FOURIER TRANSFORM INFRARED SPECTROSCOPY

IN

SIZE EXCLUSION CHROMATOGWHY

Keivan Torabi

A thesis submitted in conformïty with the requirements for the Degree of Master of Applied Science

Graduate Department of Chernical Engineering and Applied Chemistry University of Toronto

O Copyright by Keivan Torabi, 1999

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Size Exclusion Chromatography (SEC) is now a cornmon method for analyzing the

molecular weight distribution of polyrners. SEC separates the molecules accordhg to

their size in soiution to permit each size to be exarnined by a "detector". A

differential rehctive index (DRI) detector is most fiequently used to obtain

concentration of each size. Howeve. this detector provides ambiguous data if the

polymer molecules Vary in composition as well as size (e-g. are fiom a copolymer or

a polymer blend). If a Fourier Transform Infiared (FTIR) spectrometer could be used

instead of the DRI it could more than overcome this disadvantage by providing a

great deal of information on rhe concentration of individual functional groups. FTIR

has begun to be used for SEC. However, there are d l large uncertainties associated

with this application particuiarly when it is used for quantitative d y s i s .

Quantitative analysis using FTIR detection for is the topic of this work. Polystyrene,

poly(methy1 methacrylate) and their blends as well as a sytrene methyl methacrylate

copolymer were analyzed. The first objective was to assess a SEC flow ceil

approach. It was rapidly demonstrated that absorbance interference of the carrier

solvent was intoierdbie. The dilute polymer concentrations used in SEC, combined

with the very limited wavelength windows present in SEC mobile phases, greatly

reduced FTIR utility. The second objective was to develop experimental methods for

obtaining FTIR calibration data applicable to the solvent evaporation interface by

using conventional solvent cast films. This involved determining how best to solvent

cast polymer films and successfully devising a method for effectively measuring film

quality. Use of a mask to detennine localized spectra at different points on the nIm

provided the latter. The third objective dominated the work. It was to develop

quantitative interpretation methods for FTIR data obtained using a solvent

evaporation interfixe with SEC. The solvent evaporation interface allows the

chromatograph to produce each molecular sue as a dried polymer f i h on a

germanium pellet. Accomplishing this objective required the development of both

intemal and extemal calibration methods. Internai calibration refers to the use of a

DR1 detector with the FTIR detector to obtain concentration versus mass data based

on pure linear homopolymers. Extemai calibration refers to the use of solvent cast

films to obtain such information. Linear regression and partial least squares were

used for calibration and then for prediction to determine quantitative estimates of

composition. The mass variation with retention tirne in the size exclusion

chromatopph was integïated to provide total mass of polymer recovered in the

solvent evaporation interface. it was found that partial least squares and the use of

annestled sampies provided the best precision and accuracy in estirnates of both

composition and total mass recovered.

ACKNOWLEDGEMENT

I would like to thank Professor S.T. Balke for aii his advice, guidance,

encouragement. and patience during this work. His dedicated supervision and

continuai support have contributed greatly to my research accomplishmen~

1 am also indebted to Dr. Timothy C. Schunk of Eastman Kodak (Rochester, New

York) for his invaluable guidance and involvement in my project In particuiar 1 am

gratehl for his helpfid suggestions in the use of the analytical software and the

experimental techniques.

This project would not have been possible without the financial support of the

Eastman Kodak Company (Rochester New York).

1 wouid also like to acknowledge my fnends in the Department of Chemicai

Engineering and Applied Chemistry: Lianue hg, Chistopher Gilmor, and Audrey

Yakimov.

Finally, the great support of my parents has been instrumental in the completion of

this thesis.

Table of Contents

ABSTRACT

A C K N O m E D G m T S

TABLE OF C O N m T S

LIST OF FIGURES

LIST OF TABLES

LIST OF APPENDICES

NOMENCLATURE

1. rNTRODUCTION 1

2. THEORY

2.1. Fundamentals of FTIR

2.1.1. FTIR Instrument

2.1 2. Beer-Lambert's Law

2.1.3. Resolution

2.1 -4. The Spectral Manipulation

2.1.5. The Advantages and Limitations of FTZR Spectroscopy

2.2. Fundamentals of SEC

2.2.1. SEC Instrument

2 - 2 2 Calibration for Molecular Prediction

2.2.3. DR1 C hromatogran hterpretation

2.3. Data lnterfacing Techniques in SECETIR

2.3.l Flow Ceil

2.3.2 Solvent Evaporative Interface (SEI)

2.4. Data Andysis Techniques

2.4.1. Linear Regression (LR)

2.4.2. Partial Least Squares (PLS)

2.4.3. Data lnterpretation

2.5. Calibration

2.5.1. Internai Calibration based on DR1

2 - 5 2 Externai Caiibratioa by Hand Casting

2.5.3. Cornparison of Calibration Methods

3. EXPERIMENTAL

3.1. Materials

3 -2. Size-Exclusion C hromatography (SEC)

3.3. Flow Ce11

3 -4. Solvent Evaporative Interface (SEI)

3 S. Sample Preparation and FTIR Analysis

3.6. Data halysis

4. RESULTS AND DISCUSSION

FTIR Analysis of Solutions

Solid Films for FTlR Analysis

4.2.1 Film quality from the Solvent Evaporation Interface

4.2.2. Film quality from Film Casting

Use of the Solvent Evaporation Interface with Extemal Calibration 51

4.3.1. Spectral Deconvolution 51

4.3 -2. Linear Regression Calibrarion 52

4.3.3. The Effect of Molecuiar Weight 54

4.3 -4. Assessrnent of Beer's Law Deviations 55

4.3 -5. The Composition of Polymer Blends and Total Mass Collected

57

Use of the Solvent Evaporative Interface with Internal Calibration 60

4.4.1. Internal calibration for the Compositional Analysis of

Annealed Films Using Linear Regression 61

4.4.2. Intemal calibration for the Analysis of Annealed and As

Collected Polyrner Blend Films Using PLS

4.5. Quantitative Analysis of the Composition of Copolymers

4.6. Quantitative Anaiysis of Total Mass

4.6.1. PS and PMMABIends

4.6.2. SMM Copolymer

5. CONCLUSIONS

6 . RECOMMENDATIONS

7. REFERENCES

8. APPENDICES

LIST OF FIGURES

Figure

FTIR Spectrum of PMMA

FTIR Spectrometer components

resolution Cornparison in FTIR spectnim

Second Denvative Spectnun of PMMA

SEC components

A dernountable infrared liquid ce11

Evaporative Interface designed by Dekmezian in 1990

The Collection Stage of the Solvent Evaporative interface

Diagram of the solvent evaporative interface developed by

Eastman Kodaknf

Experimental system configuration with altemate DR1 or

solvent evaporation interface connection

Detectability of Liquid Ce1 in High Concentrations

Detectabili~ of Liquid Ce11 in a broad range of concentrations

FTIR Spectra for 10 mgml PMMA in THF (0.3 mm Spacer)

FTIR Spectra for 1 -5 m g h l PMMA solution in TEE

(0.1 mm Spacer)

FTIR Spectra for 0.0 15 m g h i PMMA solution in THF

(0.1 mm Spacer)

The effect of increasing the resolution and the nurnber of

scans to improve detectability for PMMA in SEC concentration

-g=

Calibration for PMMA with large volume liquid ce11

Calibration for f S in THF with large volume liquid ce11

PMMA detectabi lity in C H s l z

detection window for PS and PMMA with dichloromethane

vii

Lack of detectability for PS in CHzClz within the SEC

concentration range

Impact of solvent annealing on the IR scattering background for

50-50 PS - PMMA blend fraction collected fiom SEC with

the solvent evaporation interface [15]

impact on 1730 c d band absorbance of casting conditions

observed for manuaily cast reference films of PMMA on polished

Ge disks

Determination of film unifonnity of mandly cast PMMA f i h

using masked areas as shown in the inset

Example resdt of PeakFit software baseline and Gaussian band

fitang for a narrow region of a PS film spectnun

Calibration plots of absorbance band area determined with

PeakFit sohvare for manually cast polymer films

Online Calibration for PS and PMMA

The Effect of the ~Molecular Weight on the Performance of SEI

The band ratio cornparison of PS infr-ared peaks for 75% blend

and pure sarnples

The band ratio cornparison of PS ùifiared peaks for 50% blend

and pure samples

Caiculated 5050 PSPMMA blend composition using LR

external calibration expressed as weight percent PMMA of

anneded S EC fractions O btained fiom the solvent-evaporation

interface

LR extemal caiibration relative error in wt.% PMMA prediction

Cornparison of W.% PMMA across the SEC chromatograms

determined by FTIR LR external calibration and DIU

Nomalized DR1 chromatogram of pure PS and PMMA used in

blend SEC experiments

Calibration alternative for PMMA

Internai Calibration for PMMA

viii

Calibration alternatives for PS

Internai Calibration for PS

Comparison of the composition prediction by DM, LR, and PLS

techniques

PLS internai cdibration relative percent error in W.% PMMA

prediction fiom anneaied film spectra

PLS intemal cdibration relative percent error in wt.% PMMA

prediction fiom "as collected" film spectra

Monomers distribution across the SEC Chromatogram for SMM

Copoiymer

Internai Calibration for SlMM Copolymer based on FTIT Spectra

Intenial Calibration for SMM Copoiymer based on second

derivative FTIR spectra

Comparison of integrated polymer mass results fiom different

quantitation methods [ 1 51

LIST OF TABLES

Table

1

II

m IV v

VI

VII

VrIX

Chatacteristic fiequencies in FTiR

Sample Dependent Resolution Settings

Comparison of Cdibration Methods

PLS training set spectral regions

Comparison of the calibration techniques based on the

homopolyrners

Comparison o f the caiibration techniques based on the

Copolyrner

Comparison of accuracy and precision of integrated polymer

mass for both blend components using different quantitation

methods 75

Comparison of accuracy and precision of integrated polymer

mass for SMM copolymer using different quantitation methods 76

LIST OF APPENDIX

Appendix page

1 ANOVA for IR peak area and height ratios in SMM Copolymer 84

NOMENCLATURE

Scalars

Abs. (A) Absorbance Absorptivity Path 1eng.h Speed of light Concentration Concentration at the corresponding retention time Enml9 Residual error Plank's constant Intensity of IR light Characteristic constant of material for IR Light absorbtivity Predicted mass Predicted mass of component j Injected mass of polymer into the SEC column Number of samples Number of the parameters in regression modei Correlation coefficient squared Standard deviation of residual enors Trsrnsmitance Retention time Student distribution Retention volume of component I Retention volume increment Wavenurnber Di fferential re fractive index at the corresponding retention time Normalized differential refiactive index at the corresponding retention time Weight fraction of component j Bare area fraction of the sample on the substrate in FTIR spectroscopy

