A smart textile fabric with two-way action

Abstract

The aim of the paper was to develop a prototype of smart textile material with shape memory elements that give variable thermal insulation dependent on the emission-absorption of heat. Shape memory elements were made in the form of spirals of two-way action from nitinol (NiTi) one-way wire. Two groups of samples were made: active and non-active. The active spirals expand at temperatures lower than the characteristic inner state transition temperature and contract as the temperature becomes higher than the transient temperature, which was about 45℃. The non-active spirals do not change dimensions under the influence of heat supply. The material of the layered structure was prepared. The first layer consisted of cotton woven fabric and the second layer featured a system of NiTi spiral elements, while the final layer was made of a thin Teflon foil. The behavior of samples during absorption-emission of heat was studied. Temperature measurements were conducted using an infrared camera; samples were placed on a heater to ensure contact between the Teflon layer and the base, and the temperature was recorded at the sample surface (woven fabric) as a function of the heating time for both active and non-active samples. A theoretical model that makes it possible to determine the time variable thermal parameters of the smart textile material was developed. Good agreement between the experimental and theoretical results was received. The temperature on the surface of the active sample was approximately 10℃ higher at the end of heating than the temperature of the non-active sample after the same heating pattern.

Keywords

temperature control shape memory smart textile material one-way action two-way action nitinol thermal insulating

Textiles have always accompanied man. Their main purpose is to provide adequate thermal protection. Man's contact with clothing is constant, independent of the time of day or year. The textile industry is always looking for new materials to produce clothing. Synergistic research by scientists in different fields has led to the creation of “smart textiles”. What exactly are smart textiles? In¹ the authors write:

Smart textiles are fabrics that have been developed with new technologies that provide added value to the wearer, what makes smart fabrics revolutionary is that they have the ability to do many things that traditional fabrics cannot, including communicate, transform, conduct energy and even grow. Smart textiles can be broken into two different categories: Aesthetic and Performance Enhancing. Aesthetic examples include everything from fabrics that light up to fabrics that can change color. Some of these fabrics gather energy from the environment by harnessing vibrations, sound or heat, reacting to this input. Some fabrics have been developed for protective clothing to guard against extreme environmental hazards like radiation and the effects of space travel … The health and beauty industry is also taking advantage of these innovations, which range from drug-releasing medical textiles, to fabric with moisturizer, perfume, and anti-aging properties.

Smart fabrics can be used as sensors of chemical substances,^2–5 printed sensors of breathing or electrical conductors⁶⁷ and fabrics as thermal sensors or for measuring and monitoring of physiological parameters of human beings in extreme conditions,⁸ or transmitting data to the center of diagnosing and controlling systems.^9,10 Pinchuk and Goldade¹¹ write:

A smart material, under the influence of external stimuli, having reached a threshold value as a result of them, can convert quantitative changes of energy into a qualitative change of its own properties, thereby performing a useful function either once or repeatedly.

Shape memory is one of the most understood and common phenomena characterizing smart materials. There are a number of kinds of shape memory materials in the literature. The most common of them is the shape memory alloy of nickel-titanium (NiTi) or nitinol, first discovered in 1959.¹² NiTi has been widely used in the field of medicine, including in orthopedics, cardiology and dentistry;^13–16 it can also be used in the textile industry. NiTi in the form of fine wires is suitable for being processed on textile machines.^17,18 NiTi alloys are characterized by two stable phases – a high-temperature and a low-temperature phase. These phases are called as martensite (low temperatures) and austenite (high temperatures). The latter phase is called the parent phase. Some properties of austenite and martensite phases differ significantly.^14–16 In the martensitic state, the material is characterized by high plasticity and is easily deformed. Heating a material with shape memory in the martensitic state leads to a transition into the austenite state, characterized by high rigidity. The transition temperatures depend on the conditions of the metallurgic processing and the alloy composition. If a shape memory material is subjected to deformation in the low-temperature phase, the deformation will be reversed, that is, it will return to its original shape after the transition to austenite. This is an example of the one-way shape memory phenomenon. The two-way shape memory material remembers two different shapes: one at low temperatures, and one at the high-temperature shape. The wire of one-way action does not automatically return to its initial state after cooling. The wire of two-way action automatically returns to its initial state after cooling.

