Advances in Topographic Characterization of Textile Materials

7/22/2019 Advances in Topographic Characterization of Textile Materials

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Textile Research Journal Article

Textile Research JournalVol 0(0): 112 DOI: 10.1177/0040517509348331 The Author(s), 2009. Reprints and permissions:

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Advances in Topographic Characterization of Textile Materials

Alfredo Calvimontes1, Victoria Dutschk and

Manfred StammLeibniz Institute of Polymer Research Dresden, Hohe

Strasse 6, 01069 Dresden, Germany

Recent studies [13] have shown that textile constructionparameters, such as fineness of filaments and yarn, warpand weft density as well as the type of weave, control thetexture, surface topography, and morphology of fabrics.Fabric topography affects the porosity and strongly influ-ences the textile characteristics such as fabric mass, thickness,draping ability, stressstrain behavior, or air permeability.Moreover, there are significant differences between the soil-ing behavior and soil release of textile materials with dif-ferent topographic structures despite the similarity of theirchemical nature [46].

In the studies cited above, a large number of roughness

and waviness parameters were obtained that did not takeinto account the scaled-morphologic periodicity of eachsurface studied and its influence on the whole topography.All textile materials having periodic surfaces show somehorizontal and vertical repetitive patterns; therefore, dif-ferent length scales have to be taken into account for aproper interpretation of the topographic data measured[7].

Materials

Polyester fabrics of three different types of weave (Figure 1)were manufactured at the Institut fr Textil- und Beklei-dungstechnik (ITB) at the Technische Universitt Dresdenusing filaments produced by spinning of the same polymermaterial (polyethylene therephthalate). Warp yarn wasformed from flat filaments, while weft yarn was texturedby three different processes (Figure 2, Table 1).

Experimental methodsTopography measurements

An imaging measuring instrument was used for the opticalanalysis of the topography of textile materials, MicroGlider

Abstract All textile materials, having periodicsurfaces, show horizontal and vertical repetitiveunities. For this reason, different length scales haveto be taken into account by interpreting topo-graphic data measured. In this study, a topographi-cal characterization method for textile materials atdifferent length scales is presented and justified.The topographical study of textile materials usingdifferent length scales permits us to characterizethe surfaces considering their specific morpholo-

gies due to the type of weave, yarn and filament/fibers separately. The use of a scale concept tocharacterize textile surfaces seems to be a new skillthat helps to correlate textile parameters, topogra-phy, and topographical changes with interfacephenomena such as spreading, wetting, capillarypenetration, and soil release.

Key words textiles, roughness, different lengthscales

1Corresponding author: tel: +49 351 4658 212; fax:+ 49 351

4658 474; e-mail: [email protected]

Textile Research Journal OnlineFirst, published on October 13, 2009 as doi:10.1177/0040517509348331


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2 Textile Research Journal 0(0)RJRJ

(FRT, Germany). Unlike conventional microscopes, whichsimultaneously image all the points in the field of view andcapture a 2D image, a chromatic confocal microscoperecords only one object point per given unit of time. Thefield measured is constructed by xyscanning. This novel

optoelectronic setup based on a quasi confocal, z-axisextended field, was developed for high-resolution non-contact 3D surface metrology, including roughness charac-terization and surface flaw detection.

The instrument uses a chromatic white-light sensor(CWL), based on the principle of chromatic aberration oflight [8]. As can be seen in Figure 3, white light is focusedon the surface by a measuring head with a strongly wave-length-dependent focal length (chromatic aberration). Thespectrum of the light scattered on the surface generates apeak in the spectrometer. The wavelength of this peak alongwith a calibration table reveals the distance from the sensorto the sample. The sensor works on transparent, highly

reflective or even matt black surfaces [9]; it is extremely fastand has virtually no edge effects.

The instrument used allows a lateral measure range anda vertical measure range up to 100 mm and 380 m,respectively, and a lateral resolution and vertical resolutionup to 1 m and 3 nm, respectively.

In [10,11], the use of chromatic confocal microscopy tomeasure topography of textile surfaces was compared withthe use of high-resolution scandisk confocal microscopy(SCDM). According to these studies, wider cut-off lengthsand larger z-ranges make chromatic confocal imaging

Table 1 Textile parameters of filaments.

