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Optical Devices|1170 Article(s)
Design and Research on a Reconfigurable Microwave Photonic Mixer
Yishi Han, Xian Li, Yongming Zhong, and Changsheng Zeng
A design and research scheme for a reconfigurable microwave photonic mixer is proposed. The scheme can reconstruct and generate a linear frequency modulation signal, a frequency conversion signal, or a phase shift signal only by changing the driving signal and direct-current bias voltage. The generated linear frequency-modulated signal has three bands, and the bandwidth can be increased to four times at most. Up and down conversion signals can be generated at the same time. The obtained phase shift signal can be continuously tuned at 0?360°. The simulation results show that the scheme can generate linear frequency-modulated signals with a frequency of 11 GHz and a bandwidth of 2 GHz, a frequency of 18 GHz and a bandwidth of 4 GHz, and a frequency of 29 GHz and a bandwidth of 2 GHz. The pulse compression performance is good. It can simultaneously generate an up-conversion signal with a frequency of 32 GHz and a down-conversion signal with a frequency of 8 GHz, and the electric stray suppression ratio is higher than 30 dB. It can also generate a continuously adjustable phase-shift signal with a 0?360° phase, and the power fluctuation is within 0.1 dB. The system has a spurious free dynamic range of 114.1 dB?Hz2/3. A design and research scheme for a reconfigurable microwave photonic mixer is proposed. The scheme can reconstruct and generate a linear frequency modulation signal, a frequency conversion signal, or a phase shift signal only by changing the driving signal and direct-current bias voltage. The generated linear frequency-modulated signal has three bands, and the bandwidth can be increased to four times at most. Up and down conversion signals can be generated at the same time. The obtained phase shift signal can be continuously tuned at 0?360°. The simulation results show that the scheme can generate linear frequency-modulated signals with a frequency of 11 GHz and a bandwidth of 2 GHz, a frequency of 18 GHz and a bandwidth of 4 GHz, and a frequency of 29 GHz and a bandwidth of 2 GHz. The pulse compression performance is good. It can simultaneously generate an up-conversion signal with a frequency of 32 GHz and a down-conversion signal with a frequency of 8 GHz, and the electric stray suppression ratio is higher than 30 dB. It can also generate a continuously adjustable phase-shift signal with a 0?360° phase, and the power fluctuation is within 0.1 dB. The system has a spurious free dynamic range of 114.1 dB?Hz2/3.
Laser & Optoelectronics Progress
- Publication Date: Mar. 10, 2024
- Vol. 61, Issue 5, 0523003 (2024)
AlGaN-Based Deep-UV LED with Novel Transparent Electrodes and Integrated Array Device for Efficient Disinfection
Zefeng Lin, Lucheng Yu, Qicheng Zhou, Yehang Cai, Fawen Su, Shengrong Huang, Feiya Xu, Xiaohong Chen, Ling Li, and Duanjun Cai
The COVID-19 pandemic since 2019 has brought huge impacts and economic losses to the world. AlGaN-based deep-ultraviolet light emitting diode (DUV-LED) as a new and efficient sterilization device has attracted broad research attentions. The transparent electrode covering deep-UV band plays an important role in improving the performance of deep-UV LEDs. Here, we propose a novel core-shell structure Cu@metal nanosilks (Cu@metal NSs) network electrode with high transparency (>90%) to enhance the output power of deep-UV LED. In addition, based on the optimized design of integrated array module of deep-UV LEDs, a 180 mW DUV-LED sterilization device is fabricated. The device shows high inactivation performance for Escherichia coli and Staphylococcus aureus (>99.99%) and for COVID-19 virus (>99.9%). This work provides a novel method for improving the performance of deep-UV LEDs and pushing forward the efficient sterilization applications. The COVID-19 pandemic since 2019 has brought huge impacts and economic losses to the world. AlGaN-based deep-ultraviolet light emitting diode (DUV-LED) as a new and efficient sterilization device has attracted broad research attentions. The transparent electrode covering deep-UV band plays an important role in improving the performance of deep-UV LEDs. Here, we propose a novel core-shell structure Cu@metal nanosilks (Cu@metal NSs) network electrode with high transparency (>90%) to enhance the output power of deep-UV LED. In addition, based on the optimized design of integrated array module of deep-UV LEDs, a 180 mW DUV-LED sterilization device is fabricated. The device shows high inactivation performance for Escherichia coli and Staphylococcus aureus (>99.99%) and for COVID-19 virus (>99.9%). This work provides a novel method for improving the performance of deep-UV LEDs and pushing forward the efficient sterilization applications.
