Ruocun Wang

Assistant Professor

University of North Texas
Country flagUnited States

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Articles (10)

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2023

The rise of the Internet of Things has spurred extensive research on integrating conductive materials into textiles to turn them into sensors, antennas, energy storage devices, and heaters. MXenes, owing to their high electrical conductivity and solution processability, offer an efficient way to add conductivity and electronic functions to textiles through simple dip coating. However, manual development of MXene‐coated textiles restricts their quality, quantity, and variety. Here, a versatile automated yarn dip coater tailored for producing continuously high‐quality MXene‐coated yarns and conducted the most comprehensive MXene‐yarn dip coating study to date is developed. Compared to manual methods, the automated coater provides lower resistance, superior uniformity, faster speed, and reduced MXene consumption. It also enables rapid coating parameter optimization, resulting in a thin Ti 3 C 2 coating uniform over a 1 km length on a braided Kevlar yarn while preserving its excellent mechanical properties (over 800 MPa) and adding Joule heating and damage sensing to composites reinforced by the yarns. By dip‐coating five different yarns of varying materials, diameters, structures, and chemistries, new insights into MXene‐yarn interactions are gained. Thus, the automated dip coating presents ample opportunities for scalable integration of MXenes into a wide range of yarns for diverse functions and applications.

Year:

2023

Year:

2023

Collaborators (4)

Christopher Shuck

Assistant Professor

Rutgers University - Busch Campus

UNITED STATES
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Martin Dahlqvist

Associate Professor

Linköping University

SWEDEN
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Bhavik Anil Patel

University of Brighton

UNITED KINGDOM
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Yury Gogotsi

-

UNITED STATES
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