Small Published the Latest Research Findings of Academician Ding Han and Prof. Wu Zhigang’s Team of MSE
Author:Jiang Jiajun Edit:Liao Liangmin, Wu Yangtian       Release time:Sep 3, 2020       click:

On August 23rd, Small (IF=11.459) published the latest research findings of MSE Academician Ding Han and Prof. Wu Zhigang’s team on liquid alloy titled “Hydroprinted Liquid-Alloy-Based Morphing Electronics for Fast-Growing/Tender Plants: From Physiology Monitoring to Habit Manipulation”. MSE doctoral students Jiang Jiajun and Zhang Shuo were the co-first authors, and Prof. Wu Zhigang was the corresponding author.

Monitoring physiological signals and manipulating growth habits of living plants in real time are important for botany research, biohybrid plant robots, and precision agriculture. Although emerging epidermal electronics that can conveniently acquire vital signals of living organisms exhibit a high potential for such scenarios, it is a significant challenge to adapt such devices for plants, because they are fragile and usually have complex surfaces that can change significantly during rapid growth. A gentle fabrication process is critical in order to employ compliant electronic systems to adapt to this highly dynamic situation. In this study, a hydroprinted liquid-alloy-based morphing electronics (LAME) process is employed for fast-growing plants that will sense physiological signals and even function as a biohybrid to determine plant behavior on demand. Besides various surfaces of inorganic targeting substrates, pinning liquid alloy circuits onto the complex plant epidermis is enhanced by introducing high-surface-energy liquid. Functionally, the new developed LAME can be used to monitor leaf moisture content and length, and manipulate leaf and bean sprout orientation.

The study proved the excellent compliance, deformability, and functionality of liquid alloy circuits used on rapidly growing plants. It laid the foundation for a new form of morphing electronics for botany or biohybrid plant robots, potentially impacting the next generation of precision agriculture and smart hybrid robots.

This work was partly financially supported by National Key R&D Program of China (Grant No. 2017YFB1303100) and National Natural Science Foundation of China (Grant No. U1613204).


Link of the paper: https://doi.org/10.1002/smll.202003833

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