Laser & Optoelectronics Progress
- Publication Date: Mar. 10, 2024
- Vol. 61, Issue 5, 0523002 (2024)
Lithium Niobate Waveguide Mode Converter Based on V-Shaped Silicon
Cheng Zhang, Yin Xu, Yue Dong, Bo Zhang, and Yi Ni
Mode converter, achieving the mode conversion task from fundamental mode to higher-order mode, is a key component for the on-chip multimode transmission and mode division multiplexing transmission. Here, we propose an array of V-shaped silicon mode converter based on the thin film lithium niobate (TFLN) waveguide. The mode conversion structure is consisted of an array of V-shaped silicon, where it is deposited atop the TFLN waveguide. Based on such structure, we conduct detailed structural analyses and optimizations, where the required conversion length is only 11 μm and the central wavelength is 1550 nm for the mode conversion from input TE0 mode to output TE1 mode. The mode conversion efficiency, crosstalk, and insertion loss are 96.8%, -28.6 dB, and 0.78 dB, respectively. We further extend the device structure and obtain the mode conversion from input TE0 mode to output TE2 mode in the same length, where the mode conversion efficiency, crosstalk, and insertion loss are 91.3%, -?14.3 dB, and 1 dB, respectively. If we further extend the device structure, other higher-order modes can also be obtained. We believe the proposed device structure and scheme could benefit the multimode transmission for the TFLN waveguide and boost the development of photonic integrated components and circuits based on the TFLN platform. Mode converter, achieving the mode conversion task from fundamental mode to higher-order mode, is a key component for the on-chip multimode transmission and mode division multiplexing transmission. Here, we propose an array of V-shaped silicon mode converter based on the thin film lithium niobate (TFLN) waveguide. The mode conversion structure is consisted of an array of V-shaped silicon, where it is deposited atop the TFLN waveguide. Based on such structure, we conduct detailed structural analyses and optimizations, where the required conversion length is only 11 μm and the central wavelength is 1550 nm for the mode conversion from input TE0 mode to output TE1 mode. The mode conversion efficiency, crosstalk, and insertion loss are 96.8%, -28.6 dB, and 0.78 dB, respectively. We further extend the device structure and obtain the mode conversion from input TE0 mode to output TE2 mode in the same length, where the mode conversion efficiency, crosstalk, and insertion loss are 91.3%, -?14.3 dB, and 1 dB, respectively. If we further extend the device structure, other higher-order modes can also be obtained. We believe the proposed device structure and scheme could benefit the multimode transmission for the TFLN waveguide and boost the development of photonic integrated components and circuits based on the TFLN platform.
Laser & Optoelectronics Progress
- Publication Date: Mar. 10, 2024
- Vol. 61, Issue 5, 0523001 (2024)
Polarity-Controllable Laser-Processed Graphene Oxide-Based Memristor (Invited)
Suling Liu, Zhengfen Wan, Yutian Wang, Min Gu, and Qiming Zhang
In recent years, neuromorphic computing, inspired by the structure and function of biological nervous systems, has gained substantial attention. Memristors, which are capable of modulating conductivity via electric charge or magnetic flux, mimic synaptic interactions in the human brain, making them promising candidates for neuromorphic computing. This study proposes a method using femtosecond laser-processed graphene oxide memristors. Adjusting the scanning voltage at both device ends achieves polarity-controlled resistance switching. The device exhibits unipolar resistance switching at low voltages and stability over 150 cycles with a power consumption of only 0.75 nW. At higher voltages, bipolar switching occurs with increased conductivity over the test cycles. This study explores switching mechanisms under two voltage conditions, thus providing a comprehensive understanding of these mechanisms. This innovative approach using femtosecond laser-processed graphene oxide memristors shows promise for neuromorphic computing, offering efficient performance, stability, and adaptability across voltage scenarios. In recent years, neuromorphic computing, inspired by the structure and function of biological nervous systems, has gained substantial attention. Memristors, which are capable of modulating conductivity via electric charge or magnetic flux, mimic synaptic interactions in the human brain, making them promising candidates for neuromorphic computing. This study proposes a method using femtosecond laser-processed graphene oxide memristors. Adjusting the scanning voltage at both device ends achieves polarity-controlled resistance switching. The device exhibits unipolar resistance switching at low voltages and stability over 150 cycles with a power consumption of only 0.75 nW. At higher voltages, bipolar switching occurs with increased conductivity over the test cycles. This study explores switching mechanisms under two voltage conditions, thus providing a comprehensive understanding of these mechanisms. This innovative approach using femtosecond laser-processed graphene oxide memristors shows promise for neuromorphic computing, offering efficient performance, stability, and adaptability across voltage scenarios.
