Laser‐Induced Graphene‐Enabled Programmable Ion‐Gradient Composites for Hundred‐Hour‐Stable, High‐Power Moisture‐Electric Generation Toward Self‐Sustaining IoT Systems

ABSTRACT Moisture‐electric generators (MEGs) are emerging as promising green power sources for distributed micro‐devices. However, achieving stable and reproducible electrical output remains a major challenge, largely due to the lack of a unified material platform that allows systematic control over ion‐gradient design. Herein, a novel composite‐engineering strategy is proposed that integrates proton‐ and anion‐doped polybenzimidazole (PBI) with a hydrophilic, laser‐induced graphene (LIG) electrodes in a single‐step fabrication process. This approach provides the tailored construction of both mono‐ionic and hetero‐ionic gradient configurations within the same polymer system, offering a compatible platform to decipher the relationships between ion concentration and bilayer structure for device performance. The optimized MEG delivers a high short‐circuit current density of 1 mA cm − 2 , a maximum power density of 43.3 µW cm − 2 , and an integrated open‐circuit voltage up to 6.26 V. Crucially, scalable MEG arrays maintain a stable output of 2 V and 1 µA cm −2 after 5 days of continuous operation, demonstrating exceptional long‐term stability. Optimized MEGs (arrays) can further power electronics and sense humidity, enabling self‐sustaining water–electric cycling for autonomous IoT systems. This work establishes a material‐level design framework for high‐performance, durable moisture‐driven energy generation.

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Journal
Small
Published
2026-08-31
DOI
https://doi.org/10.1002/smll.75567
Primary Topic
Solar-Powered Water Purification Methods
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article
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Laser‐Induced Graphene‐Enabled Programmable Ion‐Gradient Composites for Hundred‐Hour‐Stable, High‐Power Moisture‐Electric Generation Toward Self‐Sustaining IoT Systems

Haibin Duan, Shaohua Yang, Weixiong Yang, Sida Luo et al.
Small
Solar-Powered Water Purification Methods
article

Laser‐Induced Graphene‐Enabled Programmable Ion‐Gradient Composites for Hundred‐Hour‐Stable, High‐Power Moisture‐Electric Generation Toward Self‐Sustaining IoT Systems

Haibin Duan, Shaohua Yang, Weixiong Yang, Sida Luo, Xilun Ding, Mingguang Han, Han Gao, Yuhan Guo
article en

Abstract

ABSTRACT Moisture‐electric generators (MEGs) are emerging as promising green power sources for distributed micro‐devices. However, achieving stable and reproducible electrical output remains a major challenge, largely due to the lack of a unified material platform that allows systematic control over ion‐gradient design. Herein, a novel composite‐engineering strategy is proposed that integrates proton‐ and anion‐doped polybenzimidazole (PBI) with a hydrophilic, laser‐induced graphene (LIG) electrodes in a single‐step fabrication process. This approach provides the tailored construction of both mono‐ionic and hetero‐ionic gradient configurations within the same polymer system, offering a compatible platform to decipher the relationships between ion concentration and bilayer structure for device performance. The optimized MEG delivers a high short‐circuit current density of 1 mA cm − 2 , a maximum power density of 43.3 µW cm − 2 , and an integrated open‐circuit voltage up to 6.26 V. Crucially, scalable MEG arrays maintain a stable output of 2 V and 1 µA cm −2 after 5 days of continuous operation, demonstrating exceptional long‐term stability. Optimized MEGs (arrays) can further power electronics and sense humidity, enabling self‐sustaining water–electric cycling for autonomous IoT systems. This work establishes a material‐level design framework for high‐performance, durable moisture‐driven energy generation.

Small
Beihang University (CN)
Affordable and clean energy
Openalex Percentile: Top 28%
Solar-Powered Water Purification Methods
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Laser‐Induced Graphene‐Enabled Programmable Ion‐Gradient Composites for Hundred‐Hour‐Stable, High‐Power Moisture‐Electric Generation Toward Self‐Sustaining IoT Systems — Haibin Duan, Shaohua Yang, et al. · Small (2026) | TGRS Research Map | TGRS