Use of Optoelectronic Systems for the Analysis of Technique in Trials

Optoelectronic systems represent the gold standard of technologies used in the motion analysis for the evaluation of kinematics. Trials, a specialty of mountain biking, differ a lot from other cycling specialties, because in addition to pedaling, they require jumping techniques to overcome obstacles that involve the whole body. In this sport, more than in others, the evaluation of technical movements using optoelectronic systems goes far beyond simply assessing the biomechanics of pedaling or the correct positioning on the bike. Starting from a previous study conducted with video analysis technique applied to the lateral jumping technique, two versions of this technique were compared, considering the kinematics of the act, taking into account both the data relating the subject and the bicycle. The joint angles of the lower limbs and the angles described by the bicycle on the three space plane were considered. The major differences have been found in the ＂leap over＂ phase, about the bending of the lower limbs and the angles described by the bicycle.

Recent advances in soft electronic materials for intrinsically stretchable optoelectronic systems

In recent years,significant progress has been achieved in the design and fabrication of stretchable optoelectronic devices.In general,stretchability has been achieved through geometrical modifications of device components,such as with serpentine interconnects or buckled substrates.However,the local stiffness of individual pixels and the limited pixel density of the array have impeded further advancements in stretchable optoelectronics.Therefore,intrinsically stretch-able optoelectronics have been proposed as an alternative approach.Herein,we review the recent advances in soft elec-tronic materials for application in intrinsically stretchable optoelectronic devices.First,we introduce various intrinsically stretchable electronic materials,comprised of electronic fillers,elastomers,and surfactants,and exemplify different in-trinsically stretchable conducting and semiconducting composites.We also describe the processing methods used to fabricate the electrodes,interconnections,charge transport layers,and optically active layers used in intrinsically stretch-able optoelectronic devices.Subsequently,we review representative examples of intrinsically stretchable optoelectronic devices,including light-emitting capacitors,light-emitting diodes,photodetectors,and photovoltaics.Finally,we briefly discuss intrinsically stretchable integrated optoelectronic systems.

Fully implantable and battery-free wireless optoelectronic system for modulable cancer therapy and real-time monitoring

Photodynamic therapy(PDT)is attracting attention as a next-generation cancer treatment that can selectively destroy malignant tissues,exhibit fewer side effects,and lack pain during treatments.Implantable PDT systems have recently been developed to resolve the issues of bulky and expensive conventional PDT systems and to implement continuous and repetitive treatment.Existing implantable PDT systems,however,are not able to perform multiple functions simultaneously,such as modulating light intensity,measuring,and transmitting tumor-related data,resulting in the complexity of cancer treatment.Here,we introduce a flexible and fully implantable wireless optoelectronic system capable of continuous and effective cancer treatment by fusing PDT and hyperthermia and enabling tumor size monitoring in real-time.This system exploits micro inorganic light-emitting diodes(μ-LED)that emit light with a wavelength of 624 nm,designed not to affect surrounding normal tissues by utilizing a fully programmable light intensity ofμ-LED and precisely monitoring the tumor size by Si phototransistor during a long-term implantation(2–3 weeks).The superiority of simultaneous cancer treatment and tumor size monitoring capabilities of our system operated by wireless power and data transmissions with a cell phone was confirmed through in vitro experiments,ray-tracing simulation results,and a tumor xenograft mouse model in vivo.This all-in-one single system for cancer treatment offers opportunities to not only enable effective treatment of tumors located deep in the tissue but also enable precise and continuous monitoring of tumor size in real-time.

Optoelectronic Synapses Based on MXene/Violet Phosphorus van der Waals Heterojunctions for Visual‑Olfactory Crossmodal Perception

The crossmodal interaction of different senses,which is an important basis for learning and memory in the human brain,is highly desired to be mimicked at the device level for developing neuromorphic crossmodal perception,but related researches are scarce.Here,we demonstrate an optoelectronic synapse for vision-olfactory crossmodal perception based on MXene/violet phosphorus(VP)van der Waals heterojunctions.Benefiting from the efficient separation and transport of photogenerated carriers facilitated by conductive MXene,the photoelectric responsivity of VP is dramatically enhanced by 7 orders of magnitude,reaching up to 7.7 A W^(−1).Excited by ultraviolet light,multiple synaptic functions,including excitatory postsynaptic currents,pairedpulse facilitation,short/long-term plasticity and“learning-experience”behavior,were demonstrated with a low power consumption.Furthermore,the proposed optoelectronic synapse exhibits distinct synaptic behaviors in different gas environments,enabling it to simulate the interaction of visual and olfactory information for crossmodal perception.This work demonstrates the great potential of VP in optoelectronics and provides a promising platform for applications such as virtual reality and neurorobotics.