Laser & Optoelectronics Progress
- Publication Date: Feb. 10, 2024
- Vol. 61, Issue 3, 0323002 (2024)
Metasurfaces for Manipulating and Controlling Visible-Light Emission and Its Diverse Applications (Invited)
Shaojun Wang, Zhenghe Zhang, Ziyue Hou, Yiheng Zhai, Chaojie Xu, and Xiaofeng Li
Artificially constructed planar metasurfaces play a crucial role in photonics and emerging optoelectronic technologies due to their unique electromagnetic characteristics, ultrathin profiles, and seamless integration capabilities. Light-emitting metasurfaces based on near-field resonance modes exhibit unique advantages in scattering radiative photons, directing and enhancing light emission, expanding their applications in advanced photonics. This review provides an insightful overview of the basic principles of manipulating and controlling the emission behavior of ensembled quantum emitters, and provides a detailed introduction to the latest research and application progress of light-emitting metasurfaces within the visible light spectrum, including applications in fields such as miniature solid-state lighting devices, virtual reality and augmented reality high-definition displays, visible light communication, high-energy X-ray detection, chiral light-sources, and low threshold micro/nano lasers, etc. Finally, future development directions of light-emitting metasurfaces are prospected. Artificially constructed planar metasurfaces play a crucial role in photonics and emerging optoelectronic technologies due to their unique electromagnetic characteristics, ultrathin profiles, and seamless integration capabilities. Light-emitting metasurfaces based on near-field resonance modes exhibit unique advantages in scattering radiative photons, directing and enhancing light emission, expanding their applications in advanced photonics. This review provides an insightful overview of the basic principles of manipulating and controlling the emission behavior of ensembled quantum emitters, and provides a detailed introduction to the latest research and application progress of light-emitting metasurfaces within the visible light spectrum, including applications in fields such as miniature solid-state lighting devices, virtual reality and augmented reality high-definition displays, visible light communication, high-energy X-ray detection, chiral light-sources, and low threshold micro/nano lasers, etc. Finally, future development directions of light-emitting metasurfaces are prospected.
Laser & Optoelectronics Progress
- Publication Date: Feb. 10, 2024
- Vol. 61, Issue 3, 0323001 (2024)
Efficient Photoelectric Coupling Simulation and Machine Learning Study of Perovskite Solar Cells (Invited)
Ruiying Kong, Yijun Wei, Jiacheng Chen, Tianshu Ma, Yaohui Zhan, and Xiaofeng Li
In recent years, perovskite solar cells (PSCs) have attracted much attention because of their remarkable advantages in power conversion efficiency and manufacturing cost. However, their complex physical mechanisms and numerous constraints pose challenges to experimental design, process fabrication, and comprehensive optimization strategies. Here, we carried out a series of multi-physical field simulations with the optoelectronic multi-physical field coupling model as the core, and studied the underlying physics and boundary conditions of the optoelectronic coupling model, and then obtained a large amount of data on the optical and electrical properties of PSCs. Based on these data, we established the machine learning models and neural network models for the micro physical quantities and macro photoelectric responses, which predicted the performance of PSCs with an error of less than 3% in a fast speed. Combined with the genetic algorithm, the model reversely optimized the structural parameters according to the given response curves to obtain the more efficient PSCs. This study effectively solves the problem that PSCs are difficult to optimize design due to complex photoelectric coupling mechanism, numerous physical property parameters and slow simulation speed, and provides a feasible path for rapid and intelligent design of photovoltaic devices. In recent years, perovskite solar cells (PSCs) have attracted much attention because of their remarkable advantages in power conversion efficiency and manufacturing cost. However, their complex physical mechanisms and numerous constraints pose challenges to experimental design, process fabrication, and comprehensive optimization strategies. Here, we carried out a series of multi-physical field simulations with the optoelectronic multi-physical field coupling model as the core, and studied the underlying physics and boundary conditions of the optoelectronic coupling model, and then obtained a large amount of data on the optical and electrical properties of PSCs. Based on these data, we established the machine learning models and neural network models for the micro physical quantities and macro photoelectric responses, which predicted the performance of PSCs with an error of less than 3% in a fast speed. Combined with the genetic algorithm, the model reversely optimized the structural parameters according to the given response curves to obtain the more efficient PSCs. This study effectively solves the problem that PSCs are difficult to optimize design due to complex photoelectric coupling mechanism, numerous physical property parameters and slow simulation speed, and provides a feasible path for rapid and intelligent design of photovoltaic devices.
