CHARACTERIZATION OF SURFACE FINISHES ON...

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CHARACTERIZATION OF SURFACE FINISHES ON TEXTILES BY IN-LINE NIR CHEMICAL IMAGING 3rd OCM Karlsruhe , 22-23. März 2017 Gabriele Mirschel, 1 Olesya Daikos, 1 Tom Scherzer, 1 C. Steckert 2 , K.Heymann 1 1 Leibniz Institute of Surface Modification (IOM), Leipzig, Germany 2 LLA Instruments GmbH, Berlin, Germany

Transcript of CHARACTERIZATION OF SURFACE FINISHES ON...

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CHARACTERIZATION OF SURFACE FINISHES ON TEXTILES BY IN-LINE NIR CHEMICAL IMAGING

3rd OCM Karlsruhe , 22-23. März 2017

Gabriele Mirschel,1 Olesya Daikos,1 Tom Scherzer,1 C. Steckert2, K.Heymann1

1 Leibniz Institute of Surface Modification (IOM), Leipzig, Germany2 LLA Instruments GmbH, Berlin, Germany

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3rd OCM, Karlsruhe, March 22-23, 2017

Motivation

Germany is global market leader in the production of technical textiles (polyester, polyamid or cotton)

Working widths up to 4 m

Typical applications: Materials for automotive (roof-liner or seat cover), ink-jet printing (banners), curtains, functional clothing, …

Wet-chemical surface finishing of textiles Coating weight, homogeneity

Finishes: Stiffening, flame retardant, wett-able, hydrophobic, stain-resistant, anti-static, brightening, …

Well-established production processes, butnowadays with very high quality require-ments Process monitoring necessary

Residual moisture of textiles after drying

Detection and identification of contaminants

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3rd OCM, Karlsruhe, March 22-23, 2017

Surface Finishing of Textiles

Finishes

Optical brighteners

Flame retardants

Hydrophobizing agents

Stiffening agents

Sizes

Improve the processabilityon textile machines

Have to be removed before the further processing steps

Textiles

Polyester

Cotton

Wet-Chemical Treatment

Process Steps

Treatment in aqueous disper-sion

Squeezing in a foulard

Drying and heat setting

Objectives of Chemical Imaging

Applied quantity (finishes)

Cleanness (sizes) extremely impor-

tant for further processing

Homogeneity

Detection and identification of impuri-ties: oil, grease, processing agents, … (often poorly visible)

Degree of dryness

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3rd OCM, Karlsruhe, March 22-23, 2017

Highlights

Quantification of Flame Retardants

Monitoring of Desizing/Cleaningness of Textiles

Identification of Contaminants

Monitoring of the Moisture Content

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3rd OCM, Karlsruhe, March 22-23, 2017

NIR Camera System

Mounting of the NIR camera above a conveyor belt at IOM

KUSTA1.9 MSI (LLA Instruments, Berlin, Germany)

InGaAs sensor, TE-cooled

192 x 96 pixel (spatial x spectral resolu-tion)

Spectral range 1320-1900 nm(option: 1280-2200 nm)

NIR objective 15 mm/2.0 (Specim)

Lateral resolution ~2.6 mm

Frame rate max. 795 Hz

Illumination unit with 8 NIR lamps (120 W)

Conveyor belt with a highly absorbing black PUR coating (width 0.5 m, 2-60 m min-1)

Working width up to 1000 mm ( vertical

mounting distance 1 m)

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3rd OCM, Karlsruhe, March 22-23, 2017

Calibration Process

1300 1400 1500 1600 1700 1800 1900

0.0

0.2

0.4

0.6

0.8

1.0

untreated

4.6 g m-2

13.19 g m-2

25.65 g m-2

39.80 g m-2

51.31 g m-2

Reflectivity

Wavelength [nm]

Fig. 1: NIR spectra (normalized) of PES fabric

untreated and treated with a flame retardant.

Aminourea: CH5ON3

N-H asymmetric and N-H symmetric

combination vibration at 1500 nm

NIR Imaging = indirect method

calibration is necessary

Samples with a coating weight from

5-52 g/ m-2 were prepared

(sample size 30 x 40 cm)

Random 5000 spectra of each

sample were taken + related to

corresponding coating weights

Various preprocessing methods

were applied

PLS model with lowest RMSEP and

highest R2 was choosen

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3rd OCM, Karlsruhe, March 22-23, 2017

Calibration – Flame retardant on PES fabric

6.8 6.9 7.0 7.1 7.2 7.3

-0.15

-0.10

-0.05

0.00

0.05

0.10

0.15

0.20

0.25

untreated

4.6 g m-2

7.6 g m-2

13.2 g m-2

25.6 g m-2

39.8 g m-2

51.3 g m-2

Score

s P

C2

Scores PC1

Fig. 2 : Scores plot PC2 against PC1 of

samples with and without flame-retarding

agent.

0 20 40 60

0

20

40

60

EV 3

RMSEE 1.78 g m-2

Bias -0.014 g m-2

SEC 1.78g m-2

RMSEP 2,07 g m-2

Bias 0.524 g m-2

SEP 2.01 g m-2

R² 98.67 %

r² 0,9933

Pre

dic

ted C

oating W

eig

ht

[g m

-2]

Gravimetrical Coating Weight [g m-2]

Fig. 3: PLS regression of a calibration

model for the coating weight of a flame

retardant on PES fabric.