Researchers have previously attempted to create intelligent textiles with self-regulating structures and performances from a blend of traditional textile materials and shape memory materials.¹⁹ Only in one study²⁰ was the possibility of creating elements of varying length under the influence of heat used. One-way NiTi wire spring-like elements were created and introduced between layers of aramid fabric, which was then exposed to a flame and characterized by increased heat resistance. The tested fabric is active at very high temperatures (flame) and can be applied only once, because after the experiment the material is charred and crushed, that is, it is not suitable for further use.

The aim of this paper was to develop a prototype of textile material with shape memory elements that has variable thermal insulation dependent on the emission-absorption of heat. The experiment was also directed to investigate the elaborated material at providing–subtracting heat using a suitable method.

Test methods for thermal characteristics can be classified into methods of measuring the steady-state and the transient state. There are many known measuring methods.^21–31 The methods often differ only by the introduced modifications. Particular attention should be paid to the recommended PN-EN ISO 15831³² method for testing the thermal insulation of the clothing ensemble, which simulates the practical effect of such a set per user. Elements of a set of garments are to be placed on a mannequin in the shape and size of an adult human with movable legs and arms. The test items of clothing are placed in the same order as in practical use. The mannequin is internally heated to a constant temperature of the coating surface. It is placed in a climate chamber in which the temperature can be set, and air speed, and the moisture can be adjusted. This method is suitable for testing in stationary conditions. As follows from the review of the standard and original methods, there is no method that can be applied to textile materials having thermal characteristics dependent on heat.

The study of thermal properties of materials with variable thermal parameters requires methods suitable for non-stationary conditions. Because in the literature there are no known standardized test methods for a transient state, the thermal properties were investigated using Michalak’s³³ contactless method.

The heat of the textile layer is transferred by thermal conductivity, convection and infrared (IR) radiation. In Nadzeikienė et al.,³⁴ a theoretical equivalent thermal conductivity coefficient taking into account all three heat transfer mechanisms was proposed to evaluate the total heat transfer in the air interlayer.

In our method, like in Nadzeikienė et al.,³⁴ the equivalent thermal conductivity was introduced.

In our previous studies^35,36 we described a new textile material characterized by two-way action. The thermal insulation of this material increased during heating and decreased during cooling, without any additional stimulus.

The present study is dedicated to the development of a textile material with similar two-way action but of the reverse operation. Its thickness decreases when heated and increases when cooled. Clothing made of this kind of material would constitute a smart garment that adapts its heat conductivity to its surroundings. In this study, like in Nadzeikienė et al.,³⁴ NiTi wire was used. The spirals have been subjected to “training” that allows them to increase in length during heating and reduce in length during cooling. Samples containing non-trained NiTi wires were also studied as a control group. The samples were designed on the basis of woven fabric, taking into account the possibility of examining the heat flow. The tested samples constitute a prototype of the envisioned final material. The final material can have a range of operating temperatures depending on the characteristics of the alloy present. This study employs a wire with a phase transition occurring at approximately 45℃. Thermal insulating properties were investigated by the contactless method using a thermographic camera. The first part of the study concerns the development of the active elements and the sample structure, while the second part focuses on developing test methods and a theoretical model for analysis of the obtained results.

Materials

Methodology

This study includes the preparation of active elements, the development of the active textile structures and a test stand, heat flow measurements and theoretical development of the obtained results. The active elements were prepared from shape memory wires. The activity range was determined by means of differential scanning calorimetry (DSC; Q2000),³⁷ which measures the differences in energy supplied between the test and reference samples that are either heated or cooled under the same conditions according to a specified program. The surface mass of the fabric used to make the tested textile structure was determined according to the PN-EN 12127:2000-1 standard,³⁸ the fabric thickness was determined according to the PN-EN ISO 9073-2-2002 standard³⁹ and the thickness of the measurement sample was determined according to the ISO 5084:1996 standard⁴⁰ using a device with a laser measuring instrument from P. J. Kontech Sp. z o. o. Thermal properties were determined by means of a non-standardized stand described later in this article.