Tailoring Classical Conditioning Behavior in TiO_(2) Nanowires:ZnO QDs-Based Optoelectronic Memristors for Neuromorphic Hardware

Neuromorphic hardware equipped with associative learn-ing capabilities presents fascinating applications in the next generation of artificial intelligence.However,research into synaptic devices exhibiting complex associative learning behaviors is still nascent.Here,an optoelec-tronic memristor based on Ag/TiO_(2) Nanowires:ZnO Quantum dots/FTO was proposed and constructed to emulate the biological associative learning behaviors.Effective implementation of synaptic behaviors,including long and short-term plasticity,and learning-forgetting-relearning behaviors,were achieved in the device through the application of light and electrical stimuli.Leveraging the optoelectronic co-modulated characteristics,a simulation of neuromorphic computing was conducted,resulting in a handwriting digit recognition accuracy of 88.9%.Furthermore,a 3×7 memristor array was constructed,confirming its application in artificial visual memory.Most importantly,complex biological associative learning behaviors were emulated by mapping the light and electrical stimuli into conditioned and unconditioned stimuli,respectively.After training through associative pairs,reflexes could be triggered solely using light stimuli.Comprehen-sively,under specific optoelectronic signal applications,the four features of classical conditioning,namely acquisition,extinction,recovery,and generalization,were elegantly emulated.This work provides an optoelectronic memristor with associative behavior capabilities,offering a pathway for advancing brain-machine interfaces,autonomous robots,and machine self-learning in the future.

Predictive Control of Optoelectronic Tracking System

Aim To solve the time delay problem in the optoelectronic tracking system, improving the tracking accuracy. Methods The discount least square algorithm was applied to forecast the tracking error caused by the 40?ms delay, and the predicting algorithm was improved by the adaptive discount method.Results The tracking errors of the two methods were compared, and an optimal controller with the improved adaptive discount predicting algorithm was adopted for simulation. Conclusion The predicting algorithms, especially the adaptive discount predicting algorithm, can decrease the tracking error greatly, and the desired tracking prediction can be achieved both in the transient state and in the steady state.

Optoelectronic Detecting System for Inner Walls of Pipes

This paper is concerned with a high characteristic image processing and recognition system that is used for inspecting real-time blemishes, streaks and cracks on the inner walls of high accuracy pipes. As a regular detector, the BP neural network is used for extracting features of the image inspected and classifying these images, it takes fully advantage of the function of artificial neural network, such as the information distributed memory, large scale self-adapting parallel processing, high fault-tolerant ability and so forth. Besides, an improved BP algorithm is used in the system for training the network, and making the learning procedure of the net converges to the minimum of overall situation at high rate.

Manufacturing of graphene based synaptic devices for optoelectronic applications

Neuromorphic computing systems can perform memory and computing tasks in parallel on artificial synaptic devices through simulating synaptic functions,which is promising for breaking the conventional von Neumann bottlenecks at hardware level.Artificial optoelectronic synapses enable the synergistic coupling between optical and electrical signals in synaptic modulation,which opens up an innovative path for effective neuromorphic systems.With the advantages of high mobility,optical transparency,ultrawideband tunability,and environmental stability,graphene has attracted tremendous interest for electronic and optoelectronic applications.Recent progress highlights the significance of implementing graphene into artificial synaptic devices.Herein,to better understand the potential of graphene-based synaptic devices,the fabrication technologies of graphene are first presented.Then,the roles of graphene in various synaptic devices are demonstrated.Furthermore,their typical optoelectronic applications in neuromorphic systems are reviewed.Finally,outlooks for development of synaptic devices based on graphene are proposed.This review will provide a comprehensive understanding of graphene fabrication technologies and graphene-based synaptic device for optoelectronic applications,also present an outlook for development of graphene-based synaptic device in future neuromorphic systems.

