Communications engineering最新文献

A bio-inspired customizable mechanical central pattern generator enables one-to-many scalable pneumatic control. 生物灵感可定制的机械中央图案生成器实现一对多可扩展的气动控制。

Communications engineering Pub Date : 2026-05-06 DOI: 10.1038/s44172-026-00680-x

Yuyan Qi, Yongjian Zhao, Jiaqi Shao, Bin Sun, Songyi Zhong, Shaorong Xie, Xiaote Xu, Xiaoqiang Guo, Ying Hong, Biao Wang, Yang Yang

{"title":"A bio-inspired customizable mechanical central pattern generator enables one-to-many scalable pneumatic control.","authors":"Yuyan Qi, Yongjian Zhao, Jiaqi Shao, Bin Sun, Songyi Zhong, Shaorong Xie, Xiaote Xu, Xiaoqiang Guo, Ying Hong, Biao Wang, Yang Yang","doi":"10.1038/s44172-026-00680-x","DOIUrl":"https://doi.org/10.1038/s44172-026-00680-x","url":null,"abstract":"As pneumatic robotics evolve toward high-degree-of-freedom arrays with multiple actuators, the conventional one-valve-one-actuator control paradigm inevitably leads to component redundancy and convoluted tubing layouts. To fundamentally reduce the controller's quantity, here we propose a bioinspired customizable mechanical central pattern generator as an entirely electronics-free one-to-many scalable pneumatic control core. As an externally-clocked mechanical central pattern generator analog, this device integrates multi-channel timing logic into a single physical unit, enabling a single pneumatic input to drive multiple output channels in coordinated, predefined sequences and thereby achieving efficient 1:n pneumatic control over multiple actuators. Experimental characterizations of four- and five-channel configurations demonstrate pressure retention rates exceeding 90.8% across varying input pressures and loads. Leveraging discrete and mechanically-latched state transitions, the device decouples its internal clock from external load dynamics, ensuring exceptional sequence fidelity even under physical disturbances. Applications involving a three-chamber pipeline robot, a point-to-point material handling system, and a five-fingered dexterous hand comprehensively demonstrate the device's remarkable multi-channel coordination, scalability, and customizability. By embedding control logic into its physical structure, this work fundamentally breaks the coupling between system complexity and controller count, providing a new paradigm for electronics-free and autonomous pneumatic systems.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147846926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimized sensor-embedded loose garment for accurate motion detection. 优化传感器嵌入式宽松服装，准确的运动检测。

Communications engineering Pub Date : 2026-05-06 DOI: 10.1038/s44172-026-00675-8

Mohamed Elgendi, Tomasz Raczyński, Alexander Shokurov, Daniel Janczak, Małgorzata Jakubowska, Carlo Menon

{"title":"Optimized sensor-embedded loose garment for accurate motion detection.","authors":"Mohamed Elgendi, Tomasz Raczyński, Alexander Shokurov, Daniel Janczak, Małgorzata Jakubowska, Carlo Menon","doi":"10.1038/s44172-026-00675-8","DOIUrl":"https://doi.org/10.1038/s44172-026-00675-8","url":null,"abstract":"Wearable technology has become increasingly important for health monitoring, sports performance, and ergonomic assessments because it enables continuous, non-invasive, and real-time tracking of physiological and biomechanical signals in real-world environments, overcoming limitations of laboratory-based assessments. This paper presents the development, testing, and initial study of a sensor-embedded loose garment designed for motion analysis using conductive ink. Sensors were strategically placed across key areas of the T-shirt to capture comprehensive motion data from the torso. Positioned on the chest, shoulders, ribcage, and lower torso, these sensors detect detailed movements. The study evaluates various sensor combinations with four classifiers-XGBoost, RandomForest, SVM, and K-Nearest Neighbors-using data from ten sensor locations analyzed with three holdout methods (20-80%, 30-70%, and 50-50%). Results underscore the impact of specific sensor placements, with combinations on the shoulder, ribcage, and abdomen yielding the highest accuracy. This work advances textile-based motion recognition, showing the potential for wearable technology to distinguish among eight movements in a loose garment.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147846855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Domain knowledge embedded anti-disturbance autonomous navigation for marine vehicles. 船舶自主导航领域知识嵌入。

