A Comprehensive Characterization of Commercial Conductive Yarns for Smart Textile Applications

At AUTEX 2025, we presented  a work, where we systematically evaluated 15 commercially available conductive yarns, representing a diverse range of fabrication methods — including spun yarns, multifilament structures, and twisted filaments — to assess their suitability for use in wearable electronics, particularly in embroidery-based integration. 

Using a combination of microscopy, structural analysis, mechanical abrasion tests, and electrical resistance measurements under both controlled and simulated wear conditions, we identified key properties that influence performance.

Thick Places

“Thick places” refer to localized sections of a yarn where its diameter exceeds the average by at least 50%. These inconsistencies can disrupt the performance of conductive yarns during fabrication, particularly in high-precision processes like embroidery. In your study, these were carefully quantified by measuring the diameter over 8 cm yarn segments using a high-resolution microscope.

Among the spun yarns, Bart-Francis Marino and Bart-Francis Coated showed the highest frequency of thick places — averaging about 2 per segment — suggesting structural irregularities possibly caused by uneven fiber blending or tension issues during manufacturing. In contrast, Schoeller Nm 50/1 and Bart-Francis 3721 had much smoother profiles, showing approximately 0.5 to 1 thick place, which correlated with better embroidery performance and fewer machine jams. Multifilament yarns, by comparison, showed no measurable thick or thin places, suggesting their structural uniformity offers distinct advantages for machine integration. However, Amann Steel-Tech 100 stood out for frequent entanglements, likely caused by post-production winding rather than true diameter variation.

These thick regions are critical because they introduce points of friction or blockage when passing through embroidery machine needles and tensioning systems. In turn, this leads to breakage, skipped stitches, and uneven conductivity in finished textile circuits. Therefore, minimizing thick places is essential for stable fabrication and electrical reliability.

Hairiness Test

Hairiness in yarns refers to the presence of fibers protruding from the main yarn body. This not only affects the mechanical handling of the yarn in machines but also has implications for abrasion resistance and electrical noise in conductive applications. Your study used a digital microscope and automated image analysis software to quantify two key parameters:

1. Number of protruding hairs, and
2. Average length of those hairs.

The spun yarn Bart-Francis Coated showed the highest hairiness, with approximately 85 hairs per 8 cm segment, many of which reached an average length of 5.5 mm. This level of fuzziness can dramatically increase friction in embroidery guides and lead to misalignment, breakage, or inconsistent stitching. Other spun yarns like Schoeller Nm 50/1 and Bart-Francis Marino had moderate hairiness values (around 50 hairs with lengths between 4–4.5 mm), while Bart-Francis 3721 performed better, with only ~20 hairs of shorter lengths (~2 mm), reflecting a more compact structure.

In contrast, twisted filament yarns such as Amann Silver-Tech 30 and Clever Tex 53A PUR exhibited minimal to no hairiness, making them ideal for smooth machine processing.

Hairiness is particularly problematic in conductive yarns, where loose fibers may cause short circuits, signal interference, or degrade the material under repeated use. Your study demonstrated that yarns with low hair count and short fiber length performed significantly better across all tests—from embroidery to abrasion and environmental exposure.

Stitch patterns

Stitch pattern also played a role: plain embroidery offered the best durability across all yarns, while more open structures led to faster degradation. Our results provide a practical framework for selecting conductive yarns based on fabrication behavior, structural consistency, and environmental resilience.

Wearability Test Using a Thermal Manikin

To simulate real-world wearing conditions, we conducted a comprehensive wearability test using a thermal manikincapable of mimicking both dry and sweating human skin. This setup allowed us to evaluate how different conductive yarns behave under varying thermal and moisture conditions, reflecting the dynamic environment of wearable textiles in everyday use.

Embroidered yarn samples were attached to the manikin’s arm and subjected to two distinct phases: first in a dry mode, and then under active sweating (at 1000 ml/h/m²). During both phases, we continuously measured the electrical resistance of each sample, while monitoring skin temperature and heat flux. This setup provided critical insight into how yarns respond to perspiration, skin contact, and thermal gradients—factors that are rarely captured in standard lab tests but are crucial for wearable integration.

Most of the yarns demonstrated stable resistance across both dry and wet conditions, confirming their reliability for wearable applications. Notably, Madeira HC 40, Clever Tex 27A PUR, and Clever Tex 53A PUR showed consistent electrical behavior, even when exposed to sweat. However, Bart-Francis 3721 exhibited high resistance variability and a marked drop in conductivity once sweating began—highlighting repeatability issues and reduced stability in humid environments.

This test confirmed that for yarns intended for on-skin applications, both material composition and structural integritysignificantly affect performance. The thermal manikin method offers a valuable and realistic lens for evaluating conductive yarns under realistic body-worn scenarios, going beyond conventional temperature chamber tests.

This work is a step forward in enabling reliable, scalable integration of electronics into fabrics, laying the foundation for next-generation wearables in health, sports, and interactive clothing.

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Team

Aftab Ahmed¹, Mira Haberfellner¹, Federica Morandi¹, Thomas Preindl¹, Andreas Pointner¹, Anita Vogl², Cohen Nitzan¹, Andrea Gasparella¹, Niko Münzenrieder¹, and Michael Haller¹

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(1) Free University of Bozen-Bolzano

(2) University of Applied Sciences Upper Austria