Yarn Number of filaments Structure Filament fineness [dtex]a Filament diameter [m] Yarn fineness [tex]a

Warp 128 flat 0.78 6 19.9

Weft 128 textured, tangled 0.92 7.5b 11.5

a Measured according to DIN 1973.1996; b before texturing.

Figure 1 Polyester fabrics used in

the present study.

Figure 2 Microscopic images of warp yarns (a), weft

yarns (b), warp filaments (c) and weft filaments (d).


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Advances in Topographic Characterization of Textile Materials A. Calvimontes et al. 3 TRJ

more appropriate than SCDM to measure topographicalcharacteristics of polyester and cotton fabrics.

Depending on the fabric characteristics, and the structureand size of repetitive units, other non-contact measurementmethods (scanning electron microscopy, Confocal laser scan-ning microscopy, Confocal Scanning Optical Microscopy(CSOM), Conoscopy holography (CSL), etc.) can be used. Itis absolutely necessary that a combination of cut-off length,z-range, and resolution have to provide statistically representa-tive topographical data. It is important to note that the

selection of a method due to its high resolution could beinadequate if the cut-off length available or z-range is toosmall. On the other hand, the use of a very high resolutionand larger cut-off lengths (scan areas) results in data whoseexcessive size could demand extremely long calculation timesand special or non-existent hardware and software.

Calculating Optimal Sampling Conditions

Cut-off length (Lm), defined as the length of one side of thesquare sampling area, and resolution (distance betweenmeasured points x, assuming that x =y) are the mostimportant sampling parameters, which apart from particu-

lar instrumental dependent parameters, such as light inten-sity, measuring frequency, etc., have to be optimally definedbefore characterizing topography.

Tsukada and Sasajima [12] and Yim and Kim [13] dis-cussed the problem of an optimum sampling interval (Lm)by checking the variance of the root mean square rough-ness (Rq) for a surface under different sampling intervals.According to Stout et al. [14], the recommendation men-tioned above for the choice of sampling interval is doubtfulbecause of the fact that optimumLmseems to influence theamplitude parameters (wave height Wtand waviness Wz).

The use of tables that relate predicted values of themean rough height (Rz), the root mean square roughness(Rq), and arithmetic mean roughness (Ra) to Lm is fre-quently recommended to set the optimal value of Lm forperiodic as well as non-periodic surfaces. As optimal sam-pling conditions are strongly dependent on the type of mate-rial to be characterized, researcher experience is usuallyrequired. For this reason, a systematic procedure to defineoptimal cut-off length and resolution values is proposed:

1. Acquiring topographical data at the highest resolu-tion available (minimal value of x) using different

Lmvalues. Here two different procedures are recom-mended:(a) only one measurement at the highest Lm and

posterior zooming (sub-area extractions), or(b) independent measures using the same zero point

position.

2. The use of statistical criteria in order to define anoptimal value of Lm by analyzing Wz, Rz, and Racurves as functions ofLm.

3. Acquiring topographical data with the defined opti-malLmusing different values of resolution.

4. The use of statistical and topographical criteria toanalyze Rz and Ra as functions of x, in order todefine an optimal resolution.

Woven plain and twill polyester fabrics were used to probethe presented procedure concerning optimization of sam-pling conditions. Figure 4 shows that the waviness of wovenplain fabrics is statistically reliable aboveLm = 2 mm, but in

the case of twill fabric, the optimal cut-off length has to behigher than 3 mm. However, this reasoning takes only intoaccount the statistical behavior of Wz. By applying fast Fou-rier transform (FFT) filtering [15], the waviness images cal-culated, as illustrated in Figure 5, show that almost constantvalues of Wz, as shown in Figure 4, correspond in both casesto a quantification of plane irregularities (wrinkles) of thefabrics.

If the characterization is aimed at the morphologyquantification caused by the fabric structure, the calcula-tion of the waviness has to be realized using Lm in therange of 0.5 to 1 and 1 to 2 mm for woven plain and twillfabrics, respectively.

