Elastic rebound engineering via leaf venation mimicry: boosting droplet spreading for high-performance triboelectric nanogenerators.

Zhengnan Sun, Xu Zeng, Aiwu Zhou, Junchang Guo, Xu Deng, Xiaosheng Zhang, Yi Zhang

Abstract read

In one paragraph

Article in Microsystems & nanoengineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Zhengnan SunSchool of Integrated Circuit Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China.

Xu ZengSchool of Integrated Circuit Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China.

Aiwu ZhouSchool of Integrated Circuit Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China.

Junchang GuoInstitute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China.

Xu DengInstitute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China.ORCID http://orcid.org/0000-0002-9659-0417

Xiaosheng ZhangSchool of Integrated Circuit Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China. zhangxs@uestc.edu.cn.ORCID http://orcid.org/0000-0001-9719-0573

Yi ZhangSchool of Integrated Circuit Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China. yi_zhang@uestc.edu.cn.ORCID http://orcid.org/0000-0002-1239-3441

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Droplet-based energy generator (DEG) has emerged as a promising platform for sustainable micro-energy harvesting, yet improving its energy conversion efficiency remains a primary research focus. In this work, we report an artificial leaf droplet-based energy generator (ALDEG) that mimics the interspaced soft-rigid venation pattern of plant leaves to enhance energy conversion by promoting droplet spreading. Testing reveals that the optimal interplay between membrane energy absorption and elastic rebound, modulated by venation pattern, leads to a 216% enhancement in voltage output and 233% enhancement in current output compared to conventional planar DEGs. An analytical model is developed to describe the relationship between the artificial venation pattern and droplet spreading dynamics, elucidating a "soft-over-hard" principle in which membrane elastic rebound enhances droplet spreading and thus charge generation. Furthermore, a multitier ALDEG architecture inspired by rainfall cascading through forest canopies demonstrates scalable energy harvesting and exhibits robust performance when powering a diverse range of electronic devices. This work establishes a new bio-inspired design framework for DEGs, demonstrating how biomimicry can be harnessed to modulate the substrate structure of DEGs for enhanced performance. The ALDEG platform holds promise for powering self-powered systems for autonomous environmental monitoring, smart agriculture, and other decentralized applications.

Identifiers

PMID42120362

DOI10.1038/s41378-026-01299-w

PMCPMC13168661

What OpenQuestion holds

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LicenceCC BY-NC-ND

Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.