Structure-Property Relations in Polymers - American Chemical Society

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9 Qualitative Identification of Polymeric Materials Using Near-Infrared Spectroscopy Huston E . Howell and James R. Davis Research and Development, Fibers Division, BASF Corporation, Enka, N C 28728

During the past decade near-infrared (near-IR) spectroscopy has become a widely used analytical technique. Most applications have been for quantitative analysis. In the past several years, near-IR spectroscopy has been successfully used for qualitative analysis through the use of computer-assisted data processing. Two major methods of data analysis have yielded successful results: discriminant analysis and spectral searching. Discriminant analysis is useful for discrete wave length spectra obtained with bandpass filters and continuous spectra obtained with a scanning monochromator. Spectral searching of first derivative spectra is used for continuous spectra from a scanning monochromator. In this study, we demonstrate the ability to qualita tively identify various textile fibers and thermoplastic polymers with near-IR spectroscopy using these two methods.

ΙΝίEAR-INFRARED SPECTROSCOPY has b e e n w i d e l y used f o r over a decade f o r quantitative measurements i n many areas. Extensive calibration algorithms and diagnostic statistics have b e e n developed ( I , 2 ) . Recently the potential o f near-IR spectroscopy as a qualitative identification technique has b e e n recog nized. T h e near-IR region is c o m p r i s e d o f overtones ( 1 1 0 0 - 1 8 0 0 n m ) a n d combinations ( 1 8 0 0 - 2 5 0 0 n m ) o f the fundamental vibrations o f the m i d - I R region. B a n d assignments f o r many c o m m o n organic compounds have b e e n made ( I , 3). I n general, visual interpretation o f spectra is more difficult than 0065-2393/93/0236-0263$06.75/0 © 1993 American Chemical Society

Urban and Craver; Structure-Property Relations in Polymers Advances in Chemistry; American Chemical Society: Washington, DC, 1993.

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i n the m i d - I R region because o f the nature o f the bands (i.e., overtones a n d combinations). T h e spectral bands are often overlapped, a n d differentiation between similar materials appears less definitive than i n the m i d - I R region. I n spite o f these apparent disadvantages, the n e a r - I R region provides useful qualitative information, especially w h e n computer-assisted data analysis tech niques, such as multivariate statistics and spectral searching, are used. M a r k a n d T u n n e l ( 4 ) demonstrated the qualitative classification o f various materials using discriminant analysis w i t h Mahalanobis distances. L o a n d B r o w n ( 5 ) demonstrated the ability to qualitatively identify materials using c o m p u t e r i z e d spectral library searching. C i u r c z a k a n d co-workers (6,7) used qualitative n e a r - I R spectroscopy for a variety o f applications i n the pharmaceutical area. G h o s h a n d Rodgers demonstrated the ability to identify heat-set type a n d distinguish nylon 6 f r o m n y l o n 6,6 using n e a r - I R d i s c r i m i nant analysis (8). I n this study, w e examine the usefulness o f n e a r - I R spectroscopy to quafitatively identify various textile fibers a n d thermoplastic polymers. Q u a l i tative identification is very important w h e n w o r k i n g w i t h p o l y m e r i c materials. Consistency of composition, to a large extent, determines the consistency o f physical properties that impact all aspects o f usage: f r o m quality control i n manufacturing to performance of the final product. Because our intent was to p e r f o r m an e m p i r i c a l survey o f the qualitative capabilities, w e d i d not attempt to extensively interpret relationships between spectra a n d c h e m i c a l struc tures. A l t h o u g h such a fundamental exercise w o u l d be useful, it is b e y o n d the i n t e n d e d scope o f this investigation. Overall, w e f o u n d that near-IR spec troscopy is a very useful technique for the qualitative identification o f p o l y m e r composition, especially w h e n computer-assisted data analysis tech niques are used.