In the characterization case aimed at the study oftopography of the complete fabric surface without regard-ing the fabric structure (morphology), the recommended

Lmvalue is 3 mm for both fabrics, since over this cut-offlength the values of Rzand Ra remain approximately con-stant (cf. Figure 4).

ByLm = 3 mm, different resolution values were used toobtain new topographical data. Figure 6 shows that a lat-eral resolution of 4 m is enough to produce reliable infor-mation concerningRz. On the other hand, values ofRaandtheir correspondent standard deviation (cf. Table 2) show

Figure 3 Schematic presentation of the measuring prin-

ciple of chromatic confocal microscopy.


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that, using Lm = 3 mm, the arithmetic mean roughnesshardly depends on resolution. However, standard devia-

tions ofRafor woven plain and twill fabric obtained usingLm = 1 mm are 0.51 and 0.62, respectively, which areclearly much more dependent on resolution.

Topographic Characterization

As shown in Figure 5, topographic parameters obtainedby FFT filtering provide different types of informationdepending on the cut-off length used. Due to the structuraldiversity of textile materials, their classification by unit sizeand morphology on different length scales is necessary. Asuggestion to find the general range values of Lmin orderto identify the different measurable length scales is notreasonable. However, the specification of at least three dif-ferent length scales (macro-, meso- and micro-scale) isabsolute necessary to describe morphologically the homo-geneous textile groups. From a conceptual point of view,each one of the length scales proposed for a textile struc-

ture has to provide specific information about the surfacemorphology and topometry of the materials. In all cases,the highest available lateral resolution by confocal chro-matic imaging (x=1 m) was used, while the value ofLmwas the parameter used to determine the length scale to bestudied.

Results and Discussion

Textile Macro-topography

Macro-morphological irregularities of textile surfaces such

as folds and wrinkles can be studied using FFT filtering oftopographical data measured by large values of Lm. A cut-off length value larger than 3 mm was suggested above toquantify the plane irregularities (waves and wrinkles) of thefabrics. In order to provide the macro-topographical infor-mation desired, according to the large amount of topo-graphical data measured for three different types of wovenpolyester textile surfaces (plain, twill, and Panama), a totalmeasured area (Lm Lm) should cover at least 169 (13

2)repetitive units (r.u.). In 3D-waviness diagrams Wz values(Figure 7) can be used as macro-morphological parameters,especially to characterize changes that occurred after treat-ment. In this case, the characterization has to be accompa-

nied by quantification of the 2D relaxation/shrinkage (cf.ISO 5077:2007) that occurred while wetting or duringmechanical processes, or by a combination of both.

Dimensional changes (relaxation/shrinkage) of fabricson a macro-scale influence their meso- and micro-topogra-phy due to the modification of the repetitive unit dimen-sions and, therefore, the distances between yarns,filaments, and fibers [16].

In Figure 7, only the macro-waviness diagram for wovenplain fabric does not show any morphological influence ofrepetitive unit morphology; in this case, r.u. > 132. For

Table 2 The Ravalues of the studied fabric by Lm= 3 mm

are nearly independent of the resolution up to x= 30m.

x[ m] Ra[ m]

woven plain twill

1 15.67 17.24

2 15.69 17.26

3 15.79 17.39

4 15.68 17.23

5 15.79 17.38

30 15.70 17.17

= 0.056

= 0.070

Figure 4 Topographic parameters for polyester fabric

surfaces as functions of Lm.


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macro-topographical characterization of twill and panamatypes, their optimalLmvalues have to be larger than 5 mm.

Textile Meso-topography

The meso-scale of textile materials should be used todescribe the surface topography produced by the type ofweave and yarn used, without considering the previouslydefined macro-topographic irregularities and details corre-

sponding to fibers or filaments. A study of fabric surfacetopography on a meso-scopic scale using FFT filteringstarts with the selection of a new optimal Lm value, whichbasically depends on the size of the fabric repetitive unit.From the large amount of experimental data for polyesterfabrics studied, it was revealed that a sample area (Lm Lm)has to cover about eight repetitive units (Table 3).

Another way to construct meso-topographic diagrams isthe use of digital surface filtering, which calculates thearithmetical mean of each data point within its neighbor-hood [14,15,17]. The filter density used depends on the

Figure 5 Waviness images of polyester fabric surfaces as a function of Lm.

