High‐Bandwidth InGaAs Photodetectors Heterogeneously Integrated on Silicon Waveguides Using Optofluidic Assembly

Exploring the extraordinary optoelectronic properties of two‐dimensional (2D) materials to construct advanced optoelectronic devices is a major goal for academic researchers and industrialists. Emerging 2D Janus materials are the innovative class of 2D materials in which two sides are either asymmetrical functionalized or exposed to different environments. Distinctive features of Janus 2D materials such as tunable bandgaps, electronic structures, the presence of Rashba effects, excitonic effects, piezoelectric effects etc. make its magnificent candidates for optoelectronic devices. The van der Waals (vdWs) heterostructure with novel properties assembled by Janus 2D materials and low dimensional materials provides new opportunities and promising applications. This review aims to offer the recent advances in the Janus 2D materials and inside mechanism in 2D Janus vdWs heterostructure from an optoelectronics point of view. Here, the latest progress in the Janus 2D materials including their vdWs heterostructures from the perspective of theoretical prediction, and synthesis techniques is presented. The investigation of their physical optoelectronics properties and optoelectronic device applications is summarized. Finally, the future directions, challenges, and opportunities regarding the research process of Janus 2D materials and their vdWs heterostructure are discussed for designing promising optoelectronic devices.

Janus 2D Transition Metal Dichalcogenides: Research Progress, Optical Mechanism and Future Prospects for Optoelectronic Devices

Ahmad,

Wang,

Kazmi

et al. 2024

Self‐Excited Free‐Standing VO₂ Film for Infrared Optical Limiter

Zhao,

Li,

Zhu

et al. 2024

Effective optical limiters (OLs) are necessary devices for the protection of various sensitive photo‐detectors, cameras, infrared sensors, or even the human eyes once encountering unexpected high‐intensity illumination or laser blinding attacks. Vanadium dioxide (VO2) shows pronounced infrared switching behavior across the phase transition, which is considered as an idea optical limiter for broad‐band infrared laser protection. However, the self‐adapting optical limiter function based on VO2 is quite difficult to realize since the open‐state absorptance of the VO2 layer is always very low, which makes the laser irradiation cannot trigger the phase transition quickly. In the current study, a self‐excited VO2 infrared optical limiter is proposed, which is integrated by a transferred VO2 layer, InGaAs micro/nano wires, and a local heater. Based on the“optical response–electric heating” strategy, the phase transition of VO2 layer can be quickly triggered once the incident laser beam intensity exceeds the pre‐set threshold value. In addition, this integrated device has an excellent switching ratio, flexible controllability, and stability. This work achieves a practical VO2 optical limiter device and provides a promising strategy for developing VO2‐based integrated multifunctional devices in the future.

Artificial‐Intelligence‐Enhanced Mid‐infrared Lab‐on‐a‐Chip for Mixture Spectroscopy Analysis

Zhou,

Liu,

Zhou

et al. 2024

Bio/chemical mixture sensing in a water environment is of great importance in sensing applications. Relying on plentiful molecular fingerprints in mid‐infrared (MIR) and high integration potential, nanophotonic waveguide‐based MIR lab‐on‐a‐chip (LoC) provides a miniaturized and versatile solution for specific and label‐free bio/chemical detection. However, it is still challenging to implement an MIR LoC with on‐chip photodetection for chemical sensing in water, due to the strong MIR water absorption and limited MIR on‐chip photodetector scheme, let alone the spectral overlap issue in mixture analysis. Here, a MIR LoC integrating zero‐bias graphene photodetector is reported and the real‐time monitoring of three analytes in water leveraging the MIR LoC is demonstrated. Besides, using machine learning, the on‐chip collected spectra of the ternary mixture in water with 27 mixing ratios are successfully classified with an accuracy of 95.77%. Moreover, concentration prediction of individual analytes in a mixture is performed by developing a convolution regression network for mixture spectrum decomposition: 83.33% of the single‐component concentration predictions are within the 1 vol% error range, and an average root‐mean‐squared error of 1 vol% for mixture concentration predictions is achieved. The MIR LoC offers new opportunities for highly integrated intelligent sensing systems in various sensing scenarios in the Internet of Things era.