Organic Optoelectronic Synapses for Sound Perception

The neuromorphic systems for sound perception is under highly demanding for the future bioinspired electronics and humanoid robots.However,the sound perception based on volume,tone and timbre remains unknown.Herein,organic optoelectronic synapses(OOSs)are constructed for unprecedented sound recognition.The volume,tone and timbre of sound can be regulated appropriately by the input signal of voltages,frequencies and light intensities of OOSs,according to the amplitude,frequency,and waveform of the sound.The quantitative relation between recognition factor(ζ)and postsynaptic current(I=I_(light)−I_(dark))is established to achieve sound perception.Interestingly,the bell sound for University of Chinese Academy of Sciences is recognized with an accuracy of 99.8%.The mechanism studies reveal that the impedance of the interfacial layers play a critical role in the synaptic performances.This contribution presents unprecedented artificial synapses for sound perception at hardware levels.

Preparation and promising optoelectronic applications of lead halide perovskite patterned structures:A review

Lead halide perovskites have received considerable attention from researchers over the past several years due to their superior optical and optoelectronic properties,because of which they can be a versatile platform for fundamental science research and applications.Patterned structures based on lead halide perovskites have much more novel properties compared with their more commonly seen bulk-,micro-,and nano-crystals,such as improvement in antireflection,light-scattering effects,and light absorption,as a result of their adjustability of spatial distributions.However,there are many challenges yet to be resolved in this field,such as insufficient patterned resolution,imperfect crystal quality,complicated preparation process,and so on.To pave the way to solve these problems,we provide a systematic presentation of current methods for fabricating lead halide perovskite patterned structures,including thermal imprint,use of etching films,two-step vapor-phase growth,template-confined solution growth,and seed-assisted growth.Furthermore,the advantages and disadvantages of these methods are elaborated in detail.In addition,thanks to the extraordinary properties of lead halide perovskite patterned structures,a variety of potential applications in optics and optoelectronics of these structures are described.Lastly,we put forward existing challenges and prospects in this exciting field.

Patterning of Metal Halide Perovskite Thin Films and Functional Layers for Optoelectronic Applications

In recent years,metal halide perovskites have received significant attention as materials for next-generation optoelectronic devices owing to their excellent optoelectronic properties.The unprecedented rapid evolution in the device performance has been achieved by gaining an advanced understanding of the composition,crystal growth,and defect engineering of perovskites.As device performances approach their theoretical limits,effective optical management becomes essential for achieving higher efficiency.In this review,we discuss the status and perspectives of nano to micron-scale patterning methods for the optical management of perovskite optoelectronic devices.We initially discuss the importance of effective light harvesting and light outcoupling via optical management.Subsequently,the recent progress in various patterning/texturing techniques applied to perovskite optoelectronic devices is summarized by categorizing them into top-down and bottom-up methods.Finally,we discuss the perspectives of advanced patterning/texturing technologies for the development and commercialization of perovskite optoelectronic devices.

Optoelectronic oscillator-based interrogation system for Michelson interferometric sensors

High-performance interrogation systems for optical fiber sensors are extensively required for environmental condition monitoring applications.In this article,we propose and demonstrate a Michelson interferometer(MI)interrogation system based on an optoelectronic oscillator(OEO).The frequency of the OEO is related to the free spectral range(FSR)of the MI.Thus,when the FSR of the MI varies with a change in external physical factors,the frequency of the OEO shifts and can be used for interrogation.We demonstrate that the temperature sensitivity and interrogation resolution are 35.35 MHz/℃and 0.012℃,respectively.Such an OEO-based scheme enables wavelength-to-frequency mapping and promises a wide linear interrogation range,high resolution and high-speed interrogation.

