewidth fiber laser ...

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7th Optics Young Scientist Summit, OYSS 2024

作者： Ye, Yun Wang, Xiaolin Wang, Yanbin Zhou, Xuanfeng Jiang, Chenglong Zhang, Defeng Xi, Xiaoming Xu, Xiaojun State Key Lab. of Complex Electromagnetic Environment Effects on Electronics and Information System Luoyang471003 China College of Advanced Interdisciplinary Studies National University of Defense Technology Changsha410073 China

ISBN: (数字)9781510688377

ISBN: (纸本)9781510688360

Compared to conventional uniform fibers, long tapered Yb-doped fibers (T-YDF) have outstanding potential to alleviate the detrimental nonlinear effects due to their unique mode field characteristics along the length direction. In this work, an T-YDF-based short-wavelength narrow linewidth monolithic fiber amplifier was constructed through one-stage MOPA configuration. The fiber amplifier emits at the central wavelength of ~1050 nm, and the output lasing performance is carefully studied for different pumping scheme. The experimental results indicated that compared with the co-pumping scheme, the counter-pump one holds a better properties involving spectral broadening suppression, SRS suppression and TMI threshold enhancement in the 1050 nm narrow-linewidth fiber lasers. As a result, an output power of 3.56 kW was achieved with a slope efficiency of ~83.6% by adopting bidirectional pumping scheme. At the maximum lasing power, the 3dB spectral linewidth was measured ~0.58 nm, and the SRS suppression ratio was greater than ~27.3dB. This work could offer a promising approach for extending the operating wavelength of high-power narrow linewidth fiber lasers. © 2025 SPIE.

关键词： Fiber lasers

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The Power of Graph Signal Processing for Chip Placement Acceleration 24

The Power of Graph Signal Processing for Chip Placement Acce...

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43rd International Conference on Computer-Aided Design, ICCAD 2024

作者： Liu, Yiting Zhou, Hai Wang, Jia Yang, Fan Zeng, Xuan Shang, Li School of Computer Science Fudan University Shanghai China Department of ECE Northwestern University Evanston United States Department of ECE IIIinois Institute of Technology Chicago United States State Key Lab of ASIC & System Microelectronics Department Fudan University Shanghai China

ISBN: (纸本)9798400710773

Placement is a critical task with high computation complexity in VLSI physical design. Modern analytical placers formulate the placement objective as a nonlinear optimization task, which suffers a long iteration time. To accelerate and enhance the placement process, recent studies have turned to deep learning-based approaches, particularly leveraging graph convolution networks (GCNs). However, learning-based placers require time- and data-consuming model training due to the complexity of circuit placement that involves large-scale cells and design-specific graph statistics. This paper proposes GiFt, a parameter-free technique for accelerating placement, rooted in graph signal processing. GiFt excels at capturing multi-resolution smooth signals of circuit graphs to generate optimized placement solutions without the need for time-consuming model training, and meanwhile significantly reduces the number of iterations required by analytical placers. Experimental results show that GiFt significantly improving placement efficiency, while achieving competitive or superior performance compared to state-of-the-art placers. In particular, compared to DREAMPlace, the recently proposed GPU-accelerated analytical placer, GF-Placer improves total runtime over 45%. © 2024 Copyright is held by the owner/author(s).

关键词： Nonlinear programming

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Toward Optimal Filler Cell Insertion with Complex Implant Layer Constraints 23

Toward Optimal Filler Cell Insertion with Complex Implant La...

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Proceedings of the 60th Annual ACM/IEEE Design Automation Conference

作者： Peng Zou Guohao Chen Zhifeng Lin Jun Yu Jianli Chen State Key Lab of ASIC & System Fudan University Shanghai China Center for Discrete Mathematics and Theoretical Computer Science Fuzhou University Fuzhou China

ISBN: (纸本)9798350323481

Modern circuits often contain standard cells of different threshold voltages (multi-VTs) to achieve a better trade-off between timing and power consumption. Due to the heterogeneous cell structures, the multi-VTs cells impose various implant layer constraints, further complicating the already time-consuming filler cell insertion process. In this paper, we present a fast and near-optimal algorithm to solve the filler insertion problem with complex implant layer rules and minimum filler width constraints. We first propose an inference-driven detecting algorithm to identify each design rule violation accurately. Then, a dynamic-programming-based insertion method is developed to reduce the implant layer violations. Finally, we design a contour-driven violation refinement strategy to further improve manufacturability. Experimental results show that our algorithm can reduce the number of violations significantly compared with state-of-the-art works. Besides, with our identifier in the legalization stage, we can avoid conflicts in advance and solve almost all violations after filler insertion in industrial cases.

