In Press
In Press articles are edited and published online ahead of issue. When the final article is assigned to volumes/issues, the Article in Press version will be removed and the final version will appear in the associated published volumes/issues.
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Achieving over 95% yield of sub-1 ppm BER with retention over 10 years at 125 °C and endurance of 1 × 1012 cycles towards automotive non-volatile RAM applications
Dinggui Zeng, Fantao Meng, Ruofei Chen, Yang Gao, Yihui Sun, Junlu Gong, Yongzhao Peng, Qijun Guo, Zhixiao Deng, Weiming He, Baoyu Xiong, Jia Hou, Jichao Li, Wei Fang, Qiang Dai, Yaohua Wang, Shikun He
, Available online  
doi: 10.1088/1674-4926/24090037

Magnetic tunnel junction (MTJ) based spin transfer torque magnetic random access memory (STT-MRAM) has been gaining tremendous momentum in high performance microcontroller (MCU) applications. As eFlash-replacement type MRAM approaches mass production, there is an increasing demand for non-volatile RAM (nvRAM) technologies that offer fast write speed and high endurance. In this work, we demonstrate highly reliable 4 Mb nvRAM type MRAM suitable for industry and auto grade-1 applications. This nvRAM features retention over 10 years at 125 °C, endurance of 1 × 1012 cycles with 20 ns write speed, making it ideal for applications requiring both high speed and broad temperature ranges. By employing innovative MTJ materials, process engineering, and a co-optimization of process and design, reliable read and write performance across the full temperature range between −40 to 125 °C, and array yield that meets sub-1 ppm error rate was significantly improved from 0 to above 95%, a concrete step toward applications.

Magnetic tunnel junction (MTJ) based spin transfer torque magnetic random access memory (STT-MRAM) has been gaining tremendous momentum in high performance microcontroller (MCU) applications. As eFlash-replacement type MRAM approaches mass production, there is an increasing demand for non-volatile RAM (nvRAM) technologies that offer fast write speed and high endurance. In this work, we demonstrate highly reliable 4 Mb nvRAM type MRAM suitable for industry and auto grade-1 applications. This nvRAM features retention over 10 years at 125 °C, endurance of 1 × 1012 cycles with 20 ns write speed, making it ideal for applications requiring both high speed and broad temperature ranges. By employing innovative MTJ materials, process engineering, and a co-optimization of process and design, reliable read and write performance across the full temperature range between −40 to 125 °C, and array yield that meets sub-1 ppm error rate was significantly improved from 0 to above 95%, a concrete step toward applications.
Synaptic devices based on silicon carbide for neuromorphic computing
Boyu Ye, Xiao Liu, Chao Wu, Wensheng Yan, Xiaodong Pi
, Available online  
doi: 10.1088/1674-4926/24100020

To address the increasing demand for massive data storage and processing, brain-inspired neuromorphic computing systems based on artificial synaptic devices have been actively developed in recent years. Among the various materials investigated for the fabrication of synaptic devices, silicon carbide (SiC) has emerged as a preferred choices due to its high electron mobility, superior thermal conductivity, and excellent thermal stability, which exhibits promising potential for neuromorphic applications in harsh environments. In this review, the recent progress in SiC-based synaptic devices is summarized. Firstly, an in-depth discussion is conducted regarding the categories, working mechanisms, and structural designs of these devices. Subsequently, several application scenarios for SiC-based synaptic devices are presented. Finally, a few perspectives and directions for their future development are outlined.

To address the increasing demand for massive data storage and processing, brain-inspired neuromorphic computing systems based on artificial synaptic devices have been actively developed in recent years. Among the various materials investigated for the fabrication of synaptic devices, silicon carbide (SiC) has emerged as a preferred choices due to its high electron mobility, superior thermal conductivity, and excellent thermal stability, which exhibits promising potential for neuromorphic applications in harsh environments. In this review, the recent progress in SiC-based synaptic devices is summarized. Firstly, an in-depth discussion is conducted regarding the categories, working mechanisms, and structural designs of these devices. Subsequently, several application scenarios for SiC-based synaptic devices are presented. Finally, a few perspectives and directions for their future development are outlined.
Ion-modulation optoelectronic neuromorphic devices: mechanisms, characteristics, and applications
Xiaohan Meng, Runsheng Gao, Xiaojian Zhu, Run-Wei Li
, Available online  
doi: 10.1088/1674-4926/24100025

The traditional von Neumann architecture faces inherent limitations due to the separation of memory and computation, leading to high energy consumption, significant latency, and reduced operational efficiency. Neuromorphic computing, inspired by the architecture of the human brain, offers a promising alternative by integrating memory and computational functions, enabling parallel, high-speed, and energy-efficient information processing. Among various neuromorphic technologies, ion-modulated optoelectronic devices have garnered attention due to their excellent ionic tunability and the availability of multidimensional control strategies. This review provides a comprehensive overview of recent progress in ion-modulation optoelectronic neuromorphic devices. It elucidates the key mechanisms underlying ionic modulation of light fields, including ion migration dynamics and capture and release of charge through ions. Furthermore, the synthesis of active materials and the properties of these devices are analyzed in detail. The review also highlights the application of ion-modulation optoelectronic devices in artificial vision systems, neuromorphic computing, and other bionic fields. Finally, the existing challenges and future directions for the development of optoelectronic neuromorphic devices are discussed, providing critical insights for advancing this promising field.

The traditional von Neumann architecture faces inherent limitations due to the separation of memory and computation, leading to high energy consumption, significant latency, and reduced operational efficiency. Neuromorphic computing, inspired by the architecture of the human brain, offers a promising alternative by integrating memory and computational functions, enabling parallel, high-speed, and energy-efficient information processing. Among various neuromorphic technologies, ion-modulated optoelectronic devices have garnered attention due to their excellent ionic tunability and the availability of multidimensional control strategies. This review provides a comprehensive overview of recent progress in ion-modulation optoelectronic neuromorphic devices. It elucidates the key mechanisms underlying ionic modulation of light fields, including ion migration dynamics and capture and release of charge through ions. Furthermore, the synthesis of active materials and the properties of these devices are analyzed in detail. The review also highlights the application of ion-modulation optoelectronic devices in artificial vision systems, neuromorphic computing, and other bionic fields. Finally, the existing challenges and future directions for the development of optoelectronic neuromorphic devices are discussed, providing critical insights for advancing this promising field.
Electrolyte-gated optoelectronic transistors for neuromorphic applications
Jinming Bi, Yanran Li, Rong Lu, Honglin Song, Jie Jiang
, Available online  
doi: 10.1088/1674-4926/24090042

The traditional von Neumann architecture has demonstrated inefficiencies in parallel computing and adaptive learning, rendering it incapable of meeting the growing demand for efficient and high-speed computing. Neuromorphic computing with significant advantages such as high parallelism and ultra-low power consumption is regarded as a promising pathway to overcome the limitations of conventional computers and achieve the next-generation artificial intelligence. Among various neuromorphic devices, the artificial synapses based on electrolyte-gated transistors stand out due to their low energy consumption, multimodal sensing/recording capabilities, and multifunctional integration. Moreover, the emerging optoelectronic neuromorphic devices which combine the strengths of photonics and electronics have demonstrated substantial potential in the neuromorphic computing field. Therefore, this article reviews recent advancements in electrolyte-gated optoelectronic neuromorphic transistors. First, it provides an overview of artificial optoelectronic synapses and neurons, discussing aspects such as device structures, operating mechanisms, and neuromorphic functionalities. Next, the potential applications of optoelectronic synapses in different areas such as artificial visual system, pain system, and tactile perception systems are elaborated. Finally, the current challenges are summarized, and future directions for their developments are proposed.

