Organic photodiodes (OPDs) have made remarkable strides and now poised to surpass traditional silicon photodiodes (PDs) in various aspects including linear dynamic range (LDR), detectivity, wavelength selectivity, and versatility.[1] Tunable mechanical and optoelectronic properties of organic semiconductors, coupled with lower process costs, have propelled OPDs into the spotlight across fields such as wearable light fidelity systems, flexible image sensors, and biomedical imaging.[2–5] While most advanced organic imaging systems to date rely on polymer-based solution processes, challenges such as the use of toxic organic solvents and reproducibility issues hinder their commercialization.[6,7] Vacuum-processed OPDs offer a promising alternative, boasting eco-friendliness and compatibility with large-scale fabrication facilities.[8,9] In this review, recent advancements and challenges in vacuum-processed OPDs, an area that has received less attention compared to solution-processed counterparts, are explored. Herein, four primary pathways for development of vacuum-processed OPDs are outlined: 1) ultraviolet-selective OPDs, 2) visible-light-selective OPDs, 3) near-infrared or short-wave-infrared-sensitive OPDs, and 4) addressing challenges such as higher noise currents compared to inorganic PDs. In this review, it is aimed to furnish readers with a comprehensive understanding of vacuum-processed OPDs, spanning from materials design to device engineering.
{"title":"Advancements and Challenges of Vacuum-Processed Organic Photodiodes: A Comprehensive Review","authors":"Chan So, Won Jun Pyo, Dae Sung Chung","doi":"10.1002/adpr.202400094","DOIUrl":"https://doi.org/10.1002/adpr.202400094","url":null,"abstract":"<p>Organic photodiodes (OPDs) have made remarkable strides and now poised to surpass traditional silicon photodiodes (PDs) in various aspects including linear dynamic range (LDR), detectivity, wavelength selectivity, and versatility.<sup>[</sup><sup>1</sup><sup>]</sup> Tunable mechanical and optoelectronic properties of organic semiconductors, coupled with lower process costs, have propelled OPDs into the spotlight across fields such as wearable light fidelity systems, flexible image sensors, and biomedical imaging.<sup>[</sup><sup>2–5</sup><sup>]</sup> While most advanced organic imaging systems to date rely on polymer-based solution processes, challenges such as the use of toxic organic solvents and reproducibility issues hinder their commercialization.<sup>[</sup><sup>6,7</sup><sup>]</sup> Vacuum-processed OPDs offer a promising alternative, boasting eco-friendliness and compatibility with large-scale fabrication facilities.<sup>[</sup><sup>8,9</sup><sup>]</sup> In this review, recent advancements and challenges in vacuum-processed OPDs, an area that has received less attention compared to solution-processed counterparts, are explored. Herein, four primary pathways for development of vacuum-processed OPDs are outlined: 1) ultraviolet-selective OPDs, 2) visible-light-selective OPDs, 3) near-infrared or short-wave-infrared-sensitive OPDs, and 4) addressing challenges such as higher noise currents compared to inorganic PDs. In this review, it is aimed to furnish readers with a comprehensive understanding of vacuum-processed OPDs, spanning from materials design to device engineering.</p>","PeriodicalId":7263,"journal":{"name":"Advanced Photonics Research","volume":"6 2","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adpr.202400094","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143186383","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}
Zhexian Zhao, Weizuo Zhang, Jin Zhang, Yuzhao Li, Han Bai, Fangming Zhao, Zhongcai Jin, Ju Tang, Yiming Xiao, Wen Xu, Yanfei Lü
Carbon dots (CDs) show great application potential with their unique and excellent performances. Coal and its derivatives are rich in aromatic ring structure, which is suitable for preparing CDs in microstructure. Coal-burning dust from coal-fired power plants can be utilized as a rich resource to separate and extract CDs. It is shown in the results that there are two main possible mechanisms for the formation of CDs in coal-burning dust. One is the self-assembly of polycyclic aromatic hydrocarbons contained in coal or produced by incomplete combustion of coal. The other mechanism is that the bridge bonds linking different aromatic structures in coal break, which will form CDs with different functional groups when the coals burn at high temperature. Under violet light excitation at 310–340 nm or red light at 610–640 nm, CDs extracted from coal-burning dust can emit purple fluorescence around 410 nm. The mechanism of up-conversion fluorescence emission of CDs is due to a two-photon absorption process. The recycling of CDs from coal-burning dust from coal-fired power plants are not only good to protect environment but will also be helpful for mass production of CDs.