Amorphous gallium oxide homojunction-based optoelectronic synapse for multi-functional signal processing

In the era of accelerated development in artificial intelligence as well as explosive growth of information and data throughput,underlying hardware devices that can integrate perception and memory while simultaneously offering the bene-fits of low power consumption and high transmission rates are particularly valuable.Neuromorphic devices inspired by the human brain are considered to be one of the most promising successors to the efficient in-sensory process.In this paper,a homojunction-based multi-functional optoelectronic synapse(MFOS)is proposed and testified.It enables a series of basic electri-cal synaptic plasticity,including paired-pulse facilitation/depression(PPF/PPD)and long-term promotion/depression(LTP/LTD).In addition,the synaptic behaviors induced by electrical signals could be instead achieved through optical signals,where its sen-sitivity to optical frequency allows the MFOS to simulate high-pass filtering applications in situ and the perception capability integrated into memory endows it with the information acquisition and processing functions as a visual system.Meanwhile,the MFOS exhibits its performances of associative learning and logic gates following the illumination with two different wave-lengths.As a result,the proposed MFOS offers a solution for the realization of intelligent visual system and bionic electronic eye,and will provide more diverse application scenarios for future neuromorphic computing.

Experimental verification of nanonization enhanced solubility for poorly soluble optoelectronic molecules

Solubility enhancement has been a priority to overcome poor solubility with optoelectronic molecules for solution-processable devices. This study aims to obtain experimental data on the effect of particle sizes on the solubility properties of several typical optoelectronic molecules in organic solvents, including the solubility results of 1,3-bis(9-carbazolyl)benzene(m CP), 1,3,5-tris(1-phenyl-1H-benzimidazol-2-yl)ben zene(TPBi) and 2-(4-tert-butylphenyl)-5-(4-biphenyl)-1,3,4-oxadiazole(PBD) in ethanol and acetonitrile,respectively. Nanoparticles of m CP, TPBi and PBD with sizes from dozens to several hundred nanometers were prepared by solvent antisolvent precipitation method and their solubility were determined by using isothermal saturation method. The saturation solubility of nanoparticles of three kinds of optoelectronic molecules exhibited increase of 12.9%-25.7% in comparison to the same raw materials in the form of microparticles. The experimental evidence indicates that nanonization technology is a feasible way to make optoelectronic molecules dissolve in liquids with enhanced solubility.

Applications and potentials of machine learning in optoelectronic materials research:An overview and perspectives

Optoelectronic materials are essential for today's scientific and technological development,and machine learning provides new ideas and tools for their research.In this paper,we first summarize the development history of optoelectronic materials and how materials informatics drives the innovation and progress of optoelectronic materials and devices.Then,we introduce the development of machine learning and its general process in optoelectronic materials and describe the specific implementation methods.We focus on the cases of machine learning in several application scenarios of optoelectronic materials and devices,including the methods related to crystal structure,properties(defects,electronic structure)research,materials and devices optimization,material characterization,and process optimization.In summarizing the algorithms and feature representations used in different studies,it is noted that prior knowledge can improve optoelectronic materials design,research,and decision-making processes.Finally,the prospect of machine learning applications in optoelectronic materials is discussed,along with current challenges and future directions.This paper comprehensively describes the application value of machine learning in optoelectronic materials research and aims to provide reference and guidance for the continuous development of this field.

Two-dimensional silicon nanomaterials for optoelectronics

Silicon nanomaterials have been of immense interest in the last few decades due to their remarkable optoelectronic responses,elemental abundance,and higher biocompatibility.Two-dimensional silicon is one of the new allotropes of silicon and has many compelling properties such as quantum-confined photoluminescence,high charge carrier mobilities,anisotropic electronic and magnetic response,and non-linear optical properties.This review summarizes the recent advances in the synthesis of two-dimensional silicon nanomaterials with a range of structures(silicene,silicane,and multilayered silicon),surface ligand engineering,and corresponding optoelectronic applications.

Multilevel optoelectronic hybrid memory based on N-doped Ge_(2)Sb_(2)Te_(5)film with low resistance drift and ultrafast speed

