Communications engineering最新文献_第2页

A catalyst-coated diaphragm assembly to improve the performance and energy efficiency of alkaline water electrolysers.

Communications engineering Pub Date : 2025-01-25 DOI: 10.1038/s44172-025-00344-2

Zhuang Xu, Yanying Liu, Xiaobo Cheng, Yunshan Shang, Yongtao Wang, Jing Wang, Wenshi Li, Guangli He

{"title":"A catalyst-coated diaphragm assembly to improve the performance and energy efficiency of alkaline water electrolysers.","authors":"Zhuang Xu, Yanying Liu, Xiaobo Cheng, Yunshan Shang, Yongtao Wang, Jing Wang, Wenshi Li, Guangli He","doi":"10.1038/s44172-025-00344-2","DOIUrl":"10.1038/s44172-025-00344-2","url":null,"abstract":"Alkaline water electrolysers are ideal for gigawatt-scale hydrogen production due to the usage of non-precious metal and low-cost raw materials. However, their performances are modest with the separated electrode and diaphragm structure which can date back to more than 100 years ago. Here we report a catalyst-coated diaphragm assembly to improve the performance of alkaline water electrolysers. The transport resistance of OH- ions is reduced and the electrochemical surface area of catalysts is enlarged by more than forty fold, representing more than 40% increase in hydrogen production rate or as much as 16% reduction in energy consumption. The electrolyser with our catalyst-coated diaphragm assembly delivers current densities as high as 1 A cm-2 at 1.8 V or 2 A cm-2 at 2 V and shows good stability after more than 1000 hours of operation. Therefore, the catalyst-coated diaphragm assembly route is promising for the development of high-performance and efficient alkaline water electrolysers.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":"4 1","pages":"9"},"PeriodicalIF":0.0,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11759708/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143043473","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

Editors' Choice 2024.

Communications engineering Pub Date : 2025-01-24 DOI: 10.1038/s44172-024-00335-9

Miranda Vinay, Maria Sakovsky, Alessandro Rizzo, Yasaman Ghasempour, Rosamund Daw, Chaoran Huang, Saleem Denholme, Ali Behnood, Wan-Ting Chen, Or Perlman, Anastasiia Vasylchenkova, Massimo Mastrangeli, Sandra Rugonyi, Jordan Raney

引用次数: 0

Distributed training of foundation models for ophthalmic diagnosis.

Communications engineering Pub Date : 2025-01-22 DOI: 10.1038/s44172-025-00341-5

Sina Gholami, Fatema-E Jannat, Atalie Carina Thompson, Sally Shin Yee Ong, Jennifer I Lim, Theodore Leng, Hamed Tabkhivayghan, Minhaj Nur Alam

{"title":"Distributed training of foundation models for ophthalmic diagnosis.","authors":"Sina Gholami, Fatema-E Jannat, Atalie Carina Thompson, Sally Shin Yee Ong, Jennifer I Lim, Theodore Leng, Hamed Tabkhivayghan, Minhaj Nur Alam","doi":"10.1038/s44172-025-00341-5","DOIUrl":"10.1038/s44172-025-00341-5","url":null,"abstract":"Vision impairment affects nearly 2.2 billion people globally, and nearly half of these cases could be prevented with early diagnosis and intervention-underscoring the urgent need for reliable and scalable detection methods for conditions like diabetic retinopathy and age-related macular degeneration. Here we propose a distributed deep learning framework that integrates self-supervised and domain-adaptive federated learning to enhance the detection of eye diseases from optical coherence tomography images. We employed a self-supervised, mask-based pre-training strategy to develop a robust foundation encoder. This encoder was trained on seven optical coherence tomography datasets, and we compared its performance under local, centralized, and federated learning settings. Our results show that self-supervised methods-both centralized and federated-improved the area under the curve by at least 10% compared to local models. Additionally, incorporating domain adaptation into the federated learning framework further boosted performance and generalization across different populations and imaging conditions. This approach supports collaborative model development without data sharing, providing a scalable, privacy-preserving solution for effective retinal disease screening and diagnosis in diverse clinical settings.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":"4 1","pages":"6"},"PeriodicalIF":0.0,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11754456/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143026082","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

Ultrafast humidity sensor and transient humidity detections in high dynamic environments. 高动态环境下的超快速湿度传感器和瞬态湿度检测。

Communications engineering Pub Date : 2025-01-18 DOI: 10.1038/s44172-025-00342-4

Fang Liu, Jin Hong, Xiangdong Chen, Xing Ding, Shaopeng Li, Xiang Yu, Jiaqi Lu, Xuan Zhao, Kun Tang, Chenghua Xie, Kemei Zhao