The traditional von Neumann architecture has demonstrated inefficiencies in parallel computing and adaptive learning, rendering it incapable of meeting the growing demand for efficient and high-speed computing. Neuromorphic computing with significant advantages such as high parallelism and ultra-low power consumption is regarded as a promising pathway to overcome the limitations of conventional computers and achieve the next-generation artificial intelligence. Among various neuromorphic devices, the artificial synapses based on electrolyte-gated transistors stand out due to their low energy consumption, multimodal sensing/recording capabilities, and multifunctional integration. Moreover, the emerging optoelectronic neuromorphic devices which combine the strengths of photonics and electronics have demonstrated substantial potential in the neuromorphic computing field. Therefore, this article reviews recent advancements in electrolyte-gated optoelectronic neuromorphic transistors. First, it provides an overview of artificial optoelectronic synapses and neurons, discussing aspects such as device structures, operating mechanisms, and neuromorphic functionalities. Next, the potential applications of optoelectronic synapses in different areas such as artificial visual system, pain system, and tactile perception systems are elaborated. Finally, the current challenges are summarized, and future directions for their developments are proposed.
Preface to Special Issue on Optoelectronic Neuromorphic Devices
Zhenyi Ni, Zhongqiang Wang, Jia Huang, Xiaodong Pi
, Available online  
doi: 10.1088/1674-4926/25020802

Charge carrier management via semiconducting matrix for efficient self-powered quantum dot infrared photodetectors
Jianfeng Ding, Xinying Liu, Yueyue Gao, Chen Dong, Gentian Yue, Furui Tan
, Available online  
doi: 10.1088/1674-4926/24100028

Quantum dot (QD)-based infrared photodetector is a promising technology that can implement current monitoring, imaging and optical communication in the infrared region. However, the photodetection performance of self-powered QD devices is still limited by their unfavorable charge carrier dynamics due to their intrinsically discrete charge carrier transport process. Herein, we strategically constructed semiconducting matrix in QD film to achieve efficient charge transfer and extraction. The p-type semiconducting CuSCN was selected as energy-aligned matrix to match the n-type colloidal PbS QDs that was used as proof-of-concept. Note that the PbS QD/CuSCN matrix not only enables efficient charge carrier separation and transfer at nano-interfaces but also provides continuous charge carrier transport pathways that are different from the hoping process in neat QD film, resulting in improved charge mobility and derived collection efficiency. As a result, the target structure delivers high specific detectivity of 4.38 × 1012 Jones and responsivity of 782 mA/W at 808 nm, which is superior than that of the PbS QD-only photodetector (4.66 × 1011 Jones and 338 mA/W). This work provides a new structure candidate for efficient colloidal QD based optoelectronic devices.

Quantum dot (QD)-based infrared photodetector is a promising technology that can implement current monitoring, imaging and optical communication in the infrared region. However, the photodetection performance of self-powered QD devices is still limited by their unfavorable charge carrier dynamics due to their intrinsically discrete charge carrier transport process. Herein, we strategically constructed semiconducting matrix in QD film to achieve efficient charge transfer and extraction. The p-type semiconducting CuSCN was selected as energy-aligned matrix to match the n-type colloidal PbS QDs that was used as proof-of-concept. Note that the PbS QD/CuSCN matrix not only enables efficient charge carrier separation and transfer at nano-interfaces but also provides continuous charge carrier transport pathways that are different from the hoping process in neat QD film, resulting in improved charge mobility and derived collection efficiency. As a result, the target structure delivers high specific detectivity of 4.38 × 1012 Jones and responsivity of 782 mA/W at 808 nm, which is superior than that of the PbS QD-only photodetector (4.66 × 1011 Jones and 338 mA/W). This work provides a new structure candidate for efficient colloidal QD based optoelectronic devices.
Calculation of the carrier dynamics and impedance spectroscopy model in quantum well infrared photodetectors
Chenzhe Hu, Yuyu Bu, Xianying Dai, Fengqiu Jiang, Yue Hao
, Available online  
doi: 10.1088/1674-4926/24090033

Quantum well infrared photodetectors (QWIPs) based on intersubband transitions hold significant potential for high bandwidth operation. In this work, we establish a carrier transport optimization model incorporating electron injection at the emitter to investigate the carrier dynamics time and impedance spectroscopy in GaAs/AlGaAs QWIPs. Our findings provide novel evidence that the escape time of electrons is the key limiting factor for the 3-dB bandwidth of QWIPs. Moreover, to characterize the impact of carrier dynamics time and non-equilibrium space charge region on impedance, we developed an equivalent circuit model where depletion region resistance and capacitance are employed to describe non-equilibrium space charge region. Using this model, we discovered that under illumination, both net charge accumulation caused by variations in carrier dynamics times within quantum wells and changes in width of non-equilibrium space charge region exert different dominant influences on depletion region capacitance at various doping concentrations.