Yi Experimental value in regression

Yi Predicted value in regression

Mean experimental value in regression

Greek Letters

a Significance level

Cr Characteristic constant for IR Light absorptivity

A WaveIen-gth K Prgportionality constant in DR1

Abbreviations

DR1 FTIR IR LR U4 MLR PLS PS PMMA RE SEC SEI SMM SNR TCB THF UV

DiEerential refiactive index Fourier Transforrn Infkared Infiareci Linear regression Mass accuracy Multivariate linear regression Partial least squares Polystyrene Poly(rnethy lmetacrylate) Relative error Size exclusion chromatography Solvent evaporative interface Poly (nyrene-CO-methyhetacrylate) Signal to noise ratio Trichlorobenzene Tetrahydro furan Ultraviolet

xii

1. INTRODUCTION

Commercial synthetic polyrners are ofien very complex fkom a molecular viewpoint.

They typicaily conrain a wide variety of long chah molecules ciifferhg in

composition and molecular weight. Copolymers are an example of these materials.

Variations in chab architecture are also cornmonplace: some chains can be branched

instead of linear. Molecular properties have a profound impact on both the

processing and product performance properties of polymers. Thus, there are strong

motivations to anaiyze such materials.

Size exclusion chromatography (SEC), introduced in 1964, is now a well-known

method for analyzing polyrners. This method allows polymer molecules to k

separated (fiactionated) into different sizes. Then each size can be examined with

"detectors" of choice. Concentration of each size is needed and is normally detected

using a differential refractive index (DRI) detector. However, unfortunately this

detector is also sensitive to the type of molecules that are present. That is, the

detector response is a function of both the composition of the Long chain molecules

that constitute a particular molecular size as well as their total concentration. The

concentration of each size of molecule in a copolymer then cannot generally be

accurately obtained. The composition information cannot be factored out fiom the

total concentration information without some additionai information (e.g. input f?om

another type of detector). Sometimes even simple polymers cannot be analyzed using

the DRI: the instrument depends upon there being a significant difference between the

refiactive index of the polymer solution and that of pure solvent suitable for the

chromatographie s e p d o n . For some cornmon industrial polymea that difference is

too small for precise results.

Fourier Transform I n h e d (FTIR) spectrometry is a detection method which

potentially overcomes the disadvantages of DRI. It is a powemil, and very widely

applicable, method for obtaining chemicai functionai group information for polymenc

materials. The direct interfacing of SEC and FTIR has evolved fkom two directions:

in-line flow cells and solvent evaporation interfaces (which remove the solvent prior

to FTIR spectral analysis). Low-volume flow celis offer continuous monitoring of the

eluates with little loss of chromatographie resolution. However, b f k e d absorbance

interference fiom the carrier solvent is of concern. The SEC soivent evaporative

interface (SEI) currently offers the only practical method for removing the solvent

fkom the polymer for using FTIR in SEC. Such an interface allows full use of the

mid-IR spectral range by providing analyte films fke fiom solvent interference. The

evaporative interface removes the SEC mobile phase at the exit of the coiumn and

deposits the efuüng poiymer as a c o n h o u s fiIm stripe or as a series of discrete films

on an idhred transparent substrate (e.g., germanium). Initially this detection

approach was used only for qualitative analysis. More recently, it is king used

quantitatively. ïhuç. assessrnent and deveiopment of quantitative methods suited to

interpretation of the resulting FTIR data has become exûemely important and is the

main topic of this thesis.

The objectives of the work were as follows:

1 . To assess a SEC flow ce11 approach as an alternative to use of the solvent

evaporation interface. The flow ce11 approach is much less expensive and

easier to operate than the so lvent evaporation interface.

. . 11. To develop experimental methods for obtaining FTIR caiibration data

applicable to the solvent evaporation interface data by using conventionai

solvent cast films. Experimental techniques for fonning the films and for

assessing their uniformity are needed.

S..

111. To develop quantitative interpretation methods for FTIR data obtained using a

solvent evaporation interface with SEC. Data supplied by Dr. T.C. Schunk,

Eastman Kodak Company, Rochester, NY, were central to the method

development. Data on polystyrene-poly(methy1 methacrylate) blends as weli

as on a poiy(sytrene-methyl methacrylate) copolymer were used.

Accomplishment of this objective dominated the thesis work.

2. THEORY

2.1. Fundarnentals of FTIR

As mentioned in the introduction, FTIR is a powerfùl and widely applicable

spectroscopy method implemented to identiw chemical functional groups. An FTIR

spectrometer is an analytical instrument used to study materiais in the gas, iiquid or

solid phase. FTIR has broad application in many fields of science and engineering.

Over the years, FTIR spectroscopy has become one of the most important tools fur

both qualitative and quantitative characterization of organic matenals, and in

particular, polyrners.

FTIR spectroscopy is based on the interaction of infrared light with molecules. The

energy absorptivity of chemical bands creates their FTlR spectnun. The energy

content of the light is directly proportional to its wavenumber:

where E and W represent energy and wavenumber, respectively. The other tenns are

both constant: h is the Planck's constant (6 .63~10'~ Us) and C is the speed of iight.

Mid-infi?ired light is defined as light in the range of wavenumbers between 4000 and

400 cm-'. Ail matenals above absolute zero (-273.1 5 OC) emit infrared (IR) light.

However, when molecuies are IR radiated by infiared light, it can be absorbed and the

absorbed energy causes vibration in the atomic bonds. Specific atomic groups tend to

absorb infrared light at particuiar wavenumbers, regardless of the response of other

chemical bonds in the rest of the molecule. The fact that different atomic groups

absorb at different IR wavenumbers c m be used to identie the structure of molecules.

The plot of measured infkred absorbance versus wavenurnber is cailed the in6rared

spectrurn. A typical FTIR spectrum with some characteristic bands is shown in Figure

1. The intensity of the IR absorption band is proportional to the rate of change of the

dipole moment in a molecule, with respect to the displacement of the atoms.

However, molecules with inherent dipole moments demonstrate stronger responses

than molecules with induced dipole moments. Therefore, groups such as -NH and

-OH with strong dipole moments generally give strong absorption bands.

.15

1

Abs.

05

O

L 7

l5oa 3mo ZUXI zmo 15QQ lm sa0

Wavenumber, cm-'

Figure 1 : FTIR spectrum of PMMA

Consequently, the infiared spectnun c m be used as a fingerprint for molecules. For

example, the chernical groups shown in Table 1 can identified by an absorption band

at their characteristic wavenumber.

Table 1: Characteristic frequencies in FTIR

I Chernical bond l Wavenumber cm" I

Aromatic Ring CH (Stretch)

CH (Bending)

3 100-3000

Monosubstituted Aromatic Ring 710-665

2.1.1. FTIR Instrument

The FTIR spectrometer consists of an i-ed light source and detector. a laser light

source and detector. moving mirrors and several of fixed mirrors. The other FTIR

components are shown in Figure S [l].

IR Detector

Light Source

He-Ne Laser

'\ Mirror Sarnple U Mirror

Figure 2: FTIR Spectrorneter components

The design of infrared spectrometers is based on the idea of the two-beam

interferometer originally desimed by Michetson in 1891. The Michelson

interferometer is a device that can divide a bearn of i h e d light into two parts and

then recombine them afier they travel different paths. The difference between these

paths is called the optical path difference. Therefore, the beam splitter is the

centerpiece of the interferometer. The beam splitter is ofien made out of a thin

germanium plate coated with potassium brornide (Dr) . Potassium bromide does not

split the IR light, but it is a substrate that protects the germanium layer fiom the

environment The germanium splitter reflects about 50% of the incident light and at

the same time transmits the remahhg 50%. One part of this spiit light travels to a

moving interferometer rnirror while the other part travels to the stationary

interferometer mirror. The nvo mirron reflect both beams back to the beam spiitter

where the light rays recombine. When the two light beams recombine at the beam

splitter, an interference pattern is generated. As long as the path difference is equai to

multiples of the wavelength, the beams are in phase, cailed zero path difference

(ZPD). When these bearns add together, an intense wave will be produced. This

phenornenon is called constructive interference. Recombining two beams that are out

of phase will produce a weak wave. This effect is calleci destructive interference. A s

the moving minor travels back and forth, the beam bnghtness varies h m intense to

weak. The variation of tight intensity versus optical path ciifference is calied the

interferogram. A Fourier transformation of the interferogram generates the FTIR

spectrum. Every scan is the result of a complete back and forth movements of the

moving mirror.

