Aqueously Upcycled Lignin with Emergent Tribonegativity for Skin‐Integrated Triboelectronics

TL;DR

Researchers developed a sustainable electronic ink from lignin waste that can be printed into skin-integrated sensors for monitoring health and mental workload.

Contribution

A scalable aqueous process transforms lignin into printable electronic ink with emergent tribonegativity for triboelectric sensors.

Findings

The urea-based formulation increases lignin dispersibility to 100 mg mL−1 while preserving molecular integrity.

Skin-integrated sensors from the ink generate high-fidelity signals comparable to electrocardiography for mental workload classification.

Abstract

Valorizing lignin, a vast industrial byproduct and abundant biomass, is critical for a circular bioeconomy. However, the potential of lignin as a feedstock for functional polymers remains unrealized owing to poor aqueous solubility. Herein, a scalable aqueous process is reported that transforms lignin into printable electronic ink. The benign urea‐based formulation increases lignin dispersibility by two orders of magnitude to 100 mg mL−1, while preserving its molecular integrity by retaining 97.6% of its fragile β‐O‐4′ ether linkages. This process enables the thermodynamically driven self‐assembly of lignin polymers during printing to create a functional, nanotextured surface with emergent tribonegativity, without the use of harsh solvents or lithography. As a proof of concept, skin‐integrated triboelectric sensors fabricated from this ink generate high‐fidelity signals sufficient for objectively classifying human mental workload, with a performance comparable to gold‐standard electrocardiography. This study establishes a generalizable strategy for creating high‐performance, sustainable electronics from waste biomass.

Aqueously upcycled lignin is transformed into a printable ink that self‐assembles into a nanotextured surface during printing with the highest reported biopolymer‐based tribonegativity. The resulting skin‐integrated triboelectric sensor enables high‐fidelity cardiovascular monitoring and objective mental workload classification, demonstrating a scalable route to high‐performance, sustainable electronics from otherwise wasted biomass.

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