Quantum well infrared photodetectors (QWIPs) based on intersubband transitions hold significant potential for high bandwidth operation. In this work, we establish a carrier transport optimization model incorporating electron injection at the emitter to investigate the carrier dynamics time and impedance spectroscopy in GaAs/AlGaAs QWIPs. Our findings provide novel evidence that the escape time of electrons is the key limiting factor for the 3-dB bandwidth of QWIPs. Moreover, to characterize the impact of carrier dynamics time and non-equilibrium space charge region on impedance, we developed an equivalent circuit model where depletion region resistance and capacitance are employed to describe non-equilibrium space charge region. Using this model, we discovered that under illumination, both net charge accumulation caused by variations in carrier dynamics times within quantum wells and changes in width of non-equilibrium space charge region exert different dominant influences on depletion region capacitance at various doping concentrations.
Pressure sensor with wide detection range and high sensitivity for wearable human health monitoring
Lingchen Liu, Ying Yuan, Hao Xu, Xiaokun Qin, Xiaofeng Wang, Zheng Lou, Lili Wang
, Available online  
doi: 10.1088/1674-4926/24110017

High-performance flexible pressure sensors have garnered significant attention in fields such as wearable electronics and human-machine interfaces. However, the development of flexible pressure sensors that simultaneously achieve high sensitivity, a wide detection range, and good mechanical stability remains a challenge. In this paper, we propose a flexible piezoresistive pressure sensor based on a Ti3C₂Tx (MXene)/polyethylene oxide (PEO) composite nanofiber membrane (CNM). The sensor, utilizing MXene (0.4 wt%)/PEO (5 wt%), exhibits high sensitivity (44.34 kPa−1 at 0−50 kPa, 12.99 kPa−1 at 50−500 kPa) and can reliably monitor physiological signals and other subtle cues. Moreover, the sensor features a wide detection range (0−500 kPa), fast response and recovery time (~150/45 ms), and excellent mechanical stability (over 10 000 pressure cycles at maximum load). Through an MXene/PEO sensor array, we demonstrate its applications in human physiological signal monitoring, providing a reliable way to expand the application of MXene-based flexible pressure sensors.

High-performance flexible pressure sensors have garnered significant attention in fields such as wearable electronics and human-machine interfaces. However, the development of flexible pressure sensors that simultaneously achieve high sensitivity, a wide detection range, and good mechanical stability remains a challenge. In this paper, we propose a flexible piezoresistive pressure sensor based on a Ti3C₂Tx (MXene)/polyethylene oxide (PEO) composite nanofiber membrane (CNM). The sensor, utilizing MXene (0.4 wt%)/PEO (5 wt%), exhibits high sensitivity (44.34 kPa−1 at 0−50 kPa, 12.99 kPa−1 at 50−500 kPa) and can reliably monitor physiological signals and other subtle cues. Moreover, the sensor features a wide detection range (0−500 kPa), fast response and recovery time (~150/45 ms), and excellent mechanical stability (over 10 000 pressure cycles at maximum load). Through an MXene/PEO sensor array, we demonstrate its applications in human physiological signal monitoring, providing a reliable way to expand the application of MXene-based flexible pressure sensors.
Light and matter co-confined multi-photon lithography: an innovative way to break through the limits of traditional lithography
Jingyu Wang, Zhanfeng Guo, Zhu Wang, Zhengwei Liu, Daixuan Wu, He Tian
, Available online  
doi: 10.1088/1674-4926/24110023

Optical network-on-chip (ONoC) architectures: a detailed analysis of optical router designs
Yasin Asadi
, Available online  
doi: 10.1088/1674-4926/24060006

Optical network-on-chip (ONoC) systems have emerged as a promising solution to overcome limitations of traditional electronic interconnects. Efficient ONoC architectures rely on optical routers, enabling high-speed data transfer, efficient routing, and scalability. This paper presents a comprehensive survey analyzing optical router designs, specifically microring resonators (MRRs), mach zehnder interferometers (MZIs), and hybrid architectures. Selected comparison criteria, chosen for their critical importance, significantly impact router functionality and performance. By emphasizing these criteria, valuable insights into the strengths and limitations of different designs are gained, facilitating informed decisions and advancements in optical networking. While other factors contribute to performance and efficiency, the chosen criteria consistently address fundamental elements, enabling meaningful evaluation. This work serves as a valuable resource for beginners, providing a solid foundation in understanding ONoC and optical routers. It also offers an in-depth survey for experts, laying the groundwork for further exploration. Additionally, the importance of considering design constraints and requirements when selecting an optimal router design is highlighted. Continued research and innovation will enable the development of efficient optical router solutions that meet the evolving needs of modern computing systems. This survey underscores the significance of ongoing advancements in the field and their potential impact on future technologies.

Optical network-on-chip (ONoC) systems have emerged as a promising solution to overcome limitations of traditional electronic interconnects. Efficient ONoC architectures rely on optical routers, enabling high-speed data transfer, efficient routing, and scalability. This paper presents a comprehensive survey analyzing optical router designs, specifically microring resonators (MRRs), mach zehnder interferometers (MZIs), and hybrid architectures. Selected comparison criteria, chosen for their critical importance, significantly impact router functionality and performance. By emphasizing these criteria, valuable insights into the strengths and limitations of different designs are gained, facilitating informed decisions and advancements in optical networking. While other factors contribute to performance and efficiency, the chosen criteria consistently address fundamental elements, enabling meaningful evaluation. This work serves as a valuable resource for beginners, providing a solid foundation in understanding ONoC and optical routers. It also offers an in-depth survey for experts, laying the groundwork for further exploration. Additionally, the importance of considering design constraints and requirements when selecting an optimal router design is highlighted. Continued research and innovation will enable the development of efficient optical router solutions that meet the evolving needs of modern computing systems. This survey underscores the significance of ongoing advancements in the field and their potential impact on future technologies.
Broadband full-stokes polarimeter based on ReS2 nanobelts
Tinghao Lin, Wendian Yao, Zeyi Liu, Haizhen Wang, Dehui Li, and Xinliang Zhang
, Available online  
doi: 10.1088/1674-4926/24080023

Full-Stokes polarimeters can detect the polarization states of light, which is critical for the next-generation optical and optoelectronic systems. Traditional full-Stokes polarimeters are either based on bulky optical systems or complex metasurface structures, which cause the system complexity with unessential energy loss. Recently, filterless on-chip full-Stokes polarimeters have been demonstrated by using optical anisotropic materials which are able to detect the circularly polarized light. Nevertheless, those on-chip full-Stokes polarimeters have either the limited detection wavelength range or relatively poor device performance that need to be further improved. Here, we report the high performance broadband full-Stokes polarimeters based on rhenium disulfide (ReS2). While the anisotropic structure of the ReS2 introduces the in-plane optical anisotropy for linearly polarized light (LP) detection, Schottky contacts formed by the ReS2-Au could break the symmetry, which can detect circularly polarized (CP) light. By building a proper model, all four Stokes parameters can be extracted by using the ReS2 nanobelt device. The device delivers a photoresponsivity of 181 A/W, a detectivity of 6.8 × 1010 Jones and can sense the four Stokes parameters of incident light within a wide range of wavelength from 565−800 nm with reasonable average errors. We believe our study provides an alternative strategy to develop high performance broadband on-chip full-Stokes polarimeters.