Qualitative Identification Using Discriminant Analysis D i s c r i m i n a n t analysis using Mahalanobis distances, w h i c h is a multivariate statistical technique for classifying groups, has p r o v e d to be a p o w e r f u l technique i n qualitative spectroscopic identification. T h i s technique was demonstrated a n d thoroughly described b y M a r k a n d T u n n e l (4). Initially, a calibration set that consists of " k n o w n " materials (i.e., standards) is analyzed. T h e discriminant analysis program (used i n this study) calculates the ab sorbance relationships at various wavelengths for each sample, a n d t h e n mathematically selects a set o f wavelengths that best reveal the differences between groups of materials that are identified as b e i n g o f similar composi tion. I n practice, three to six wavelengths usually are adequate to p r o v i d e good classification. F i n a l l y , the results are expressed as the Mahalanobis distances between the various groups. A n intergroup distance 15 or m o r e generally indicates that discrimination is feasible. W h e n the calibration is


9.

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Near-IR Spectroscopy

265

complete, " u n k n o w n s " are analyzed to determine i f they are similar to any o f the calibration samples.


Qualitative Identification Using Spectral Searching Qualitative identification c a n also b e p e r f o r m e d b y c o m p u t e r i z e d spectral library searching. T h e spectrum o f an u n k n o w n material is c o m p a r e d w i t h the spectra o f reference materials. T h i s approach is w i d e l y used i n t h e m i d - I R region to identify u n k n o w n materials. Spectral searching programs may vary according to t h e particular vendor; however, most operate i n t h e same general manner. T h e c o m p u t e r mathematically compares the spectrum o f the u n k n o w n w i t h a set o f reference spectra. T h e results are expressed i n a listing o f reference materials, w h i c h is rank-ordered b y the goodness o f agreement between the spectrum o f the u n k n o w n a n d the spectrum o f each reference material. F o r the particular software used i n this study, the goodness o f the m a t c h is expressed b y a n u m e r i c a l value called the h i t quality index ( H Q I ) . A H Q I = 0 indicates a perfect spectral m a t c h w i t h n o dissimilarity. T h e good ness o f match decreases as t h e H Q I increases. T h e spectral search p r o g r a m also displays the spectrum o f the u n k n o w n material o n the c o m p u t e r m o n i t o r together w i t h each h i t f r o m the spectral library to allow the user to visually compare the spectra.

Experimental Details T h e various textile fibers studied i n c l u d e most o f those c o m m o n l y e n c o u n t e r e d i n the textile industry: p o l y (ethylene terephthalate) ( P E T ) , polypropy lene, cotton, acrylic, w o o l , rayon, a n d n y l o n . Spectra o f the fibers were obtained f o r several different forms o f each fiber type, such as variable deniers, w i t h a n d without t i t a n i u m dioxide, yarn a n d fabric f o r m , a n d staple a n d continuous filament. Twenty-five w i d e l y used thermoplastic materials w e r e analyzed: p o l y (vinyl chloride) ( P V C ) , p o l y (vinyl acetate) ( P V A c ) , p o l y (methyl methacrylate) ( P M M A ) , p o l y ( v i n y l i d e n e fluoride) ( P V D F ) , polyacetal ( P A ) , n y l o n 6, n y l o n 12, n y l o n 6 - a r a m i d , polyethylene ( P E ) , polypropylene ( P P ) , p o l y (methyl p e n t e n e ) ( P M P ) , p o l y (ethylene terephthalate) ( P E T ) , thermoplastic polyurethane ( T P U ) , poly (butylène terephthalate) ( P B T ) , cellulose acetate ( C A ) , polysulfone ( P S U ) , p o l y ( a r y l ether sulfone) ( P E S ) , polycarbonate ( P C ) , p o l y ( p h e n y l e n e sulfide) ( P P S ) , p o l y ( a r y l ether ether ketone) ( P E E K ) , p o l y ( a r y l ether ether ketone ether ketone) ( P E E K E K ) , polystyrene ( P S T ) , acrylonitrile-butadiene-styrene (ABS), acrylonitrile-styrene-acrylate (ASA), a n d styrene-acrylonitrile ( S A N ) . Thermoplastic materials received i n pellet f o r m were g r o u n d i n a laboratory m i l l a n d separated into particle-size groups o f 20, 30, a n d > 3 0 mesh. P o w e r e d thermoplastic materials were analyzed as received.