Communications engineering Pub Date : 2026-05-06 DOI: 10.1038/s44172-026-00666-9

Yujiao Zhao, Yong Ma, Guibing Zhu, Songlin Hu, Wenqi Wang, Xinping Yan

{"title":"Domain knowledge embedded anti-disturbance autonomous navigation for marine vehicles.","authors":"Yujiao Zhao, Yong Ma, Guibing Zhu, Songlin Hu, Wenqi Wang, Xinping Yan","doi":"10.1038/s44172-026-00666-9","DOIUrl":"10.1038/s44172-026-00666-9","url":null,"abstract":"The complex ocean disturbances in ocean engineering have long constrained the precise autonomous navigation of intelligent marine vehicles, such as surface vessels and underwater vehicles. Nevertheless, the unpredictable wind-wave-current coupling effects pose severe challenges to the safety of autonomous navigation for marine vehicles. Here we introduce a domain knowledge embedded disturbance observation-control framework, fusing real-time observation and compensation for composite environmental disturbances using model-free control. This framework embeds specialized basis functions from domain knowledge into a specialized Kolmogorov-Arnold network and extracts control knowledge therefrom to train a machine learning controller. Our approach achieves better adaptability and robustness, surpassing conventional model-based controllers. It enables more accurate path-following and safer operations under complex ocean disturbances. It is worth noting that this method has been validated to be effective for both surface vessels and underwater vehicles through offshore wind farms inspection task scenarios. It fundamentally extends the adaptive control theory for marine cyber-physical systems and has potential applications in multi-domain oceanographic operations.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13149777/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147846919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Vat photopolymerization of gel polymer electrolytes with solvent-dependent performance and complex geometries for Li-ion batteries. 具有溶剂依赖性能和复杂几何形状的凝胶聚合物电解质的还原光聚合用于锂离子电池。

Communications engineering Pub Date : 2026-05-05 DOI: 10.1038/s44172-026-00682-9

Alexis Maurel, Katherine R Gonzalez, Hugo A Garcia, Laura C Merrill, Ana C Martinez

{"title":"Vat photopolymerization of gel polymer electrolytes with solvent-dependent performance and complex geometries for Li-ion batteries.","authors":"Alexis Maurel, Katherine R Gonzalez, Hugo A Garcia, Laura C Merrill, Ana C Martinez","doi":"10.1038/s44172-026-00682-9","DOIUrl":"https://doi.org/10.1038/s44172-026-00682-9","url":null,"abstract":"Additive manufacturing offers new opportunities for fabricating next-generation battery components with unprecedented control over three-dimensional architecture and spatial complexity. This study presents the development and electrochemical characterization of 3D printable gel polymer electrolytes (GPEs) based on a UV-curable PEGDA resin and a liquid electrolyte composed of 1 M LiClO4 in EC:DEC or EC:PC (1:1 v/v). The impact of resin-to-electrolyte ratios on ionic conductivity and processability is systematically evaluated, with 1:4 v/v identified as the optimal formulation. GPEs fabricated via vat photopolymerization exhibit high ionic conductivities of up to 3.4 × 10-3 S.cm-1 (DEC-based) and 3.1 × 10-3 S.cm-1 (PC-based), closely matching their tape-cast counterparts. Electrochemical stability is maintained up to ~4.5 V vs. Li0/Li+, with symmetric cell testing confirming effective Li0 plating/stripping over 100 cycles. The 3D printed GPEs retain their electrochemical performance despite performing the printing process in ambient air, demonstrating robustness and compatibility with scalable manufacturing. In addition, the GPEs can be printed into complex geometries, further underscoring their suitability for advanced device architectures. This work highlights the critical role of solvent selection and printing parameters in designing printable GPEs and paves the way toward shape-conformable, solid-state battery systems.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147846877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Foldable magnetic flux transformation for wide-area, misalignment-tolerant and interoperable wireless charging. 可折叠磁通量变换，用于广域、容差和可互操作的无线充电。

Communications engineering Pub Date : 2026-05-05 DOI: 10.1038/s44172-026-00625-4

Jianwei Mai, Ao Yang, Wei Bi, Yijie Wang, Haoyu Wang, Jiewen Zhang, Zhigang Liu, Dianguo Xu

引用次数: 0

Microwave-acoustic-based isolated gate driver for power electronics. 基于微波声的电力电子隔离栅驱动器。

Communications engineering Pub Date : 2026-05-05 DOI: 10.1038/s44172-026-00681-w

Liyang Jin, Zichen Xi, Joseph G Thomas, Jun Ji, Yuanzhi Zhang, Nuo Chen, Yizheng Zhu, Linbo Shao, Liyan Zhu