Active elements

Active spirals were made of NiTi wire; after being deformed at a temperature lower than the transition temperature from the martensite to the austenite phase, NiTi wire recovers its initial shape after heating. The activity range within which the martensite phase passes to austenite was determined by DSC. The dependence of the heat flux and specific heat on the temperature is described in Figure 1. Measurements were made in heating–cooling–heating cycles.

Figure 1.

Dependence of heat flux and specific heat on temperature.

Figure 1 indicates a sharp decrease of heat flues at a temperature of approximately 45℃. This leads to the conclusion that the range of the phase transition is at a temperature of approximately 45℃.

Measurement samples

Measurement samples with layered structures were prepared for analysis. The first layer of each sample consisted of cotton woven fabric, the second layer featured a system of NiTi spiral elements and the final layer was made of Teflon foil with the nominal thickness of 0.2 mm. The woven fabric was of plain weave and the surface mass of the fabric was 200 g/m²; the thickness was equal to 0.2 mm, cv was equal to 1.9%, the number of warp threads was equal to 230 units/dm and cv was equal to 2.17%; the number of weft threads was equal to 230 units/dm and cv was equal to 2.17%. The linear density of warp and weft yarns was equal to 25 dtex and cv was equal to 2%. The Teflon foil was selected due to its high permeability to IR radiation, as this surface was in tests in direct contact with a heating element. The initial sample dimensions were 40 mm × 40 mm × 8 mm. One sample contained non-active spirals and the other contained active ones. A schematic of the measurement structure is shown in Figure 2.

Figure 2.

Diagram of the measurement structure at the temperature of 25℃. 1 denotes the woven fabric of 0.2 mm thickness, 2 denotes the spiral nitinol elements of 8 mm long and 3 denotes the Teflon foil of 0.2 mm thickness.

Each sample contains nine uniformly distributed spirals, that is, three rows of spirals with three spirals in each row.

Measurement set-up

A base with a high heat capacity was placed on the heater. The surface, on which a sample was placed, was covered with a layer of mat black paint. The sample was placed so as to provide contact between the Teflon layer and the base, and the temperature was recorded on the fabric surface. A SC550 FLIR camera was placed over the sample to record IR radiation. The base was then heated to a temperature of 60℃; this temperature was highly stable, and the temperature fluctuations (determined by means of thermovision) did not exceed the camera’s innate precision. A sample was placed on the base, and the temperature distribution on the surface was recorded as a function of the heating time. The recording was carried out with a frequency of two frames per second, over a recording time of 5 min. This time interval was selected after preliminary measurements showed that it was sufficient to obtain stable conditions.

Results and discussion

Active elements

In the first stage, spirals were made from NiTi wires according to a previously described method.³⁶ The spirals made in this stage do not react automatically to heat. In the next stage, the spirals were subjected to “training” that resulted in a decrease in the spiral length at heating and expansion after cooling.⁴¹ This means that the obtained spirals show two-way action under the influence of heating and cooling. This change in spiral length occurred in all observed spirals. The spirals show a high susceptibility to deformation in the cooled state, but invariably assume a spiral shape and two-way action after heating. Two types of spirals were used for testing, those being spirals subjected to training (active spirals) and untreated spirals (non-active spirals). Images of the active spirals at 25℃ and at 50℃ are presented in Figures 3 and 4.

Figure 3.

Spiral at the temperature of 25℃.

Figure 4.

Spiral at the temperature of 25℃.

Samples

Two prototype samples were prepared, one containing non-active spirals and the other containing active spirals. The spirals used in these samples contained five coils 3 mm in diameter and NiTi wire was equal to 0.18 mm in diameter. The wire length in each element in the initial straightened state was 45 mm. The average length of the expanded spiral was about 7.5 mm. The length of the heated spiral was about 1.75 mm, which means that the spiral efficiency reached about 400%. Different spirals were characterized by different values of elongation when heated, due to the fact that spirals are produced and trained without the use of factory equipment. Each spiral is produced and trained separately. Therefore, the dispersion of the properties of the spirals was observed; the non-uniformity of elongation did not exceed 20%.

