Pub Date : 2025-04-16DOI: 10.1021/acsphotonics.4c01924
Hanna Bandarenka, Davoud Adinehloo, Evgenii Oskolkov, Andrey Kuzmin, Artem Pliss, Onoruoiza David Shaibu, Jonathan Bird, Alexander Baev, Vasili Perebeinos, Paras N. Prasad
We employ third-harmonic generation (THG) imaging for noninvasive characterization of silicon wafers and microchips and demonstrate that a much higher contrast can be achieved in THG compared to reflection imaging. In particular, the THG signal clearly distinguishes between n-type and p-type silicon samples coated with native silicon dioxide, which were indistinguishable in the reflection imaging mode. The THG response showed a higher contrast in mechanically stressed samples and under in-plane electric fields. Our experimental results, supported by first-principles calculations, demonstrate that THG imaging is a robust tool for assessing doping, mechanical stress, and electric fields in silicon-based structures, offering significant potential for advanced semiconductor diagnostics and the development of next-generation electronic components.
{"title":"Third-Harmonic Generation Imaging of Local Doping, Mechanical Stress, and Stray Electric Fields in Silicon Microchips","authors":"Hanna Bandarenka, Davoud Adinehloo, Evgenii Oskolkov, Andrey Kuzmin, Artem Pliss, Onoruoiza David Shaibu, Jonathan Bird, Alexander Baev, Vasili Perebeinos, Paras N. Prasad","doi":"10.1021/acsphotonics.4c01924","DOIUrl":"https://doi.org/10.1021/acsphotonics.4c01924","url":null,"abstract":"We employ third-harmonic generation (THG) imaging for noninvasive characterization of silicon wafers and microchips and demonstrate that a much higher contrast can be achieved in THG compared to reflection imaging. In particular, the THG signal clearly distinguishes between n-type and p-type silicon samples coated with native silicon dioxide, which were indistinguishable in the reflection imaging mode. The THG response showed a higher contrast in mechanically stressed samples and under in-plane electric fields. Our experimental results, supported by first-principles calculations, demonstrate that THG imaging is a robust tool for assessing doping, mechanical stress, and electric fields in silicon-based structures, offering significant potential for advanced semiconductor diagnostics and the development of next-generation electronic components.","PeriodicalId":23,"journal":{"name":"ACS Photonics","volume":"108 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143841669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-16DOI: 10.1021/acsphotonics.5c00384
Ieng-Wai Un, Naama Harcavi, Yonatan Sivan
Transparent conducting oxides (TCOs) have recently been shown to have a remarkably strong nonlinear optical response. We show that the popular ascription of their nonlinearity to the temperature-dependence of the plasma frequency is only a partial description of their response to intense illumination. Specifically, we show that an increase in the electron collision rate upon illumination and consequent heating contributes to the permittivity in a manner that can be quantitatively comparable to the contribution of the temperature-dependent plasma frequency. This behavior makes the optical nonlinearity of TCOs more similar to that of noble metals than realized so far, and as far as the imaginary part of the permittivity is concerned, this behavior is qualitatively opposite compared to that assumed so far.
