A Strategy for Fabricating Ultra-Flexible Thermoelectric Films Using Ag2Se-Based Ink.

Flexible thermoelectric materials have drawn significant attention from researchers due to their potential applications in wearable electronics and the Internet of Things. Despite many reports on these materials, it remains a significant challenge to develop cost-effective methods for large-scale, patterned fabrication of materials that exhibit both excellent thermoelectric performance and remarkable flexibility. In this study, we have developed an Ag2Se-based ink with excellent printability that can be used to fabricate flexible thermoelectric films by screen printing and low-temperature sintering. The printed films exhibit a Seebeck coefficient of -161 µV/K and a power factor of 3250.9 µW/m·K2 at 400 K. Moreover, the films demonstrate remarkable flexibility, showing minimal changes in resistance after being bent 5000 times at a radius of 5 mm. Overall, this research offers a new opportunity for the large-scale patterned production of flexible thermoelectric films.

Paper Information Recording and Security Protection Using Invisible Ink and Artificial Intelligence.

Conventional paper information protection mainly relies on stimuli-responsive functional materials that can display color or luminescence under external stimuli; however, this method is rather predictable and can be easily cracked. In this work, a paper information protection scheme combining fluorescent invisible ink and artificial intelligence was proposed. The ink was prepared by dissolving carbon nanoparticles in water, which has a high quantum yield and outstanding light stability and salt stability, thus ensuring the integrity of information in complex environments. A five-layer convolutional neural network (one of the two mainstream architectures in today's artificial intelligence fields) was specially trained based on ultraviolet light excited symbols printed by invisible ink. Using this scheme, the correct information could only be read with the specially trained neural network after ultraviolet (UV) irradiation. Without this trained neural network or UV irradiation, misleading messages will be presented. Moreover, it was possible to design unpredictable and highly complex password books to further increase information security. This smart strategy provides new opportunities for high-level paper information encryption and also proposes new ideas for the applications of carbon nanoparticles and artificial intelligence.

Development of a Ni-Doped VAl3 Topological Semimetal with a Significantly Enhanced HER Catalytic Performance.

Topological materials with robust topological surface states appear to be well-suited as electrochemical catalysts. However, few studies have been published on the development of non-noble metal topological catalysts, most likely because the topological properties tend to be attributed to the s and p orbital electrons, while transition-metal catalysis mainly involves d orbital electrons. Herein, we proposed a topological semimetallic (TSM) compound, VAl3, with a surface state consisting mainly of d orbital electrons, as an electrocatalyst for the hydrogen evolution reaction (HER). Density functional theory (DFT) calculations showed that the surface state electrons enhanced the adsorption of H atoms. Moreover, the transfer of surface state electrons between the surface and adsorbed H atoms was optimized through nickel doping. We experimentally prepared single-crystals VAl3 and V0.75Ni0.25Al3 alloys. Electrochemical analysis showed that not only did V0.75Ni0.25Al3 outperform VAl3 but also it was among the best non-noble metal topological HER electrocatalysts currently available.