Full-Stokes polarimeters can detect the polarization states of light, which is critical for the next-generation optical and optoelectronic systems. Traditional full-Stokes polarimeters are either based on bulky optical systems or complex metasurface structures, which cause the system complexity with unessential energy loss. Recently, filterless on-chip full-Stokes polarimeters have been demonstrated by using optical anisotropic materials which are able to detect the circularly polarized light. Nevertheless, those on-chip full-Stokes polarimeters have either the limited detection wavelength range or relatively poor device performance that need to be further improved. Here, we report the high performance broadband full-Stokes polarimeters based on rhenium disulfide (ReS2). While the anisotropic structure of the ReS2 introduces the in-plane optical anisotropy for linearly polarized light (LP) detection, Schottky contacts formed by the ReS2-Au could break the symmetry, which can detect circularly polarized (CP) light. By building a proper model, all four Stokes parameters can be extracted by using the ReS2 nanobelt device. The device delivers a photoresponsivity of 181 A/W, a detectivity of 6.8 × 1010 Jones and can sense the four Stokes parameters of incident light within a wide range of wavelength from 565−800 nm with reasonable average errors. We believe our study provides an alternative strategy to develop high performance broadband on-chip full-Stokes polarimeters.
Fabrication and application of SiNWs based PANI:MOx heterostructures for human respiratory monitoring
Muhammad Taha Sultan, Anca Dumitru, Elham Fakhri, Rachel Brophy, Snorri Thorgeir Ingvarsson, Andrei Manolescu, Halldor Gudfinur Svavarsson
, Available online  
doi: 10.1088/1674-4926/24090035

In this study, we investigate an innovative hybrid structure of silicon nanowires (SiNWs) coated with polyaniline (PANI):metal oxide (MOx) nanoparticles, i.e., WO3 and TiO2, for respiratory sensing. To date, few attempts have been made to utilize such hybrid structures for that application. The SiNWs were fabricated using metal-assisted chemical etching (MACE), whereas PANI:MOx was deposited using chemical oxidative polymerization. The structures were characterized using Raman spectroscopy, X-ray diffraction, and scanning electron microscopy. The sensing characteristics revealed that the hybrid sensor exhibited a considerably better response than pure SiNWs:MOx and SiNWs:PANI. Such an enhancement in sensitivity is attributed to the formation of a p−n heterojunction between PANI and MOx, the wider conduction channel provided by PANI, increased porosity in SiNWs/PANI:WO3 hybrid structures, which creates active sites, increased oxygen vacancies, and the large surface area compared to that available in pure MOx nanoparticles. Furthermore, less baseline drift and increased sensor stability were established for the SiNWs structure coated with PANI:WO3, as compared to PANI:TiO2.

In this study, we investigate an innovative hybrid structure of silicon nanowires (SiNWs) coated with polyaniline (PANI):metal oxide (MOx) nanoparticles, i.e., WO3 and TiO2, for respiratory sensing. To date, few attempts have been made to utilize such hybrid structures for that application. The SiNWs were fabricated using metal-assisted chemical etching (MACE), whereas PANI:MOx was deposited using chemical oxidative polymerization. The structures were characterized using Raman spectroscopy, X-ray diffraction, and scanning electron microscopy. The sensing characteristics revealed that the hybrid sensor exhibited a considerably better response than pure SiNWs:MOx and SiNWs:PANI. Such an enhancement in sensitivity is attributed to the formation of a p−n heterojunction between PANI and MOx, the wider conduction channel provided by PANI, increased porosity in SiNWs/PANI:WO3 hybrid structures, which creates active sites, increased oxygen vacancies, and the large surface area compared to that available in pure MOx nanoparticles. Furthermore, less baseline drift and increased sensor stability were established for the SiNWs structure coated with PANI:WO3, as compared to PANI:TiO2.
GaN-based blue laser diodes with output power of 5 W and lifetime over 20 000 h aged at 60 °C
Lei Hu, Siyi Huang, Zhi Liu, Tengfeng Duan, Si Wu, Dan Wang, Hui Yang, Jun Wang, Jianping Liu
, Available online  
doi: 10.1088/1674-4926/24110039

Recent progress in organic optoelectronic synaptic transistor arrays: fabrication strategies and innovative applications of system integration
Pu Guo, Junyao Zhang, Jia Huang
, Available online  
doi: 10.1088/1674-4926/24120017

The rapid growth of artificial intelligence has accelerated data generation, which increasingly exposes the limitations faced by traditional computational architectures, particularly in terms of energy consumption and data latency. In contrast, data-centric computing that integrates processing and storage has the potential of reducing latency and energy usage. Organic optoelectronic synaptic transistors have emerged as one type of promising devices to implement the data-centric computing paradigm owing to their superiority of flexibility, low cost, and large-area fabrication. However, sophisticated functions including vector-matrix multiplication that a single device can achieve are limited. Thus, the fabrication and utilization of organic optoelectronic synaptic transistor arrays (OOSTAs) are imperative. Here, we summarize the recent advances in OOSTAs. Various strategies for manufacturing OOSTAs are introduced, including coating and casting, physical vapor deposition, printing, and photolithography. Furthermore, innovative applications of the OOSTA system integration are discussed, including neuromorphic visual systems and neuromorphic computing systems. At last, challenges and future perspectives of utilizing OOSTAs in real-world applications are discussed.

The rapid growth of artificial intelligence has accelerated data generation, which increasingly exposes the limitations faced by traditional computational architectures, particularly in terms of energy consumption and data latency. In contrast, data-centric computing that integrates processing and storage has the potential of reducing latency and energy usage. Organic optoelectronic synaptic transistors have emerged as one type of promising devices to implement the data-centric computing paradigm owing to their superiority of flexibility, low cost, and large-area fabrication. However, sophisticated functions including vector-matrix multiplication that a single device can achieve are limited. Thus, the fabrication and utilization of organic optoelectronic synaptic transistor arrays (OOSTAs) are imperative. Here, we summarize the recent advances in OOSTAs. Various strategies for manufacturing OOSTAs are introduced, including coating and casting, physical vapor deposition, printing, and photolithography. Furthermore, innovative applications of the OOSTA system integration are discussed, including neuromorphic visual systems and neuromorphic computing systems. At last, challenges and future perspectives of utilizing OOSTAs in real-world applications are discussed.
Adaptive optoelectronic transistor for intelligent vision system
Yiru Wang, Shanshuo Liu, Hongxin Zhang, Yuchen Cao, Zitong Mu, Mingdong Yi, Linghai Xie, Haifeng Ling
, Available online  
doi: 10.1088/1674-4926/24100042

Recently, for developing neuromorphic visual systems, adaptive optoelectronic devices become one of the main research directions and attract extensive focus to achieve optoelectronic transistors with high performances and flexible functionalities. In this review, based on a description of the biological adaptive functions that are favorable for dynamically perceiving, filtering, and processing information in the varying environment, we summarize the representative strategies for achieving these adaptabilities in optoelectronic transistors, including the adaptation for detecting information, adaptive synaptic weight change, and history-dependent plasticity. Moreover, the key points of the corresponding strategies are comprehensively discussed. And the applications of these adaptive optoelectronic transistors, including the adaptive color detection, signal filtering, extending the response range of light intensity, and improve learning efficiency, are also illustrated separately. Lastly, the challenges faced in developing adaptive optoelectronic transistor for artificial vision system are discussed. The description of biological adaptive functions and the corresponding inspired neuromorphic devices are expected to provide insights for the design and application of next-generation artificial visual systems.

