Effecting factors on electrical resistance of conductive paths

Introduction

Wearable technology concept which includes wearable devices and wearable electronics are gaining more importance every day. These concepts refer to devices that can be worn on a person and have the capability of communication and connection using Wi-Fi, Bluetooth, or another technology. There are so many examples of wearable technology as eyeglasses, wrist bands, smart watches, smart clothing, etc, in the market today. By 2022, it is estimated that there will be 1.1 billion wearable devices globally. ¹ It means that this market will be expanded exponentially in the next years. Such that, wearable market segment is projected to reach US$17,834 million in 2021. Furthermore, it is reported that fitness wrist wears, activity trackers, and smart clothes will be in-scope. ² In a 2014 study, wearing a sensor device preference were asked to 16,200 consumers from the US and Europe. The results showed that more than one-third of all consumers preferred using a sensor device on their wrist. Clipped onto clothing and embedded into clothing options followed this preference, respectively. ³ With the developments in conductive and electronic industry which can be used in the clothing manufacturing, smart garments category look set to expand in terms of wearable offerings.

Smart garments are a new concept of clothing with a high added value. It gathers the emotional and functional nature of fashion with information and communication technologies. ⁴ Besides, smart garments are better than a portable device, its wear and use is not a burden or obstacle that must be remembered. By means of facilities they provide, smart garments have become used in different areas such as health sector, military applications, athletics, and entertainment sector. ⁵ Smart clothing market size surpassed US$150 million and is poised to register over 48% growth between 2017 and 2024. The smart shirts segment is expected to grow significantly with over 50% compound annual growth rate till 2024 as these t-shirts provide biometric data. Smart jackets are also witnessing high demand due to its ability to control the mobile devices of the wearer and connect to several services such as music and camera directly from the jacket. ⁶

There are different pathways to make a garment smart. The first way is to add the electronic components such as sensors and microprocessors directly to the garment and another is to produce the electronic part using conductive textile materials such as fabrics, yarns, and inks ⁷ By all manner of means, there is a need for a path for connection between conductive components. This could be provided by cables conventionally or conductive paths can be utilized. Usually, conductive fabrics and conductive yarns produced from conductive printing and are used to create conductive paths. When using conductive yarns sewing is the most preferred technique for both electronic component and conductive path production.^8,9 When previous studies were examined, it is seen that lock stitch and zigzag stitch are the commonly used stitch types for the smart applications.^10–17 Parkova et al. studied electrical behavior of different conductive yarns in sewn and un-sewn form to define their suitability for specific applications and used lock stitch for sample production. ¹⁰ Saenz-Cogollo et al. presented the development of a mat-like pressure mapping system based on a single layer textile sensor using lock stitch. ¹¹ Moradi et al. investigated effects of sewing pattern on the performance of embroidered dipole-type radio-frequency identification tag antennas which is produced by lock stitch. ¹² Ismar et al. examined seam strength and washability of silver-coated polyamide yarns and plain stitching type was used for experiments. ¹³ Indarit et al. developed a single-yarn-based gas sensor and stainless-steel thread was seamed as conductive line. ¹⁴ Park et al. developed highly bendable and rotational textile structure with prestrained conductive sewing patterns such as straight, blind, and zigzag stitch for human joint monitoring. ¹⁵ Darabi et al. demonstrated electrically conducting wood-based yarns for machine sewed electronic textiles and used zigzag stitch for evaluations. ¹⁶ Leśnikowski analyzed characteristic impedance of microstrip and coplanar textile signal lines and used zigzag stich for production of textile signal lines. ¹⁷

Previous studies showed that the general performance of smart garments depends on the resistance values of conductive areas and it is directly related to the resistance of conductive material and the used pattern.^8,9,12 In this study, conductive paths are generated using different conductive yarns, stitch types, stitch densities, and thread positions and the effect of these parameters on electrical resistance values were investigated.

