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Soft matter‐based microlasers are widely regarded as excellent building blocks for realizing photonic interconnected networks in optoelectronic chips, owing to their flexibility and functional network topology. However, the potential of these devices is hindered by challenges such as poor lasing stability, high lasing threshold, and gaps in knowledge regarding cavity interconnection characteristics. In this study, the first demonstration of a high‐quality, low‐threshold nanoplatelets (NPLs)‐based polymer microfiber laser fabricated using capillary immersion techniques and its photonic interconnected networks are presented. CdSe/CdS@Cd1‐xZnxS core/buffer shell@graded‐shell NPLs with high optical gain characteristics are adopted as the gain medium. The study achieves a lasing threshold below 14.8 µJ cm−2, a single‐mode quality (Q)‐factor of ≈5500, and robust lasing stability in the fabricated NPLs‐based microfibers. Furthermore, the study pioneers the exploration of polygonal self‐coupling microlasers and the optical characteristics of their interconnected fiber network. Based on the signal generation mechanism observed in the photonic networks, an interconnected NPLs‐based fiber network structure achieving single‐mode lasing emission and laser mode modulation is successfully designed. The work contributes a novel method for realizing microlasers fabricated via soft‐matter technologies and provides a key foundation and new insights for unit design and programming for future photonic network systems. [ABSTRACT FROM AUTHOR]

An optical limiter (OL) is a nonlinear device that protects sensitive photodetectors or human eyes from high-intensity illumination. However, current OLs have low open-state transmittance and a limited turndown ratio in some cases. In this study, first it is demonstrated that combining the insulator-to-metal transition (IMT) of vanadium dioxide (VO2) with anti-reflection layers can enable both high and broadband open-state transmittance (>-0.9 dB at the peak wavelength) while preserving a large turndown ratio (>21.8 dB). Furthermore, optothermal simulation is conducted to analyze the performance of the VO2 OL under ultrafast laser irradiation. The result reveals that IMT of the VO2 OL occurs at 0.23 µs when the incident laser intensity is 90 kW cm-2. These benefits offer a promising alternative to OLs in technologies ranging from sensor protection to human eye defense. [ABSTRACT FROM AUTHOR]

Machine learning methods have revolutionized the discovery process of new molecules and materials. However, the intensive training process of neural networks for molecules with ever‐increasing complexity has resulted in exponential growth in computation cost, leading to long simulation time and high energy consumption. Photonic chip technology offers an alternative platform for implementing neural networks with faster data processing and lower energy usage compared to digital computers. Photonics technology is naturally capable of implementing complex‐valued neural networks at no additional hardware cost. Here, the capability of photonic neural networks for predicting the quantum mechanical properties of molecules is demonstrated. To the best of knowledge, this work is the first to harness photonic technology for machine learning applications in computational chemistry and molecular sciences, such as drug discovery and materials design. It is further shown that multiple properties can be learned simultaneously in a photonic chip via a multi‐task regression learning algorithm, which is also the first of its kind as well, as most previous works focus on implementing a network in the classification task. [ABSTRACT FROM AUTHOR]