Recently, for developing neuromorphic visual systems, adaptive optoelectronic devices become one of the main research directions and attract extensive focus to achieve optoelectronic transistors with high performances and flexible functionalities. In this review, based on a description of the biological adaptive functions that are favorable for dynamically perceiving, filtering, and processing information in the varying environment, we summarize the representative strategies for achieving these adaptabilities in optoelectronic transistors, including the adaptation for detecting information, adaptive synaptic weight change, and history-dependent plasticity. Moreover, the key points of the corresponding strategies are comprehensively discussed. And the applications of these adaptive optoelectronic transistors, including the adaptive color detection, signal filtering, extending the response range of light intensity, and improve learning efficiency, are also illustrated separately. Lastly, the challenges faced in developing adaptive optoelectronic transistor for artificial vision system are discussed. The description of biological adaptive functions and the corresponding inspired neuromorphic devices are expected to provide insights for the design and application of next-generation artificial visual systems.
6-inch AlN epitaxial films with low dislocation densities via MOCVD
Shunpeng Lu, Jianwei Ben, Ke Jiang, Shanli Zhang, Ruojia Zhang, Jialong Hao, Zhongxu Liu, Wenchao Sun, Zikai Nie, Xiaojuan Sun, Dabing Li
, Available online  
doi: 10.1088/1674-4926/24110030

High-quality AlN epitaxial layers with low dislocation densities and uniform crystal quality are essential for next-generation optoelectronic and power devices. This study reports the epitaxial growth of 6-inch AlN films on 17 nm AlN/sapphire templates using metal−organic chemical vapor deposition (MOCVD). Comprehensive characterization reveals significant advancements in crystal quality and uniformity. Atomic force microscopy (AFM) shows progressive surface roughness reduction during early growth stages, achieving stabilization at a root mean square (RMS) roughness of 0.216 nm within 3 min, confirming successful 2D growth mode. X-ray rocking curve (XRC) analysis indicates a marked reduction in the (0002) reflection full width at half maximum (FWHM), from 445 to 96 arcsec, evidencing effective dislocation annihilation. Transmission electron microscopy (TEM) demonstrates the elimination of edge dislocations near the AlN template interface. Stress analysis highlights the role of a highly compressive 17 nm AlN template (5.11 GPa) in facilitating threading dislocation bending and annihilation, yielding a final dislocation density of ~1.5 × 107 cm−2. Raman spectroscopy and XRC mapping confirm excellent uniformity of stress and crystal quality across the wafer. These findings demonstrate the feasibility of this method for producing high-quality, large-area, atomically flat AlN films, advancing applications in optoelectronics and power electronics.

High-quality AlN epitaxial layers with low dislocation densities and uniform crystal quality are essential for next-generation optoelectronic and power devices. This study reports the epitaxial growth of 6-inch AlN films on 17 nm AlN/sapphire templates using metal−organic chemical vapor deposition (MOCVD). Comprehensive characterization reveals significant advancements in crystal quality and uniformity. Atomic force microscopy (AFM) shows progressive surface roughness reduction during early growth stages, achieving stabilization at a root mean square (RMS) roughness of 0.216 nm within 3 min, confirming successful 2D growth mode. X-ray rocking curve (XRC) analysis indicates a marked reduction in the (0002) reflection full width at half maximum (FWHM), from 445 to 96 arcsec, evidencing effective dislocation annihilation. Transmission electron microscopy (TEM) demonstrates the elimination of edge dislocations near the AlN template interface. Stress analysis highlights the role of a highly compressive 17 nm AlN template (5.11 GPa) in facilitating threading dislocation bending and annihilation, yielding a final dislocation density of ~1.5 × 107 cm−2. Raman spectroscopy and XRC mapping confirm excellent uniformity of stress and crystal quality across the wafer. These findings demonstrate the feasibility of this method for producing high-quality, large-area, atomically flat AlN films, advancing applications in optoelectronics and power electronics.
All-optical nonlinear activation functions realized on phase-change photonic integrated circuits with microheaters
Jiyuan Jiang, Bingxin Ding, Shiyu Li, Xin Zhang, Haihua Wang, Jie Wu, Xiaoyan Liu, Zhou Wang, Xiaojuan Lian, Wen Huang, Lei Wang
, Available online  
doi: 10.1088/1674-4926/24090045

Photonic neural networks have garnered significant attention in recent years due to their ultra-high computational speed, broad bandwidth, and parallel processing capabilities. However, compared to conventional electronic nonlinear activation function (NAF), progress on efficient and easily implementable optical nonlinear activation function (ONAF) was barely reported. To address this issue, we proposed a programmable, low-loss ONAF device based on a silicon micro-ring resonator capped with the Antimony selenide (Sb2Se3) thin films, and with indium tin oxide (ITO) used as the microheater. Leveraging our self-developed phase-transformation kinetic and optical models, we successfully simulated the phase-transition behavior of Sb2Se3 and three different ONAFs—ELU, ReLU, and radial basis function (RBF) were achieved according to discernible optical responses of proposed devices under different phase-change extents. Classification results from the Fashion MNIST dataset demonstrated that these ONAFs can be considered as appropriate substitutes for traditional NAF. This indicated the bright prospect of the proposed device for nonlinear activation function in future photonic neural networks.