By increasing the number of scans and adding the interferograms together (a process

known as coadding), random noise is dramatically reduced, but the signals fiom the

absorbance bands remain constant. The reason for the noise reduction is that the

instrumentai error is random. Thus positive and negative fluctuations in the error are

canceLed out.

The last mirror in the path of IR light, fkom the source to the detector, focuses the

light on a smali detection area The detection element is a transducer, which sen&

voltage signals to the digitizer. Then, the infornation is transfomed into a spectnim.

One of the most cornmon detectors in mid-infrared spectroscopy is deuterated

triglycine sulfate (DTGS) [l]. A change ui light intensity affects the DTGS surfie

temperature. The main advantages of the DTGS detector are its shplicity and low

price. But it has a low sewitivity. A second type of IR detector is made fkom mercuxy

cadmium teIluride (MCT) alloy, which is a serniconductor. The MCT absorbs IR

photons and then emits electrons, which are transformed to voltage. These detectors

are 10 times more sensitive than the DTGS detector [l]. Another advantage of the

MCT detector is its fast detection compared with the DTGS detectors- However, the

most sensitive range of wavenwnbers for MCT is limited to between 4000 and 700

cm-'. Although there is a modified MCT with extended range down to 400cm-', the

resdting spectra are 5 to 10 Urnes noisier than those from the standard detector Cl].

Other limitations of the MCT detecton are their high-pnce, the possibility of

mahnction with intense light, and liquid nitrogen coasumption to keep the

temperature low.

The He-Ne laser is one of the major components in the FTIR spectrometer. It

provides a standard wvavenurnber, and emits light at exactiy 15,798.637 cm-'.

Therefore, ali other wavenurnbers generated in the instrument are compared with it

Also, the He-Ne laser allows the position of the moving mirror to be tracked.

Consequentiy, the optical path difference can be measured.

As mentioned earlier. the interferogram is a sum of several sinusoicial sigaals, and

performulg a mathematical integration on it can generate the FTIR spectnun. Since it

is a dennite integral operation there is a truncation emr, which affects the shape of

the spectral peaks at the baseline. This defect can be corrected by muitiplying by a

mathematical h c t i o n called an apodization hct ion. Unfortunately, the appodization

fimction can affect the resolution of the spectnim by peak broadening. Therefore, the

proper apodization bc t ion must be applied carefiiily in quantitative anaiysis to avoid

misleadhg results. One of the best apodizattion fimctions is the "medium Beer-

Norton" function [ 1 3.

An interferogram FTIR transformed spectnim is a plot of the detector response versus

the wavenumber. The raw specmun without any sample is caiied the background

single beam spectrum. When the interferogram is measured with a sample and then

Fourier transformed, a sample single beam spectnim is produced. The simpiest way to

see differences between the sample and background single beam spectra would be to

superimpose them. To simplib this cornparison, the ratio of the nvo spectra is

computed. This ratio is called the transmittance (T).

where I and Io represent meanired intensiw with and without the sample,

respectively. This ratio is most cornrnonly given as the absorbance (A).

2.1.2, Beer-Lambert's Law

The amount of energy absorbed by a material in spectroscopy depends upon the

nature and the thickness of the material as well as the fiequency of the radiation. For a

homogeneous sample and perpendicular incidence of IR light, the intensity of

absorption can be written as:

where p is a constant charactefistic of the fiequency and material. The thickness of

the sample and intensity of beam are given by x and I, respectively. For a f ~ t e path

length (hx), Equation 4 becomes [2]:

The dimensions of I and L are not important because they are proportional to the

energy of the IR beam. To better demonstrate the effect of concentration, p can be

split into different parts:

where c represents the concentration and k is a characteristic constant of the material.

Therefore, equation 6 can be written as:

A more convenient form of the above equation can be obtained by converting to

common logarithms :

log (Io /l) = logl/T = -4 = abc (8)

in this equation. also known as Beer's law, Io, I, a, 6 , and c represent the incident

intensity, the intensity passing through the sample. the absorptivity, the path length

(breadth) and the concentration, respectively. Beer's law can be written as:

where the summation is over al1 substances present in the sample. Almost every

quantitative analysis in spectroscopy is dependent on the validity of this equation [2].

Beer's law is dernonstrated via absorbance or peak height. However, peak area can

also be used. Integrating Beer's law over wavelength converts absorbance A to

inf'rared peak are% so that:

If the concentration of a particular fùnctional group (c,) is related to the concentration

of other hct ional groups present according to:

where cl. cz. CJ are the concentrations of the fbnctional the groups, and Kt. K3. --. are

constant (not fimctions of concentration). Functional group 1 absorbs between IL, and

k; group 2 between i,-, and &.,, etc. Then:

Equation 15 is a statement of Beer's law using area for each fiinctional group.

2.1.3. Resolution

One of the important parameters in FTIR spectroscopy is the resolution of the

spectrum. The spectral resolution defmes the ability of the specwmeter to separate

two characteristic bands in a spectnun.

Although the infrared s p e c t m appears to be a continuou fimction, it is actually a

number of discrete data points- The number of data points and the Line segments that

connect hem, speci- the smoothness of the spectnim. The instrumental resolution

determines the number of data points in the spectrum. For example, a spectnim with

32 cm" resolution contains a data point every 32 cm-'.

The resolution effect is demonstrated in Figure 3. The spectnim with 32 cm-'

resolution is a single broad peak. whereas the other spectmm with 4 cm" resolution

shows several sharp peaks. The 32 cm" spectrum is said to have a lower resolution.

Therefore, when the spectnim is taken at high resolution, there is greater potential to

determine many spectral features. However, the problem with a hi&-resolution

s p e c t m is its tendency to be much noisier than a low-resolution spectrum, even

though it may contain more information.

Noise is u s d y observed as random fluctuations in the speceum above and below the

baseline. The ratio of the height of an absorption peak to the height of the noise is

c d e d the Signal to Noise Ratio (SNR). Therefore, the SNR affects the resolution.

The performance of any FTIR spectrometer is determined by maniring its signal to

noise ratio.

Abs.

Resolution f l f l Wavenumber cm-'

Figure 3: Resolution Cornparison in FTIR Spectnim

The other parameter that influences spectral resolution is the bandwidth of the peaks.

The bandwidth depends on parameters such as temperature, pressure, and sampling

technique Cl]. To be able to identifY spectral peaks clearly, the instrumental resolution

should be at l e s t four times higher than the narrowest spectral peak. This insures a

sufficient number of data points to accurately demonstrate the entire peak [ I l .

A limiting factor for high-resolution FTIR spectrometry is the scanning tirne. Since a

high-resolution technique requires a large number of &ta points, the measurement

requires more tirne. Scannuig time can be an issue with online characterization

methods.

In practice, the resolution is selected based on several factors including the sampling

technique and the type of information that is required nom the spectrum. A summary

of typical resolution settings used for different sarnples is shown in Table II [Il.

Table II: Sample Dependent Resoiution Settings [l]

Sample Resolution, cm-'

Solids, Liquids

2.1.4. Data Interpretation

4 to 8 I

There are several mathematical methods that can be applied to an FTIR spectnim to

obtain information. The major mathematical operations are baseline fitting,

smoo thing , peak deco nvo luting, c urve fitting, and calculation of spectral derivatives.

Gases

Baselïne correction is one of the most common operations in spectral anaiysis. It is

used to determine the absorbance connibuted by a functional group. The FTIR

software allows the user to select the baseline points, which are either fit by a cuve or

joined together by straight lines drawn from point to point to f o m the baseline, The

absorbance values are obtained by subtracting the baseline value fiom the measured

absorbance value for each wavenumber.

2 to 4

Smoothing is a numerical technique used to reduce the noise level of the spectra.

Smoothing is achieved by taking the average of the data points in s m d increments

across the spectrum. The major concern in this process is the loss of spectrai

resolution.

I

Since the ïnfked spectnim is a mathematicai fiinction, its derivatives with respect to

wavenumber can be calcuiated. The are two reasons why second derivatives are used-

First, the baseline becomes zero. and therefore baseiine drift is not an issue. The

second reason is that the vaileys in the second derivative spectrum represent

absorbance peaks of the original spectrum. in complex mktures when several bands

are overlapped. the number of original bands can be discerned by examining the

number of valleys (Figure 4).

Wavenumber, cm-'

Figure 4: Second Denvative Spectnun of PMMA

Deconvolution is a mathematical approach to enbance the spectral resolution. It is

most practical when there are a few narrow overlapping peaks. Although the peak

location remains unchanged in this process, both peak shape and area are subject to

change. Therefore, quantitative analysis can be very sensitive to the deconvohtion

used [ I I . Use of the second derivative spectra is more reiiable than deconvolution for

detennining the number of spectral peaks. Also, the wavenumber of downward

pointing features (valley) in a second derivative spectnim is exactly the same as the

wavenumber of the original spectral peaks.

M e r locating the spectrai peaks. the shape of each peak is assumed and the height

and area required to match the experimentai curve is obtained. Recombining the

deconvolved peaks provides "calculated spectrum9', which is supposed to be identicai

to the original specuum. A plot of the residuals (the dif5erence between the

experimental and calculated absorbante values) at each wavenumber, shows the

adequacy of the curve fit.