266



N e a r - I R spectra w e r e collected at 4 - n m intervals over the range o f 1 1 0 0 - 2 5 0 0 n m using a scanning spectrophotometer ( B r a n + L u e b b e , InfraA l y z e r m o d e l 500) connected to a personal c o m p u t e r ( D e l l m o d e l 310). T h r e e scans w e r e averaged f o r each sample. Spectral data w e r e collected i n a q u a r t z - w i n d o w e d c u p containing 2 - 3 g o f sample. A l l spectra w e r e processed i n the l o g (1/reflectance) f o r m . D i s c r i m i n a n t analysis using Mahalanobis distances was p e r f o r m e d u s i n g software p r o v i d e d b y t h e instrument v e n d o r ( B r a n + L u e b b e ) . T h i s p r o g r a m performs a mathematical c o m p u t a t i o n that selects a set o f wavelengths that best describe the differences b e t w e e n the various samples. S i m u l a t e d filter spectra w e r e created using the filter transform software f u n c t i o n ( I D A S - P C , B r a n + L u e b b e ) . T h i s p r o c e d u r e converts t h e continuous scan spectra to the spectral f o r m obtained f r o m discrete filter instruments, w h i c h are w i d e l y used. Spectral searching was p e r f o r m e d b y i m p o r t i n g the spectra into Spect r a - C a l c (Galactic Industries) software u s i n g the Joint C o m m i t t e e o n A t o m i c a n d M o l e c u l a r Physics format. Spectral libraries o f regular l o g ( l / r e f l e c t a n c e ) a n d first derivative spectra w e r e p r e p a r e d b y averaging several spectra o f the different physical forms o f each material.

Results and Discussion Near-IR Spectra. Textile Fibers. T h e n e a r - I R spectra o f various textile fibers are s h o w n i n F i g u r e s 1 - 3 . Significant differences across the entire spectral range ( 1 1 0 0 - 2 4 0 0 n m ) are apparent between the spectra o f polypropylene, acrylic, a n d P E T shown i n F i g u r e 1. Smaller, b u t distinct, differences a r o u n d 1500 ( O - H stretch overtone) a n d 2100 n m ( C - O stretch overtone) are seen f o r the spectra o f cotton a n d rayon i n F i g u r e 2. T h e s e materials have the same c h e m i c a l structure (cellulose), b u t they differ, primarily, i n crystalline phase morphology. R a y o n exhibits the cellulose I I morphology a n d cotton exhibits the cellulose I morphology. T h e spectra o f nylon 6 a n d nylon 6,6 shown i n F i g u r e 3 exhibit very subtle, b u t observable, differences i n the region above 2000 n m (combination b a n d region). F r o m this survey o f various fiber types, i t is apparent that n e a r - I R spectra contain useful qualitative i n f o r m a t i o n . T h e s e examples clearly show h o w sensitive the n e a r - I R region is to subtle c h e m i c a l differences, a n d even morphological differences o f the same c h e m i c a l composition. T h i s result is not surprising because the bands i n the n e a r - I R region arise p r i m a r i l y f r o m C - H , O - H , a n d N - H functional groups. Qualitative differences i n the spectra are further e n h a n c e d b y the first derivative spectra. Thermoplastic Polymers. T h e n e a r - I R spectra o f a l l 2 5 thermoplastic materials analyzed w e r e sufficiently different to p e r m i t qualitative identifica tion. T h e n e a r - I R spectra o f t w o aromatic polyesters, P E T a n d P B T , are





1 10O

1500

267

2000

2500

nm Figure 1. Near-IR spectra of uncolored polypropylene,

1100

1500

acrylic, and PET fibers.

2000

nm Figure 2. Near-IR spectra of uncolored cotton and rayon fibers.


2500


268


1100

1500

2000

2500

nm Figure 3. Near-IR spectra of uncolored nylon 6 and nylon 6,6 fibers.

shown i n F i g u r e 4. A l t h o u g h these materials have very similar c h e m i c a l structures ( P B T has t w o additional - C H - groups i n the c h a i n backbone), the near-IR spectra are sufficiently different i n the 1 6 0 0 - 1 8 0 0 - n m region ( C - H a n d C = H stretch overtone) to b e distinguished f r o m each other. 2