In preliminary tests, the efficiency of the active measurement sample was verified. The sample thickness at the temperature of 25℃ was approximately 8 mm. After heating to 60℃, the sample thickness decreased to about 2.0 mm. The sample was characterized by a non-uniform expansion due to a spread in the spiral parameters. Photos of the samples at the temperatures 25℃ and 50℃ are shown in Figure 5.

Figure 5.

Color photographs of samples. 1 denotes the active sample at 25℃ and 2 denotes the active sample at 40℃. (Color online only.)

The resistance of the sample was also tested in regards to compressive strain. The sample was loaded and the dependence of its thickness d on pressure P was measured, as presented in Figure 6.

Figure 6.

Dependence of the sample thickness on pressure.

Figure 6 illustrates the decrease in the sample thickness under the influence of pressure. Once the pressure is removed, the spirals expand and the sample thickness assumes its initial value. A mechanically deformed sample (e.g. fully collapsed after heating and recooling) assumes its initial state once the pressure is removed, indicating that a garment made with this structure would maintain its expanded condition during use and would be more convenient to transport, as it could be flattened, folded or otherwise deformed to be transported. It would require slight heating (less than 1 minute at the temperature above the transient range) prior to use in order to assume its imparted shape without any loss of its imparted compression/expansion capabilities.

Thermal tests

As mentioned previously, the sample was placed on a hot base at a temperature equal to 60℃ and the distribution of the rising temperature on the outer sample surface was recorded.

Figures 7 and 8 show the color thermograms for the active and non-active samples at 300 s of recording.

Figure 7.

Color thermograms for the active sample at 300 s of recording. (Color online only.)

Figure 8.

Color thermograms for the non-active sample at 300 s of recording. (Color online only.)

Analysis of these thermograms distinctly shows that the active sample is characterized by a higher surface temperature at 300 s of recording than the non-active sample. Figures 7 and 8 indicate a distinct non-uniformity of the surface temperature during heating. The heat conductivity of the shape memory elements is considerably higher than that of air, leading to regular yellow, yellow-green colored areas (higher temperature areas) with circular shapes on the sample surface thermograms. These areas represent the surfaces of wire elements and promote a non-uniform temperature distribution. The thermal conductivity of spirals is higher than that of air and the areas covered by the spirals have a higher temperature. Due to differences between the particular spiral properties, the spacing between layers is not identical at each point. This is the next cause of the non-uniform temperature distribution seen in these thermograms.

The non-uniformity of the spiral elongation was caused by the fact that the spirals were manufactured separately in a laboratory setting, leading to differences in the manufacturing conditions, which subsequently affect the properties of each spiral. In the case of large-scale production, such uniformities could be easily eliminated.

On account of the structural non-uniformity present in the samples, areas of more uniform temperature distribution within rectangles with even geometries were selected for further analysis, as marked in Figures 7 and 8. The average temperatures were determined within the marked areas. Furthermore, in these smaller rectangular areas the uniformity of temperature distribution is higher than in the area covering the entire surface of the sample and the effect of the spirals is more visible and clearer. The purpose of the study was to demonstrate the applicability of active spirals to produce a material with variable thermal conductivity that is dependent on temperature.

One could perform a set of individual samples (for example, nine) consisting of a layer of Teflon and a spiral fabric layer and test each sample separately; measure the temperature of every separate sample; calculate the average temperature and standard deviation. However, here a sample consisting of nine single spirals was made and the possibilities of being coupled with camera AltaIR software and immediately determining the average temperature of each chosen area of sample was of benefit. There is no possibility to obtain the standard deviations; one can obtain histograms, T_mean, T_min, T_max, T_max – T_min, for every measurement time.

As an example, the histogram of the temperature of rectangular area of thermograms of active and non-active samples at 300 s of heating is shown in Figures 9 and 10.

Figure 9.

Histogram of the temperature of the rectangular area of the thermogram of the active sample at 300 s of heating.

Figure 10.

Histogram of the temperature of the rectangular area of the thermogram of the non-active sample at 300 s of heating.

One can approximate the standard deviation from these histograms. Some values of analysis of the rectangular area of the thermograms are presented below. The average temperature T_mean at 300 s of heating of the active sample is 58.6℃ and that of the non-active sample is 47.6℃. The lowest temperature T_min at 300 s of heating of the active sample is 47.53℃ and that of the non-active sample is 41.55℃. The highest temperature T_max at 300 s of heating of the active sample is 65.85℃ and that of the non-active sample is 55.06℃. The span length of the active sample is equal to 18.32℃. The span length for non-active samples is equal to 13.51℃.