Multilevel phase-change memory is an attractive technology to increase storage capacity and density owing to its high-speed,scalable and non-volatile characteristics.However,the contradiction between thermal stability and operation speed is one of key factors to restrain the development of phase-change memory.Here,N-doped Ge_(2)Sb_(2)Te_(5)-based optoelectronic hybrid memory is proposed to simultaneously implement high thermal stability and ultrafast operation speed.The picosecond laser is adopted to write/erase information based on reversible phase transition characteristics whereas the resistance is detected to perform information readout.Results show that when N content is 27.4 at.%,N-doped Ge_(2)Sb_(2)Te_(5)film possesses high ten-year data retention temperature of 175℃and low resistance drift coefficient of 0.00024 at 85℃,0.00170 at 120℃,and 0.00249 at 150℃,respectively,owing to the formation of Ge–N,Sb–N,and Te–N bonds.The SET/RESET operation speeds of the film reach 520 ps/13 ps.In parallel,the reversible switching cycle of the corresponding device is realized with the resistance ratio of three orders of magnitude.Four-level reversible resistance states induced by various crystallization degrees are also obtained together with low resistance drift coefficients.Therefore,the N-doped Ge_(2)Sb_(2)Te_(5)thin film is a promising phase-change material for ultrafast multilevel optoelectronic hybrid storage.

W-doped In_(2)O_(3) nanofiber optoelectronic neuromorphic transistors with synergistic synaptic plasticity

Neuromorphic devices that mimic the information processing function of biological synapses and neurons have attracted considerable attention due to their potential applications in brain-like perception and computing. In this paper,neuromorphic transistors with W-doped In_(2)O_(3)nanofibers as the channel layers are fabricated and optoelectronic synergistic synaptic plasticity is also investigated. Such nanofiber transistors can be used to emulate some biological synaptic functions, including excitatory postsynaptic current(EPSC), long-term potentiation(LTP), and depression(LTD). Moreover, the synaptic plasticity of the nanofiber transistor can be synergistically modulated by light pulse and electrical pulse.At last, pulsed light learning and pulsed electrical forgetting behaviors were emulated in 5×5 nanofiber device array.Our results provide new insights into the development of nanofiber optoelectronic neuromorphic devices with synergistic synaptic plasticity.

Preface to Special Issue on Towards High Performance Ga_(2)O_(3) Electronics:Power Devices and DUV Optoelectronic Devices(Ⅱ)

Gallium oxide(Ga_(2)O_(3))has garnered world-wide atten-tion as an ultrawide-bandgap semiconductor material from the area of power electronics and DUV optical devices benefit-ing from its outstanding electronic and optoelectronic proper-ties.For one thing,since Ga_(2)O_(3)features high critical break-down field of 8 MV/cm and Baliga’s figure of merit(BFOM)of 3444,it is a promising candidate for advanced high-power applications.For another thing,due to the bandgap directly corresponding to the deep-ultraviolet(DUV)region,Ga_(2)O_(3)is widely used in DUV optoelectronic devices.

Comparative Performance Analysis of MAPbI3 and FAPbI3 Perovskites: Study of Optoelectronic Properties and Stability

The exploitation of fossil resources to meet humanity’s energy needs is the root cause of the climate warming phenomenon facing the planet. In this context, non-carbon-based energies, such as photovoltaic energy, are identified as crucial solutions. Organic perovskites MAPbI3 and FAPbI3, characterized by their abundance, low cost, and ease of synthesis, are emerging as candidates for study to enhance their competitiveness. It is within this framework that this article presents a comparative analysis of the performances of MAPbI3 and FAPbI3 perovskites in the context of photovoltaic devices. The analysis focuses on the optoelectronic characteristics and stability of these high-potential materials. The optical properties of perovskites are rigorously evaluated, including band gaps, photoluminescence, and light absorption, using UV-Vis spectroscopy and photoluminescence techniques. The crystal structure is characterized by X-ray diffraction, while film morphology is examined through scanning electron microscopy. The results reveal significant variations between the two types of perovskites, directly impacting the performance of resulting solar devices. Simultaneously, the stability of perovskites is subjected to a thorough study, exposing the materials to various environmental conditions, highlighting key determinants of their durability. Films of MAPbI3 and FAPbI3 demonstrate distinct differences in terms of topography, optical performance, and stability. Research has unveiled that planar perovskite solar cells based on FAPbI3 offer higher photoelectric conversion efficiency, surpassing their MAPbI3-based counterparts in terms of performance. These advancements aim to overcome stability constraints and enhance the long-term durability of perovskites, ultimately aiming for practical application of these materials. This comprehensive comparative analysis provides an enlightened understanding of the optoelectronic performance and stability of MAPbI3 and FAPbI3 perovskites, which is critically important to guide future research and development of solar devices that are both more efficient and sustainable.