2.1 .S. Advantages and Limitations of FTIR Spectroscopy

A comparison of FTIR u-ith dispersive inf'rared spectroscopy explains why FTIR has

become the predominant way of obtaining infkred spectra. A dispersive instrument

contains a prism. which has to rotate to different positions correspondhg to different

wavenumbers. In dispersive spectroscopy, the Merent waveniimbers of Uifrared light

are introduced to the simple sequentially. In contrast, FTIR spectroscopy is a

throughput method. which means that al1 the infrared light (encornpassing ail

wavenumbers) passes through the sarnple at once. Therefore, in an FTIR device, the

detector receives a large amount of Iight during a short scanning tirne. Since a FTIR

spectrometer acquires the spectra much more rapidly than a dispersive instrument,

multiple scans can be averaged tu provide very hi& SNR.

Despite these advantages. FTIR spectroscopy has a few limitations. Since FTIR

detects chernical bonds and dipole moments between atoms, it is not practicai for the

analysis of monatomic materials. Furthemore, because of strong spectral bands

presented by some solvents. it can be extremely dficult to characterize chernicals in

a low concentration solution. In complex mixtures, it is necessary to apply numerical

techniques to distinguish. separate and categorize the responses. Another limitation of

FTIR spectroscopy is its sensitivity to background variations. Since it does not make

a sùnultaneous comparison of the background and the sarnple, these two spectra are

taken one afler the other. Any changes in the background composition between the

two readings directly affect the accuracy of the FTIR spectrum.

2.2. Fundamentals of SEC

Size Exclusion Chromatography is implemented to separate molecules in solution

based on their size. Sorting by size is followed by detennination of the concentration

and molecular weight of each size. The molecular weight distribution, a plot of

concentration versus molecular weight, can then be calculated. The entire separation

process depends on differences in the hydrodynamic volume of molecules. Porous

packing matenals such as siiica gels or polymer gels with well-characterized pore

sizes, are generaily used in the SEC columns. Al1 molecules that are Iarger than the

pores are completely excluded and pass through the column most rapidly. The

molecular weight above which molecules cannot enter the pores is cailed the

exclusion limit. Molecules which are very smdl d i h e into and out of aU of the

pores. They require the most time to elute. The range of molecular sizes that can be

resolved fiom each other lies benveen these two extremes, with the larger molecules

exiting first followed by the smaller. The major components of size exclusion

chromatography are shown in Figure 5: solvent r e se~o i r containhg the mobile phase;

positive displacement pump to provide a constant flow rate of mobile phase: injection

cornpartment, where each sarnple solution is injected in tum; columns (usually thtee

of them in series) where separation occurs: detector where concentration of each

molecular size is measured.

2.2.1. SEC Instrument

In common with other chromatography methods, the column is the centerpiece of the

SEC instrument. ïhere are two types of packing materials widely used in the SEC

columns. The fust type of packing material for SEC columns is silica particles, which

are comrnonly used in biopolper separation. Although silica gel usually has

hydroxyl fûnctional groups. the polymer king analysed should not have any

interaction with the packing materiai. The other packing material for SEC columns is

polymeric gel made fiom crosslinked polystyrene (PS) or polymethyl methacrylate

(PMMA). These columns are more commonly used in synthetic polymer separation,

and characterîzation. The crosslinked poiystyrene packing materiai is employed with

organic solvents, and crossiinked PMMA columns are used for the aqueous SEC of

synthetic polymers-

Solvent Injection

Cornpartment

Mobile Phase Waste

Figure 5: SEC components

Regarding the packing specifications, silica particles are typicaily 5 to 10 pm in

diarneter with pore sizes ranging from 50 to 1000A [3]. Similar pore sizes are usually

available for polymeric packing materiais. However? the crosslinked polymenc

packing may swell a little when placed in solvent, and can yield an effective pore

diameter as low as 10A. Although the pore size for the silica packing materials is

based on actual measurement. the pore size specified for the polymeric packing

describes the extended chah length of a polymer molecuIe. For example, a

poiystyrene SEC packing material with 1000A pore size is approximately equivalent

to a mie pore size of 80A in silica [3].

Columns with a narrow pore size distribution are available as well as mixed-bed

columns, which have a broader distribution of the pore sizes in order to separate

larger ranges of molecular weights. The most important parameter in a SEC column is

the range of pore sizes that ailows the sample components to penetrate into the

packing without complete permeation or total exclusion.

In addition to pore size. the number of available pores is also a significant

consideration. The pores should not become over-crowded with polymer molecuies.

According to the SEC rnanufacturers [3], columns with 75-80% porosity are u W y

suitable for SEC analysis-

Another SEC parameter is the operating condition of the size exclusion

chromatograph. SEC coIumn rnanufacturers often indicate 150°C as a maximum

operating temperature [3]. In fact. the columns can work at higher temperatures, but

the operating conditions wï1l affect the lifetime of the column. Although a column

might last two to three years at 30 to 50°C with t e t r ahydroh (THF) solvent, the

Iifetime typically would be six to nine months at 1 50°C with trichlorobenzene (TCB)

solvent.

In order to have reproducible results. a steady state flow rate of solvent through the

SEC column is an essentiaI factor. The constancy of flow rate is more important than

absolute accuracy. Flow rate must be constant to withïn about 0.1% during both the

calibration and sample experiments. Therefore, it is necessary to run standard samples

before and after experiments to ensure the new and old calibration curves are

consistent,

There are four detectors commonly used with SEC: differential refkactometer @Ri),

ultraviolet (UV). viscometer, and light-scattering detectors. For polymer analysis

purposes, the most commonly used concentration detector is the DRI. However, this

detector provides ambiguous data if the polymer molecules Vary in composition as

well as size. FTIR spectrorneter can be used instead of the DRI to overcome this

disadvantage. As pointed out in the Introduction to this Thesis, FTIR is potentialiy

much more powerfûl than DR1 as a concentration detector [3].

2.2.2. Calibration for Molecular Weight Prediction

To determine the molecular weight distribution of unknown polymers, the SEC

column needs to be calibrated wïth standard samples. Usually, these standards are

narrow molecular n-eight polymers which are precisely manufactured and

characterized. The molecular calibration cuve is a log plot of the molecular weight

versus the elution volume. The sfope and the intercept on the calibration curve depend

on the conformation and specific molar volume of the macromoiecuies. Absolute

molecular weight determination using the calibration curve is valid only if the sample

has the same conformation and chernical composition as the standards used to

establish the calibration.

2.2.3. DR1 Chromarogram Interpretation

A differential refiactometer is used to measure the concentrations of polymer

molecules of each size at corresponding retention times. This is done by measuring

the difference between the refractive index (RI) of poiymer solution and the RI of

pure solvent. The refractive index difference is directly proportional to concentration=

where u, c(r), and Wft) represent the proportionality constant (dependent on polymer

solution), concentration of polymer at each retention time, and differential refractive

index per retention time of e luen~ respectively. A conventional chromatogram is a

plot of the rehctometer response W ( i versus retention time. Integrating over ail

retention tirnes to obtain the area under the chromatogram results a linear relationship

between the area and the total mass of polymer that has passed through the system

t4l

r

Area = TW(t)dr = K fc(r)dr = m,,,, , O O

where min, and Area represent the injected mass of polymer and the area under the

DRI chromatogram. respectively.

To enable cornparison between DR1 chromatograms, these are often normalized. A

normalized chromatogram Wdt) is obtained by dividing each height W(t) by the area

of the chrornatogram.

By substituting Equations 16 and 17 in Equation 18, the concentration at any

retention time c(t) is proportional to the normalized detector response Wv(t):

where Wv(t) represents the normalized chromatogram response at the corresponding

retention t h e . The area under a normalized chromatogram. Wv(t) versus r . is unity. in

comparing two normalized chromatograms of two different polymers, the ratio of the

heights of these chromatograms at the same retention times is equal to the ratio of the

masses of the polymers present (Le. the composition) at that retention time.

For the SEC analysis of a polymer blend, Equation 16 is valid for each blend

component with K being different for each component (polymer). Thus:

W ( t ) = K I .cl ( t ) + K, .cl ( t ) .

where the subscripts stand for each component. Equation 19 assumes no interaction

between the pol ymer mo lecules.

2.3. Data Interfacing Techniques in SECETIR

There are several methods of i h e d sampling in the literature and each of them has

its own strengths and weaknesses. The objective of these methods is to detect the

concentration of polymers in the SEC eluthg Liquid. which is THF. The SEC eIuted

sampie is a very dilute polymer solution in a volatile solvent (mobile phase). ï h e

concentration of the dissoived polymer is less than 0.2 mghi and varies during the

elution. The FTIR instrument must be able to examine the eluting samples as they

exit of the columns. Accordingly, two types of interking techniques may be

practicai: use of an in-line Iiquid flow through cell; use of an evaporative interface

followed by off-line FTIR analysis of the deposited fiims. These two methods are

described in the following sections.

2.3.1. Flow Cell

The flow ceil in liquid chromatographyETIR was introduced in 1975 [5 ] . Currently,

there are a variety of liquid cells with potassium bromide (KBr) windows available.

Generaliy, these cells have circular. cylindrical or rectangular shapes. The cells can be

sealed or disassembled (Figure 6)- The ce11 consists of a metallic h m e , two KBr

windows (one of which has nvo tiny holes for inlet and outiet), and a gasket with a

specified thickness. The gasket is made of Teflon or lead-mercuxy amalgam. The path

length of the ceil is exactly the same as the thickness of the gasket. The inlet of the

cell is directly connected into the SEC outlet.