{"title":"Ultrafast humidity sensor and transient humidity detections in high dynamic environments.","authors":"Fang Liu, Jin Hong, Xiangdong Chen, Xing Ding, Shaopeng Li, Xiang Yu, Jiaqi Lu, Xuan Zhao, Kun Tang, Chenghua Xie, Kemei Zhao","doi":"10.1038/s44172-025-00342-4","DOIUrl":"10.1038/s44172-025-00342-4","url":null,"abstract":"Limited by the adsorption and diffusion rate of water molecules, traditional humidity sensors, such as those based on polymer electrolytes, porous ceramics, and metal oxides, typically have long response times, which hinder their application in monitoring transient humidity changes. Here we present an ultrafast humidity sensor with a millisecond-level response. The sensor is prepared by assembling monolayer graphene oxide quantum dots on silica microspheres using a simple electrostatic self-assembly technique. Benefiting from the joint action of the micro spheres and the ultrathin humidity-sensitive film, it displays the fastest response time (2.76 ms) and recovery time (12.4 ms) among electronic humidity sensors. With the ultrafast response of the sensor, we revealed the correlation between humidity changes in speech airflow and speech activities, demonstrated the noise immunity of humidity speech activity detection, confirmed the humidity shock caused by explosions, realized ultrahigh frequency respiratory monitoring, and verified the effect of humidity-triggering in the non-invasive ventilator. This ultrafast humidity sensor has broad application prospects in monitoring transient humidity changes.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":"4 1","pages":"4"},"PeriodicalIF":0.0,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11742969/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143017361","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

Efficient optimisation of physical reservoir computers using only a delayed input. 仅使用延迟输入的物理储层计算机的有效优化。

Communications engineering Pub Date : 2025-01-18 DOI: 10.1038/s44172-025-00340-6

Enrico Picco, Lina Jaurigue, Kathy Lüdge, Serge Massar

引用次数: 0

PlomBOX: a low cost bioassay for the sensitive detection of lead in drinking water. PlomBOX：一种低成本的生物测定法，用于敏感检测饮用水中的铅。

Communications engineering Pub Date : 2025-01-07 DOI: 10.1038/s44172-024-00337-7

A Dias, M Alvarez, Y Gándola, A Deisting, E Alba Posse, H Arnaldi, H Asorey, X Bertou, A Colque, F Favela-Pérez, J Gasulla, M Gómez Berisso, J O Guerra-Pulido, J Lipovetzky, J Lobera, M B Lovino, L Marpegan, D Martín, S Mejía Muñoz, J Monroe, A D Nadra, R Pregliasco, G Rumi, A Rossen, M Tallis, A Thompson, M Triana, M L Vazquez Miranda

{"title":"PlomBOX: a low cost bioassay for the sensitive detection of lead in drinking water.","authors":"A Dias, M Alvarez, Y Gándola, A Deisting, E Alba Posse, H Arnaldi, H Asorey, X Bertou, A Colque, F Favela-Pérez, J Gasulla, M Gómez Berisso, J O Guerra-Pulido, J Lipovetzky, J Lobera, M B Lovino, L Marpegan, D Martín, S Mejía Muñoz, J Monroe, A D Nadra, R Pregliasco, G Rumi, A Rossen, M Tallis, A Thompson, M Triana, M L Vazquez Miranda","doi":"10.1038/s44172-024-00337-7","DOIUrl":"https://doi.org/10.1038/s44172-024-00337-7","url":null,"abstract":"This paper reports the design of a biosensor for sensitive, low-cost measurement of lead in drinking water. The biosensor uses a genetically-modified strain of Escherichia coli, which serves as both signal amplifier and reporter of lead in water, measured via colour change. We developed the PlomBOX measurement platform to image this colour change and we demonstrate its capability to detect concentrations as low as the World Health Organisation upper limit for drinking water of 10 ppb. Our approach does not require expensive infrastructure or expert operators, and its automated sensing, detection and result visualisation platform is user-friendly and robust compared to existing lead biosensors-critical features to enable measurement by non-experts at the point of use.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":"4 1","pages":"2"},"PeriodicalIF":0.0,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11707191/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142959232","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

Bioinspired thermally conducting packaging for heat management of high performance electronic chips. 用于高性能电子芯片热管理的仿生导热封装。

Communications engineering Pub Date : 2025-01-04 DOI: 10.1038/s44172-024-00338-6

Huawei Wang, Pengfei Bai, He Cui, Xiaotong Zhang, Yifan Tang, Shaoyu Liang, Shixiao Li, Guofu Zhou

引用次数: 0

Author Correction: A tunable multi-timescale Indium-Gallium-Zinc-Oxide thin-film transistor neuron towards hybrid solutions for spiking neuromorphic applications 作者更正：一种可调谐的多时间尺度铟镓锌氧化物薄膜晶体管神经元，用于尖峰神经形态应用的混合解决方案。