{"title":"Optical Nonlinearity of Transparent Conducting Oxides: More Metallic than Realized","authors":"Ieng-Wai Un, Naama Harcavi, Yonatan Sivan","doi":"10.1021/acsphotonics.5c00384","DOIUrl":"https://doi.org/10.1021/acsphotonics.5c00384","url":null,"abstract":"Transparent conducting oxides (TCOs) have recently been shown to have a remarkably strong nonlinear optical response. We show that the popular ascription of their nonlinearity to the temperature-dependence of the plasma frequency is only a partial description of their response to intense illumination. Specifically, we show that an increase in the electron collision rate upon illumination and consequent heating contributes to the permittivity in a manner that can be quantitatively comparable to the contribution of the temperature-dependent plasma frequency. This behavior makes the optical nonlinearity of TCOs more similar to that of noble metals than realized so far, and as far as the imaginary part of the permittivity is concerned, this behavior is qualitatively opposite compared to that assumed so far.","PeriodicalId":23,"journal":{"name":"ACS Photonics","volume":"22 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143837534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-16DOI: 10.1021/acsphotonics.5c00449
Romain Quidant
The <i>ACS Photonics</i> Young Investigator Award celebrates outstanding early career researchers in photonics, recognizing their innovative research and significant contributions to the field. While only one recipient is ultimately chosen, the journal acknowledges the exceptional talent and dedication of all finalists. This year, three outstanding researchers, Dan Congreve, Francesco Monticone, and Lina Quan, distinguished themselves, showcasing the breadth and depth of cutting-edge photonics research. <b>Dan Congreve</b> (Stanford University) has demonstrated exceptional ingenuity in manipulating light, energy, and spin at the nanoscale. His work on thin-film upconversion has substantially advanced applications in photovoltaics, night vision, and anticounterfeiting, achieving significant efficiency improvements through innovative materials engineering. His exploration of <i>in situ</i> upconversion opens new avenues for deep-tissue photochemistry and volumetric 3D printing, pushing the boundaries of nanofabrication. Furthermore, Congreve’s advancements in perovskite light emission, particularly in blue and UV LEDs, are addressing critical challenges in lighting, sensing, and communication. His research is a testament to the transformative power of controlled light manipulation for real-world impact. <b>Francesco Monticone</b> (Cornell University) has rapidly established himself as a leader in topological physics, nonreciprocity, and nonlocal photonics. His profound understanding of wave phenomena and his ability to translate theoretical concepts into innovative devices, such as metalenses and nonlocal metasurfaces, have sparked important discussions about the fundamental limits of photonics technologies. Monticone’s contributions extend beyond research, encompassing leadership in the photonics community and entrepreneurial ventures in thermal photonics. His recent tenure at Cornell University and numerous accolades, including the Cornell Engineering Research Excellence Award, underscore his exceptional achievements and promising future. <b>Lina Quan</b> (Virginia Tech) is advancing the exploration of emerging semiconductors, particularly halide perovskites, for next-generation photonic and electronic applications. Her research group’s interdisciplinary approach is yielding fundamental insights into the structure–property relationships of these materials. Quan’s discovery of optical retardation effects in copper-based 2D hybrid perovskites and her development of high-temperature stable nonlinear optical switching materials are addressing long-standing challenges in the field. Her exploration of chiral semiconductors for spintronics, supported by a prestigious DOE Early Career Research Program award, further highlights her innovative approach. Quan’s work is poised to significantly impact bioimaging, optical communication, and beyond. These three finalists represent the future of photonics, each contributing unique and impactful research that pus