The difference between the T_mean of active and non-active samples is equal to 11℃.

The dependence of the average temperature on the heating time for both active and non-active samples is presented in Figure 11.

Figure 11.

Dependence of the average temperature on the heating time of samples with active and non-active shape memory spirals.

These curves differ from one another in a significant and quantitative manner. The active sample reached 58.6℃ within 300 s, whereas in that same time period the non-active sample was heated to 47.6℃. The difference between these values is equal to 11℃. The calculated determination coefficient of these dependences is equal to 0.223, what means that the difference between them is significant. This difference indicates that the active sample is a better heat conductor and has lower heat insulation than the non-active sample.

Theoretical model

A theoretical model was developed allowing one to obtain the temperature changes on the external sample surface over time. In the theoretical model, the sample was considered using a Cartesian coordinate system, as described in Figure 12. The thin Teflon layer was neglected in this calculation, under the assumption that it had no influence on the calculation results due to its high thermal conductivity properties.

Figure 12.

The sample structure analyzed in the theoretical model in an xyz coordinate system with (1) the heating plate, (2) the layer containing the spirals and (3) the woven fabric layer.

The sample dimensions were designated as b_x, b_y and b_z respectively to the coordinate axes. The mathematical model describing the field of temperature in the sample tested was formed on the basis of Kirchhoff’s equation for three-dimensional (3D) systems^42–44

\frac{\partial}{\partial x} (λ_{x} \frac{\partial T}{\partial x}) + \frac{\partial}{\partial y} (λ_{y} \frac{\partial T}{\partial y}) + \frac{\partial}{\partial z} (λ_{z} \frac{\partial T}{\partial z}) + q_{v} + \frac{\partial λ_{x}}{\partial T} (\frac{\partial T}{\partial x})^{2} + \frac{\partial λ_{y}}{\partial T} (\frac{\partial T}{\partial y})^{2} + \frac{\partial λ_{z}}{\partial T} (\frac{\partial T}{\partial z})^{2} = c ρ \frac{\partial T}{\partial t}

(1)

where t is time (s), x, y and z are Cartesian coordinates (m), T is the absolute temperature (K), λ _x , λ _y and λ _z are the heat specific conductivity in the x-, y- and z-directions, respectively (W/m K), q_v is the calorific effect of the internal sources (W/m³), ρ is the apparent density of the textile product (kg/m³) and c is the specific heat (J/K kg). In general, the heat specific conductivity is a function of the coordinate and temperature, as λ = f(T,x,y,z).

Heat is carried out into the environment through free convection and IR radiation. The heat given up through convection is designated as Q_k and the emitted heat is denoted as Q_IR. The heat given up through convection can be written by means of formula (2)^42–44

Q_{k} = α_{k} (T_{p} - T_{0})

(2)

Here, α _k is the convection coefficient (J/K), T_p is the temperature on the surface releasing heat to the surroundings (K) and T₀ is the ambient temperature (K).

The emitted heat can be calculated from formula (3)^42–44

Q_{IR} = C [(\frac{T_{p}}{100})^{4} - (\frac{T_{o}}{100})^{4}] C = ɛ C_{0}

(3)

where C is a radiation constant, ɛ is the emissivity of the sample material and C₀ is a black body radiation constant,

W / m^{2} \cdot K^{4}

The basic task in developing this algorithm is to define the boundary conditions and the sample material parameters. In defining the boundary conditions for the analyzed sample, heat is supplied to the sample by means of the heating plate with a high heat capacity. In this model, the heat capacity of the heater is assumed to be high enough to maintain the whole surface at a constant temperature. Designating the heating plate temperature as T_m, the boundary conditions can be written as follows