Photonic neural networks have garnered significant attention in recent years due to their ultra-high computational speed, broad bandwidth, and parallel processing capabilities. However, compared to conventional electronic nonlinear activation function (NAF), progress on efficient and easily implementable optical nonlinear activation function (ONAF) was barely reported. To address this issue, we proposed a programmable, low-loss ONAF device based on a silicon micro-ring resonator capped with the Antimony selenide (Sb2Se3) thin films, and with indium tin oxide (ITO) used as the microheater. Leveraging our self-developed phase-transformation kinetic and optical models, we successfully simulated the phase-transition behavior of Sb2Se3 and three different ONAFs—ELU, ReLU, and radial basis function (RBF) were achieved according to discernible optical responses of proposed devices under different phase-change extents. Classification results from the Fashion MNIST dataset demonstrated that these ONAFs can be considered as appropriate substitutes for traditional NAF. This indicated the bright prospect of the proposed device for nonlinear activation function in future photonic neural networks.
High quality 6-inch single-crystalline AlN template for E-mode HEMT power device
Zhiwen Liang, Shangfeng Liu, Ye Yuan, Tongxin Lu, Xiaopeng Li, Zirong Wang, Neng Zhang, Tai Li, Xiangdong Li, Qi Wang, Shengqiang Zhou, Kai Kang, Jincheng Zhang, Yue Hao, Xinqiang Wang
, Available online  
doi: 10.1088/1674-4926/24100041

In the present work, the high uniform 6-inch single-crystalline AlN template is successfully achieved by high temperature annealing technique, which opens up the path towards industrial application in power device. Moreover, the outstanding crystalline-quality is confirmed by Rutherford backscattering spectrometry (RBS). In accompanied with the results from X-ray diffraction, the RBS results along both [0001] and $ [1\bar{2}13] $ reveal that the in-plane lattice is effectively reordered by high temperature annealing. In addition, the constant Φepi angle between [0001] and $ [1\bar{2}13] $ at different depths of 31.54° confirms the uniform compressive strain inside the AlN region. Benefitting from the excellent crystalline quality of AlN template, we can epitaxially grow the enhanced-mode high electron mobility transistor (HEMT) with a graded AlGaN buffer as thin as only ~300 nm. Such an ultra-thin AlGaN buffer layer results in the wafer-bow as low as 18.1 μm in 6-inch wafer scale. The fabricated HEMT devices with 16 μm-LGD exhibits a threshold voltage (VTH) of 1.1 V and a high OFF-state breakdown voltage (VBD) over 1400 V. Furthermore, after 200 V high-voltage OFF-state stress, the current collapse is only 13.6%. Therefore, the advantages of both 6-inch size and excellent crystallinity announces the superiority of single-crystalline AlN template in low-cost electrical power applications.

In the present work, the high uniform 6-inch single-crystalline AlN template is successfully achieved by high temperature annealing technique, which opens up the path towards industrial application in power device. Moreover, the outstanding crystalline-quality is confirmed by Rutherford backscattering spectrometry (RBS). In accompanied with the results from X-ray diffraction, the RBS results along both [0001] and $ [1\bar{2}13] $ reveal that the in-plane lattice is effectively reordered by high temperature annealing. In addition, the constant Φepi angle between [0001] and $ [1\bar{2}13] $ at different depths of 31.54° confirms the uniform compressive strain inside the AlN region. Benefitting from the excellent crystalline quality of AlN template, we can epitaxially grow the enhanced-mode high electron mobility transistor (HEMT) with a graded AlGaN buffer as thin as only ~300 nm. Such an ultra-thin AlGaN buffer layer results in the wafer-bow as low as 18.1 μm in 6-inch wafer scale. The fabricated HEMT devices with 16 μm-LGD exhibits a threshold voltage (VTH) of 1.1 V and a high OFF-state breakdown voltage (VBD) over 1400 V. Furthermore, after 200 V high-voltage OFF-state stress, the current collapse is only 13.6%. Therefore, the advantages of both 6-inch size and excellent crystallinity announces the superiority of single-crystalline AlN template in low-cost electrical power applications.
Reconfigurable organic ambipolar optoelectronic synaptic transistor for information security access
Xinqi Ma, Wenbin Zhang, Qi Zheng, Wenbiao Niu, Zherui Zhao, Kui Zhou, Meng Zhang, Shuangmei Xue, Liangchao Guo, Yan Yan, Guanglong Ding, Suting Han, Vellaisamy A. L. Roy, Ye Zhou
, Available online  
doi: 10.1088/1674-4926/24090051

In this data explosion era, ensuring the secure storage, access, and transmission of information is imperative, encompassing all aspects ranging from safeguarding personal devices to formulating national information security strategies. Leveraging the potential offered by dual-type carriers for transportation and employing optical modulation techniques to develop high reconfigurable ambipolar optoelectronic transistors enables effective implementation of information destruction after reading, thereby guaranteeing data security. In this study, a reconfigurable ambipolar optoelectronic synaptic transistor based on poly (3-hexylthiophene) (P3HT) and poly [[N,N-bis(2-octyldodecyl)-napthalene-1,4,5,8-bis(dicarboximide)-2,6-diyl]-alt-5,5′-(2,2′-bithiophene)] (N2200) blend film was fabricated through solution-processed method. The resulting transistor exhibited a relatively large ON/OFF ratio of 103 in both n- and p-type regions, and tunable photoconductivity after light illumination, particularly with green light. The photo-generated carriers could be effectively trapped under the gate bias, indicating its potential application in mimicking synaptic behaviors. Furthermore, the synaptic plasticity, including volatile/non−volatile and excitatory/inhibitory characteristics, could be finely modulated by electrical and optical stimuli. These optoelectronic reconfigurable properties enable the realization of information light assisted burn after reading. This study not only offers valuable insights for the advancement of high-performance ambipolar organic optoelectronic synaptic transistors but also presents innovative ideas for the future information security access systems.

In this data explosion era, ensuring the secure storage, access, and transmission of information is imperative, encompassing all aspects ranging from safeguarding personal devices to formulating national information security strategies. Leveraging the potential offered by dual-type carriers for transportation and employing optical modulation techniques to develop high reconfigurable ambipolar optoelectronic transistors enables effective implementation of information destruction after reading, thereby guaranteeing data security. In this study, a reconfigurable ambipolar optoelectronic synaptic transistor based on poly (3-hexylthiophene) (P3HT) and poly [[N,N-bis(2-octyldodecyl)-napthalene-1,4,5,8-bis(dicarboximide)-2,6-diyl]-alt-5,5′-(2,2′-bithiophene)] (N2200) blend film was fabricated through solution-processed method. The resulting transistor exhibited a relatively large ON/OFF ratio of 103 in both n- and p-type regions, and tunable photoconductivity after light illumination, particularly with green light. The photo-generated carriers could be effectively trapped under the gate bias, indicating its potential application in mimicking synaptic behaviors. Furthermore, the synaptic plasticity, including volatile/non−volatile and excitatory/inhibitory characteristics, could be finely modulated by electrical and optical stimuli. These optoelectronic reconfigurable properties enable the realization of information light assisted burn after reading. This study not only offers valuable insights for the advancement of high-performance ambipolar organic optoelectronic synaptic transistors but also presents innovative ideas for the future information security access systems.
Optoelectronic memristor based on a-C:Te film for muti-mode reservoir computing
Qiaoling Tian, Kuo Xun, Zhuangzhuang Li, Xiaoning Zhao, Ya Lin, Ye Tao, Zhongqiang Wang, Daniele Ielmini, Haiyang Xu, Yichun Liu
, Available online  
doi: 10.1088/1674-4926/24100008

Optoelectronic memristor is generating growing research interest for high efficient computing and sensing-memory applications. In this work, an optoelectronic memristor with Au/a-C:Te/Pt structure is developed. Synaptic functions, i.e., excitatory post-synaptic current and pair-pulse facilitation are successfully mimicked with the memristor under electrical and optical stimulations. More importantly, the device exhibited distinguishable response currents by adjusting 4-bit input electrical/optical signals. A multi-mode reservoir computing (RC) system is constructed with the optoelectronic memristors to emulate human tactile-visual fusion recognition and an accuracy of 98.7% is achieved. The optoelectronic memristor provides potential for developing multi-mode RC system.