{"title":"Recognizing Excellence in Photonics: Finalists of the ACS Photonics Young Investigator Award","authors":"Romain Quidant","doi":"10.1021/acsphotonics.5c00449","DOIUrl":"https://doi.org/10.1021/acsphotonics.5c00449","url":null,"abstract":"The <i>ACS Photonics</i> Young Investigator Award celebrates outstanding early career researchers in photonics, recognizing their innovative research and significant contributions to the field. While only one recipient is ultimately chosen, the journal acknowledges the exceptional talent and dedication of all finalists. This year, three outstanding researchers, Dan Congreve, Francesco Monticone, and Lina Quan, distinguished themselves, showcasing the breadth and depth of cutting-edge photonics research. <b>Dan Congreve</b> (Stanford University) has demonstrated exceptional ingenuity in manipulating light, energy, and spin at the nanoscale. His work on thin-film upconversion has substantially advanced applications in photovoltaics, night vision, and anticounterfeiting, achieving significant efficiency improvements through innovative materials engineering. His exploration of <i>in situ</i> upconversion opens new avenues for deep-tissue photochemistry and volumetric 3D printing, pushing the boundaries of nanofabrication. Furthermore, Congreve’s advancements in perovskite light emission, particularly in blue and UV LEDs, are addressing critical challenges in lighting, sensing, and communication. His research is a testament to the transformative power of controlled light manipulation for real-world impact. <b>Francesco Monticone</b> (Cornell University) has rapidly established himself as a leader in topological physics, nonreciprocity, and nonlocal photonics. His profound understanding of wave phenomena and his ability to translate theoretical concepts into innovative devices, such as metalenses and nonlocal metasurfaces, have sparked important discussions about the fundamental limits of photonics technologies. Monticone’s contributions extend beyond research, encompassing leadership in the photonics community and entrepreneurial ventures in thermal photonics. His recent tenure at Cornell University and numerous accolades, including the Cornell Engineering Research Excellence Award, underscore his exceptional achievements and promising future. <b>Lina Quan</b> (Virginia Tech) is advancing the exploration of emerging semiconductors, particularly halide perovskites, for next-generation photonic and electronic applications. Her research group’s interdisciplinary approach is yielding fundamental insights into the structure–property relationships of these materials. Quan’s discovery of optical retardation effects in copper-based 2D hybrid perovskites and her development of high-temperature stable nonlinear optical switching materials are addressing long-standing challenges in the field. Her exploration of chiral semiconductors for spintronics, supported by a prestigious DOE Early Career Research Program award, further highlights her innovative approach. Quan’s work is poised to significantly impact bioimaging, optical communication, and beyond. These three finalists represent the future of photonics, each contributing unique and impactful research that pus","PeriodicalId":23,"journal":{"name":"ACS Photonics","volume":"22 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143841673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Inspired by biological nervous systems, multimodal deep learning integrates multimodal information to enhance perception and decision-making, yet its high computational demands challenge traditional microelectronic processors in energy efficiency and speed. Photonic neuromorphic computing offers a promising solution, but implementing linear weighting and nonlinear activation typically requires different photonic materials and devices, complicating large-scale integration. Here, we propose and demonstrate a hybrid optoelectronic neural network architecture based on a distributed feedback laser with a saturable absorber (DFB-SA) array, designed to mimic biological audiovisual fusion for multimodal recognition tasks. This architecture leverages the self-activated multiply accumulate (MAC) function of the DFB-SA laser, seamlessly integrating both linear weighting and nonlinear activation into a single device, thus significantly improving integration efficiency. The proposed multimodal neural network outperforms unimodal recognition methods in recognition accuracy and robustness under challenging conditions, achieving over 90% accuracy in hardware inference. Each computational core achieves a speed of 1.6 GOPS, an energy efficiency of 38.1 GOPS/W, and a unit area speed of 21.3 GOPS/mm2, with overall performance scaling linearly with the number of cores. Furthermore, we develop a robot obstacle avoidance system utilizing the self-activated MAC function of DFB-SA laser neurons. This work presents a high-performance computing hardware platform for multimodal deep learning, demonstrating its potential for simulating biological multisensory recognition and enabling scalable photonic AI models.
