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In this work, surface-functionalized microcapsules from porous carbon nanospheres (PCNs) were successfully prepared by mussel-inspired chemistry with polydopamine (PDA) and metal-free photoinduced electron transfer–atom transfer radical polymerization (PET-ATRP). These functional microcapsules are introduced into self-healing hydrogels to enhance their mechanical strength. The PCNs synthesized by a simple soft template method are mixed with linseed oil for loading of the biomass healing agent, and the microcapsules are first prepared by coating PDA. PDA coatings were used to immobilize the ATRP initiator for initiating 4-vinylpyridine on the surface of microcapsules by PET-ATRP. Using these functional microcapsules, the self-healing efficiency was about 92.5% after 4 h at ambient temperature and the healed tensile strength can be held at 2.5 MPa with a fracture strain of 625.2%. All results indicated that the surface-functionalized microcapsules for self-healing hydrogels have remarkable biocompatibility and mechanical properties.

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Robust and self-healable nanocomposite hydrogels were realized by the encapsulation of components of photoinduced electron transfer−atom transfer radical polymerization (PET−ATRP) into surface-modified silica nanoparticles (SiO 2 ). The prepared SiO 2 @P4VP was in the form of self-healing nanocomposite hydrogels, where 4-vinylpyridine (4VP) was polymerized through PET−ATRP with organic photocatalyst Rhodamine B. The modified nanoparticles were characterized by X-ray photoelectron spectroscopy (XPS), thermogravimetric analysis (TGA), transmission electron microscopy (TEM), and Fourier transform infrared (FT-IR) spectroscopy. The nanocomposite hydrogels can be healed rapidly and autonomously without any stimulation at ambient temperature. Specifically, the nanocomposite hydrogels have a tensile strength of about 2.90 MPa, which recovered to 77.0% after 12 h, and an elongation at break of about 730%. These selfhealing hydrogels with cheap raw material, possessing better strength and self-healing performance, will have broad prospects.

In response to the trend that artificial intelligence (AI) is becoming the main driver for social and economic development, enhancing the readiness of learners in AI is significant and important. The state council and the ministry of education of China put AI education for K-12 schools on a high priority in order to foster local AI talents and reduce educational disparities. However, the AI knowledge and technical skills are still limited for not only students but also the school teachers. Furthermore, many local schools in China, especially in the rural areas, are lack of the necessary software and hardware for teaching AI. Hence, we designed and implemented a structured series of AI courses, built on an online block-based visual programming platform. The AI courses are free and easily accessible for all. We have conducted the experimental classes in a local school and collected the results. The results show that the learners in general gained significant learning progress on AI knowledge comprehension, aroused strong interests in AI, and increased the degree of satisfaction towards the course. Especially, our practices significantly increased computational thinking of the students who were initially staying at a lower level.