Figure 6 Mean roughness of polyester fabric surfaces as

a function of x.


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fabric characteristics and has to be able to produce a sur-face without topographical details of fibers or filaments.Figure 8 shows the construction of meso-topographic sur-faces by using FFT filtering and smooth filtering. In orderto compare the morphologies and Wz values obtained,Lmand the filtering method used should remain the same dur-ing the characterization process.

An application of the study on these length scalesclaims to know the relativez-distances between warps andwefts for woven fabrics and the amplitude of their wave(sinoidal) trace. As shown in Figure 8, wefts describealmost a linear trace (their amplitudes are small). As aconsequence, the first contact of any solid with the fabric

surface takes place by the warps (hills) and the final pen-

etration of fluids on the fabric surface takes place princi-pally on wefts (valleys). This finding plays a crucial rolein understanding the wetting behavior of textile materials[16].

The application of volumetrical characterization crite-ria allows us to investigate the topographical conditions forfluids spreading over the surfaces (a connection betweenmeso-morphology and spreading was presented in [16]). Aheight value (hv) can be found to divide all data points intotwo groups: those forming mountains and those formingcanals between the mountains. There are two condi-tions forhv: (i) to be as small as possible and (ii) that thecanals be connected in order to allow flow in all possible

directions. In the case of twill and panama fabrics, due totheir more anisotropic morphology, independent but end-less canals can be formed. In the case of woven plain struc-tures, all canals are connected to each other (Table 4).

Textile Micro-topography

Unlike macro- and meso-scales, characterization at a microlength scale reveals the influence of filament and fiber char-acteristics on the resulting topography. Profile, fineness, aswell as the natural or machined texture of these elements or

Figure 7 2D images (left) and 3D

waviness diagrams (right) with Wzvalues for woven plain (a), twill (b)

and panama (c) polyester fabrics.

Table 3 Lmthat contain about eight repetitive units are

optimal to characterize the meso-topography.

Unit area [mm2] Lm

[mm] r.u.

Woven plain 0.126 1.0 7.94

Twill 0.396 1.8 8.18

Panama 0.478 2.0 8.37


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Table 4 Volumetrical characterization parameters by dividing the z-range according to the hvcriteria. Smooth filtering (80%)

was used to obtain the meso-topography.

plain twill Panama

Lm[mm] 1 1.8 2

Wz[m] 64.41 78.73 96.76

hv[m] 31.94 46.66 41.36

Canals z-range (hv/Wz) [%] 49.6 59.3 42.7

Canals area [%] 58.0 66.4 40.5

Canals volume [ m3/ m2] 6.787 10.083 5.300

Figure 8 Meso-topography of different polyester fabrics by FFT filtering and smooth filtering.


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the distances between them are only some of the possiblecharacteristics which define the resulting morphology andtopometry at this length scale.

The selection of an optimal cut-off length in this case no

longer depends on some statistical or mathematical criteriaas seen at macro and meso length scales, but rather on thesize and location of the set of filaments or fibers by typeand orientation. To study the micro-topography of wovenplain fabrics, warps and wefts should be zoomed separately(sub-area extraction). Optimal Lm values of warps andwefts depend on the type of weave and construction param-eters such as yarn types, their diameters, warp densities, weftdensities, etc. Depending on textile structure, more than one

Lm value could be necessary for a complete micro-topo-graphical characterization, as shown in Figure 9.

The number of sub-areas to be isolated depends on thetopographical parameters studied and on the standarddeviations of their mean values. Usually five differentzooms should be enough to characterize polyester monofil-

ament fabrics. Depending on the characterization criteria,the elimination of micro-waviness, a consequence of yarnprofile and fabric meso-topography, is possible by FFT fil-tering, as shown in Figure 10.

Using the new topographical data generated, it is possi-ble to calculate any micro-topographical parameter by pro-filing or by using the whole surface. The volumetricalcharacterization is a good tool to measure textile surfacesthrough the evaluation of porosity or filling quantities at dif-ferent deep heights. The calculation of the skewness, kurto-sis or surface relative smooth (SRS) [10] can be important

Figure 9 Optimal Lmvalues for the

characterization of warps and wefts

micro-topography separately at the

surface of woven plain polyester

fabric.

