Light-Science & Applications Pub Date : 2025-01-24 DOI: 10.1038/s41377-024-01739-0

Eun-young Choi, Sung-Cheon Kang, Kanghoon Kim, Su-Hyeon Lee, Jeong-Beom Kim, Jang-Kun Song

{"title":"Transparent OLED displays for selective bidirectional viewing using ZnO/Yb:Ag cathode with highly smooth and low-barrier surface","authors":"Eun-young Choi, Sung-Cheon Kang, Kanghoon Kim, Su-Hyeon Lee, Jeong-Beom Kim, Jang-Kun Song","doi":"10.1038/s41377-024-01739-0","DOIUrl":"https://doi.org/10.1038/s41377-024-01739-0","url":null,"abstract":"Transparent organic light-emitting diode (TrOLED) displays represent cutting-edge technology posed to significantly enhance user experience. This study addresses two pivotal challenges in TrOLED development. Firstly, we focus on the innovation of transparent cathodes, a fundamental component in TrOLEDs, by introducing a ZnO/Yb:Ag cathode. This cathode employs a combination of seed layer and metal doping techniques to achieve a highly uniform surface morphology and a low surface energy barrier. The optimized Yb:Ag cathode on ZnO, with a mere thickness of 15 nm, exhibits remarkable properties: an extremely low surface roughness of 0.52 nm, sheet resistance of 11.6 Ω ϒ−1, an optical transmittance of 86.7% at 510 nm, and tunable work function (here, optimized to be 3.86 eV), ensuring superior electron injection capability. Secondly, we propose a novel TrOLED pixel structure that features selective bidirectional viewing, allowing different types of information to be selectively displayed on each side while preserving overall transparency and minimizing pixel complexity. This design innovation distinguishes itself from conventional TrOLEDs that display images on only one side. The bidirectional TrOLED design not only enhances openness and esthetic appeal but also holds promise for diverse applications across various user environments.","PeriodicalId":18069,"journal":{"name":"Light-Science & Applications","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143026587","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

Capillary condensation-driven growth of perovskite nanowire arrays for multi-functional photodetector

Light-Science & Applications Pub Date : 2025-01-24 DOI: 10.1038/s41377-024-01680-2

Gangjian Hu, Jiajun Guo, Jizhong Jiang, Lei Wang, Jiaqi Zhang, Hongxu Chen, Gangning Lou, Wei Wei, Liang Shen

{"title":"Capillary condensation-driven growth of perovskite nanowire arrays for multi-functional photodetector","authors":"Gangjian Hu, Jiajun Guo, Jizhong Jiang, Lei Wang, Jiaqi Zhang, Hongxu Chen, Gangning Lou, Wei Wei, Liang Shen","doi":"10.1038/s41377-024-01680-2","DOIUrl":"https://doi.org/10.1038/s41377-024-01680-2","url":null,"abstract":"Metal-halide perovskite nanowire array photodetectors based on the solution method are valuable in the field of polarized light detection because of their unique one-dimensional array structure and excellent photoelectric performance. However, the limited wettability of liquids poses challenges for achieving large-scale and high-quality perovskite nanowire arrays. To address this issue, we develop a facile method utilizing capillary condensation to grow high-quality centimeter-scale perovskite nanowire arrays. Based on these nanowires, the fabricated photodetector showcases specific detectivities of 1.95 × 1013 jones, surpassing commercially available silicon detectors in weak-light detection capabilities. The weak-light imaging capability of our nanowire photodetectors has been successfully demonstrated at intensities below 54 nW/cm2. Moreover, the nanowire arrays also display excellent polarization absorption characteristics, promising applications in polarized light detection. Notably, the perovskite nanowire arrays can be grown on flexible substrates by employing capillary condensation, which retains 83% of their properties after 2000 bending cycles. This research enhances the potential of perovskite nanowire arrays photodetector in practical applications.","PeriodicalId":18069,"journal":{"name":"Light-Science & Applications","volume":"110 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143026586","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

Optical semantic communication through multimode fiber: from symbol transmission to sentiment analysis 多模光纤光语义通信：从符号传递到情感分析

Light-Science & Applications Pub Date : 2025-01-23 DOI: 10.1038/s41377-024-01726-5

Zheng Gao, Ting Jiang, Mingming Zhang, Hao Wu, Ming Tang

引用次数: 0

Using light to image millimeter wave based on stacked meta-MEMS chip 基于堆叠元mems芯片的光成像毫米波