Since the path length is known. and there is no possibility of leak or evaporation, the

sealed liquid cells are very usefül in quantitative malysis [Il . The major Limitation of

sealed cells is that they are dificult to clean.

Window

Figure 6: A dernountable i h e d tiquid ce11

In order to maintain the separation obtained in the size exclusion chromatograph, the

flow ceil should not ailow fluid mixùig in the axial direction between the end of the

SEC column and the FTIR specuometer. This requires that the ce11 volume be much

smaller than the chromatogram volume (the solvent fiow rate times the duration of the

chromatogram peak). It is cmcial to utiiize a minimum number of connections and

tubing between the column outlet and the flow ce11 inside the FTTR instrument.

Compared with the solvent elimination approach, the flow ce11 interfacing technique

has several advantages. The most important characteristic of the flow cell is its

simplicity of operation. Generally, flow cells do not require any particular

maintenance. except the isolation fiom water vapor. Also the online infrared detection

takes place within the SEC time frame.

The most limiting constraint to utiiizing the flow ceil as an interface for SECFTIR is

the necessity of using infrared transparent mobile phase. In fact, the mobile phase

should:

r dissolve the sample

be suitable for SEC colurnn

demonstrate transparent windows for FTIR anaiysis

However, there are few solvents that meet al1 these requirements. In addition to

dificulties in the solvent selection, the flow ceil technique is comparatively noisy

since it permits only a few scans be completed during online datz acquisition. F i d y ,

there is the possibility of contamination and water absorption through the KBr

windows.

2.3 -2. Solvent Evaporative Interface (SEI)

To avoid the problem OF the mobile phase spectral interference in FTIR anaiysis,

solvent elimination methods have been recently empioyed. This approach in general,

involves presoncentrating the SEC eluent through flash vaporization. foilowed by

solvent evaporation from the substrate. After the solvent removal, the solute deposit

remains on the substrate for analysis by spectroscopy. The reason for this two step

evaporation is to eliminate the large amount of solvent in the eluent. With the solvent

evaporation technique. mobile phase âransparency is not an issue.

The first solvent elimination technique was introduced in 1977 [6] and practical

instrumentation for analysis of small molecuies (non-polymeric materials) was

developed in 1979 [7]. The collection stage was consisted of a set of small cups fïiled

with potassium chloride (KCI) powder. which were subjected to spectroscopy via

diaise reflectance. A hyphenated technique consisting of a thermo-spray and a

moving belt system for on-line Liquid Chromatography (LC) with FTIR spectrometry

was introduced in 1990 [a].

The fïrst solvent evaporation interface to be used with SEC was designed by

Dekmezian and CO-workers [9, 10) in 1989. It consisted of a vacuum oven equipped

with an ultrasonic atomizer and a programmable stepper motor, as shown in Figure 7.

The interface was comected to a high temperature SEC, and the eluent was sprayed

on potassium bromide ( KB r) plates using a nonelectrostatic ultrasonic nebulizer. The

KBr dishes were c w e d to prevent sarnpie loss, also flat substrates resulted in sample

accumulation on the edges of the disk. making FTIR analysis dinicult [9]. This

interface was successfidly empioyed in the composition drifi analysis of a copolymer.

The FTIR spectra were obtained after 500 scans with 8 cm-' resoiution, The detection

limit was 660 ng.

Figure 7: Evaporative Interface Designed by Dekrnezian in 1990 1101

A modification to this design was introduced by P.C. Cheung, S.T. Balke, TC.

Schunk, and T.H. Mourey in 1993 [Il]. They developed solvent evaporative interface

(SEI) and assessed its applications in quantitative analpis of polymers [12]. [n 1996

they published the effecr of evaporation conditions on the polymer fih morphology

and the importance of the film quaiity for quantitative analysis. in their quantitative

analysis of polymer blends. they used laser confocai fluorescence microscopy to

evaluate nIm quality. SEI was used for both hi&-temperature and room-tempeanae

size exclusion chromatography. Low operating pressures were used to avoid polymcr

decomposition. Some additional safety features. such as a vapor condenser and in-

gas purge were utilized- .- uitrasonic nozzle was used here instead of a nebuiizcr

(atomiPng nonle) to deliver a soft spray of dropiets preventing <hem f+om bouncing

back (Figute 8). Different collection substrates were wd Le. genaanium, potassium

chloride. and potassium bromide. This SEI was equipped with several thennocouples

to monitor temperature changes during the operation- The polymer film was collected

as a set of discrete ftactions on the disks.

Disks

Figure 8: The Collection Stage of the Solvent Evaporative Interface

Lab Connections. Inc.. developed the fmt commercial version of SEI in 1997. In this

interface a one-piece germanium disk was used to collect the polymer fiim as a

continuou stripe during size exclusion chromatography. Since one side of the disk

was aiuminurn coated O nI y re fiactive infiared spectroscopy was possible. That same

year, LN. Willis. J.L. Dwyer and M.X. LIU (Lab Connections Inc.) utilized SEI to

measure the compositionai dismbution of CO-polymers [13.14]. ï h e y concluded that

the main limitations of this technique were:

O lack of reproducibiii~ with sample to sample variations

O IR peak overlap and confusion in the identity of components

O operation interruption and lack of automation

O handling of solvent vapor difficulty and environmental concerns.

L.T. Taylor. and S.L. Jordan used the HPLCETIR with SEI in the detection of

polymer additives in 1997 [83. They expenenced the same difficulties in tems of the

reproducibility of quantitative result, as J.N. Willis et al. did. In their study, they

concluded that some factors related to the film lifetime? stabiiity and consistency

required consideration for the quantitative detection.

Eastman Kodakm contributed to the development of a solvent evaporation interface

suitable for the quantitative analysis of poiymers with extended sensitivity in 1996

(Figure 9).

SEC E luent

View Port

Heated Chamber

Figure 9: Diagram of the solvent-evaporation interface developed by Eastman

Kodakm [15].

This SEI. designed by T.C. Schunk and used in the present study, consists of three

major components: an ultrasonic nozzie, a vacuum chamber, and a collection stage

substrate. The ultrasonic nozzle is used to atomize the SEC eluent. The chamber is

jacketed with hot thermal oii and equipped with a vacuum pump. A condenser is

attached to the outlet. in front of the suction of the pump. Since the SEC solvents are

flammable. a nitrogen purge is used. The collection stage is maintained at a higher

temperature (via electrical heating) than the chamber to prevent solvent condensation.

The stage is covered with 20 germanium disks, which are located directly under the

n o d e . The germanium (Ge) substrate is transparent to infkred Iight and opaque to

visible light. Once the solution droplets corne out of the n o d e , the solvent is flash

vaporized and the polymer particles deposit on the Ge disk. If, for any reason, a few

droplets of the solvent reach the collection disk, the solvent will boil off immediately

because of the high temperature of the surface. The entire collection stage is

connected to a prograrnmabie stepper motor to enable easy rotation. The polymer

films collected on the germanium disks are themselves discrete fractions of the SEC

eluent.

Compared with the tlow ce11 rnethod. the SEI has the potentially much lower

detection limits with the absence of an interferhg solvent and the unlimited scanning

tune for high resolution. However. a major concern of the SEI method is that the

results are sensitive to the quaiity of the deposited films. Thus, the most crucial step

in the soivent evaporation technique is the deposition of the analyte on the substrate

[4]. It is extremely important to optimize the parameters in the evaporation chamber

to yield a uniform film. Any non-miformity in the thickness of the polymer film can

cause substantial errors and lack of reproducibiiïty in the FTIR spectroscopy .

Another potentially large source of error in the use of the SEI is the possibility of

sarnple loss. Polymers may be lost through deposition on the walis of the collection

chamber, and entrainment of particles in the SEI exit flow.

2.4. Data Analysis Techniques

Interpretation of FTIR spectra requires the calculation of concentration fiom

absorbance values using Beer's L a w This is generally a two step process: calibration

followed by prediction. Calibration establishes a correlation of absorbance values

with concentration of a particular functionai group. Prediction uses that correlation to

convert measured absorbance values to concentration values for "unknown sarnples".

To accompiish calibration and prediction. a variety of mathematical methods can be

used. The most cornmon are linear regression CR), muitivariate linear regression

(MLR) and partial least squares (PLS). PLS is a multivariate rnethod, which has

become most cornmonly used in the interpretation of near infrared spectra.

2.4.1. Linear Regression (LR)

In F m interpretation LR is the fitting of equations linear in the unknown parameters

to absorbance versus concentration data This includes straight lines and polynornials.

Inspection of Beeis Law would indicate that a straight line through the o r i w wouid

be appropriate. However this is not always the case. Deviations ffom Beer's law can

be caused by stray light or concentration effects for example. Also, if data fiom

several different wavenumbers are considered together then multiple linear regression

must be used.

In these linear regression methods as applied in FTIR interpretation, the unknown

coefficients are determined in a calibration equation by rninimizing the s u m of the

squares of the deviation between the measured absorbance and that predicted by the

fitting equation. An implicit assumption in the method is that the error in the

measured absorbance values is much less than the error in the concentration values.

Also, it is assumed that the error variance of the absorbance values does not Vary with

concentration. No weighting factors are used.