{"title":"Photonics Neural Networks for Multimodal Recognition Based on the Self-Activated MAC Function of DFB-SA","authors":"Dianzhuang Zheng, Shuiying Xiang, Yahui Zhang, Xingxing Guo, Yuechun Shi, Yue Hao","doi":"10.1021/acsphotonics.5c00415","DOIUrl":"https://doi.org/10.1021/acsphotonics.5c00415","url":null,"abstract":"Inspired by biological nervous systems, multimodal deep learning integrates multimodal information to enhance perception and decision-making, yet its high computational demands challenge traditional microelectronic processors in energy efficiency and speed. Photonic neuromorphic computing offers a promising solution, but implementing linear weighting and nonlinear activation typically requires different photonic materials and devices, complicating large-scale integration. Here, we propose and demonstrate a hybrid optoelectronic neural network architecture based on a distributed feedback laser with a saturable absorber (DFB-SA) array, designed to mimic biological audiovisual fusion for multimodal recognition tasks. This architecture leverages the self-activated multiply accumulate (MAC) function of the DFB-SA laser, seamlessly integrating both linear weighting and nonlinear activation into a single device, thus significantly improving integration efficiency. The proposed multimodal neural network outperforms unimodal recognition methods in recognition accuracy and robustness under challenging conditions, achieving over 90% accuracy in hardware inference. Each computational core achieves a speed of 1.6 GOPS, an energy efficiency of 38.1 GOPS/W, and a unit area speed of 21.3 GOPS/mm<sup>2</sup>, with overall performance scaling linearly with the number of cores. Furthermore, we develop a robot obstacle avoidance system utilizing the self-activated MAC function of DFB-SA laser neurons. This work presents a high-performance computing hardware platform for multimodal deep learning, demonstrating its potential for simulating biological multisensory recognition and enabling scalable photonic AI models.","PeriodicalId":23,"journal":{"name":"ACS Photonics","volume":"1 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143837533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-15DOI: 10.1021/acsphotonics.5c00147
Zarko Sakotic, Noah Mansfeld, Amogh Raju, Alexander Ware, Divya Hungund, Daniel Krueger, Daniel Wasserman
Plasmonic response in metals, defined as the ability to support subwavelength confinement of surface plasmon modes, is typically limited to a narrow frequency range below the metals’ plasma frequency. This places severe limitations on the operational wavelengths of plasmonic materials and devices. However, when the volume of a metal film is massively decreased, highly confined quasi-two-dimensional surface plasmon modes can be supported out to wavelengths well beyond the plasma wavelength. While this has, thus far, been achieved using ultrathin (nm-scale) metals, such films are quite difficult to realize and suffer from even higher losses than bulk plasmonic films. To extend the plasmonic response to the infrared, here we introduce the concept of metaplasmonics, representing a novel plasmonic modality with a host of appealing properties. By fabricating and characterizing a series of metaplasmonic nanoribbons, we demonstrate large confinement, high-quality factors, and large near-field enhancements across a broad wavelength range, extending well beyond the limited bandwidth of traditional plasmonic materials. We demonstrate 35× plasmon wavelength reduction, and numerical simulations suggest that further wavelength reduction, up to a factor of 150, is achievable using our approach. The demonstration of the metaplasmonics paradigm offers a promising path to fill the near- and mid-infrared technological gap for high-quality plasmonic materials and provides a new material system to study the effects of extreme plasmonic confinement for applications in nonlinear and quantum plasmonics.
{"title":"Infrared Metaplasmonics","authors":"Zarko Sakotic, Noah Mansfeld, Amogh Raju, Alexander Ware, Divya Hungund, Daniel Krueger, Daniel Wasserman","doi":"10.1021/acsphotonics.5c00147","DOIUrl":"https://doi.org/10.1021/acsphotonics.5c00147","url":null,"abstract":"Plasmonic response in metals, defined as the ability to support subwavelength confinement of surface plasmon modes, is typically limited to a narrow frequency range below the metals’ plasma frequency. This places severe limitations on the operational wavelengths of plasmonic materials and devices. However, when the volume of a metal film is massively decreased, highly confined quasi-two-dimensional surface plasmon modes can be supported out to wavelengths well beyond the plasma wavelength. While this has, thus far, been achieved using ultrathin (nm-scale) metals, such films are quite difficult to realize and suffer from even higher losses than bulk plasmonic films. To extend the plasmonic response to the infrared, here we introduce the concept of metaplasmonics, representing a novel plasmonic modality with a host of appealing properties. By fabricating and characterizing a series of metaplasmonic nanoribbons, we demonstrate large confinement, high-quality factors, and large near-field enhancements across a broad wavelength range, extending well beyond the limited bandwidth of traditional plasmonic materials. We demonstrate 35× plasmon wavelength reduction, and numerical simulations suggest that further wavelength reduction, up to a factor of 150, is achievable using our approach. The demonstration of the metaplasmonics paradigm offers a promising path to fill the near- and mid-infrared technological gap for high-quality plasmonic materials and provides a new material system to study the effects of extreme plasmonic confinement for applications in nonlinear and quantum plasmonics.","PeriodicalId":23,"journal":{"name":"ACS Photonics","volume":"21 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143832407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-14DOI: 10.1021/acsphotonics.4c02496
Luana Olivieri, Andrew R. Cooper, Luke Peters, Vittorio Cecconi, Alessia Pasquazi, Marco Peccianti, Juan S. Totero Gongora
Photonic Ising machines are leading key advancements in solving large combinatorial problems, leveraging large-scale platforms with parallel computing capabilities. A well-known bottleneck of complex problems is the appearance of multiple minima in the energetic landscape that attract Metropolis-based iterations in suboptimal solutions, thus hindering the performance of standard optical solvers in large systems. By introducing a double single-pixel detection scheme based on intensity and field averages in an optical-based Ising machine, we effectively implement local and nonlocal nonlinear Hamiltonians, representing a complex and simple state, respectively. Transitioning from nonlocal to local nonlinear detection enables to adiabatically morph the energetic landscape, enhancing the success rate of finding the optimal solution compared to standard isothermal approaches.
