Silk-templated Nanostrips as Superprotonic Fibre Sensors
Abstract
Transforming textile fibres into sensors can facilitate continuous physiological monitoring for improving human healthcare. Coating fibres with electronic conductors can help detect physiological stimuli but their sensitivity scales with thickness and often lowers the fibre mechanical flexibility. Proton conductors are potential alternatives; however, they suffer from fragile physical interfaces, and sluggish kinetics. Here, we report a bio-templated, scalable strategy to create superprotonic interfaces using natural silk fibres. We exploit ordered nanofibrils on silk fibres to selectively grow continuous metal-organic framework (MOF) nanostrips. This patterned, ca. 10 μm-diameter fibre-structure provides low-defect interfacial pathways for ultrafast proton transport, yielding conductivities up to 40 S cm−1 - two orders of magnitude above the state of the art - with millisecond response and high mechanical robustness. The individual micro-thread sensors facilitate respiratory monitoring with a mean bias of 0.01 breaths min−1 in volunteer testing, unaffected by human movement and readily capture breathing signature in high-flow oxygen therapy devices. We integrate arrays of micro-thread sensors in textiles and exploit deep learning to demonstrate high-resolution spatiotemporal humidity mapping in dynamic flow-fields and resolve asymmetric respiratory patterns that elude conventional single-point detectors. Our results should have broad-ranging implications, e.g. in wearable health monitoring, bioelectronics, and human-machine interfaces.
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BibTeX
@misc{zhang2026silktemplated,
title = {{Silk-templated Nanostrips as Superprotonic Fibre Sensors}},
author = {Jianhui Zhang and Ahmed Salem and Robert Tidswell and Haowei Wang and Vikramjeet Singh and Laurence B. Lovat and Manish K. Tiwari},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.25293},
eprint = {2609.25293},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.25293},
}
RIS
TY - UNPB
TI - Silk-templated Nanostrips as Superprotonic Fibre Sensors
AU - Jianhui Zhang
AU - Ahmed Salem
AU - Robert Tidswell
AU - Haowei Wang
AU - Vikramjeet Singh
AU - Laurence B. Lovat
AU - Manish K. Tiwari
PY - 2026
DA - 2026/09/21
PB - arXiv
DO - 10.48550/arxiv.2609.25293
UR - https://arxiv.org/abs/2609.25293
AB - Transforming textile fibres into sensors can facilitate continuous physiological monitoring for improving human healthcare. Coating fibres with electronic conductors can help detect physiological stimuli but their sensitivity scales with thickness and often lowers the fibre mechanical flexibility. Proton conductors are potential alternatives; however, they suffer from fragile physical interfaces, and sluggish kinetics. Here, we report a bio-templated, scalable strategy to create superprotonic interfaces using natural silk fibres. We exploit ordered nanofibrils on silk fibres to selectively grow continuous metal-organic framework (MOF) nanostrips. This patterned, ca. 10 μm-diameter fibre-structure provides low-defect interfacial pathways for ultrafast proton transport, yielding conductivities up to 40 S cm^−1 - two orders of magnitude above the state of the art - with millisecond response and high mechanical robustness. The individual micro-thread sensors facilitate respiratory monitoring with a mean bias of 0.01 breaths min^−1 in volunteer testing, unaffected by human movement and readily capture breathing signature in high-flow oxygen therapy devices. We integrate arrays of micro-thread sensors in textiles and exploit deep learning to demonstrate high-resolution spatiotemporal humidity mapping in dynamic flow-fields and resolve asymmetric respiratory patterns that elude conventional single-point detectors. Our results should have broad-ranging implications, e.g. in wearable health monitoring, bioelectronics, and human-machine interfaces.
ER -