Measures of the adequacy of the fit include the multiple correlation coefficient

squared, the standard error of the estimate and the randomness and magnitude of

residuds. In multiple linear regression of a for example, Beer's law would be given in

matrix notation by :

where [A] is a (n x m) mavix of n calibration samples and rn wavenumbers (calied the

vector of absorbances), [q is a (n x p) matrïx of n calibration samples and p

components (called the vector of concentrations), and [KJ is a ( p x m) matrix of

coefficients to be detennined. To obtain a calibration mat* the absorbance and the

concentration values obtained from the standards is used to calculate the values in the

K ma& as follows [l ] :

where [qT is the %anspose" of [Cl, and the superscript -1 represents the inverse of

matrix. Once [KJ is calculated. the unknown concentration can be predicted as

folIows:

The Equation 21 suggests the best possible prediction for h o w n concentrations.

The multiple correlation coefficient squared (rz), is the ratio of the sum of variations

in y due to the regression (explained variation) to the sum of the variations in y due to

the regression and the random errors (unexplained variation)[16]. Or in other words, it

is the fiaction of the total surn of squares explained by the fit and is given by:

where

9i = predicted value fiom the fit

yi = experimental value

= s i / n = rnean experirnental value

n = number of samples.

The standard error of estimate (Syk) is the standard deviation for the residuals due to

ciifferences between the actuai values and the predicted values. S,,,, represents how

data are scattered around the fitted line. Therefore, the Lower is S,/, the better

regression.

Residuals (ei) are defined by deviation between the observed values and the predicted

vafues:

Residuals can be plotted versus the estimated values fiom the regression equation.

Lack of a non-random trend and low magnitude indicate a good fit.

2.4.2. Partial Least Squares (PLS)

Although, regression anaiysis is one of the most popular techniques in data analysis,

this method is susceptible to outliers [Il . Graphical display of the data allows

detecting such data- For complicated systems, multivarïate regression is often useci.

However, the dimension of [A] is often large compared with that of [q (in Equation

22), and in rnatrix manipulations (e-g. calculation of a determinant) it is possible

encounter "collinearity? In this situation the calculation of an inverse matrix (in

Equation 22) is impossible, and ordinary MLR cannot be used. Amongst the

alternatives, PLS is one of the most practical techniques. Table III compares LR,

MLR and PLS [17]. Each of these models is based on different variables and

assumptions, which cause errors in the results of each.

Table III: Cornparison of Calibration Models [17]

LR: Instrument responses = f (concentration) + error I MLR: concentration = f (Instrument responses x,, x2, . . .) + error

1 1 PLS: concentration = f (regession factors a,. a,, . . .) + error I Instniment responses x,. +, . . .= 5 (regression factors a,. a,, . . .) + emor

Ln the PLS aigorithm, the absorbance matrix [A],, and the concentration matrix

[Cj,, can be decomposed as follows:

The loading matrices [Q,, and [BI,, and diagonal matrix [Dl,, are calculated

during calibration (a step termed "training7' for PLS) as well as the component

number (a). [7'Jn, is the matrix of latent variables (''factors"). PLS treats both [A] and

[a as random variables. connected through the latent variables. For the "validation"

(Le. the prediction) step the matrices are [Ml:

where [Cl,, is the desired solution.

The spectral variations with concentration are used by the PLS mode1 to establish the

caiibration equation. Therefore, PLS needs a set of the training spectra which

represents the composition range of the samples. These samples mus contain the

constituents of interest, and encompass the range of expected concentrations for the

unknown samples.

PLS creates a set of eigenvectors that represent the changes in the absorbance. Mer

the training step has been accomplished. the mode1 is reduced to two main matrices:

the eigenvectors (spectra) and the scores (weighted values for ail the caiibration

spectra). In fact, PLS uses the concentration information during training. In other

words, the spectrurn with higher concentration will be weighted more than one with

low concentration. This minimizes the effect of the variables. which have a Iarge

fluct~liition but are irrelevant to the calibration cuve.

Aithough many regression techniques have been successfully applied for spectral

quantitative analysis. PLS has been found to have supenor predictive ability [19].

Furthemore, PLS can be easiiy applied to the quantitative analysis of complex

mixtures.

Nevertheless, there are many cases where certain calibration techniques have

performed better than PLS. One major concem with PLS is the uncertainty in

selection of the correct "training set" of data. Also, it has been shown that PLS can

produce misleading results if applied directly to raw data [20].

2.4.3. Data Interpretation

There are two main types of caiibration examined in this study: extemai calibration

and intemal calibration. For extemal calibration, polymer films are made by a film

casting method. Spectral deconvolution with baseline and absorbance band fitting is

used to rneasure the absorbance response of these standards. Fitting of the absorbance

versus concentration data using linear regression provides the necessary calibration

c w e . Intemal calibration utilizes "slices" of the DR1 chromatogram obtained fiom a

concentration detector on the SEC to provide the known composition values which

are correlated with the measured absorbances for the correspondhg polymer fiaction

obtained fkom the interface. PLS is used for calibration with the spectral input king

the second derivative of the absorbance with respect to wavelength.

2.5. Calibration

Calibration is the f i t stage in quantitative analysis. As mentioned in the previous

section, calibration establishes the relationship between the dependent and the

independent (measured) variables (i.e. between absorbance and concentration). When

a 80w ceii is used the sample is a polymer solution hctionated by the SEC. The

sample provided to the cell depends upon the SEC operating conditions. The usud

concems of good chromatography such as resolution of the coliimns and the

concentration of sample injected are the main concerns. However, when the SEI is

used then polymer films of the unknowns are to be anaiyzed and the situation is more

complicated. There are then two major calibration techniques: internai calibration

and e x t e d caiibration. These are described in turn in the following sections.

2.5.1. Intemal Calibration based on DRI

The most common detecto. used for concentration determination in SEC, is the

differential rehctive index (Du. This detector measures the rehctive index

'y ciifferences between the SEC eluent and the pure solvent. Since the DR1 response is

proportional to the concentration, the area under the DR1 chromatogram is equivaient

to the total nass injected into the SEC column_ Therefore, each slice of the DR1

chromatogram represents the concentration of the SEC eluent at certain times. These

elution times can be related to the molecular size of the polymer sample.

Although this appears simple, in practice there are many potential sources of error.

For example, axial mixing in the columns results in more than one molecular size

exiting at the same retention volume and a consequent enoneous concentration values

for a specific molecular weight. Incorrect specification of the time required for

molecules to pass fÏom one detector to another (or in the case considered here, the

time required to reach the DR1 as opposed to the time required to reach the substrate

in the SEI) can mean <bat difTerent groups of molecules are king compared rather

than the same group. Finaily, the mechanics of treating the raw data, notably the

drawing of a baseline c m easily contribute significant enor to the resuits.

If there is some noise, baseline drift, or instability in the signal, fitting can be difncuit.

More ofien there is a baseline specification problem at the tails of the chromatogram.

The baseline specifies the height of the chromatogram so that a 2% error in the height

c m cause up to a 20% error in the chromatogram area and a 20% error in the average

molecular weight (MJ prediction [2 11.

Finaily, the complexity of the molecule can easily render assumptions involved in

conventional SEC interpretation invalid. If a copolymer is analyzed using a DR1

detector for exarnple the detector will respond differently to the two different

monomer units present. ïhen if the composition of the molecules varies with

molecular size the DR1 response wiil be reflecting both composition and

concentration of the molecules (i.e. not only concentration).

2 .52 . Extemal Calibration by Solvent Casting

, The other option for the calibration of SECIFTIR with SEI interface, is to the use

solvent cast films. Just as the SEC eluent is sent to the solvent evaporation chamber to

generate a polymer film on the germanium disc, a similar process can be

accomplished manuaily with the standard solutions. The objective is to develop thin

polymer films of difZerent thickness on the same germanium disks that are used in

SEI. Since the concentrations of the standard solutions are already determined, the

deposited mass on each substrate is known. The f i h can then be rneasured using

FTKR to obtain an "extemal caiibration" for absorbance versus mass.

Although the process is straightfoward, there are several technical difficulties that

c a . produce significant errors. The morphology of the polymer film on the

germanium disk c m cause dramatic distortions in the FTIR spectnim. When the film

is not uniform and flac IR Iight scattering may increase distortions in the specnim.

The non-uniformity may provoke a sioping baseline, affecthg the height of

absorption bands [22]. If there are bare spots or pinholes on the disk, the m e a d

absorbance wiil be lower than its true value. There is a mathematical relationship

between bare area and the observed absorbance, which quautifies this effect [22]:

where AmeDIFUred, A, -Y represent the measured absorbance, the tnie absorbance and the

bare area hction on the substrate. respectively. Therefore, it is evident that the non-

uniformity will be a major issue. Moreover, different evaporation rates can

dramatically affect the degree of the non-unifonnity.

The other issue is the difference between the morphoiogy of the extemal standards

and the experimental samples from SEI. Even if the calibration standards have a

uniform appearance. the SEI samples can have a different morphology, and vice

versa Thus, the suitability of -'extemai calibration" for analysis of samples obtained

fiom the SEI becomes more uncertain because of the morphology effect.

2.5.3. Comparison of Calibration Methods

In this midy the above two distinct methods of interpreting the data were compared

To accomplish this cornparison, two quantities were calcuiated: polymer composition

and total mas.

i. Poiymer Composition

Composition (weight percent of one of the polymer components present) versus

retention time as measured by:

i.a Chromatogram heights nom separate PS and PMMA chromatograms.

i.b. The ratio of concentrations of PS and PMMA as obtained fiom the external

caiibration curve

i.c. The ratio of concentratioas of PS and PMMA as obtained from PLS based on

the internai calibration.