Optoelectronic memristor is generating growing research interest for high efficient computing and sensing-memory applications. In this work, an optoelectronic memristor with Au/a-C:Te/Pt structure is developed. Synaptic functions, i.e., excitatory post-synaptic current and pair-pulse facilitation are successfully mimicked with the memristor under electrical and optical stimulations. More importantly, the device exhibited distinguishable response currents by adjusting 4-bit input electrical/optical signals. A multi-mode reservoir computing (RC) system is constructed with the optoelectronic memristors to emulate human tactile-visual fusion recognition and an accuracy of 98.7% is achieved. The optoelectronic memristor provides potential for developing multi-mode RC system.
Nanowatt-level optoelectronic GaN-based heterostructure artificial synaptic device for associative learning and neuromorphic computing
Teng Zhan, Jianwen Sun, Jin Lin, Banghong Zhang, Guanwan Liao, Zewen Liu, Junxi Wang, Jinmin Li, Xiaoyan Yi
, Available online  
doi: 10.1088/1674-4926/24080049

In recent years, research focusing on synaptic device based on phototransistors has provided a new method for associative learning and neuromorphic computing. A TiO2/AlGaN/GaN heterostructure-based synaptic phototransistor is fabricated and measured, integrating a TiO2 nanolayer gate and a two-dimensional electron gas (2DEG) channel to mimic the synaptic weight and the synaptic cleft, respectively. The maximum drain to source current is 10 nA, while the device is driven at a reverse bias not exceeding −2.5 V. A excitatory postsynaptic current (EPSC) of 200 nA can be triggered by a 365 nm UVA light spike with the duration of 1 s at light intensity of 1.35 μW∙cm−2. Multiple synaptic neuromorphic functions, including EPSC, short-term/long-term plasticity (STP/LTP) and paried-pulse facilitation (PPF), are effectively mimicked by our GaN-based heterostructure synaptic device. In the typical Pavlov’s dog experiment, we demonstrate that the device can achieve "retraining" process to extend memory time through enhancing the intensity of synaptic weight, which is similar to the working mechanism of human brain.

In recent years, research focusing on synaptic device based on phototransistors has provided a new method for associative learning and neuromorphic computing. A TiO2/AlGaN/GaN heterostructure-based synaptic phototransistor is fabricated and measured, integrating a TiO2 nanolayer gate and a two-dimensional electron gas (2DEG) channel to mimic the synaptic weight and the synaptic cleft, respectively. The maximum drain to source current is 10 nA, while the device is driven at a reverse bias not exceeding −2.5 V. A excitatory postsynaptic current (EPSC) of 200 nA can be triggered by a 365 nm UVA light spike with the duration of 1 s at light intensity of 1.35 μW∙cm−2. Multiple synaptic neuromorphic functions, including EPSC, short-term/long-term plasticity (STP/LTP) and paried-pulse facilitation (PPF), are effectively mimicked by our GaN-based heterostructure synaptic device. In the typical Pavlov’s dog experiment, we demonstrate that the device can achieve "retraining" process to extend memory time through enhancing the intensity of synaptic weight, which is similar to the working mechanism of human brain.
Broadband PZT electro-optic modulator
Peng Wang, Hongyan Yu, Yujun Xie, Jie Peng, Chengyang Zhong, Ang Li, Zehao Guan, Jungan Wang, Chen Yang, Yu Han, Feng Qiu, Ming Li
, Available online  
doi: 10.1088/1674-4926/24110019

Visual synapse based on reconfigurable organic photovoltaic cell
Xiangrong Pu, Fan Shu, Qifan Wang, Gang Liu, Zhang Zhang
, Available online  
doi: 10.1088/1674-4926/24080018

The hierarchical and coordinated processing of visual information by the brain demonstrates its superior ability to minimize energy consumption and maximize signal transmission efficiency. Therefore, it is crucial to develop artificial visual synapses that integrate optical sensing and synaptic functions. This study fully leverages the excellent photoresponsivity properties of the PM6 : Y6 system to construct a vertical photo-tunable organic memristor and conducts in-depth research on its resistive switching performance, photodetection capability, and simulation of photo-synaptic behavior, showcasing its excellent performance in processing visual information and simulating neuromorphic behaviors. The device achieves stable and gradual resistance change, successfully simulating voltage-controlled long-term potentiation/depression (LTP/LTD), and exhibits various photo-electric synergistic regulation of synaptic plasticity. Moreover, the device has successfully simulated the image perception and recognition functions of the human visual nervous system. The non-volatile Au/PM6 : Y6/ITO memristor is used as an artificial synapse and neuron modeling, building a hierarchical coordinated processing SLP-CNN cascade neural network for visual image recognition training, its linear tunable photoconductivity characteristic serves as the weight update of the network, achieving a recognition accuracy of up to 93.4%. Compared with the single-layer visual target recognition model, this scheme has improved the recognition accuracy by 19.2%.

The hierarchical and coordinated processing of visual information by the brain demonstrates its superior ability to minimize energy consumption and maximize signal transmission efficiency. Therefore, it is crucial to develop artificial visual synapses that integrate optical sensing and synaptic functions. This study fully leverages the excellent photoresponsivity properties of the PM6 : Y6 system to construct a vertical photo-tunable organic memristor and conducts in-depth research on its resistive switching performance, photodetection capability, and simulation of photo-synaptic behavior, showcasing its excellent performance in processing visual information and simulating neuromorphic behaviors. The device achieves stable and gradual resistance change, successfully simulating voltage-controlled long-term potentiation/depression (LTP/LTD), and exhibits various photo-electric synergistic regulation of synaptic plasticity. Moreover, the device has successfully simulated the image perception and recognition functions of the human visual nervous system. The non-volatile Au/PM6 : Y6/ITO memristor is used as an artificial synapse and neuron modeling, building a hierarchical coordinated processing SLP-CNN cascade neural network for visual image recognition training, its linear tunable photoconductivity characteristic serves as the weight update of the network, achieving a recognition accuracy of up to 93.4%. Compared with the single-layer visual target recognition model, this scheme has improved the recognition accuracy by 19.2%.
Deep-UV-photo-excited synaptic Ga2O3 nano-device with low-energy consumption for neuromorphic computing
Liubin Yang, Xiushuo Gu, Min Zhou, Jianya Zhang, Yonglin Huang, Yukun Zhao
, Available online  
doi: 10.1088/1674-4926/24050037