碳点(CD)以其独特而优异的性能显示出巨大的应用潜力。煤及其衍生物富含芳香环结构,适合制备微结构的碳点。燃煤电厂的燃煤粉尘是分离和提取 CD 的丰富资源。研究结果表明,燃煤粉尘中 CD 的形成可能有两种主要机制。一种是煤中含有的或煤不完全燃烧产生的多环芳烃的自组装。另一种机制是煤炭中连接不同芳香结构的桥键断裂,在高温燃烧时会形成具有不同官能团的 CD。在波长为 310-340 纳米的紫光或波长为 610-640 纳米的红光激发下,从燃煤粉尘中提取的 CD 可在波长为 410 纳米左右发出紫色荧光。CD 上转换荧光发射的机理是双光子吸收过程。从燃煤电厂的燃煤粉尘中回收 CD 不仅有利于保护环境,还有助于大规模生产 CD。
{"title":"Formation Mechanisms and Fluorescence Properties of Carbon Dots in Coal Burning Dust from Coal-Fired Power Plants","authors":"Zhexian Zhao, Weizuo Zhang, Jin Zhang, Yuzhao Li, Han Bai, Fangming Zhao, Zhongcai Jin, Ju Tang, Yiming Xiao, Wen Xu, Yanfei Lü","doi":"10.1002/adpr.202400010","DOIUrl":"https://doi.org/10.1002/adpr.202400010","url":null,"abstract":"<p>Carbon dots (CDs) show great application potential with their unique and excellent performances. Coal and its derivatives are rich in aromatic ring structure, which is suitable for preparing CDs in microstructure. Coal-burning dust from coal-fired power plants can be utilized as a rich resource to separate and extract CDs. It is shown in the results that there are two main possible mechanisms for the formation of CDs in coal-burning dust. One is the self-assembly of polycyclic aromatic hydrocarbons contained in coal or produced by incomplete combustion of coal. The other mechanism is that the bridge bonds linking different aromatic structures in coal break, which will form CDs with different functional groups when the coals burn at high temperature. Under violet light excitation at 310–340 nm or red light at 610–640 nm, CDs extracted from coal-burning dust can emit purple fluorescence around 410 nm. The mechanism of up-conversion fluorescence emission of CDs is due to a two-photon absorption process. The recycling of CDs from coal-burning dust from coal-fired power plants are not only good to protect environment but will also be helpful for mass production of CDs.</p>","PeriodicalId":7263,"journal":{"name":"Advanced Photonics Research","volume":"5 10","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adpr.202400010","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142435231","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}
Herein, deep learning-ghost imaging (DLGI) based on a digital micromirror device is realized to avoid the difficulties of a charge-coupled device (CCD) scientific camera being unable to obtain the sample images in extremely weak illumination conditions and to solve the problem of the inverse relationship between imaging quality and imaging time in practical applications. Deep learning for computational ghost imaging typically requires the collection of a large set of labeled experimental data to train a neural network. Herein, we demonstrate that a practically usable neural network can be prepared based on the simulation results. The acquisition results of the CCD scientific camera and the simulation results with low sampling are used as the training set (1000 observations) and we can complete the data acquisition process within one hour. The results show that the proposed DLGI method can be used to significantly improve the quality of the reconstructed images when the sampling rate is 60%. This method also reduces the imaging time and the memory usage, while simultaneously improving the imaging quality. The imaging results of the proposed DLGI method have great significance for application in clinical diagnosis.
{"title":"Simulation-Training-Based Deep Learning Approach to Microscopic Ghost Imaging","authors":"Binyu Li, Yueshu Feng, Cheng Zhou, Siyi Hu, Chunwa Jiang, Feng Yang, Lijun Song, Xue Hou","doi":"10.1002/adpr.202400052","DOIUrl":"https://doi.org/10.1002/adpr.202400052","url":null,"abstract":"<p>Herein, deep learning-ghost imaging (DLGI) based on a digital micromirror device is realized to avoid the difficulties of a charge-coupled device (CCD) scientific camera being unable to obtain the sample images in extremely weak illumination conditions and to solve the problem of the inverse relationship between imaging quality and imaging time in practical applications. Deep learning for computational ghost imaging typically requires the collection of a large set of labeled experimental data to train a neural network. Herein, we demonstrate that a practically usable neural network can be prepared based on the simulation results. The acquisition results of the CCD scientific camera and the simulation results with low sampling are used as the training set (1000 observations) and we can complete the data acquisition process within one hour. The results show that the proposed DLGI method can be used to significantly improve the quality of the reconstructed images when the sampling rate is 60%. This method also reduces the imaging time and the memory usage, while simultaneously improving the imaging quality. The imaging results of the proposed DLGI method have great significance for application in clinical diagnosis.</p>","PeriodicalId":7263,"journal":{"name":"Advanced Photonics Research","volume":"5 12","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adpr.202400052","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142861417","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}