广东工业大学 物理与光电工程学院,广州 510006
针对传统Cascade算法协商效率低、吞吐量不高的问题,提出了一种面向共驱混沌同步密钥分发的Cascade-Biconf信息协商算法。该算法基于奇偶校验和二分法纠错算法的原理,将所得密钥进行置乱、分块并传输校验值用以二分法纠错。与传统Cascade算法不同,Cascade-Biconf信息协商算法通过优化分块的大小降低了协商过程中的交互次数和计算量。仿真结果表明:在通信双方初始密钥误码率为0.1的情况下,Cascade-Biconf信息协商算法可将传统Cascade算法的协商效率由0.76提升到0.84,总吞吐量提升27.9%。
信息协商 Cascade算法 密钥分发 混沌同步 保密通信 information reconciliation, Cascade algorithm, key
Author Affiliations
Abstract
1 Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei 230026, China
2 College of Light-Textile Engineering and Art, Anhui Agriculture University, Hefei 230036, China
Metallic few-layered 1T phase vanadium disulfide nanosheets have been employed for boosting sodium ion batteries. It can deliver a capacity of 241 mAh?g?1 at 100 mA?g?1 after 200 cycles. Such long-term stability is attributed to the facile ion diffusion and electron transport resulting from the well-designed two-dimensional (2D) electron-electron correlations among V atoms in the 1T phase and optimized in-planar electric transport. Our results highlight the phase engineering into electrode design for energy storage.
metallic 1T phase vanadium disulfide ultrathin nanosheet sodium ion batteries Journal of Semiconductors
2023, 44(11): 112701
合肥工业大学 微电子设计研究所 教育部IC设计网上合作研发中心, 合肥 230601
在无人机3D地形测绘中, 作为核心模块的时间数字转换器(TDC)需要具有远距离测量能力和高测量分辨率。基于对测距系统的长续航、公里级测距能力和厘米级测量精度的综合考量, 文章设计了一种用于TDC的低功耗多相位时钟生成电路。采用了伪差分环形压控振荡器, 通过优化交叉耦合结构, 在保证低功耗的前提下, 提升了信号边缘的斜率, 增强了时钟的抖动性能和对电源噪声的抑制能力。在电荷泵设计中, 通过对环路带宽的考量选取了极低的偏置电流, 在进一步降低功耗的同时缩小了环路滤波器的面积。基于SMIC 180 nm CMOS工艺完成了对多相时钟生成电路的设计。仿真结果表明, 在400 MHz的输出频率下, 环路带宽稳定在1 MHz。该电路在不同工艺角下均能达到较快的锁定速度, 相位噪声为-88 dBc@1 MHz, 功耗为1 mW, 均方根抖动为27 ps, 满足厘米级测距的精度需求。
时间数字转换器 多相时钟 低功耗 压控振荡器 电荷泵 TDC multi-phase clock low power consumption voltage controlled oscillator charge pump
为了进一步提升P-GaN 栅HEMT器件的阈值电压和击穿电压, 提出了一种具有P-GaN栅结合混合掺杂帽层结构的氮化镓高电子迁移率晶体管(HEMT)。新器件利用混合掺杂帽层结构, 调节整体极化效应, 可以进一步耗尽混合帽层下方沟道区域的二维电子气, 提升阈值电压。在反向阻断状态下, 混合帽层可以调节栅极右侧电场分布, 改善栅边电场集中现象, 提高器件的击穿电压。利用Sentaurus TCAD进行仿真, 对比普通P-GaN栅增强型器件, 结果显示, 新型结构器件击穿电压由593 V提升至733 V, 增幅达24%, 阈值电压由0509 V提升至1323 V。
氮化镓高电子迁移率晶体管 增强型 击穿电压 混合帽层 GaN HEMT enhancement-mode breakdown voltage hybrid cap layer
Author Affiliations
Abstract
1 Key Laboratory of Nanodevices and Applications, Suzhou Institute of Nano-Tech and Nano-Bionics (SINANO), Chinese Academy of Sciences (CAS), Suzhou 215123, China
2 School of Nano-Tech and Nano-Bionics, University of Science and Technology of China, Hefei 230026, China
3 Jiangsu Key Laboratory of Micro and Nano Heat Fluid Flow Technology and Energy Application, School of Physical Science and Technology, Suzhou University of Science and Technology, Suzhou 215009, China
4 e-mail: ykzhao2017@sinano.ac.cn
5 e-mail: sllu2008@sinano.ac.cn
The fast development of the brain-inspired neuromorphic computing system has ignited an urgent demand for artificial synapses with low power consumption. In this work, it is the first time a light-stimulated low-power synaptic device based on a single GaN nanowire has been demonstrated successfully. In such an artificial synaptic device, the incident light, the electrodes, and the light-generated carriers play the roles of action potential, presynaptic/postsynaptic membrane, and neurotransmitter in a biological synapse, respectively. Compared to those of other synaptic devices based on GaN materials, the energy consumption of the single-GaN-nanowire synaptic device can be reduced by more than 92%, reaching only . It is proposed that the oxygen element can contribute to the synaptic characteristics by taking the place of the nitrogen site. Moreover, it is found that the dynamic “learning-forgetting” performance of the artificial synapse can resemble the behavior of the human brain, where less time is required to relearn the missing information previously memorized and the memories can be strengthened after relearning. Based on the experimental conductance for long-term potentiation (LTP) and long-term depression (LTD), the simulated network can achieve a high recognition rate up to 90% after only three training epochs. Such few training times can reduce the energy consumption in the supervised learning processes substantially. Therefore, this work paves an effective way for developing single-nanowire-based synapses in the fields of artificial intelligence systems and neuromorphic computing technology requiring low-power consumption.
