State Key Laboratory of Advanced Fiber Materials, College of Chemistry and Chemical Engineering, Center for Advanced Low-Dimension Materials, Donghua University, Shanghai, China
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Zhouyue Lei
State Key Laboratory of Advanced Fiber Materials, College of Chemistry and Chemical Engineering, Center for Advanced Low-Dimension Materials, Donghua University, Shanghai, China
Converting building and environment heat into electricity is a promising strategy for energy harvest to tackle global energy and environmental problems. The processing challenges, mechanical brittleness, and low environmental tolerance of typical thermoelectric materials, however, prevent them from realizing their full potential when employed in outdoor building systems. Herein, a general concept based on synergistic ionic associations to significantly improve the mechanical properties and harsh environment stability for high‐performance ionic‐type thermoelectric (i‐TE) gels is explored. They demonstrate extraordinarily high stretchability (1300–2100%), fast self‐healing (120 s), temperature insensitivity, and great water‐proof performance, and could be painted on a variety of surfaces. The n‐type ionic Seebeck coefficient is up to −8.8 mV K−1 and the ionic conductivity is more than 0.14 mS cm−1. Both exhibit remarkable thermal and humidity stability (293–333 K, 20–100 RH%), which are rarely achieved in previous studies. Even on a cloudy day, the open‐circuit thermovoltage for a painted i‐TE array with an area of about 8.5 × 10−3 m2 is above 2 V. This research offers a promising approach for gathering significant waste heat and even solar energy on outside building surfaces in an effective and sustainable manner.
26 February 2025 in Energy & Environmental Science
Aqueous zinc-ion batteries (AZIBs) are promising energy storage systems due to their high theoretical capacity, intrinsic safety, and potentially high cycling stability. However, their practical application is hindered by sluggish Zn-ion transfer, parasitic side reactions, and dendrite growth, leading to their suboptimal capacity and limited cycle lifespan. Herein, we report a bioinspired design of hierarchical twisted hydrogel electrolytes (HTHEs) by establishing a multi-stage collaborative regulation pathway to address these challenges. The HTHEs exhibit a high Zn2+ transference number of 0.9 and a wide electrochemical stability window of 2.61 V, effectively suppressing dendrite formation and enhancing Zn2+ deposition along the Zn (002) plane. Symmetric cells assembled with the HTHEs demonstrate exceptional cycling stability across a wide range of current densities, while pouch cells achieve an ultra-long cycle life of nearly 10 000 cycles with a high specific capacity of >100 mA h g−1 and a capacity retention of 80%. Notably, these pouch cells display outstanding flexibility and impact resistance, remaining fully operational under folding and even withstanding extreme mechanical stresses, such as those that can even crack walnuts. The multi-stage collaborative regulation pathway in the design of high-performance flexible AZIB electrolytes enhances their potential for next-generation energy storage applications.
Mimicking biological systems’ sensing, learning, and memory capabilities in synthetic soft materials remains challenging. While significant progress has been made in sensory functions in ionogels, their learning and memory capabilities still lag behind biological systems. Here, we introduce cation-π interactions and a self-adaptable ionic-double-layer interface in bilayer ionogels to control ion transport. Fast ion response enables sensing and learning, while slow ion relaxation supports long-term memory. The ionogels achieve bioinspired functions, including sensitization, habituation, classical conditioning, and multimodal memory, with low energy consumption (0.06 pJ per spike). Additionally, the ionogels exhibit mechanical adaptability, such as stretchability, self-healing, and reconfigurability, making them ideal for soft robotics. Notably, the ionogels enable a robotic arm to mimic the selective capture behavior of a Venus flytrap. This work bridges the gap between biological intelligence and artificial systems, offering promising applications in bioinspired, energy-efficient sensing, learning, and memory.
10 January 2025 in Chinese Journal of Polymer Science