Accuracy of these data was rneasured using Relative Percent Error (RE). RE

quantined the difference between i.a and i.b, or i.a and 1.c above and is defhed by:

where mj is the predicted mass of conponent j, w$% is the weight percent of

component j, RE is the relative error, 3 is the weight fkaction of component j (e.g.,

weight fiaction of poly(methy1 methacrylate)) and the method used to measure wj is

indirated by the subscript IR for FTIR measurement and DRI for diffeRntai

", rehctive index measurement-

ii. Integrated Mass

The total mass was calculated by integrating the concentration of one of the

components versus retention volume:

where m is the mass. ci is the concentration of the component at retention volume vi

and A v ~ is the retention volume increment. The ~mmation was carried out for aU

vaiues of vi.

Mass accuracy (MA) was obtained from:

where r n l ~ is the m a s obtained using the FTIR and m m is the m a s obtained using

the DRI.

Precision (i.e., repeatability) was quantified for total intepted mass by computing

the coefficient of variation (the sample estimate of the standard deviation divided by

the mean). Precision of local composition vaiues was not quantified but can be

judged from the scatter in the plots of composition versus retention t h e .

3. EXPERIMENTAL

This pmject was accomplished in close collaboration with Dr. T.C. Schunk at

Eastman Kodak Company in Rochester, NY. Experimentaî data for the thesis was

obtained both there and at the University of Toronto (U of T). AU SEC nms were

performed at Eastman Kodak Also, FTIR =ans of the product h m the SEI were

also done there. Experimentai work done (U of T) included the evaluation of the flow

cell alternative to the SEI and development of the extemal calibration m e t h d AU

data interpreîation work was done at the University of Toronto. This section

describes material and equipment. Experimental procedures described in this section

were only routine procedures. Two of the objectives of the thesis are development of

experimental techniques. That work is detailed in the Results and Discussion section.

3.1. Materials

Three polymers were used in this study: polystyrene (PS) NBS 706 fiom NIST

(Washington, DC, USA), poly(methyimethacry1ate) (PMMA) broad standard lot

037B fiom Scientific Polymer Products (SP2) (Ontario, NY, USA), and commercial

me thacxy late) copolymer fÏom Polysciences Inc., (Warrington, *

\ PA, USA).

3 -2. Size-Exclusion Chrornatography (SEC)

SEC separations were performed on a three-coiumn set of PLgel 10 pm 300 x 7.5 mm

mixed bed columns (Polymer Laboratones, Amherst, MA, USA). A Waters 590

pump (Waters Associates, Milford, h4A, USA) was used to deliver 1.0 ml/min of

fkshly distilled helium sparged tetrahydrofüran (THF). HPLC grade THF (J. T.

Baker, Phiiiipsburg, NJ, USA) was distilled h m d c i u m hydride (Eastman Kodak

Company, Rochester, NY, USA) to eliminate peroxides and water. Polymer samples

at 5.00 mg/mL total concentration in THF were injected h m a 100 pL Ioop using a

Rheodyne (Cotati, CA, USA) injection valve. AU samples were anaiyzed at least in

triplicate. A second Rheodyne valve was used to switch the solvent flow after the

columns to either a Waters Assoc. Model R401 differential refkctive index @RI)

detector or the solvent-evaporaîion interface as shown in Figure 10. The solvent flow

path shown in Figure 1 0 was configured to provide equal volume fiom the switching

valve to either the DR1 or solvent-evaporation interface.

A .minimum of three replicates for each SEC experiment with twcj homopolymers . . -

three polymer-blends and one copoiymer were performed.

3.3. Flow Ce11

A circular Spectra-Tech demountable Iiquid ce11 and a rectanguiar Perkin-Elmer

demountable liquid cell. both manufactured by S pectral-tec h (Shelton, CT, USA),

were used for the liquid sampling. Teflon spacers and 2mm thick KBr windows were

utilized in b t h types of flow cells.

3.4: Solvent Evaporation Interface (SEI) '.

The resuits described in this work were generated using a custom built solvent-

evaporation interface similar in basic design to that described by Dekmezian, et al.

[IO]. A diagram of the solvent-evaporation interface is shown in Figure 9. The I

interface consisted of a stainless steel temperature-controlled vacuum chamber. The

temperature of the evaporation chamber was controlled by circulating silicone ail

through the double walled chamber at 60°C with a Haake Model DCS-GH (Paramus,

NJ, USA) circulating bath. During sample collection the chamber pressure was

maintained at 25 mmHg (0.483 psia) using a dry ice trapped vacuum pump to remove

solvent vapor and a 4.5 Vmin N, purge. The stainiess steel sarnple collection wheel

was 150 mm in diameter with 20 equaUy spaced wells holding 13 x 2 mm polished

germanium (Ge) disks (Spectral Systems, Hopeweli Junction, N'Y, USA) as coUection

substrates. The collection wheei was maintained at 90°C on a nickel-piated copper

stage temperature controlled with silicone oil fiom a Haake Mode1 A81 circuiaiing

bath. The SEC solvent Stream was sprayed onto the Ge disks using a Sonotek Corp.

(Poughkeepsie, NY, USA) 120 kHz uftrasonic nozzie at 0.50 W power. The nozzie

temperature was stabilized at 30°C with a 40 psig & Stream inside the nozzle

- --

For each SEC analysis the interface chamber was equilibrated with the THF vapor of

the SEC eluent for 17 min after sample injection prior to the start of sample coilection

(see Figure 20). SEC samples were collected as 19 fiactions each 20 sec in duration

across the SEC chromatogam by positioning the sample wheel with a computer

controlied Slo-Syn stepper motor (Superior Electric, Bristol, CT, USA).

A minimum of three replicates for eaçh SEI expetiment with two homopoiymers three

polymer-blends and one copolymer was performed.

3.5.. Sample Preparation and FTIR Analysis

\ m e r sample collection. a cover plate was placed over the sample wheel and the

assembiy removed from the collection chamber. To irnprove coilected film unifonnity

and minimize IR scattering distortions, each Ge disk was briefly exposed to the vapor

above refluxing dichioromethane (J.T. Baker) after the sample wheel was removed

fkom the interface. M e r this solvent annealing, the sample wheei was placed on a

similar stepper motor drive in the FTIR spectrometer. FTïR spectra were obtained at 8

cm" resolution with 32 CO-averaged scans using Mattson WinFirst software. Spectra

nom manually cast calibration films were obtained with a M a o n Gaiaxy 6020

Spectrometer (Madison, WI, USA). Spectra from SEC fiaction fiims collected with

the soivent-evaporation interface were obtained on a Matwn Polaris spectrometer.

3.6. Data Analysis

S pectrai deconvolution was performed using PeakFit software (SPS S lac., Chicago,

IL, USA). Partial Least Squares calibration models and quantitative calculations were

perforrned using PLS IQ GRAMS/32 samare (Gaiactic Industries Corp., Salem,

New Hampshire, USA).

PUP 1 I

1 mL/min . Freshly distiIled THF w/ He purge

100 & Valve SEC Coiumns

DR1 Detector Switching Vaive 11 FTIR Spectrometer

e #

Solvent Evaporation Interface

l

Vacuum Pump Dry Ice Trap

Figure 10: Experimental system configuration with alternate DR[ or solvent-

evaporation-intefiace comection [ 1 51

4. RESULTS AND DISCUSSION The main objective of this study was to investigate the use of FTIR as a SEC detector.

The most direct approach to accompiishing this was to simply measure the

absorbance of the polymer in solution as it exited the chromatograph. Iffeasible, this

approach was potentially much easier and l e s expensive than the use of the solvent

evaporation interface (SEI). Feasibiiity depended upon the location of the mid

inhred absorbance bands present in the polymer compared to those present in the

solvent Polystyrene and PMMA were the polymers of interest here. The approach

was evaluated by simply filling the ceii describeci in Section 2.3.1 with solution and

measuring absorbance without any SEC. As detailed in Section 2.3.1, this ce11 had a

low dead volume and could be used in a flow through mode with SEC if the redts of

the evaiuation were positive. These r e d t s are presented and discussed in the next

section.

4.1. FTIR Analysis of Solutions

IR solution spectra were obtained for a senes of PMMA and PS sampies in the off-

line liquid cell. Dichloromethane was found to provide improved mid-IR

transparency compared to THF, for absorbance bands of PS and PMMA. However,

the *background absorbance of the solvent signincantly reduced the usable mid-IR

range and produced many low level interfering bands. Although it was possible to

obtain a linear calibration response for PMMA at concentration levels present in SEC,

no usable calibration at al1 could be obtained for PS. /

The validity of Beer's law for PMMA in THF is demonstrated in Figure 1 1. The plot

shows a consistent response for three Merent samples. However, most of the

concentration values were greater than 0.2 mghi , the maximum value present in SEC

analysis. Thus, although these results confinned the reproducibility and the reliability

of the flow ceil for off-line quantitative analysis it was necessary to examine its

performance at concentrations used in SEC.