T h e near-IR spectra o f three polyolefins, h i g h density P E , P P , a n d P M P , are s h o w n i n F i g u r e 5 . These materials also have similar c h e m i c a l structures, particularly P P a n d P M P . P M P has four - C H - groups between each pendant - C H group, whereas P P has o n l y t w o - C H - groups b e t w e e n each pendant ~ C H group. T h e spectrum o f P E , linear - C H ~ w i t h a m i n o r amount o f pendant ~ C H groups, is significantly different f r o m P P a n d P M P i n the 1 6 0 0 - 1 8 0 0 - ( C - H stretch overtone) a n d 2 0 0 0 - 2 4 0 0 - n m (combination bands) regions. T h e spectral differences b e t w e e n P P a n d P M P are very slight, b u t apparent i n the 1 6 0 0 - 1 8 0 0 - n m region ( C - H stretch overtone). T h e subtle differences are m o r e apparent i n the first derivative spectra. F i g u r e 6 shows the n e a r - I R spectra o f three structurally similar high-per formance thermoplastic materials: P E S , P E E K , a n d P E E K E K . Subtle, b u t 2

3

2

3

2

3

distinct, differences are present i n the region above 1800 n m (combination bands), particularly i n the first derivative spectra. Similar differences w e r e f o u n d for other classes o f similar thermoplastic materials that have similar compositions, such as polyolefins, polyesters, polystyrenes, a n d polyamides. A l t h o u g h qualitative identification c a n b e p e r f o r m e d b y manual inspec tion, computer-assisted interpretation provides enhanced capabilities. T h i s





1100

1500

i

269

r-

nm

2000

f 250C

Figure 4. Near-IR spectra of PET and PBT

1100

, 1500

nm

Figure 5. Near-IR spectra of PMP,

, 2000 PP, and HOPE.


j 2500


270


capability is particularly useful i n the n e a r - I R region because b a n d assign ments are less definitive i n the n e a r - I R region than i n the m i d - I R region. Bands i n the n e a r - I R region arise f r o m overtones a n d combinations that t e n d to be broader a n d m o r e overlapped than i n the m i d - I R region. T w o types o f c o m m e r c i a l l y available software designed for qualitative classificationidentification were evaluated: discriminant analysis a n d spectral searching.

Discriminant Analysis. Fibers. W e f o u n d discriminant analysis using Mahalanobis distances very useful for qualitatively identifying u n c o l o r e d or lightly c o l o r e d fibers a n d thermoplastic polymers, b u t problems were encountered w i t h dark-colored materials. T h e discriminant analysis parameters a n d results expressed as M a h a lanobis distances for the various fibers studied are shown i n T a b l e I. T h e magnitudes ( > 15) o f most o f the intergroup distances indicate a significant discrimination between most of the groups. F o r continuous scan spectra, four wavelengths provide a significant discrimination between the various fiber types, except for rayon versus cotton. H o w e v e r , these two fibers can be easily distinguished f r o m each other b y inspection o f the spectra or b y using a discriminant analysis search based o n standards o f these two fibers only. T h e discriminant analysis results for the same fibers using simulated discrete filter wavelengths (i.e., B r a n + L u e b b e m o d e l 450) are also shown i n T a b l e I. Six wavelengths w e r e used to provide intergroup distances comparable to those


9.


271


Table I. Discriminant Analysis Results for Various Fibers Expressed as Mahalanobis Distances between Groups 0

To

Continuous Scan

Discrete Filters

Acrylic

PET polypropylene rayon cotton nylon

38 53 31 26 24

42 45 26 32 20

PET

polypropylene rayon cotton nylon

32 34 39 26

33 35 21 41

Polypropylene

rayon cotton nylon

36 42 29

49 41 46

Rayon

cotton nylon

9 19

15 14

Cotton

nylon

20

23


From

Discrimination wavelengths: continuous scan; 2480, 2260, 2440, and 2380 nm; discrete filters: 1445, 1778, 2139, 2208, 2270, and 2348 nm.