Laser & Optoelectronics Progress
- Publication Date: Jan. 10, 2024
- Vol. 61, Issue 1, 0123002 (2024)
Research Progress of Metasurface-Based Jones Matrix Modulation (Invited)
Chao Feng, Tao He, Yuzhi Shi, Zhanshan Wang, and Xinbin Cheng
Polarization, a fundamental degree of freedom of the optical field, has important applications in many fields of optical technology. The optical field modulation performance of optical devices is often expressed by the Jones matrix with its number of controllable channels characterizing the polarization control capability. With the rapid development of optical technology, novel applications, such as polarization imaging, information coding, and optical encryption, require optical devices to independently modulate multiple Jones-matrix channels while considering the need for miniaturization. Metasurface, a planar optical device composed of artificial subwavelength nano-structures with specific order, is expected to have a greater role in the field of polarization optics devices owing to its natural advantage of integration and powerful ability to modulate electromagnetic waves with arbitrary customization. In this paper, we first introduce the phase and amplitude modulation mechanisms of the metasurfaces, then systematically review the development of Jones matrix modulated metasurfaces with an increase in the number of controllable channels, and finally, provide an outlook on the future development of Jones matrix modulation technology for metasurfaces. Polarization, a fundamental degree of freedom of the optical field, has important applications in many fields of optical technology. The optical field modulation performance of optical devices is often expressed by the Jones matrix with its number of controllable channels characterizing the polarization control capability. With the rapid development of optical technology, novel applications, such as polarization imaging, information coding, and optical encryption, require optical devices to independently modulate multiple Jones-matrix channels while considering the need for miniaturization. Metasurface, a planar optical device composed of artificial subwavelength nano-structures with specific order, is expected to have a greater role in the field of polarization optics devices owing to its natural advantage of integration and powerful ability to modulate electromagnetic waves with arbitrary customization. In this paper, we first introduce the phase and amplitude modulation mechanisms of the metasurfaces, then systematically review the development of Jones matrix modulated metasurfaces with an increase in the number of controllable channels, and finally, provide an outlook on the future development of Jones matrix modulation technology for metasurfaces.
Laser & Optoelectronics Progress
- Publication Date: Jan. 10, 2024
- Vol. 61, Issue 1, 0123001 (2024)
Goos-Hänchen Shifts of Metal Layer and Quasicrystals with Monolayer Graphene
Zhengyang Li, Haixia Da, and Xiaohong Yan
Since the magnitudes of the Goos-H?nchen (GH) shifts in multilayered photonic crystals are generally small, it is desirable to find the alternative configurations to achieve the large GH shift. In this work, we investigated the GH shift of the reflected wave in the structure with a metal layer, a dielectric material, and the quasiperiodic photonic crystal by the transfer matrix method, where the quasiperiodic photonic crystal is composed of a dielectric material and monolayer graphene arranged in a Fibonacci sequence. It is found that the GH shift can be enhanced up to 7330 times of the incident wavelength at the specified operating wavelength 2 μm due to the excitation of surface plasmon polaritons of metal. In addition, we discussed the influence of the optical parameters of monolayer graphene, and the thickness of the dielectric material on the GH shift, and confirmed that changing these parameters could achieve the control of GH shift. Since the magnitudes of the Goos-H?nchen (GH) shifts in multilayered photonic crystals are generally small, it is desirable to find the alternative configurations to achieve the large GH shift. In this work, we investigated the GH shift of the reflected wave in the structure with a metal layer, a dielectric material, and the quasiperiodic photonic crystal by the transfer matrix method, where the quasiperiodic photonic crystal is composed of a dielectric material and monolayer graphene arranged in a Fibonacci sequence. It is found that the GH shift can be enhanced up to 7330 times of the incident wavelength at the specified operating wavelength 2 μm due to the excitation of surface plasmon polaritons of metal. In addition, we discussed the influence of the optical parameters of monolayer graphene, and the thickness of the dielectric material on the GH shift, and confirmed that changing these parameters could achieve the control of GH shift.