Material and method

Materials for this study included one non-conductive and three different conductive threads, three different non-conductive textile substrates, sewing machines, and a digital multimeter. Non-conductive thread was 100% polyester. Three different kinds of commercially available conductive threads (A, B, and C) were used to investigate in this study. Thread A (Shieldex 235/36 dtex HC) is a silver-coated nylon yarn with an average resistance value of 100 Ω/m. Thread B (X-Silver 410 denier) is a 100% silver yarn with an average resistance value of 110 Ω/m. Thread C (X-Static 310 denier) is a2-ply 99.9% pure silver yarn with an average resistance value of 150 Ω/m. Microscopic images of the conductive threads which are taken with JEOL JSM-6060 scanning electron microscope are shown in Figure 1. It is seen that the surface of Thread B and Thread C are well plated while Thread A has some gaps in the plating surface which can cause electrical resistance differences.OPEN IN VIEWER

Three different non-conductive textile substrates were used for the sample production in this study. All fabrics were 2 × 2 twill woven fabrics with different raw material properties as 100% cotton, 100% polyester, and 50% cotton−50% polyester. Weft density is 28 thread/cm and warp density is 18 thread/cm for 100% cotton fabric, weft density is 20 thread/cm and warp density is 16 thread/cm for 100% polyester fabric, and weft density is 26 thread/cm and warp density is 18 thread/cm for 50% cotton−50% polyester fabric. The aim of using different fabrics was to investigate the effect of the material type on electrical resistance. To prevent the electrical resistance change connected with elasticity, all fabrics were chosen as woven fabrics. ¹⁸

The stitch types used in this study are 101 single thread chain stitch, 301 lock stitch, 304 zigzag stitch, and 406 cover seaming stitch. Stitch types can be seen in Figure 2. Juki MF-7723 sewing machine was used for single thread chain stitch and cover seaming stitch, Garudan GF-115-107LM sewing machine was used for lock stitch, and Pfaff 332 sewing machine was used for zigzag stitch. In sample production process, different stitch densities and conductive thread position combinations were used. Sewing was performed using the highest and lowest densities permitted by the machine for each stitch type. The stitch densities are 6 SPI and 4 SPI for 101 single thread chain stitch, 11 SPI and 3 SPI for 301 lock stitch, 13 SPI and 2 SPI for 304 zigzag stitch, and 7 SPI and 4 SPI for 406 cover seaming stitch. In addition to stitch densities, conductive threads are positioned as only needle thread, only bobbin thread and both needle and bobbin thread.OPEN IN VIEWER

Using these combinations totally 216 samples, each 5 cm width and 10 cm long, were produced. A TENMA dual display LCR meter 72–960 was used to measure the electrical resistance. The effect of factors such as stitch type, conductive thread type, fabric type, stitch density, and conductive thread position on electrical resistance values was investigated using bar charts and multiple regression analysis. The statistical tests were conducted using IBM SPSS version 22.0. software.

Results and discussion

The results of the bar charts which show the mean electrical resistance values for each factor such as stitch type, conductive thread type, fabric type, stitch density, and conductive thread position are given in Figure 3. Here, mean electrical resistance values are given in Ohm. They are used to visualize quantities associated with a set of items. When factors were evaluating, all samples of the related factor were considered.OPEN IN VIEWER

When bar charts were investigated in terms of stitch types, it is seen that the zigzag stitch is resulted in the highest electrical resistance values, and it is followed by single thread chain stitch when lock stitch and cover seaming stitch cause the lowest electrical resistance values. When conductive thread types were examined, it is seen that Thread C (X-Static 310 denier) results in the highest electrical resistance values while Thread A (Shieldex 235/36 dtex HC) and Thread B (X-Silver 410 denier) cause lower and nearly same electrical resistance values. It is seen that the difference in fabric types does not affect the electrical resistance values. Stitch density is directly affecting the electrical resistance values and high stitch density causes higher electrical resistance values as expected. When conductive thread positions were examined, it is seen that if conductive thread is used as both needle and bobbin thread, electrical resistance values are decreased significantly.