{"title":"Adiabatic Energetic Annealing via Dual Single-Pixel Detection in an Optical Nonlinear Ising Machine","authors":"Luana Olivieri, Andrew R. Cooper, Luke Peters, Vittorio Cecconi, Alessia Pasquazi, Marco Peccianti, Juan S. Totero Gongora","doi":"10.1021/acsphotonics.4c02496","DOIUrl":"https://doi.org/10.1021/acsphotonics.4c02496","url":null,"abstract":"Photonic Ising machines are leading key advancements in solving large combinatorial problems, leveraging large-scale platforms with parallel computing capabilities. A well-known bottleneck of complex problems is the appearance of multiple minima in the energetic landscape that attract Metropolis-based iterations in suboptimal solutions, thus hindering the performance of standard optical solvers in large systems. By introducing a double single-pixel detection scheme based on intensity and field averages in an optical-based Ising machine, we effectively implement local and nonlocal nonlinear Hamiltonians, representing a complex and simple state, respectively. Transitioning from nonlocal to local nonlinear detection enables to adiabatically morph the energetic landscape, enhancing the success rate of finding the optimal solution compared to standard isothermal approaches.","PeriodicalId":23,"journal":{"name":"ACS Photonics","volume":"37 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143832408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-14DOI: 10.1021/acsphotonics.5c00104
Lu Zhu, Cong Lv, Wei Hua, Dechang Huang, Yuanyuan Liu
Accurate and rapid optical predictions of metasurfaces are essential for assessing their performance. However, traditional data-driven models depend on large-scale data sets and necessitate retraining of parameters for different data set paradigms. Furthermore, these models are often limited in generalization and transfer abilities due to neglecting physical prior knowledge and spatial-physical correlations in data. This paper addresses these challenges by introducing the physical transfer learning based optical response prediction network (PTLOR-Net) of metasurfaces, consisting of the physical representation model (PRM) and the fusion-prediction model (FPM). The encoder of PRM captures physical information applicable across many optical scenarios under the constraints of governing equations, while the FPM integrates multiscale features and maps them to predict optical responses. PTLOR-Net can transfer knowledge across similar and different types of data sets, which facilitates the physical transfer from all-dielectric metasurfaces to metasurfaces or absorbers at different frequency bands. Remarkably, with merely 1800 samples, the PTLOR-Net can effectively predict the absorption spectrum of the absorbers with high degrees of freedom (DOFs)─a 10-fold reduction in training data compared to conventional neural networks. Additionally, the generative model integrated with the PTLOR-Net achieves the inverse design of the absorber and further verifies the effectiveness of the prediction.