{"title":"Microwave-acoustic-based isolated gate driver for power electronics.","authors":"Liyang Jin, Zichen Xi, Joseph G Thomas, Jun Ji, Yuanzhi Zhang, Nuo Chen, Yizheng Zhu, Linbo Shao, Liyan Zhu","doi":"10.1038/s44172-026-00681-w","DOIUrl":"https://doi.org/10.1038/s44172-026-00681-w","url":null,"abstract":"Electrical isolation is critical to ensure safety and minimize electromagnetic interference (EMI), yet existing methods struggle to simultaneously transmit power and signals through a unified channel. Here we demonstrate a mechanically-isolated gate driver based on microwave-frequency surface acoustic wave (SAW) device on lithium niobate that achieves galvanic isolation of 2.75 kV with ultralow isolation capacitance (0.032 pF) over 1.25 mm mechanical propagation length, delivering 13.4 V open-circuit voltage and 44.4 mA short-circuit current. We demonstrate isolated gate driving for a gallium nitride (GaN) high-electron-mobility transistor, achieving a turn-on time of 108.8 ns and validate its operation in a buck converter. In addition, our SAW device operates over an ultrawide temperature range from 0.5 K (-272.6 °C) to 544 K (271 °C). The microwave-frequency SAW devices offer inherent EMI immunity and potential for heterogeneous integration on multiple semiconductor platforms, enabling compact, high-performance isolated power and signal transmission in advanced power electronics.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147846934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Solar radiation prediction using multivariate signal decomposition and physics-informed time-frequency feature extraction. 基于多变量信号分解和物理信息时频特征提取的太阳辐射预测。

Communications engineering Pub Date : 2026-05-05 DOI: 10.1038/s44172-026-00677-6

Xingchen Mo, Jingzhou Xin, Yan Jiang, Qizhi Tang

{"title":"Solar radiation prediction using multivariate signal decomposition and physics-informed time-frequency feature extraction.","authors":"Xingchen Mo, Jingzhou Xin, Yan Jiang, Qizhi Tang","doi":"10.1038/s44172-026-00677-6","DOIUrl":"https://doi.org/10.1038/s44172-026-00677-6","url":null,"abstract":"Accurate prediction of solar radiation plays a crucial role in optimizing the solar energy system design and enhancing the efficiency of photovoltaic power grid integration. However, due to the complex dynamic characteristics of solar radiation data, the realization of such a tough task faces a formidable challenge. To this end, this study presents a solar radiation prediction method which mainly consists of the high-quality data preprocessing technique and the frequency-domain physics-informed convolutional network (FD-PICN). This method can handle the complex characteristics embedded in the solar radiation data from the spatial-temporal-frequency domain. Specifically, multivariate fast iterative filtering is first employed to synchronously decompose the multi-station solar radiation data into a series of time-frequency consistent subseries where the spatiotemporal and time-frequency correlations among multiple stations are considered. Then, FD-PICN is designed to capture the evolution pattern of solar radiation by integrating cross-attention-assisted time-frequency feature extraction and two physical coherence functions (i.e., frequency-domain coherence function and phase lock value) for high-performance prediction. Finally, numerical examples grounded in the measured data from multiple stations are utilized to validate the capability of this method. Experimental analyses demonstrate that this method outperforms other compared methods across various predictive scenarios.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147846929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Reinforcement learning increases wind farm power production by enabling closed-loop collaborative control. 强化学习通过实现闭环协同控制来提高风力发电场的发电量。