In addition to bar charts, multiple regression analyzes were also conducted. In multiple regression, unlike binary regression, the cumulative effect of more than one independent variable on the dependent variable is investigated.

There are five parameters that can change electrical resistance values in this study. These are stitch type, conductive thread type, fabric type, stitch density and conductive thread position. In order to determine the significance level of factors, multiple regression analysis was performed by IBM SPSS Statistics 22 software. The multiple regression analysis results can be seen in Table 1. The statistical significance level α was set up p = 0.05 for all tests.

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Table 1.

Multiple regression analysis results.

Coefficients a
Model		Unstandardized coefficients		Standardized coefficients		Sig.	Correlations			Collinearity statistics
		B	Std. Error	Beta	t		Zero-order	Partial	Part	Tolerance	VIF
1	(Constant) stitch_type conductive_thread fabric_type stitch_density conductive_thread_position	41,284	7660		5389	.000
		2071	1193	.104	1737	.084	.104	.119	.104	1000	1000
		7038	1633	.258	4309	.000	.258	.285	.258	1000	1000
		.045	1633	.002	.028	.978	.002	.002	.002	1000	1000
		−12,841	2667	−.288	−4815	.000	−.288	−.315	−.288	1000	1000
		−8118	1633	−.297	−4970	.000	−.297	−.324	−.297	1000	1000

It is seen from the table above that conductive thread type ( p < 0.05 ) , stitch density ( p < 0.05 ) , and conductive thread position ( p < 0.05 ) are significant factors on electrical resistance values. The table showed that stitch type ( p < 0.05 ) and fabric type are statistically non-significant.

Conclusion

General performance of smart garments depends on the resistance values of conductive areas and it is directly related to the resistance of conductive material and the pattern used to develop the smart garment. In this study, conductive paths are generated using different conductive yarns, stitch types, stitch densities, and thread positions, and the effect of these factors on electrical resistance values was investigated. Three different non-conductive textile substrates were used for the sample production to see the effect of textile substrate on electrical resistance values. The results showed that the type of non-conductive textile substrates is statistically non-significant.

Four different stitch types such as 101 single thread chain stitch, 301 lock stitch, 304 zigzag stitch, and 406 cover seaming stitch with different stitch densities used to produce conductive paths and it is seen that zigzag stitch is resulted in the highest electrical resistance values, and it is followed by single thread chain stitch when lock stitch and cover seaming stitch cause the lowest electrical resistance values. Similarly, Ruppert-Stroescu and Balasubramanian were reported that lock stitch showed significantly lower resistance compared to zigzag stitch. ⁸ In addition to stitch type, stitch density is also directly affecting the electrical resistance values and high stitch density causes higher electrical resistance values as expected. Here, different stitch types are used to see the effects on the electrical resistance values and give an opinion to the designers in terms of productivity, usability, and performance.

Another factor is chosen as conductive yarn type and it is seen that different conductive yarns are resulted with different electrical values as expected because they have their own electrical resistance regardless of other factors. Similar results are stated in the literature.^8,19

And lastly conductive thread positions were examined, and it is seen that if conductive thread is used as both needle and bobbin thread, electrical resistance values are decreased significantly. Ruppert-Stroescu and Balasubramanian were used conductive yarn at the bottom (as needle thread) and top and bottom (as both needle and bobbin thread) and a little decrease was reported when conductive thread was used at top and bottom together. ⁸ When conductive threads were used as both needle and bobbin thread more junction points are generated which cause connection in parallel and electrical resistance decreases.

In this study, only silver-plated yarns were used; however, in further studies, the conductive yarns produced from other raw materials such as steel, and graphene could be used. Also, investigating the flexible textile substrates can suggest a course of action for stretchable textile products.