{"title":"PTLOR-Net: Physical Transfer Learning Based Optical Response Prediction Network of Metasurfaces","authors":"Lu Zhu, Cong Lv, Wei Hua, Dechang Huang, Yuanyuan Liu","doi":"10.1021/acsphotonics.5c00104","DOIUrl":"https://doi.org/10.1021/acsphotonics.5c00104","url":null,"abstract":"Accurate and rapid optical predictions of metasurfaces are essential for assessing their performance. However, traditional data-driven models depend on large-scale data sets and necessitate retraining of parameters for different data set paradigms. Furthermore, these models are often limited in generalization and transfer abilities due to neglecting physical prior knowledge and spatial-physical correlations in data. This paper addresses these challenges by introducing the physical transfer learning based optical response prediction network (PTLOR-Net) of metasurfaces, consisting of the physical representation model (PRM) and the fusion-prediction model (FPM). The encoder of PRM captures physical information applicable across many optical scenarios under the constraints of governing equations, while the FPM integrates multiscale features and maps them to predict optical responses. PTLOR-Net can transfer knowledge across similar and different types of data sets, which facilitates the physical transfer from all-dielectric metasurfaces to metasurfaces or absorbers at different frequency bands. Remarkably, with merely 1800 samples, the PTLOR-Net can effectively predict the absorption spectrum of the absorbers with high degrees of freedom (DOFs)─a 10-fold reduction in training data compared to conventional neural networks. Additionally, the generative model integrated with the PTLOR-Net achieves the inverse design of the absorber and further verifies the effectiveness of the prediction.","PeriodicalId":23,"journal":{"name":"ACS Photonics","volume":"39 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143827475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-14DOI: 10.1021/acsphotonics.5c00097
Longjie Lei, Kaiyu Yang, Yang Liu, Qingkai Zhang, Kuibao Yu, Fushan Li
In the era of burgeoning information technology, ensuring the impregnable transmission of confidential information has emerged as a paramount global imperative. Traditional fluorescent encryption materials are limited in advanced encryption due to their visible properties under ultraviolet light, while improved stimulus-responsive encryption strategies are usually based on static information. Herein, we exploit a novel high-security encryption strategy using metal halides and perovskite quantum dots as invisible inks and developer, respectively. The decryption of the information is impervious to traditional decryption means, necessitating the possession of the appropriate quadruple key to accomplish the decryption process. This approach leverages the anion exchange mechanism between metal halides and perovskite quantum dots, thereby enabling a multilevel encryption system. Consequently, the strategy establishes a multitiered and multifaceted security framework, which has significant application potential in the protection of confidential information requiring a superior level of security and provides a novel encryption and decryption scheme in the field of information security.
{"title":"Anion Exchange-Induced Invisible Perovskite Encryption System with Time-Dependence for Confidential Information Security","authors":"Longjie Lei, Kaiyu Yang, Yang Liu, Qingkai Zhang, Kuibao Yu, Fushan Li","doi":"10.1021/acsphotonics.5c00097","DOIUrl":"https://doi.org/10.1021/acsphotonics.5c00097","url":null,"abstract":"In the era of burgeoning information technology, ensuring the impregnable transmission of confidential information has emerged as a paramount global imperative. Traditional fluorescent encryption materials are limited in advanced encryption due to their visible properties under ultraviolet light, while improved stimulus-responsive encryption strategies are usually based on static information. Herein, we exploit a novel high-security encryption strategy using metal halides and perovskite quantum dots as invisible inks and developer, respectively. The decryption of the information is impervious to traditional decryption means, necessitating the possession of the appropriate quadruple key to accomplish the decryption process. This approach leverages the anion exchange mechanism between metal halides and perovskite quantum dots, thereby enabling a multilevel encryption system. Consequently, the strategy establishes a multitiered and multifaceted security framework, which has significant application potential in the protection of confidential information requiring a superior level of security and provides a novel encryption and decryption scheme in the field of information security.","PeriodicalId":23,"journal":{"name":"ACS Photonics","volume":"60 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143827473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-10DOI: 10.1021/acsphotonics.4c01956
Claudia Triolo, Antonella Lorusso, Sofia Masi, Fabrizio Mariano, Antonio Della Torre, Gianluca Accorsi, Valentina Arima, Stefano De Leo, Rosaria Rinaldi, Salvatore Patané, Marco Mazzeo
The understanding and management of the optical behavior of dielectric/metal/dielectric (DMD)-based electrodes are crucial for the design of fully transparent OLEDs. Specifically, the chromatic stability with the viewing angle of white OLED emission remains an important issue due to the angle dependence of internal reflection at the organic/electrode interface as the wavelength varies. The purpose of the present work is to provide a complete analysis of the optical behavior of DMD structures by Variable Angle Spectroscopic Ellipsometry in order to optimize the transmittance of DMD-based transparent white OLEDs over a wide viewing angle. The analysis of the optical modes contributing to power dissipation reveals that the reduction of plasmonic and waveguided modes is related to the antireflection properties of the DMD electrode. This results in a simultaneous significant improvement in the absolute value of the transmittance across the full visible spectral range and in the color stability of white OLED emission over a wide viewing cone of 120°, thus paving the way for a new generation of transparent white lighting sources.