Communications engineering Pub Date : 2026-05-05 DOI: 10.1038/s44172-026-00667-8

Andrew Mole, Max Weissenbacher, Georgios Rigas, Sylvain Laizet

{"title":"Reinforcement learning increases wind farm power production by enabling closed-loop collaborative control.","authors":"Andrew Mole, Max Weissenbacher, Georgios Rigas, Sylvain Laizet","doi":"10.1038/s44172-026-00667-8","DOIUrl":"https://doi.org/10.1038/s44172-026-00667-8","url":null,"abstract":"Traditional wind farm control operates each turbine independently to maximize individual power output. However, coordinated wake steering across the entire farm can substantially increase the combined wind farm energy production. Although dynamic closed-loop control has proven effective in flow control applications, wind farm optimization has relied primarily on static, low-fidelity simulators that do not resolve critical dynamic turbulent fluctuations in the flow. In this work, we present a reinforcement learning controller trained using high-fidelity turbulence resolving simulations, enabling real-time response to atmospheric turbulence through collaborative, dynamic control strategies. In a three wind turbine test case, our reinforcement learning controller achieves a 4.30% (95% CI = [4.10%, 4.49%]) increase in wind farm power output compared to baseline operation, nearly doubling the 2.19% (95% CI = [1.98%, 2.39%]) gain from static optimal yaw control and a substantial increase over the gain from global wind direction based dynamic control obtained through Bayesian optimization of 2.67% (95% CI = [2.47%, 2.87%]). These results establish that reinforcement learning is able to utilize the increased information available from turbulence resolved simulations to learn improved, dynamic flow-responsive control for wind farm power maximization, with direct implications for accelerating renewable energy deployment to net-zero targets.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147846885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Beam manipulation for terahertz communications. 太赫兹通信的波束操纵。

Communications engineering Pub Date : 2026-05-04 DOI: 10.1038/s44172-026-00676-7

Mingxiang Li, Josep M Jornet, Daniel M Mittleman, Chong Han

{"title":"Beam manipulation for terahertz communications.","authors":"Mingxiang Li, Josep M Jornet, Daniel M Mittleman, Chong Han","doi":"10.1038/s44172-026-00676-7","DOIUrl":"https://doi.org/10.1038/s44172-026-00676-7","url":null,"abstract":"The terahertz frequency band, ranging from 0.1 to 10 THz, offers extensive spectral resources for next-generation wireless communications systems. To compensate for the limited transmit power of terahertz transceivers and severe propagation losses, high-gain directional transmission is essential, making dynamic beam manipulation a key enabler for practical terahertz communications. The stringent gain requirements further extend the Fresnel region, necessitating efficient beam manipulation across both near-field and far-field conditions. The increasing reliance on beam manipulation reflects a paradigm shift in terahertz communications, where performance scaling is achieved through architecture-level innovation rather than solely through incremental hardware or algorithmic improvements. This article provides a comprehensive overview of terahertz beam manipulation techniques. It begins with an introduction of diffraction theory as the foundational propagation model for beam manipulation. Detailed examples tailored to specific communication scenarios are then presented. Experimental verifications using lenses and metasurfaces are included for three distinct beam manipulation cases. Alternative approaches for achieving beam manipulation, such as reconfigurable intelligent surfaces, are briefly discussed.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13139571/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147846899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Microstructure-informed constitutive modeling of granular media under multidirectional loading: From particle-scale to continuum. 多向加载下颗粒介质的微观结构本构建模：从颗粒尺度到连续体。

Communications engineering Pub Date : 2026-04-30 DOI: 10.1038/s44172-026-00652-1

Nazanin Irani, Pegah Golestaneh, Mohammad Salimi, Merita Tafili, Yuha Park, Johannes Lederer

{"title":"Microstructure-informed constitutive modeling of granular media under multidirectional loading: From particle-scale to continuum.","authors":"Nazanin Irani, Pegah Golestaneh, Mohammad Salimi, Merita Tafili, Yuha Park, Johannes Lederer","doi":"10.1038/s44172-026-00652-1","DOIUrl":"10.1038/s44172-026-00652-1","url":null,"abstract":"Simulating the response of granular materials under realistic loading scenarios is essential for ensuring the reliability of geotechnical infrastructure. This task is particularly challenging because natural soils exhibit inherently non-uniform particle arrangements due to gravitational sedimentation and are subjected to complex, multidirectional loading conditions from environmental forces such as wind and seismic activity. Unlike crystalline solids, there is no closed-form mathematical framework that fully describes soil's collective response. In engineering practice, this complexity is typically addressed using nonlinear constitutive models calibrated against laboratory data. However, such data are often specific to the site and material, influenced by variations in soil type, particle morphology, experimental apparatus, and loading conditions, making them difficult to generalize. The discrete element method (DEM) offers a unique pathway to overcome these limitations by providing direct access to particle-scale kinematics, contact forces, and evolving microstructure. As assemblies of particles exhibit chaotic rearrangements under loading, predicting their collective behavior becomes highly nonlinear and computationally intensive. Here, deep-learning models offer a promising route to replicate these complex relationships. In this work, we develop a deep-learning model using DEM simulations to address fundamental challenges in predicting the response of granular media under multidirectional loading paths, with direct applications to pressing engineering problems such as optimizing wind turbine foundations.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13133363/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147790768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0