For z = 0; 0 \leq x \leq b_{x}; 0 \leq y \leq b_{y} Q = 0 For z = b_{z}; 0 \leq x \leq b_{x}; 0 \leq y \leq b_{y} Q = 0 For x = 0; 0 \leq y \leq b_{y}; 0 \leq z \leq b_{z} T = T_{m} For x = b_{x}; 0 \leq y \leq b_{y}; 0 \leq z \leq b_{z} Q = (Q_{k} + Q_{IR}) For y = 0; 0 \leq x \leq b_{x}; 0 \leq z \leq b_{z} Q = (Q_{k} + Q_{IR}) For y = b_{y}; 0 \leq x \leq b_{x}; 0 \leq z \leq b_{z} Q = (Q_{k} + Q_{IR})

(4)

As the X and Y surfaces are near the textile electric contacts and are subjected to the action of heat emitted from the heating layer, we have assumed that there is no heat exchange with the environment at this location. The initial temperature of the sample is assumed to be equalized and equal to the ambient temperature T₀. To solve Equation (1) describing the heat field in the sample with the boundary conditions presented, commercial FlexPDE 6 software was used. The program transforms a system of partial differential equations into a system of finite elements, solves the equations and presents the results in a graphic or numerical form. The program includes all functions necessary to solve partial differential equations, an editor of the solution’s description, a generator to create a finite elements net, a software package for equation solving and a system for graphic interpretation of the results.

Once the sample parameters are defined, the parameters of a particular layer can be separately determined. The quantities characterizing the fabric layer were described previously in the paper. The Teflon layer was used to maintain the sample structure and was not taken into account in this model. The apparent density of the external layer (z), that is, the fabric, ρ _z , was 900 kg/m³, whereas the textile fabric specific heat c_z and specific heat conductivity were estimated on the basis of material data taking into account the contributions of the fibers and air. For this model, the following values were used: c_z = 2500 J/kgċK, λ _z = 0.035 W/mċK. The layer with the spirals, constituting the active part of the sample, was treated as a uniform substitute layer with parameters being derivatives of the constituent elements. The volume of the interlayer with active or non-active elements in the initial state was 1.28 10^–5m³, with a mass of 10.8 10^–3kg. As mentioned previously, both active and non-active samples were investigated.

The thickness was the same for both samples in the initial state. The non-active sample does not change its dimensions during heating, whereas the thickness of the active sample decreases, which leads to a decrease in the density of the sample interlayer space with the spirals. In this model, one can use a simple calculation of the apparent density, since the main relay of the heat energy is the metallic spirals of fixed density. A substitution method was used to take into account the change in the layer thickness through which the thermal flux transmits from the heater to the environment. Instead of changing the sample dimensions (which are not accounted for in this algorithm), the apparent density of the layer with spirals was increased. The initial density of both the non-active and active sample ρ₀ was estimated on the basis of literature data¹⁶ concerning the density of alloy material and the part of air in the sample. In the case of the non-active sample, this value remains constant during heating (i.e. during the measurement) and amounts to ρ₀ = 845 kg/m³. Meanwhile, the apparent density of the active sample ρ _NiTi increases, and at the end of the active sample measurement ρ _NiTi = 3360 kg/m³. Thus, when calculating the temperature on the external sample surface, we assumed a constant density of the non-active sample and a variable density resulting from the change in thickness during the measurement for the active sample, expressed using Equation (5)

ρ = 3360 \cdot ((1 - e^{(- t / 100))})^{3} kg / m^{3}

(5)

For the specific heats of both layers c₀ and c_NiTi, the same values were assumed considering that these quantities are influenced only by the specific heat of the spiral material, as c₀ = c_NiTi = 600 J/kg K.

Heat conductivity is a substitute conductivity determined by using the conductivity of the wire and that of air. Calculations were made assuming the specific heat conductivity of the area between the layers, described as

λ = 0.6 (1 - e^{- \frac{t}{300}})^{2} + 0.035, W / m \cdot K

(6)

The results of this calculation, together with the measurement results, are presented in Figure 13 for the active sample and Figure 14 for the non-active sample.

Figure 13.

The measured and calculated temperature dependence of the active sample heating time.

Figure 14.

The measured and calculated temperature dependence of the non-active sample heating time.

As shown, the calculations provide results similar to the experimental measurements. The determination coefficient for material with active elements is equal to 0.846, and the determination coefficient for material with non-active elements is equal to 0.748.

