Solar steam generation as a promising technology has great potential for application in wastewater treatment and seawater desalination. However, it remains challenging to develop low-cost, high-efficiency steam generators that are suitable for large scale application. Here, inspired by the natural transpiration process of trees, we fabricated a three-dimensional (3D) hierarchical tree-shaped biomimetic flax fabric (TBFF) using an ordinary loom, consisting of a float layer, basket weave layer and plain weave layer, which showed directional water transport properties along the continuous warp yarns of the fabric. Then, the obtained TBFF was modified by one-step synthesis of large-area polydopamine–polypyrrole composite (PDA–PPy) nanofibers for a high hydrophilicity and a higher surface area. The hierarchical micro-capillary pores of yarns and macro-interlaced pore structures between the warp and weft yarns in such modified TBFF-PDA-PPy exhibit broadband light absorption, high-efficiency water supply, large evaporation area, and easy steam escape. Therefore, the continuous water transport paths formed by TBFF-PDA-PPy could deliver an attractive evaporation rate of 1.37 kg m⁻² h⁻¹, where the solar energy conversion efficiency was up to 87.4% under 1 sun illumination. Based on the facile fabrication, low cost and scalable manufacturing process, this nature-inspired design of 3D hierarchical TBFF-PDA-PPy is expected to promote large-scale applications in water purification and seawater desalination.

Hydrogel strain sensors have received increasing attention due to their potential applications in human–machine interfaces and flexible electronics. However, they usually suffer from both mechanical and electrical hysteresis and poor water retention, which limit their practical applications. To address this challenge, a poly(acrylic acid-co-acrylamide) hydrogel crosslinked by silica nanoparticles is fabricated via photo polymerization and salting-out of hydrophilic ions for the strain sensor. The resulting hydrogel strain sensor possessed low electrical hysteresis (1.6%), low mechanical hysteresis (10 000 cycles), high durability, water retention and anti-freezing ability. Moreover, this strain sensor can be used as a wearable sensor for real-time control of robotic hands and hand gesture recognition. Finally, a sign language translation system has been demonstrated with the aid of machine learning, achieving recognition rates of over 98% for 15 different sign languages. This work offers a promising prospect for human–machine interfaces, smart wearable devices, and the Internet of Things.