a

obtained f r o m t h e continuous scans. T h e s e results show that discrete filter data are capable o f p r o v i d i n g qualitative i n f o r m a t i o n , even t h o u g h visual interpretation is m o r e difficult than w i t h continuous scan data. A n x-y p l o t o f two o f the discriminant calibration wavelengths is s h o w n i n F i g u r e 7. T h e separation o f the various groups (fiber types) is observed, although n o t completely w i t h o u t overlap. A n o t h e r x-y plot o f t w o other discriminant wavelengths is s h o w n i n F i g u r e 8. A g a i n , resolution o f the groups is observed, although t h e pattern is different f r o m t h e pattern i n F i g u r e 7. T h i s comparison o f two-dimensional projections aids visualization o f h o w the separation b e t w e e n groups is increased i n m u l t i d i m e n s i o n a l space. I n this case, f o u r wavelengths (four dimensions) w e r e used i n t h e d i s c r i m i nant calibration. N y l o n 6 a n d n y l o n 6,6 w e r e intentionally g r o u p e d together as n y l o n for the discriminant calibration i n t h e set o f a l l fiber types. P o o r resolution b e t w e e n these materials was obtained w h e n they w e r e treated separately i n the set o f a l l fibers. H o w e v e r , w h e n n y l o n 6 a n d n y l o n 6,6 samples w e r e treated as a separate set, t h e discriminant calibration s h o w e d g o o d d i s c r i m i nation. T h e Mahalanobis distance was 21, w i t h d i s c r i m i n a t i o n wavelengths o f 1759, 2230, 2270, a n d 2 3 1 0 n m . I f a n u n k n o w n sample w e r e classified as nylon, t h e n t h e discriminant equation d e v e l o p e d to specifically discriminate



0.4000

0.4500

0.5000

0.5500 2260 NM

0.6000

0.6500

0.7000

0.7500

Figure 7. An x-y plot of two of the discriminant wavelengths (2480 and 2260 nm) for classifying various types of fibers.

0.3500



:

0.5000

0.6000

0.7000 2340 NM

0.8000

0.9000

polypropylene

1.0000

Figure 8. An x-y plot of two of the discriminant wavelengths (2440 and 2340 nm) for classifying various types of fibers.

0.4500 0.4000

0.8500-

0.9000-;


274



n y l o n 6 versus n y l o n 6,6 w o u l d b e used to identify the specific n y l o n type. T h i s example implies that discriminant analysis is more p o w e r f u l w h e n used i n a series o f classifications that b e c o m e progressively narrower i n d e f i n i n g the differences between groups. D i s c r i m i n a n t analysis c a n also be u s e d to classify groups c o m p o s e d o f mixtures o f the same materials, such as textile blends. I n manufacturing, the consistency o f the b l e n d ratio is necessary to maintain constant performance attributes o f the product, such as dye uptake a n d other physical properties. F i g u r e 9 shows the spectra o f rayon, P E T , a n d two r a y o n - P E T blends. T h e results o f the discriminant classification using three wavelengths are s h o w n i n T a b l e II. A n x-y plot o f two discriminant wavelengths that shows the group separation is s h o w n i n F i g u r e 10. T h e s e results show that discriminant

nm Figure 9. Near-IR spectra of uncolored rayon, PET, and two blends.

rayon/PET

Table II. Discriminant Analysis Results for Rayon-PET Rlends Expressed as Mahalanobis Distances between Groups a

Rayon 75:25 R a y o n - P E T 50:50 R a y o n - P E T a

75:25

50:50

PET

592

1539 947

6348 5756 809

Discrimination wavelengths: 1722, 1734, and 2336 nm.



0.3400

+

0.3600

~f h

+

0.3800

•*

50/50 PET / rayon

PET

-f-

0.4000 2 0 8 0 NM

0.4200

-f-

+

+

0.4400

25/75 PET / rayon

0.4600

rayon-PET

-Ι 0.4800

rayon

Figure 10. An x-y plot of two of the discriminant wavelengths (2432 and 2080 nm) used for classifying composition.