Conclusions

A prototype of textile material containing active elements with two-way action was developed from NiTi wires with one-way action. The developed textile material decreases its thickness when heated, leading to a decrease in its thermal insulation. By lowering of the temperature of the textile material, it increases its thickness as well as its thermal insulation. The temperature-time dependencies of material with active and non-active elements differ in a significant and quantitative manner. A theoretical model was developed to obtain the time dependence of these temperature changes, enabling us to determine the time variable thermal conductivity of this smart textile material. These findings could be used in the development of innovative garments with reversible and variable heat insulating parameters. This means that proposed material will be able to be used in the clothing industry for the production of smart clothing, the thickness of which will increase with decreasing of the temperature and will decrease with increasing of the temperature. Because it is possible to perform NiTi wires of different temperature phase transitions, it is possible to elaborate material active in a wide temperature range – from below zero to very high. The temperature range depends on the chosen shape memory material.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The manuscript was financed from funds assigned for 14-148-1-2117 statuary activity, by Lodz University of Technology, Department of Material and Commodity Sciences and Textile Metrology, Poland.

References

Forbes. http://www.forbes.com/sites/forbesstylefile/2014/05/07/what-is-the-future-of-fabric-these-smart-textiles-will-blow-your-mind/#1c7b1ae04914 (accessed 23 February 2017).

Skrzetuska

Puchalski

Krucinska

. Chemically Driven printed textile sensors based on graphene and carbon nanotubes. Sensors 2014; 14: 16816–16828.

Smart Textiles for Medicine and Healthcare. http://www.sciencedirect.com/science/book/9781845690274 (accessed 28 February 2017).

Krucińska

Skrzetuska

Urbaniak-Domagała

. Printed textiles with chemical sensor properties. F&T 2014; 22: 68–72.

Gliścińska

. Solvent vapour-sensitive activated carbon submicrofibres based on electrospun polyacrylonitrile fibre mat. F&T 2015; 23: 96–102.

Furtak

Skrzetuska

Krucińska

. Development of a screen-printed breathing rate sensor. F&T 2013; 21: 84–88.

Krucińska

Skrzetuska

Urbaniak-Domagała

. Prototypes of carbon nanotube-based textile sensors manufactured by the screen printing method. F&T 2012; 20: 79–83.

Gniotek

Krucińska

. The basic problems of textronics. Fibres Text East Eur 2004; 12: 45–45.

Januszkiewicz

Hausman

Nowak

et al.

Textile vee antenna made with PVD process. Int J Appl Electromagn Mech 2014; 46: 361–361.

10.

Januszkiewicz

Hausman

Kacprzak

et al.

Textile antenna for personal radio communications system– materials and technology. F&T 2012; 95: 129–133.

11.

Pinchuk

Goldade

. Smart materials in materials science. J Siberian Fed Univ Eng Technol 2013; 7: 805–817.

12.

Ölander

. An electrochemical investigation of solid cadmium-gold alloys. J Am Chem Soc 1932; 54: 3819–3833.

13.

Kauffman

Mayo

. The story of nitinol: the serendipitous discovery of the memory metal and its applications. Chem Educat 1997; 21: 1–21.

14.

Bojarski Z and Morawiec H. Metale z pamięcią kształtu (Shape-memory metals), Wydawnictwo Naukowe PWN, http://materialyinzynierskie.pl/nitinol-material-zpamiecia-ksztaltu/ pamiecia-ksztaltu (1989, accessed 28 October 2013).

15.

NiTi nitinol – material z pamiecia ksztaltu (NiTi nitinol – shape memory material). http://materialyinzynierskie.pl/wp-content/uploads/2013/08/przemiany-nitinol.jpg (accessed 28 October 2013).

16.

Cwikła A. Medyczne zastosowanie materiałów inteligentnych (The medical use of smart materials). In: Scientific Bulletin of Chemistry, Section of Technical Sciences, Nr. 1/2008.

17.

Vasile

Grabowska

Ciesielska-Wrobel

et al.

Analysis of hybrid woven fabrics with shape-memory alloys wires embedded. F&T 2010; 18: 64–69.

18.

Ahmad

Yahya

MHM

Hassan

et al.

