Realization of remote wearable health monitoring (RWHM) technology for the flexible photodiodes is highly desirable in remote-sensing healthcare systems used in space stations, oceans, and forecasting warning, which demands high external quantum efficiency (EQE) and detectivity in NIR region. Traditional inorganic photodetectors (PDs) are mechanically rigid and expensive while the widely reported solution-processed mixed tin-lead (MSP) perovskite photodetectors (PPDs) exhibit a trade-off between EQE and detectivity in the NIR region. Herein, a novel functional passivating antioxidant (FPA) strategy has been introduced for the first time to simultaneously improve crystallization, restrain Sn 2+ oxidization, and reduce defects in MSP perovskite films by multiple interactions between thiophene-2-carbohydrazide (TAH) molecules and cations/anions in MSP perovskite. The resultant solution-processed rigid mixed Sn-Pb PPD simultaneously achieves high EQE (75.4% at 840 nm), detectivity (1.8 × 10 12 Jones at 840 nm), ultrafast response time (t rise /t fall = 94 ns/97 ns), and improved stability. This work also highlights the demonstration of the first flexible photodiode using MSP perovskite and FPA strategy with remarkably high EQE (75% at 840 nm), and operational stability. Most importantly, the RWHM is implemented for the first time in the PIN MSP perovskite photodiodes to remotely monitor the heart rate of humans at rest and after-run conditions.

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Visible light communication (VLC) is a highly promising complement to conventional wireless communication for local-area networking in future 6G. However, the extra electro-optical and photoelectric conversions in VLC systems usually introduce exceeding complexity to communication channels, in particular severe nonlinearities. Artificial intelligence (AI) techniques are investigated to overcome the unique challenges in VLC, whereas considerable obstacles are found in practical VLC systems applied with intelligent learning approaches. In this paper, we present a comprehensive study of the intelligent physical and network layer technologies for AI-empowered intelligent VLC (IVLC). We first depict a full model of the visible light channel and discuss its main challenges. The advantages and disadvantages of machine learning in VLC are discussed and analyzed by simulation. We then present a detailed overview of advances in intelligent physical layers, including optimal coding, channel emulator, MIMO, channel equalization, and optimal decision. Finally, we envision the prospects of IVLC in both the intelligent physical and network layers. This article lays out a roadmap for developing machine learning-based intelligent visible light communication in 6G.

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Visible light communication (VLC) has emerged as a promising communication method in 6G. However, the development of receiving devices is much slower than that of transmitting devices, limited by materials, structures, and fabrication. In this paper, we propose and fabricate an InGaN/GaN multiple-quantum-well-based vertical-structure micro-LED-based photodetector (μPD) on a Si substrate. A comprehensive comparison of the photoelectrical performance and communication performance of three sizes of μPDs, 10, 50, and 100 μm, is presented. The peak responsivity of all three μPDs is achieved at 400 nm, while the passband full-widths at half maxima are 87, 72, and 78 nm for 10, 50, and 100 μm μPDs, respectively. The − 20    dB cutoff bandwidth is up to 822 MHz for 50 μm μPD. A data rate of 10.14 Gbps is experimentally demonstrated by bit and power loading discrete multitone modulation and the proposed digital pre-equalizer algorithm over 1 m free space utilizing the self-designed 4 × 4 50 μm μPD array as a receiver and a 450 nm laser diode as a transmitter. This is the first time a more than 10 Gbps VLC system has been achieved utilizing a GaN-based micro-PD, to the best of our knowledge. The investigation fully demonstrates the superiority of Si substrates and vertical structures in InGaN/GaN μPDs and shows its great potential for high-speed VLC links beyond 10 Gbps.