0.5200 Ο. 3 2 0 0

0.5400+

0.5600+

0.5Θ00+

0.6000+

0.6200+

0.6400+


276



analysis may be used qualitatively, a n d perhaps quantitatively, to identify composition variation w i t h i n a product. T h e technique can b e u s e d quantita tively i n a process c o n t r o l situation b y having a calibration f r o m compositions that represent the lower limit, u p p e r limit, a n d target level. Thermoplastic Polymers. D i s c r i m i n a n t analysis also y i e l d e d successful qualitative results for the 25 thermoplastic materials analyzed. T h e d i s c r i m i nant analysis p r o g r a m selected five wavelengths between 2400 a n d 2500 n m that p r o v i d e d the best differentiation between the set o f 25 thermoplastic materials. T h e 325 intergroup Mahalanobis distances are displayed graphi cally, rather than i n tabulated n u m e r i c a l f o r m , i n F i g u r e 11. T h e y axis is truncated at 50 to better show the majority o f intergroup values, w h i c h are between 20 a n d 50. O n l y two groups have intergroup distances o f less than 10: n y l o n 6 versus P V D F a n d P M M A versus P V D F . T h e spectra o f these materials are shown i n F i g u r e 12. T h e spectrum o f n y l o n 6 is noticeably different f r o m that o f P V D F , particularly over the range o f 1 1 0 0 - 2 2 0 0 n m . P V D F a n d P M M A have m o r e similar spectra, although they are distinguish able i n the 1 5 0 0 - 2 0 0 0 - n m region ( C - H a n d C = 0 stretch overtones). I n b o t h cases, the regions w h e r e the spectra have the most differences are not w i t h i n the 2 4 0 0 - 2 5 0 0 - n m region (combination bands) where most o f the other materials were better differentiated. T w e n t y intergroup distances are

POLYMER TYPES Figure 11. Mahalanobis distances for the 325 intergroup distances for 25 thermoplastic polymers. The upper limit is truncated at 50 to better show the lower portion of the scale. (A histogram presentation is used instead of the conventional x-y form to more clearly show all 325 intergroup values.)



9.



277

b e t w e e n 10 a n d 2 0 (poor t o marginal separation), a n d the r e m a i n i n g 303 intergroup distances are greater than 2 0 (good separation). A severely sloping baseline is a major pitfall f o r the discriminant analysis approach. F i g u r e 13 shows t h e spectra o f a n u n c o l o r e d (reference) a n d dark-colored (black) acrylic fiber. T h e dye that produces t h e totally absorbing (i.e., black) color i n the visible region appears to b e tailing into the n e a r - I R region. T h i s effect was f o u n d t o have a severely adverse consequence o n the discriminant classification.

First Derivative Near-IR Spectra. U t i l i z a t i o n o f first derivative spectra was f o u n d to greatly reduce the adverse effect o f a sloping baseline due to absorbance f r o m dyes a n d scattering. F i g u r e 14 shows the first derivative spectra o f the same two acrylic samples whose regular spectra are shown i n F i g u r e 13. N o t e that the first derivative almost eliminates t h e sloping baseline for the black acrylic sample. T h e other advantage o f the first derivative is that it accentuates t h e subtle differences o f b a n d shoulders a n d b a n d shapes that usually account f o r t h e differences b e t w e e n the n e a r - I R spectra o f similar materials. Fibers. T h e first derivative spectra o f cotton a n d rayon shown i n F i g u r e 15 are clearly m o r e distinctive than the regular spectra ( F i g u r e 2). T h e first derivative spectra o f n y l o n 6 a n d n y l o n 6,6 shown i n F i g u r e 16 also



278


Γ 1100

« 1500

1

—

1

2000

2500

nm Figure 13. Near-IR spectra of an uncolored and dark-colored acrylic fiber.

nm Figure 14. First derivative near-IR spectra of uncolored and acrylic fiber (as shown in Figure 13).

dark-colored



9.


Near-IR

I

«

1100

1500

279

Spectroscopy

nm

2000

2500

Figure 15. First derivative near-IR spectra of uncolored cotton and rayon.

nm Figure 16. First derivative near-IR spectra of uncolored nylon 6 and nylon 6,6.