Laser & Optoelectronics Progress
- Publication Date: May. 10, 2023
- Vol. 60, Issue 9, 0923001 (2023)
Experimental Research on Visible Light Positioning Using Machine Learning and Multi-Photodiode
Fen Wei, Yi Wu, and Shiwu Xu
Aiming at the shortage of a single-photodiode (PD) receiver and geometric algorithms, we set up a real visible light positioning (VLP) scene of a multi-PD receiver and then use the fingerprint positioning technology based on the received signal strength, which commonly uses machine learning algorithms (MLAs). The positioning performance of four typical MLAs is studied. The results show that in two-dimensional positioning, the probabilities that the positioning error is less than 2 cm are 96.67%, 48.57%, 67.14%, and 15.24% for the K-nearest neighbor (KNN), extreme learning machine (ELM), random forest (RF), and adaptive boosting (AdaBoost), respectively, and in three-dimensional positioning, the probabilities that the positioning error is less than 2 cm for the KNN, ELM, RF, and AdaBoost are 74.52%, 38.81%, 59.76%, and 6.43%, respectively. Therefore, the positioning performance of the KNN is better in both the cases. On this basis, the influence of factors such as the number of light-emitting diodes (LEDs), number of PDs, and emission power of LEDs on the positioning accuracy is compared in detail. The results show that the increase in both the number of LEDs and PDs effectively reduces the positioning error. When the emission power of LEDs is 5 W, the positioning error convergence is achieved. The results provide a new theoretical support and practical application value for the design of VLP systems in the low LED distribution density scenes. Aiming at the shortage of a single-photodiode (PD) receiver and geometric algorithms, we set up a real visible light positioning (VLP) scene of a multi-PD receiver and then use the fingerprint positioning technology based on the received signal strength, which commonly uses machine learning algorithms (MLAs). The positioning performance of four typical MLAs is studied. The results show that in two-dimensional positioning, the probabilities that the positioning error is less than 2 cm are 96.67%, 48.57%, 67.14%, and 15.24% for the K-nearest neighbor (KNN), extreme learning machine (ELM), random forest (RF), and adaptive boosting (AdaBoost), respectively, and in three-dimensional positioning, the probabilities that the positioning error is less than 2 cm for the KNN, ELM, RF, and AdaBoost are 74.52%, 38.81%, 59.76%, and 6.43%, respectively. Therefore, the positioning performance of the KNN is better in both the cases. On this basis, the influence of factors such as the number of light-emitting diodes (LEDs), number of PDs, and emission power of LEDs on the positioning accuracy is compared in detail. The results show that the increase in both the number of LEDs and PDs effectively reduces the positioning error. When the emission power of LEDs is 5 W, the positioning error convergence is achieved. The results provide a new theoretical support and practical application value for the design of VLP systems in the low LED distribution density scenes.
Laser & Optoelectronics Progress
- Publication Date: Apr. 10, 2023
- Vol. 60, Issue 7, 0723002 (2023)
Optimization of Deep Ultraviolet Laser Diode with Monotonic Compositionally Graded Hole Reservoir Layer and Symmetric Compositionally Graded Hole Blocking Layer
Aoxiang Zhang, Pengfei Zhang, Liya Jia, Muhammad Nawaz Sharif, Fang Wang, and Yuhuai Liu
A monotonic compositionally graded hole reservoir layer (MCG-HRL) and a symmetric compositionally graded hole blocking layer (SCG-HBL) structures are proposed to optimize the electro-optical conversion efficiency and output power of the deep ultraviolet laser diode (DUV-LD). Crosslight software is used to simulate the DUV-LD with infrastructure, rectangular HRL (R-HRL), MCG-HRL, and MCG-HRL structures. The simulation results indicate that the MCG-HRL and SCG-HBL effectively contribute to the increased hole concentration in the quantum wells (QWs), reduce hole leakage in the n-type region, increase radiation recombination rate in the QWs, reduce threshold voltage and resistance, and increase electro-optical conversion efficiency and output power of the DUV-LD. A monotonic compositionally graded hole reservoir layer (MCG-HRL) and a symmetric compositionally graded hole blocking layer (SCG-HBL) structures are proposed to optimize the electro-optical conversion efficiency and output power of the deep ultraviolet laser diode (DUV-LD). Crosslight software is used to simulate the DUV-LD with infrastructure, rectangular HRL (R-HRL), MCG-HRL, and MCG-HRL structures. The simulation results indicate that the MCG-HRL and SCG-HBL effectively contribute to the increased hole concentration in the quantum wells (QWs), reduce hole leakage in the n-type region, increase radiation recombination rate in the QWs, reduce threshold voltage and resistance, and increase electro-optical conversion efficiency and output power of the DUV-LD.
Laser & Optoelectronics Progress
- Publication Date: Apr. 10, 2023
- Vol. 60, Issue 7, 0723001 (2023)
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