Light-Science & Applications Pub Date : 2025-01-22 DOI: 10.1038/s41377-024-01733-6

Han Wang, Zhigang Wang, Cheng Gong, Xinyu Li, Tiansheng Cui, Huiqi Jiang, Minghui Deng, Bo Yan, Weiwei Liu

引用次数: 0

Bayesian optimization with Gaussian-process-based active machine learning for improvement of geometric accuracy in projection multi-photon 3D printing 基于高斯过程主动机器学习的贝叶斯优化提高投影多光子3D打印的几何精度

Light-Science & Applications Pub Date : 2025-01-20 DOI: 10.1038/s41377-024-01707-8

Jason E. Johnson, Ishat Raihan Jamil, Liang Pan, Guang Lin, Xianfan Xu

{"title":"Bayesian optimization with Gaussian-process-based active machine learning for improvement of geometric accuracy in projection multi-photon 3D printing","authors":"Jason E. Johnson, Ishat Raihan Jamil, Liang Pan, Guang Lin, Xianfan Xu","doi":"10.1038/s41377-024-01707-8","DOIUrl":"https://doi.org/10.1038/s41377-024-01707-8","url":null,"abstract":"Multi-photon polymerization is a well-established, yet actively developing, additive manufacturing technique for 3D printing on the micro/nanoscale. Like all additive manufacturing techniques, determining the process parameters necessary to achieve dimensional accuracy for a structure 3D printed using this method is not always straightforward and can require time-consuming experimentation. In this work, an active machine learning based framework is presented for determining optimal process parameters for the recently developed, high-speed, layer-by-layer continuous projection 3D printing process. The proposed active learning framework uses Bayesian optimization to inform optimal experimentation in order to adaptively collect the most informative data for effective training of a Gaussian-process-regression-based machine learning model. This model then serves as a surrogate for the manufacturing process: predicting optimal process parameters for achieving a target geometry, e.g., the 2D geometry of each printed layer. Three representative 2D shapes at three different scales are used as test cases. In each case, the active learning framework improves the geometric accuracy, with drastic reductions of the errors to within the measurement accuracy in just four iterations of the Bayesian optimization using only a few hundred of total training data. The case studies indicate that the active learning framework developed in this work can be broadly applied to other additive manufacturing processes to increase accuracy with significantly reduced experimental data collection effort for optimization.","PeriodicalId":18069,"journal":{"name":"Light-Science & Applications","volume":"205 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142989683","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

Comment on “Early cancer detection by serum biomolecular fingerprinting spectroscopy with machine learning” “基于机器学习的血清生物分子指纹光谱早期癌症检测”述评

Light-Science & Applications Pub Date : 2025-01-20 DOI: 10.1038/s41377-024-01663-3

Ivan A. Bratchenko, Lyudmila A. Bratchenko

引用次数: 0

Reply to: comment on “Early cancer detection by serum biomolecular fingerprinting spectroscopy with machine learning” 回复：关于“基于机器学习的血清生物分子指纹光谱早期癌症检测”的评论

Light-Science & Applications Pub Date : 2025-01-20 DOI: 10.1038/s41377-024-01664-2

Shilian Dong, Dong He, Qian Zhang, Chaoning Huang, Zhiheng Hu, Chenyang Zhang, Lei Nie, Kun Wang, Wei Luo, Jing Yu, Bin Tian, Wei Wu, Xu Chen, Fubing Wang, Jing Hu, Xiangheng Xiao

引用次数: 0

Cascaded metalenses boost applications in near-eye display 级联超透镜促进近眼显示的应用

Light-Science & Applications Pub Date : 2025-01-20 DOI: 10.1038/s41377-024-01699-5

Jiacheng Sun, Tao Li

引用次数: 0

Enhanced multiscale human brain imaging by semi-supervised digital staining and serial sectioning optical coherence tomography 增强多尺度人脑成像的半监督数字染色和连续切片光学相干断层扫描

Light-Science & Applications Pub Date : 2025-01-20 DOI: 10.1038/s41377-024-01658-0

Shiyi Cheng, Shuaibin Chang, Yunzhe Li, Anna Novoseltseva, Sunni Lin, Yicun Wu, Jiahui Zhu, Ann C. McKee, Douglas L. Rosene, Hui Wang, Irving J. Bigio, David A. Boas, Lei Tian