Communications engineering Pub Date : 2024-12-31 DOI: 10.1038/s44172-024-00336-8

Mauricio Velazquez Lopez, Bernabe Linares-Barranco, Jua Lee, Hamidreza Erfanijazi, Alberto Patino-Saucedo, Manolis Sifalakis, Francky Catthoor, Kris Myny

引用次数: 0

Microscopy image reconstruction with physics-informed denoising diffusion probabilistic model 基于物理信息去噪扩散概率模型的显微图像重建。

Communications engineering Pub Date : 2024-12-29 DOI: 10.1038/s44172-024-00331-z

Rui Li, Gabriel della Maggiora, Vardan Andriasyan, Anthony Petkidis, Artsemi Yushkevich, Nikita Deshpande, Mikhail Kudryashev, Artur Yakimovich

{"title":"Microscopy image reconstruction with physics-informed denoising diffusion probabilistic model","authors":"Rui Li, Gabriel della Maggiora, Vardan Andriasyan, Anthony Petkidis, Artsemi Yushkevich, Nikita Deshpande, Mikhail Kudryashev, Artur Yakimovich","doi":"10.1038/s44172-024-00331-z","DOIUrl":"10.1038/s44172-024-00331-z","url":null,"abstract":"Light microscopy is a practical tool for advancing biomedical research and diagnostics, offering invaluable insights into the cellular and subcellular structures of living organisms. However, diffraction and optical imperfections actively hinder the attainment of high-quality images. In recent years, there has been a growing interest in applying deep learning techniques to overcome these challenges in light microscopy imaging. Nonetheless, the resulting reconstructions often suffer from undesirable artefacts and hallucinations. Here, we introduce a deep learning-based approach that incorporates the fundamental physics of light propagation in microscopy into the loss function. This model employs a conditioned diffusion model in a physics-informed architecture. To mitigate the issue of limited available data, we utilise synthetic datasets for training purposes. Our results demonstrate consistent enhancements in image quality and substantial reductions in artefacts when compared to state-of-the-art methods. The presented technique is intuitively accessible and allows obtaining higher quality microscopy images for biomedical studies. Rui Li, Gabriel della Maggiora and co-authors present a deep learning approach for attenuating diffraction and optical imperfections in light microscopy images. By incorporating the underlying physics of light propagation in microscopy into the loss function and designing a conditional diffusion model, they obtained improved performance compared to the state-of-the-art.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":" ","pages":"1-12"},"PeriodicalIF":0.0,"publicationDate":"2024-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44172-024-00331-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142911235","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

Fast detection of protein kinase B in chrysin treated colorectal cancer cells using a novel multicore microfiber biosensor 利用新型多芯微纤维生物传感器快速检测大肠癌细胞中蛋白激酶B。

Communications engineering Pub Date : 2024-12-26 DOI: 10.1038/s44172-024-00332-y

Zhen Tian, Hongzhuan Xuan, Yicun Yao, Shengyu Hao, Zhichao Zhang, Bingyuan Zhang, Jingao Zhang, Liqiang Zhang, Xinzhu Sang, Jinhui Yuan, Gerald Farrell, Qiang Wu

{"title":"Fast detection of protein kinase B in chrysin treated colorectal cancer cells using a novel multicore microfiber biosensor","authors":"Zhen Tian, Hongzhuan Xuan, Yicun Yao, Shengyu Hao, Zhichao Zhang, Bingyuan Zhang, Jingao Zhang, Liqiang Zhang, Xinzhu Sang, Jinhui Yuan, Gerald Farrell, Qiang Wu","doi":"10.1038/s44172-024-00332-y","DOIUrl":"10.1038/s44172-024-00332-y","url":null,"abstract":"Rapid and accurate determination of target proteins in cells provide essential diagnostic information for early detection of diseases, evaluation of drug responses, and the study of pathophysiological mechanisms. Traditional Western blotting method has been used for the determination, but it is complex, time-consuming, and semi-quantitative. Here, a tapered seven-core fiber (TSCF) biosensor was designed and fabricated. By immobilizing protein kinase B (PKB), also known as AKT, antibody onto TSCF surface, the microfiber biosensor can be used for quantitatively detecting the AKT level in solution concentrations as low as 0.26 ng/mL. To test the reliability of the TSCF sensing method in a medical application, the TSCF biosensor was used to study the relationship between chrysin’s anticancer effect and the concentration of AKT in a human colorectal cancer cell line (LoVo cells). The results reveal that the inhibitory effect of chrysin on LoVo cells is positively correlated with the dose, agreeing well with the equivalent results using the traditional Western blotting method. Zhen Tian, Hongzhuan Xuan, and colleagues show an optical fiber sensor for measuring concentration changes of protein kinase B, also known as AKT, extracted from human Lovo cells. Their biosensor allows studying anti-cancer mechanisms in the human body.","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":" ","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44172-024-00332-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142900806","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