Figure 10 Micro-topographical ima-

ges of a warp and a weft. The eli-

mination of micro-waviness was

possible by FFT filtering.


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for studies of surface modification treatments such as byheat setting or plasma modifications. Fractal dimension orWenzel roughness factor could be of interest to character-ize micro-topographical modifications of natural fibers,e.g. changes caused by enzymatic action.

Example of Application 1: Meso-topography

and SpreadingIn [10,16], 14 different polyester fabrics having plain, twill,and panama structures were characterized to show how theuse of topographic characterization at different scales canprovide important information of the spreading behavior.

On the basis of macroscopic water drop base changesmeasured with a dynamic contact angle tester (Fibro DAT1122, Fibro System, Sweden), the wetting behavior of awater drop can be divided into three regimes (Figure 11):dynamic wetting, defined as growing of the drop diameterdepending on time (also known as spreading); quasi-staticwetting, where the drop diameter remains approximatelyconstant; and penetration, which is marked by liquid drop

absorption into fabrics depending on time. By using the wav-iness as meso-topographical parameter, it is evident that themeso-topography of the fabrics controls the spreading rateof a liquid drop (Figure 12). For the plain weave, an increaseof the waviness depth causes a decrease of the spreadingrate; warp yarns (hills) slow down the liquid motion (Fig-ure 13). For twill weave, an increase of the waviness depthcauses formation of deep and long domains of weft yarns(canals) with small islands. As a consequence, anincrease of the spreading rate is observed. Finally, for pan-ama weave, an increase of the waviness depth causes for-

mation of long and quasi-endless (without islands) deepdomains (canals). Consequently, the waviness depth andspreading rate are proportional to each other.

A thorough comparison between topographic parame-ters for the 14 fabrics having three different types of weavesreveals that the respective morphology at a meso lengthscale controls the spreading rate.

Example of Application 2: Micro-topography,Wetting and Cleanability

At a smaller scale, by zooming of warps and wefts sepa-rately, topography measurements and characterization atdifferent length scales provide important informationabout changes in textile microstructures. Using this infor-mation, the behavior of a liquid drop on a fabric surfacewhile wetting can be explained. In [10,16], on the basis ofexperimental results, revealing differences in three basictypes of woven fabrics plain, twill, and Panama in respectto capillarity and water penetration (Figure 14), the conceptof a novel wicking model was developed. This conceptual

model was verified in respect to the cleanability behavior ofparaffin oil and acetylene black soils.

The results illustrated in Figure 14 show that: (i) warpyarn topography hardly affects the cleanability; (ii) spacesbetween fibers make the plain weave surface oleophil (thelarger they are, the more stains penetrate); (iii) spacesbetween fibers make the twill weave surface oleophob. Thelarger and deeper they are, the more stain penetrates andthe worse their cleanability and (iv) the weft yarn roughnesscontrols the hydrophobicity or hydrophilicity of fabrics and,as a consequence, their cleanability (cf. Figure 15).

Figure 11 Three different wetting regimes for a textile

surface.

Figure 12 Dynamic wetting: meso-morphology controls

the spreading rate of a liquid drop on a textile structure.


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Conclusion

The topographical study of textile materials using a lengthscale concept allows us to characterize surfaces separatelyby considering and analyzing their specific morphologiescaused by the type of weave, yarn, and filament/fibers.

With the resulting information, the correlation oftopography and topographical changes due to modificationprocesses, such as heat setting, impregnation, and washdry cycles with interface phenomena such as spreading,wetting, capillary actions, and cleanability, is more specificand explanatory.

Acknowledgements

This research is financially supported by Sasol GermanyGmbH. The authors are grateful to Dr Beata Lehmannand Dr Birgit Mrozik (both from the Institut fr Textil- undBekleidungstechnik, Dresden) for providing textile materi-als.

Figure 13 Respective textile mor-

phology at a meso-length scale

controls the spreading rate. Above:

morphology; below: spreading di-

rections of a liquid drop.

Figure 14 Liquid flow in the warp and weft directions occurs by two different regimes, depending on micro-topography.


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Advances in Topographic Characterization of Textile Materials