Synaptic nano-devices have powerful capabilities in logic, memory and learning, making them essential components for constructing brain-like neuromorphic computing systems. Here, we have successfully developed and demonstrated a synaptic nano-device based on Ga2O3 nanowires with low energy consumption. Under 255 nm light stimulation, the biomimetic synaptic nano-device can stimulate various functionalities of biological synapses, including pulse facilitation, peak time-dependent plasticity and memory learning ability. It is found that the artificial synaptic device based on Ga2O3 nanowires can achieve an excellent "learning−forgetting−relearning" functionality. The transition from short-term memory to long-term memory and retention of the memory level after the stepwise learning can attribute to the great relearning functionality of Ga2O3 nanowires. Furthermore, the energy consumption of the synaptic nano-device can be lower than 2.39 × 10‒11 J for a synaptic event. Moreover, our device demonstrates exceptional stability in long-term stimulation and storage. In the application of neural morphological computation, the accuracy of digit recognition exceeds 90% after 12 training sessions, indicating the strong learning capability of the cognitive system composed of this synaptic nano-device. Therefore, our work paves an effective way for advancing hardware-based neural morphological computation and artificial intelligence systems requiring low power consumption.

Synaptic nano-devices have powerful capabilities in logic, memory and learning, making them essential components for constructing brain-like neuromorphic computing systems. Here, we have successfully developed and demonstrated a synaptic nano-device based on Ga2O3 nanowires with low energy consumption. Under 255 nm light stimulation, the biomimetic synaptic nano-device can stimulate various functionalities of biological synapses, including pulse facilitation, peak time-dependent plasticity and memory learning ability. It is found that the artificial synaptic device based on Ga2O3 nanowires can achieve an excellent "learning−forgetting−relearning" functionality. The transition from short-term memory to long-term memory and retention of the memory level after the stepwise learning can attribute to the great relearning functionality of Ga2O3 nanowires. Furthermore, the energy consumption of the synaptic nano-device can be lower than 2.39 × 10‒11 J for a synaptic event. Moreover, our device demonstrates exceptional stability in long-term stimulation and storage. In the application of neural morphological computation, the accuracy of digit recognition exceeds 90% after 12 training sessions, indicating the strong learning capability of the cognitive system composed of this synaptic nano-device. Therefore, our work paves an effective way for advancing hardware-based neural morphological computation and artificial intelligence systems requiring low power consumption.
Electropolymerized dopamine-based memristors using threshold switching behaviors for artificial current-activated spiking neurons
Bowen Zhong, Xiaokun Qin, Zhexin Li, Yiqiang Zheng, Lingchen Liu, Zheng Lou, Lili Wang
, Available online  
doi: 10.1088/1674-4926/24070007

Memristors have a synapse-like two-terminal structure and electrical properties, which are widely used in the construction of artificial synapses. However, compared to inorganic materials, organic materials are rarely used for artificial spiking synapses due to their relatively poor memrisitve performance. Here, for the first time, we present an organic memristor based on an electropolymerized dopamine-based memristive layer. This polydopamine-based memristor demonstrates the improvements in key performance, including a low threshold voltage of 0.3 V, a thin thickness of 16 nm, and a high parasitic capacitance of about 1 μF∙mm−2. By leveraging these properties in combination with its stable threshold switching behavior, we construct a capacitor-free and low-power artificial spiking neuron capable of outputting the oscillation voltage, whose spiking frequency increases with the increase of current stimulation analogous to a biological neuron. The experimental results indicate that our artificial spiking neuron holds potential for applications in neuromorphic computing and systems.

Memristors have a synapse-like two-terminal structure and electrical properties, which are widely used in the construction of artificial synapses. However, compared to inorganic materials, organic materials are rarely used for artificial spiking synapses due to their relatively poor memrisitve performance. Here, for the first time, we present an organic memristor based on an electropolymerized dopamine-based memristive layer. This polydopamine-based memristor demonstrates the improvements in key performance, including a low threshold voltage of 0.3 V, a thin thickness of 16 nm, and a high parasitic capacitance of about 1 μF∙mm−2. By leveraging these properties in combination with its stable threshold switching behavior, we construct a capacitor-free and low-power artificial spiking neuron capable of outputting the oscillation voltage, whose spiking frequency increases with the increase of current stimulation analogous to a biological neuron. The experimental results indicate that our artificial spiking neuron holds potential for applications in neuromorphic computing and systems.
Colloidal synthesis of lead chalcogenide/lead chalcohalide core/shell nanostructures and structural evolution
Yang Liu, Kunyuan Lu, Yujie Zhu, Xudong Hu, Yusheng Li, Guozheng Shi, Xingyu Zhou, Lin Yuan, Xiang Sun, Xiaobo Ding, Irfan Ullah Muhammad, Qing Shen, Zeke Liu, Wanli Ma
, Available online  
doi: 10.1088/1674-4926/24050026

Lead chalcohalides (PbYX, X = Cl, Br, I; Y = S, Se) is an extension of the classic Pb chalcogenides (PbY). Constructing the heterogeneous integration with PbYX and PbY material systems makes it possible to achieve significantly improved optoelectronic performance. In this work, we studied the effect of introducing halogen precursors on the structure of classical PbS nanocrystals (NCs) during the synthesis process and realized the preparation of PbS/Pb3S2X2 core/shell structure for the first time. The core/shell structure can effectively improve their optical properties. Furthermore, our approach enables the synthesis of Pb3S2Br2 that had not yet been reported. Our results not only provide valuable insights into the heterogeneous integration of PbYX and PbY materials to elevate material properties but also provide an effective method for further expanding the preparation of PbYX material systems.

Lead chalcohalides (PbYX, X = Cl, Br, I; Y = S, Se) is an extension of the classic Pb chalcogenides (PbY). Constructing the heterogeneous integration with PbYX and PbY material systems makes it possible to achieve significantly improved optoelectronic performance. In this work, we studied the effect of introducing halogen precursors on the structure of classical PbS nanocrystals (NCs) during the synthesis process and realized the preparation of PbS/Pb3S2X2 core/shell structure for the first time. The core/shell structure can effectively improve their optical properties. Furthermore, our approach enables the synthesis of Pb3S2Br2 that had not yet been reported. Our results not only provide valuable insights into the heterogeneous integration of PbYX and PbY materials to elevate material properties but also provide an effective method for further expanding the preparation of PbYX material systems.