{"title":"Electromagnetic Mode Management in Transparent DMD Electrodes for High Angular Color Stability in White OLEDs","authors":"Claudia Triolo, Antonella Lorusso, Sofia Masi, Fabrizio Mariano, Antonio Della Torre, Gianluca Accorsi, Valentina Arima, Stefano De Leo, Rosaria Rinaldi, Salvatore Patané, Marco Mazzeo","doi":"10.1021/acsphotonics.4c01956","DOIUrl":"https://doi.org/10.1021/acsphotonics.4c01956","url":null,"abstract":"The understanding and management of the optical behavior of dielectric/metal/dielectric (DMD)-based electrodes are crucial for the design of fully transparent OLEDs. Specifically, the chromatic stability with the viewing angle of white OLED emission remains an important issue due to the angle dependence of internal reflection at the organic/electrode interface as the wavelength varies. The purpose of the present work is to provide a complete analysis of the optical behavior of DMD structures by Variable Angle Spectroscopic Ellipsometry in order to optimize the transmittance of DMD-based transparent white OLEDs over a wide viewing angle. The analysis of the optical modes contributing to power dissipation reveals that the reduction of plasmonic and waveguided modes is related to the antireflection properties of the DMD electrode. This results in a simultaneous significant improvement in the absolute value of the transmittance across the full visible spectral range and in the color stability of white OLED emission over a wide viewing cone of 120°, thus paving the way for a new generation of transparent white lighting sources.","PeriodicalId":23,"journal":{"name":"ACS Photonics","volume":"17 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143813940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-09DOI: 10.1021/acsphotonics.5c00123
Kishwar Iqbal, Jan Christoph Thiele, Emanuel Pfitzner, Philipp Kukura
Label-free microscopy on the nanoscale requires high-sensitivity imaging. The challenge of visualizing very small objects, such as nanoparticles, arises from their weak interaction with light. As a result, a combination of high signal-to-noise ratio imaging and background rejection is needed for detection and quantification. Here, we combine concepts from interferometric scattering (iSCAT) microscopy and rotating coherent scattering (ROCS) microscopy to optimize both background rejection and high-sensitivity imaging. Total internal reflection produces a background light intensity more than 2 orders of magnitude stronger than in iSCAT. Despite this, we successfully image 20 nm gold nanoparticles using our combined approach while achieving a signal-to-noise ratio (SNR) comparable to iSCAT at incident power densities as low as 0.04 kW/cm2. We experimentally characterize the effect of different incident polarizations and achieve maximal optical contrast using s-polarized illumination. We further demonstrate that ROCS-based illumination at or near total internal reflection yields an approximate 4-fold contrast enhancement and 2-fold background suppression, producing substantially improved SNR compared to iSCAT for the same illumination power entering the microscope objective and integration time. We attribute this to the increased spatial resolution, enhanced incident power density, and rotational averaging of surface-generated speckle. These advantages highlight the potential to achieve and exceed the sensitivity levels attained by related interferometric imaging techniques.
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