280



m o r e clearly emphasize the spectral differences i n the 2 2 0 0 - 2 5 0 0 - n m region (combination bands) than is observed i n the regular spectra ( F i g u r e 3). Thermoplastic Polymers. T h e first derivative n e a r - I R spectra o f P E T and P B T are shown i n F i g u r e 17. T h e first derivative significantly enhances the observation o f the spectral differences c o m p a r e d w i t h the regular spectra ( F i g u r e 4). T h e first derivative n e a r - I R spectra o f three polyolefins ( H D P E , P P , a n d P M P ) are shown i n F i g u r e 18. T h e differences b e t w e e n P P a n d P M P i n the 1 7 0 0 - 1 8 0 0 - ( C - H stretch overtone) a n d 2 3 0 0 - 2 5 0 0 - n m (combination bands) regions are m u c h m o r e obvious i n the first derivative spectra than i n the regular spectra ( F i g u r e 5). A similar accentuation i n spectral differences revealed b y first derivatives is seen for the spectra o f P E S , P E E K , a n d P E E K E K shown i n F i g u r e 19. I n particular, the differences between P E E K and P E E K E K i n the 2 0 0 0 - 2 5 0 0 - n m region ( c o m b i n a t i o n bands) are m o r e apparent than i n the regular spectra ( F i g u r e 6). T h e first derivative spectra of n y l o n 6, P V D F , a n d P M M A are shown i n F i g u r e 20. These are the three materials that w e r e not significantly distinguished f r o m each other b y d i s c r i m inant analysis. T h e first derivative enhances the spectral differences b e t w e e n P V D F a n d P M M A c o m p a r e d w i t h the regular spectra ( F i g u r e 12).

Near-IR Spectral Searching. Fibers. W e f o u n d spectral search i n g to be very p o w e r f u l for distinguishing between materials o f similar c h e m i c a l compositions, particularly w h e n using first derivative spectra. I n all the cases that w e r e tested, the spectral search results obtained f r o m first

I

1100

1

1500

1

nm

2000

Figure 17. First derivative near-IR spectra of PET and PBT.






281


282


nm Figure 20. First derivative near-IR spectra of nylon 6, PMMA, and PVDF. These are the three materials that were not differentiated from each other by discriminant analysis.

derivative spectra w e r e better, often significantly, than those obtained f r o m the l o g ( l / r e f l e c t a n c e ) f o r m . A s n o t e d previously, the first derivative accentu ates the subtle differences o f b a n d shoulders a n d b a n d shapes that usually account for the differences b e t w e e n the n e a r - I R spectra o f similar materials, a n d it eliminates sloping baselines d u e to varying amounts o f scattering a n d dye absorbance. T h e spectral search results for the first derivative spectra o f several o f the fibers studied are s h o w n i n T a b l e III. T h e results for the rayon " u n k n o w n " correctly identify the sample as a n exact m a t c h w i t h the rayon reference w i t h a H Q I o f 0.00. C o t t o n is i d e n t i f i e d as the next closest m a t c h w i t h a H Q I o f 0.24. A l t h o u g h the spectra o f the two materials appear somewhat similar ( F i g u r e 15), there is a significant difference i n the H Q I values o f rayon a n d cotton to indicate that rayon is b y far the better match. S i m i l a r results w e r e obtained for P E T . T h e P E T " u n k n o w n " was a perfect m a t c h w i t h the P E T reference, a n d n o other fiber material was close according to the H Q I values. F o r the n y l o n 6 " u n k n o w n " , the H Q I is 0.00 for the n y l o n 6 reference a n d 0.03 f o r the n y l o n 6,6 reference. A l t h o u g h the n u m e r i c a l difference b e t w e e n the H Q I s o f the two n y l o n types is small, the positive identification o f n y l o n 6 is c o n f i r m e d b y visually v i e w i n g the spectra. F o r the black acrylic w i t h the sloping baseline ( F i g u r e 13), the H Q I o f 0.12 for the first derivative


9.


283


Table III. First Derivative Near-IR Spectral Search Results for Fibers Fiber Searched

Library Match


Rayon

PET

Nylon 6

Acrylic (black)

a

Hit Quality Index"

rayon cotton wool acrylic

0.00

PET acrylic nylon 6 nylon 6,6

0.00

nylon 6 nylon 6,6 polypropylene wool

0.00

acrylic polypropylene PET nylon 6,6

0.12

0.24 0.42 0.49

0.31 0.34 0.34

0.03 0.30 0.32

0.29 0.30 0.33

A smaller value indicates a better match.

spectrum ( F i g u r e 14) is significantly better f o r b o t h t h e closeness o f t h e match w i t h the acrylic reference a n d the separation f r o m other materials.

Thermoplastic

Polymers.