Production of shape-memory alloy core-sheath friction yarns. F&T 2013; 21: 68–72.

19.

Stylios

Wan

. Shape memory training for smart fabrics. Trans Inst Measur Contr 2007; 29: 321–336.

20.

Russel DA, Elton SF, Squire J, et al. First experience with shape-memory material in functional clothing. In: Proceedings of the Avantex, International Symposium for High-Tech Apparel Textiles and Fashion Engineering with Innovation-Forum, Frankfurt-am-Main, Germany, 29 November 2000, pp.15–26.

21.

Chitrphiromsri P and Kuznetsov A. Modeling heat and moisture transport in firefighter protective clothing during flash fire exposure. Heat Mass Transf 2005; 41: 206–215.

22.

Artyukhin

. Iterative methods for estimating temperature-dependent thermophysical characteristics. High Temp High Press 1997; 29: 533–539.

23.

Balasubramaniam

Bosman

. Thermal conductivity and thermal diffusivity of biomaterials: a simultaneous measurement technique. J Biomech Eng 1997; 99: 148–154.

24.

Hryciuk

. Pomiar przewodności cieplnej i ciepła właściwego materiałów biologicznych. Acta Bio-Opica Inform Med 2000; 6: 81–86.

25.

Koniorczyk

. Wykorzystanie aparatów płytowych z ochronną płytą cieplną do pomiarów przewodności cieplnej materiałów izolacyjnych. Ciepłownictwo Ogrzewnictwo Wentylacja 1987; 6: 136–138.

26.

Kubicar

Bohac

. A stepwise method for measuring thermophysical parameters of materials. Meas Sci Technol 2000; 11: 252–258.

27.

Cernuschi F, Bison PG, Figari A, et al. Thermal diffusivity measurements by photothermal and thermographic techniques. Int J Thermophys 2004; 25: 439–457.

28.

Платунов СЕ. Теплофизические измерения и приборы, “Изд” Машиностроение’, Ленинград, 1986.

29.

Furmański

. Pomiary właściwości cieplnych izolacji. Część I 2001; 4: 34–37.

30.

PN-EN ISO 8497:1999. Izolacja cieplna. Określenie właściwości w zakresie przepływu ciepła w stanie ustalonym przez izolacje cieplne przewodów rurowych.

31.

Hughes

. Simple method for measuring pipe insulation performance. Therm Conduct 1994; 22: 425–434.

32.

PN-EN ISO 15831:2006. Odzież. Właściwości fizjologiczne. Pomiar izolacyjności cieplnej z zastosowaniem manekina termicznego.

33.

Michalak M. Study of the thermal conductivity of flat textile fabrics. Scientific bulletin of Lodz University of Technology, No. 1122, Łódź, 2012.

34.

Nadzeikienė

Milašius

Deikus

et al.

Evaluating thermal insulation properties of garment packet air interlayer. F&T 2006; 14: 52–55.

35.

Michalak

Krucińska

. A smart fabric with increased insulating properties. Text Res J 2016; 86: 97–111.

36.

Michalak M, Bilska J, Krucińska I, et al. Thermal actuator. Patent 213714, Poland, 2013.

37.

ISO 11357-4. Plastics – differential scanning calorimetry (DSC). Part 4: determination of specific heat capacity.

38.

EN 12127:2000. Textile fabrics - determination of mass per unit area using small samples, 2014.

39.

PN-EN ISO 9073-2:2002. Textiles - test methods for nonwovens - Part 2: determination of thickness.

40.

ISO 5084:1996. Textiles – determination of thickness of textiles and textile products.

41.

Michalak M and Krucińska I. A method for producing spiral from shape-memory material, intended in particular for smart textiles. Patent application P. 416190, Poland, 2016.

42.

Mихеев МА. Основы теплопередачи, Металлургиздат. Металлургиздат: Москва, 1949.

43.

Wiśniewski

. Wymiana ciepła, Wydawnictwa Naukowo-Techniczne, Warsaw: Wydawnictwa Naukowo-Techniczne, 2000.

44.

Staniszewski

. Wymiana ciepła, Państwowe Wydawnictwo Naukowe, Warsaw: Państwowe Wydawnictwo Naukowe, 1979.