Photonics Research
2023, 11(10): 1667
提出一种基于注意力和中间融合表示的三维重建模型, 旨在重建具有精细化结构的三维模型。该方法利用轴向空间注意力机制学习不同方向的信息, 将其嵌入编码器中以捕获局部结构特征; 并基于双流网络推测深度图和三维平均形状以设计中间融合表示模块, 该模块能够有效地融合可见表面细节信息, 从而更好地描绘对象的三维空间结构。实验结果表明: 所提出的轴向空间注意力机制和中间融合表示模块增强了特征提取的能力, IoU和F-score比PixVox++分别提升了1.3%和0.4%, 三维重建效果更优。
深度学习 三维重建 轴向空间注意力 深度图 中间融合表示 deep learning 3D reconstruction axial spatial attention depth map intermediate fusion representation
1 1.江苏大学 环境与安全工程学院, 镇江 212013
2 2.江苏大学 能源研究院, 镇江 212013
3 3.扬州大学 环境科学与工程学院, 扬州 225127
在光催化产氢反应中引入助催化剂可促进光生电子快速转移, 是提高光催化活性的有效方法。而目前, 高效助催化剂主要仍然是贵金属, 其高昂的价格极大限制了实际应用。本研究探讨了构筑非贵金属助催化剂CoN与g-C3N4 0D/2D紧密界面对光催化制氢性能的影响。负载非贵金属助催化剂CoN可以有效提高2D g-C3N4的光催化制氢活性, 负载量对其活性也有影响。构筑的0D/2D紧密界面有利于光生电子快速传输。两者的共同作用使得10% CoN/2D g-C3N4复合物光催化制氢效率达到403.6 μmol·g-1·h-1, 是2D g-C3N4单体的20倍。在CoN/2D g-C3N4复合材料中, 负载CoN作为析氢助催化剂可以显著促进电荷转移过程, 从而大幅提高光催化析氢活性。
非贵金属 CoN 助催化剂 光催化 产氢 non-noble metal CoN cocatalyst photocatalysis hydrogen production
Author Affiliations
Abstract
1 Xiamen University, School of Electronic Science and Engineering, Fujian Key Laboratory of Ultrafast Laser Technology and Applications, Xiamen, China
2 Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen, China
3 Huawei Technologies Co., Ltd., Shenzhen, China
4 Xiamen University, Shenzhen Research Institute, Shenzhen, China
Green semiconductor lasers are still undeveloped, so high-power green lasers have heavily relied on nonlinear frequency conversion of near-infrared lasers, precluding compact and low-cost green laser systems. Here, we report the first Watt-level all-fiber CW Pr3 + -doped laser operating directly in the green spectral region, addressing the aforementioned difficulties. The compact all-fiber laser consists of a double-clad Pr3 + -doped fluoride fiber, two homemade fiber dichroic mirrors at visible wavelengths, and a 443-nm fiber-pigtailed pump source. Benefitting from > 10 MW / cm2 high damage intensity of our designed fiber dielectric mirror, the green laser can stably deliver 3.62-W of continuous-wave power at ∼ 521 nm with a slope efficiency of 20.9%. To the best of our knowledge, this is the largest output power directly from green fiber lasers, which is one order higher than previously reported. Moreover, these green all-fiber laser designs are optimized by using experiments and numerical simulations. Numerical results are in excellent agreement with our experimental results and show that the optimal gain fiber length, output mirror reflectivity, and doping level should be considered to obtain higher power and efficiency. This work may pave a path toward compact high-power green all-fiber lasers for applications in biomedicine, laser display, underwater detection, and spectroscopy.
fiber laser high power Pr3+-doped fiber green light Advanced Photonics
2022, 4(5): 056001