RMSEP in external validation: 4.2 g/m²

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3rd OCM, Karlsruhe, March 22-23, 2017

Manual Wet-Chemical Treatment of Textiles

Chemical images of a polyester fabric (194 g/m²), provided with a flame retardant based on phosphates and amidourea

Coating weights:10.8 g/m² (left) und 20.4 g/m² (right)

Coating weights:15.5 g/m² (left) und 26 g/m² (right)

Distribution of a flame retar-dant on cotton

Distribution of a flame retar-dant on polyester fabric

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3rd OCM, Karlsruhe, March 22-23, 2017

Wet-Chemical Treatment of Textiles

Laboratory-scale foulard for well-defined squeezing of wet textile samples

Coating weight 13.2 g/m²

Coating weight 26.3 g/m²

Coating weight 43.1 g/m²

Chemical images of a polyester fabric, provided with a flame retardant on a foulard

RMSEP in external validation:

2.1 g/m²

Blots result from dried droplets of the flame retardant dripped to the squeezed textile

Tracks result from pinning-on

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3rd OCM, Karlsruhe, March 22-23, 2017

Desizing / Washing of Textiles

Coating weights: 5.3 g/m² (top)0.4 g/m² (bottom)

RMSEP 0.4 g/m²Detection Limit

Sizes

Improve the processabilityon textile machines

Can strongly affect further processing such as printing, finishing, lamination, …

Have to be completely removed before the further processing steps

Distribution of fatty acid ethoxylate used as size on a polyester fabric before and after desizing

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3rd OCM, Karlsruhe, March 22-23, 2017

Detection of Blots of Contaminants

Finishes, sizes, oils, greases, processing agents, etc.

May drop on the textile web during processing

In most cases, dried blots are invisible in the VIS region

Blots can strongly affect further processing such as printing, finishing, lamination, …

Detection and identification by chemical imaging

Differentation between mineral oil and silicon grease (synthetic)

=> PCA analysis

Identification of various oils and greases on a cotton fabric

NIR spectra of oils and greases

1300 1400 1500 1600 1700 1800 1900

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

Re

fle

ctivity a

.u.

Wavelength [nm]

Cotton Fabric

Machine Oil

Vacuum Grease

Silicon Grease

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3rd OCM, Karlsruhe, March 22-23, 2017

Determination of Contaminants

Dried droplet of a fatty acid ethoxylate used as size on a polyester fabric

Blot of a size based on amixture of paraffin andpolyethylene on a polyesterfabric

Detection of invisible traces of various textile finishing agents on cotton

Cotton

PVAc (Stiffening)

Phophate+ Amidourea (Flame Retardant)

Styryl Benzene (Brightener)

Phosphate (Flame Retardant)

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3rd OCM, Karlsruhe, March 22-23, 2017

Drying of Textiles – Preliminiary Test

25 sec30 sec

20 sec

Drying of cotton fabric using a flat iron (preliminary test, semiquantitative data: distance in the scores plot)

DryAlmost dry

Wettish

Dampish

Very wet

Saturated1400 1500 1600 1700 1800 1900

0.0

0.2

0.4

0.6

0.8

1.0

Inte

nsity

Wavelength [nm]

0.5%

5%

11%

17%

24%

32%

59%

100%

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3rd OCM, Karlsruhe, March 22-23, 2017

Drying of Textiles

36 % r.H.

46 % r.H.

62 % r.H.

Chemical images of polyester fabric with different moisture contents (after 30 min in a conditioning cabinet)

RMSEP in external validation:

2.9 %

Sample

relative

Humidity

[%]

relative

Humidity

NIR

[%]

Difference

[%]

1 36 37.2 1.2

2 45 47.1 2.1

3 55 56.6 1.6

Temperatur ~ 60°C

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3rd OCM, Karlsruhe, March 22-23, 2017

In-line Monitoring of the Moisture at a Stentering Frame

100 %

0 %

In-line monitoring of the moisture con-tent of a polyester web pinned on a sten-tering frame in the Textile Research In-stitute (TITV) Greiz after spraying wateron the fabric

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3rd OCM, Karlsruhe, March 22-23, 2017

Summary

Coating weight and homogeneity of layers applied by wet-chemical surface finishing of textiles

Precision (RMSEP): ca. 1…2 g/m² depending on the

specific system

Residual amounts after washing of textiles

Detection limit ~0.5 g/m²

Detection and identification of contaminants

Determination of the residual moisture of textiles

Precision (RMSEP): < 3 % (preliminary tests only)

Objective: In-line monitoring of textile production processes

* G. Mirschel, O. Daikos, T. Scherzer, C. Steckert, Anal. Chim. Acta 932, 69-79 (2016)

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3rd OCM, Karlsruhe, March 22-23, 2017

Acknowledgments

Udo Trimper (IOM)

Manfred Hinkefuß (IOM)

Andreas Neudeck

Hans-Jürgen Weiß

TITV Textile Research Institute, Greiz

C.H.Müller, Heinsdorfergrund

Thorey Textilveredelung, Gera

AiF, Berlin