关键词： filler insertion

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Cross-Sensor SAR Image Target Detection Based on Dynamic Feature Discrimination and Center-Aware Calibration

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IEEE Transactions on Geoscience and Remote Sensing 2025年 63卷

作者： Zhang, Xianghui Zhang, Siqian Sun, Zhongzhen Liu, Chenfang Sun, Yuli Ji, Kefeng Kuang, Gangyao National University of Defense Technology State Key Lab. of Complex Electromagnetic Environment Effects on Electronics and Information System College of Electronic Science and Technology Changsha410073 China

In practical synthetic aperture radar (SAR) target detection applications, it is often encountered that the training and testing data come from different SAR sensors, leading to a decline in the SAR target detection performance. Although domain adaptation methods can achieve model generalization through feature transfer, the change of scattering characteristics for the same target and the difference in feature distribution, caused by cross sensor, cannot be ignored in SAR images. It is inevitable to lead to the escalation of the offset in the bounding box regression and deviation of the feature alignment. To address these issues, a cross-sensor SAR image target detection method based on the dynamic feature discrimination and center-aware calibration is proposed. Based on the domain adaptation framework, initially, a dynamic feature discrimination module (DFDM) is introduced to address the exacerbated offset in the regression. A bidirectional spatial feature aggregation (BSFA) mechanism is employed to aggregate features in both horizontal and vertical directions, and a multiscale structure is adopted to enhance the scattering and semantic features, which can dynamically constrain the target position while improving target discrimination capability. Then, the center-aware calibration module (CACM) is designed to address the alignment deviation in feature transfer. The target salience relationship is modeled based on the distance between different positions and the target center to suppress the background clutter interference. The perception center of the target is focused by combining the centerness map and classification map, which can calibrate the domain-invariant features and alleviate misalignment. Finally, the proposed method is tested on two datasets, MiniSAR and FARAD, and compared with the latest domain adaption methods. Both mAP and F1 values have improved by more than 6%-20%, verifying the effectiveness of the proposed method. © 1980-2012 IEEE.

关键词： Calibration

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The Power of Graph Signal Processing for Chip Placement Acceleration

arXiv

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arXiv 2025年

关键词： Nonlinear programming

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PUFFER: A Routability-Driven Placement Framework via Cell Padding with Multiple Features and Strategy Exploration 23

PUFFER: A Routability-Driven Placement Framework via Cell Pa...

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Proceedings of the 60th Annual ACM/IEEE Design Automation Conference

作者： Zhijie Cai Peng Zou Zhengtao Wu Xingyu Tong Jun Yu Jianli Chen Yao-Wen Chang State Key Lab of ASIC & System Fudan University Shanghai China Shanghai LEDA Technology Co. Ltd. Shanghai China Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan and Department of Electrical Engineering National Taiwan University Taipei Taiwan

ISBN: (纸本)9798350323481

Placement is a critical stage in VLSI physical design, especially for routability optimization. Due to the large scale and high integration introduced by the advanced semiconductor manufacturing technology, there remains a significant challenge in routability in the placement stage, which will affect the subsequent routing process. This paper proposes a placement framework, called PUFFER, to optimize routability by cell padding and strategy exploration. The framework first estimates congestion by imitating the behaviors of routing detours and clustered cell spreading. Then it calculates cell padding based on multiple features inspired by the characteristics of convolutional and graph neural networks. Besides, it applies a Bayesian-based method to explore a better placement strategy. Compared with a commercial tool and the state-of-the-art academic RePlAce placer, experiments on industrial benchmarks show that our framework achieves the best routability on average, with a 2.7× speedup over the commercial tool.

关键词： physical design

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