T a b l e I V shows some representative

first

derivative spectral search results f o r various thermoplastic materials. T h e PEEK

standard i n t h e library is consistently t h e best m a t c h f o r P E E K

" u n k n o w n s " , although as expected, P E E K E K and P E S are also i d e n t i f i e d as close matches for P E E K (see F i g u r e 6). Similarly, the first derivative spectral search results for nylon 6 are consistently correct. E v e n though t h e near-IR spectra o f n y l o n 6,6 a n d n y l o n 12 are very similar, there are sufficient differences t o p e r m i t identification o f each material. T h e P M P " u n k n o w n " was correctly identified w i t h a n H Q I o f 0.00, w h i c h indicates a significant differentiation f r o m t h e P P reference w i t h a n H Q I o f 0.14 ( F i g u r e 18). U s i n g first derivative spectral searching, P V D F was correctly i d e n t i f i e d a n d significantly distinguished f r o m a l l other materials; however, using discriminant analysis, P V D F was n o t significantly distin guished f r o m n y l o n 6 a n d P M M A , w h i c h have similar spectra above 2000 n m (see F i g u r e 12).


284


Table IV. First Derivative Near-IR Spectral Search Results for Thermoplastic Polymers Fiber Searched

Library Match

polycarbonate Nylon 6

nylon nylon nylon nylon

0.00 0.08 0.21 0.21

PMP

PMP

PEEK PEEKEK PES


a

0.02 0.06 0.10 0.14

PEEK

6 6,6 12 6-aramid

PP PE

nylon 12 PVDF

PVDF PVAC PPS PBT

a

Hit Quality Index

0.00 0.14 0.29 0.32 0.00 0.26 0.27 0.27

A smaller value indicates a better match.

Summary and Conclusions N e a r - I R spectroscopy c a n b e used to qualitatively identify textile fibers a n d thermoplastic polymers, a n d p r o b a b l y any other organic material. Qualitative identification o f u n c o l o r e d o r light-colored materials c a n b e satisfactorily achieved b y discriminant analysis using Mahalanobis distances w i t h b o t h continuous scan a n d discrete filter spectra. H o w e v e r , discriminant analysis using Mahalanobis distances seems less useful f o r d a r k - c o l o r e d materials. Spectral searching u s i n g the first derivative is the more robust approach because it eliminates most o f the adverse effect o f sloping baselines a n d accentuates the subtle differences between spectra o f similar materials. T h e use o f higher order derivatives (not studied i n this w o r k ) w o u l d b e expected to equal, a n d possibly exceed, these results. C o n v e n t i o n a l n e a r - I R spectrome ters require a f e w grams o f sample; thus, this technique may not b e useful w h e n sample size is very small. H o w e v e r , the technique is nondestructive. S a m p l i n g techniques a n d accessories capable o f using m u c h smaller sample sizes have b e e n u t i l i z e d i n a few reports. This study is l i m i t e d i n the n u m b e r o f sample types. F u r t h e r w o r k i n this area w i t h a greater variety o f material is n e e d e d to better understand the qualitative performance o f near-IR spectroscopy.


9.

HOWELL AND DAVIS


285


References 1. Creaser C. S.; Davies A. M . C. Analytical Applications of Spectroscopy; The Royal Society of Chemistry: London, England, 1988. 2. Wetzel, D. L. Anal. Chem. 1983, 55, 1165A-1176A. 3. Weyer, L. G. Appl. Spectrosc. Rev. 1985, 21, 1-43. 4. Mark, H . L.; Tunnel, D. Anal. Chem. 1985, 57, 1449-1456. 5. Lo, S.-C.; Brown, C. W. A Near-Infrared Spectral Library; F T S / I R Notes No. 68; Bio-Rad: Cambridge, MA, 1989. 6. Ciurczak, E. W. Appl. Spectrosc. Rev. 1987, 23, 147-163. 7. Ciurczak, E. W.; Maldacker, T. A. Spectroscopy 1986, 1, 36-39. 8. Ghosh, S.; Rodgers, J. E. Milliand Textilberichte 1988, 69, 361-364. RECEIVED for review May 14, 1991. ACCEPTED revised manuscript May 26, 1992.


Structure-Property Relations in Polymers - American Chemical Society

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