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Photonic reservoir computing (RC) is a simple and efficient neuromorphic computing framework for human cortical circuits, which is featured with fast training speed and low training cost. Photonic time delay RC, as a simple hardware implementation method of RC, has attracted widespread attention. In this paper, we present and experimentally demonstrate a time delay RC system based on a Fabry Perot (FP) laser for multiple tasks processing. Here, the various tasks are attempted to perform in parallel in the multiple longitudinal modes of the FP laser. It is found that the time delay RC system based on the FP laser can successfully handle different tasks across multiple longitudinal modes simultaneously. The experimental results demonstrate the potential of the time delay RC system based on the FP laser to achieve multiple tasks processing, providing various possibilities for improving the information processing ability of neural morphology RC systems, and promoting the development of RC systems.

Undesired ice accumulation can lead to serious negative impacts on daily life and equipment safety. Slippery liquid-infused surfaces (SLISs) have been widely studied for their low ice adhesion strength (τ ice ). However, the lack of durability, weak robustness, and complex preparation process hinder the application of SLISs. In this work, robust oil-infused porous surface (RIPS) was obtained by a facile one-step method, which used epoxy resin (E44) as a substrate and contained fumed silica and silicone oil. The RIPS-6 displays outstanding anti-icing/deicing ability, superior liquid repellency, good self-cleaning performance, and excellent mechanical robustness. At −5 °C, the water droplet remained unfrozen after 7200 s. τ ice was only 6.9 kPa at −20 °C and remained below 15 kPa during 10 icing cycles. Furthermore, the mixture of E44 and fumed silica enhanced the mechanical properties including the hardness (4 H) and abrasion resistance of RIPS-6. The icephobicity can be remained (τice < 40 kPa) even after 150 cycles of sandpaper abrasion at 2.5 kPa. The anti-icing and deicing coating with excellent mechanical stability and durability significantly improves the practical application possibility of the coating in harsh environments. [ABSTRACT FROM AUTHOR]

Photonic neuromorphic computing has emerged as a promising avenue toward building a high-speed, low-latency, and energy-efficient non-von-Neumann computing system. Photonic spiking neural network (PSNN) exploits brain-like spatiotemporal processing to realize high-performance neuromorphic computing. Linear weighting and nonlinear spiking activation are two fundamental functions of a SNN. However, the nonlinear computation of PSNN remains a significant challenge. Therefore, this perspective focuses on the nonlinear computation of photonic spiking neurons, including numerical simulation, device fabrication, and experimental demonstration. Different photonic spiking neurons are considered, such as vertical-cavity surface-emitting lasers, distributed feedback (DFB) lasers, Fabry–Pérot (FP) lasers, or semiconductor lasers embedded with saturable absorbers (SAs) (e.g., FP-SA and DFB-SA). PSNN architectures, including fully connected and convolutional structures, are developed, and supervised and unsupervised learning algorithms that take into account optical constraints are introduced to accomplish specific applications. This work covers devices, architectures, learning algorithms, and applications for photonic and optoelectronic neuromorphic computing and provides our perspective on the challenges and prospects of photonic neuromorphic computing based on semiconductor lasers. [ABSTRACT FROM AUTHOR]

S-scheme possesses superior redox capabilities compared with the II-scheme, providing an effective method to solve the innate defects of g-C3N4 (CN). In this study, S-doped g-C3N4/g-C3N4 (SCN-tm/CN) S-scheme homojunction was constructed by rationally integrating morphology control with interfacial engineering to enhance the photocatalytic hydrogen evolution performance. In-situ Kelvin probe force microscopy (KPFM) confirms the transport of photo-generated electrons from CN to SCN. Density functional theory (DFT) calculations reveal that the generation of a built-in electric field between SCN and CN enables the carrier separation to be more efficient and effective. Femtosecond transient absorption spectrum (fs-TAS) indicates prolonged lifetimes of SCN-tm/CN3 (τ1: 9.7, τ2: 110, and τ3: 1343.5 ps) in comparison to those of CN (τ1: 4.86, τ2: 55.2, and τ3: 927 ps), signifying that the construction of homojunction promotes the separation and transport of electron hole pairs, thus favoring the photocatalytic process. Under visible light irradiation, the optimized SCN-tm/CN3 exhibits excellent photocatalytic activity with the hydrogen evolution rate of 5407.3 µmol·g−1·h−1, which is 20.4 times higher than that of CN (265.7 µmol·g−1·h−1). Moreover, the homojunction also displays an apparent quantum efficiency of 26.8% at 435 nm as well as ultra-long and ultra-stable cycle ability. This work offers a new strategy to construct highly efficient photocatalysts based on the metal-free conjugated polymeric CN for realizing solar energy conversion. [ABSTRACT FROM AUTHOR]