{"title":"Enhanced multiscale human brain imaging by semi-supervised digital staining and serial sectioning optical coherence tomography","authors":"Shiyi Cheng, Shuaibin Chang, Yunzhe Li, Anna Novoseltseva, Sunni Lin, Yicun Wu, Jiahui Zhu, Ann C. McKee, Douglas L. Rosene, Hui Wang, Irving J. Bigio, David A. Boas, Lei Tian","doi":"10.1038/s41377-024-01658-0","DOIUrl":"https://doi.org/10.1038/s41377-024-01658-0","url":null,"abstract":"A major challenge in neuroscience is visualizing the structure of the human brain at different scales. Traditional histology reveals micro- and meso-scale brain features but suffers from staining variability, tissue damage, and distortion, which impedes accurate 3D reconstructions. The emerging label-free serial sectioning optical coherence tomography (S-OCT) technique offers uniform 3D imaging capability across samples but has poor histological interpretability despite its sensitivity to cortical features. Here, we present a novel 3D imaging framework that combines S-OCT with a deep-learning digital staining (DS) model. This enhanced imaging modality integrates high-throughput 3D imaging, low sample variability and high interpretability, making it suitable for 3D histology studies. We develop a novel semi-supervised learning technique to facilitate DS model training on weakly paired images for translating S-OCT to Gallyas silver staining. We demonstrate DS on various human cerebral cortex samples, achieving consistent staining quality and enhancing contrast across cortical layer boundaries. Additionally, we show that DS preserves geometry in 3D on cubic-centimeter tissue blocks, allowing for visualization of meso-scale vessel networks in the white matter. We believe that our technique has the potential for high-throughput, multiscale imaging of brain tissues and may facilitate studies of brain structures.","PeriodicalId":18069,"journal":{"name":"Light-Science & Applications","volume":"37 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142989682","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

Neuron-inspired CsPbBr3/PDMS nanospheres for multi-dimensional sensing and interactive displays 神经元启发CsPbBr3/PDMS纳米球用于多维传感和交互显示

Light-Science & Applications Pub Date : 2025-01-17 DOI: 10.1038/s41377-025-01742-z

Junhu Cai, Xiang Zhang, Yu Chen, Wenzong Lai, Yun Ye, Sheng Xu, Qun Yan, Tailiang Guo, Jiajun Luo, Enguo Chen

{"title":"Neuron-inspired CsPbBr3/PDMS nanospheres for multi-dimensional sensing and interactive displays","authors":"Junhu Cai, Xiang Zhang, Yu Chen, Wenzong Lai, Yun Ye, Sheng Xu, Qun Yan, Tailiang Guo, Jiajun Luo, Enguo Chen","doi":"10.1038/s41377-025-01742-z","DOIUrl":"https://doi.org/10.1038/s41377-025-01742-z","url":null,"abstract":"Multifunctional materials have attracted tremendous attention in intelligent and interactive devices. However, achieving multi-dimensional sensing capabilities with the same perovskite quantum dot (PQD) material is still in its infancy, with some considering it currently challenging and even unattainable. Drawing inspiration from neurons, a novel multifunctional CsPbBr3/PDMS nanosphere is devised to sense humidity, temperature, and pressure simultaneously with unique interactive responses. The carefully engineered polydimethylsiloxane (PDMS) shell enables the reversible activity of the core CsPbBr3, serving a dual role similar to dendrites in conveying and evaluating external stimuli with high sensitivity. Molecular dynamics analysis reveals that the PDMS shell with proper pore density enhances the conductivity in water and heat, imparting CsPbBr3 with sensitive but reversible properties. By tailoring the crosslinking density of the PDMS shell, nanospheres can surprisingly show customized sensitivity and reversible responses to different level of stimuli, achieving over 95% accuracy in multi-dimensional and wide-range sensing. The regular pressure-sensitive property, discovered for the first time, is attributed to the regular morphology of the nanosphere, the inherent low rigidity of the PDMS shell, and the uniform distribution of the CsPbBr3 core material in combination. This study breaks away from conventional design paradigms of perovskite core-shell materials by customizing the cross-linked density of the shell material. The reversible response mechanism of nanospheres with gradient shell density is deeply explored in response to environmental stimuli, which offers fresh insights into multi-dimensional sensing and interactive display applications.","PeriodicalId":18069,"journal":{"name":"Light-Science & Applications","volume":"29 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142987322","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

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