Liquid Cell Calibrrtion for PMMA in THF 17pl Ciraiiar CeIl. 8 an" Remlution. 32 Scons

Fig 1 1 : Detectability of Liquid CeU in High Concentrations

9 o.,

0.02

O

Liquid Cal1 CIlikitio11 for PMW in THF 17pl Cirwlar CeU. 8an" Resolution. 32 Scons

-

Figure 12: Detectability of Liquid Cell in a Broad Range of Concentrations

The detector calibration curve resulting fiom using the more Wute solutions are

shown in Figure 12. The spectra shown in Figures l3,l4, and 15 demonstrate how the

signal to noise ratio for the characteristic peak at 1730 cm-' drops dramaticaily as the

solution becomes more dilute. To improve sensitivity, the FTIR resolution and the

scanning time were increased, but the resuiting spectra were not adequate for a

calibration curve. Figure 16 shows how the poor detectability for PMMA in the range

of concentrations used in SEC (c 0.2 mg/ml) tends to flatten the calibration curve in

this region.

Wavenurnber, cm"

Figure 13: FTIR Spectra for 1 O m g h i PMMA in THF (0.3m.m Spacer)

PMMA Characteristic

1 band at 1730

'l Y -

Wavenumber. cm-'

Figure 1 4: FTIR Spectra for 1 -5 mg/ml PMMA solution in THF (0.1 mm Spacer)

05

Abs.

Wavenumbar. cm"

Figure 1 5: FTIR Spectra for 0.0 1 5mg/ml PMMA solution in THF (O. 1 mm Spacer) No PMMA peak is evident

Using a larger liquid ce11 improved the detection Limit (Figure 17). However, the

larger ce11 would be expected to cause more axial dispersion when it is connecteci to

SEC. Another iimitation of such long rectangular ceils is that they have a s d e r

window area for the IR Iight beam compare with the area of circular cells.

Liquid CeII Calibmtion for PMMA in THF 17 pl Circular Cell. 2an" Remlution. 64 sans

Figure 16: The effect of increasing the resolution and the nurnber of scans to improve detectability for PMMA in SEC concentration range

liquid CeIl Cllibration for PMMA in THF 60pI Long Redanguior Liquid CeIl, 4un" Remlution. 32 s a n s

y = 0.0009~ - 0.0108 ? = 0.9837

I

Figure 1 7: Calibration for PMMA with large volume Liquid Cell

Liquid Cd1 Calibrrtion for Polyatynm in THF 60pl Long Rectangular Liquid CeII. 4cm-' Resolution, 32 S a n s

Figure 18: Calibration for PS in TW with large volume liquid ce11

~iquid Cell Calibrathri for PMMA in CHICI2 6 0 ~ 1 Long Rcdangdar Liquid CeII, 8cm-' Resolutmn. 32 Sans

Figure 19: PMMA detectabiiity in CH2C12

Although a linear calibration cuve could be generated for PMMA, no usable

relationship between the absorbance of the polystyrene IR bands and the polystyrene

concentration was evident (Figure 1 8). This was because most of the PS characteristic

bands were concealed by strong THF peaks.

To have a better window for PS peaks, dichloromethane (CH2C12) was substituted for

THF. Although the software package PeakFit, was employed to deconvolute the

overlapping peaks, it was not possible to define a reliable calibration curve for

polystyrene for concentrations used in SEC. Figure 20 shows the extensive

overlapping of the polymer and solvent peaks indicating the difncuky for

deconvolution attempts. Figure 21 demonstrates the lack of linear dependency of the

absorbance on the sampIe concentration (iack of agreement with Beer's law).

Wavenumber , cm-' Figure 20: Detection window for PS and PMMA with dichloromethane

Liquid Cell Calibmtion for Polystyrene in CH2C12 601 I Long Ractangular Cell. 8m" Resoluüon. 32 Scans

Figure 2 1 : Lack of detectability for PS in CHzClz within the SEC concentration range

From al1 of the above results it was very evident that analysis of PS and PMMA

blends and copolymers could not be accompiished by measurïng solution

absorbames. Removai of the solvent (i.e. analysis of dried polymer films) was the

only practical method for FTIR detection.

4.2. Solid Films for FTIR Analysis

As detaiied in Section 2-52, a primary consideration when poiymer films are to be

analyzed by FTiR is the quality of the film. In this study films were generated by the

SEI and by solvent casting. The latter were needed for extemal FTIR caiibration.

The following two sections examine the film quaiity considerations in each of these

respective cases.

4.2.1. Film quality From the Solvent Evaporation Interface

The properties of the polymer solution and of the collection substrate combined with

the interface conditions to provide films, which were consistent in diameter, but

variable in thickness. This adversely affected the quality of the IR spectra obtained,

most obviously in terms of scattering distortions. Figure 22 shows the typicai

improvement in spectrai baseline, band shape, and absocbance intensity obtained via

the solvent annealhg process used to improve film uniformity 1253 (with "solvent

annealing" the films are briefly exposed to solvent vapor in order to improve their

unifomiity). It is evident that spectral quality could be greatly improved by

annealing. However, the disadvantage of this approach is that it adds a slow, labor

intensive step to the andysis.

4.2.2. Film quality fiom Film Casting

Polymer film uniformity was also determined to be critical to the generation of

extemd standards of manually cast polymer films for FTIR calibration.

As Collected Fiim

CH,Cl, Vapor Annealed Film

Wavenumber [cm'']

Figure 22: impact of solvent annealing on the IR scattering background for a 50-50

PSPMMA blend fÏaction collected fiom SEC with the solvent-evaporation interface

Polymer films were solvent cast using two techniques: ofnine casting and online

casting. The offline method iovolved pipetting a hown volume (60 te 100 pi) of

polymer solution to the surface of a germanium disk and evaporating it over a one

minute period on a hot plate. The online method utilized the SEI to produce the filmn.

.. The SEC was bypassed and a high volume (2 ml) of the polymer solution was

injected into the SEI chamber to generate the needed films.

Figure 23 shows the impact of changing casting conditions for the application of a

measured volume polymer solution onto a heated germanium disk. Rapid evaporation

provided more uniform films with less of a tendency to form a "doughnut" shaped

deposit. In addition, centering of the cast fiim on the Ge disk was critical to providing

consistent absorbance response.

100 ua PMMA on Ge Disk

O I t 8

1 2 3 Replicate

Heat & Centered i Heat, but

ûfF Center IR heating

Figure 23: Impact on 1730 cm-' band absorbance of casting conditions observed for

manuaily cast reference films of PMMA on polished Ge disks [15]

Mm Full Fieid +/- 1 s a

I 1 1 1 1 I

1 2 3 4 5 6 Replicate

Figure 24: Determination of film uniformity of mandly cast PMMA fihs using

masked areas as show in the inset. The gray band indicates +/- one standard

deviation range about the mean obtained fiom full fieid spectra [15]

The unifomïty of the solvent cast poiymer film standards was evaluated by a

masking experiment as indicated in Figure 24. Four spectra were obtained for each

cast film using a smaii diameter mask to provide IR transmission. Since the masic

opening could be set at various positions around the perimeter of the nIm, absorbance

obtained through the opening could be compared to that obtained in the centet,

variations in the poiymer film thickness were detectable. For accurate absorbance

caiculations, blank spectra were obtained h m a cleau Ge disk with the same masked

area With the type of data obtained in Figures 23 and 24, it was possible to verify tht

quaiïty and consistency of al1 manualiy cast polymer films used as standards for

external calibration.

4.3. Use of the Solvent Evaporation Interface with Extemal Calibration

As can be seen fiom the previous section, nIm quality can be improved by solvent

anneahg if necessary. Also, a method of assessing the uniformity of nIms was

devised. Thus, high quality spectra couid be obtained fkom both the SEI and k m

solvent casting. The problem remaining was interpreting the spectra The foiiowing

sections describe how the spectra were interpreted to determine composition of

polymer blends and total mass collected using external calibration and the SEI. \

4.3.1. Spectral Deconvolution

For the external standard lhear regression caiibration approach, al1 spectra were

deconvoluted using fixed parameters in PeakFit Software.

Baseiine correction of a smaii IR region with Gaussian band-shape fitting of the 699

cm-' band with PeakFit Software is shown in Figure 25. Note that the best-fit baseline

passes through some positive response regions. Inspection of the fingerprint region

(1000-1500 cm*', not shown in Figure 25) often reveais the absence of any points of

zero absorbance with such a baseline. Thus, the baseline shown in Figure 25 may

provide underestimates of band intensity. However, use of the fidi spectnim degrades

the baselke fining accuracy by emphasizing large-scale baseliae shifls at the expense

of accurate baselines in the vicinity of absorbance bands. Deconvolution of narrow

spectral regions as shown in Figure 25 was chosen as the best aitemative.

- - --

650 750 850 950 Wavenumber [cm1]

0.074

0.03.

Figure 25: Example result of PeakFit software baseline and Gaussian band fitting for

a narrow region of a PS film spectnim 1151

-- - -. . Polystyrene Film 1)

B

t

Linear Baseiine fi.

I I 8 .

4.3.2. Linear Regression Calibration

The resulting extemal calibration data and LR fit for a series of m a n d y cast

polymer films of PS and PMMA are shown in Figure 26. For each polymer a strong

absorbance band not overlapped by response fiom the other polymer blend

components was selected for caiibration.

Lm 8

IR Band Area

Figure 26: Caiibration plots of absorbance band areas determinecl with PeakFit

software for manualIy cast polyrner films. The dotted lines indicate 95% confidence

intervai ranges about the regression h e s 1151

Figure 26 aiso shows the 95% confidence intervals for the extemai calibration curves.

These confidence intervals are caiculated based on the sample variance of the

estkpated mean value and tad.ox Eom the d e n t s t, tables. It can be observed haî al1

.. data points are weIi within the interval. The 95% confidence intervals include the

ongin, which agrees with Beer's law. These conf5dence intervals can also be used to

detennine the 95% confidence interval on predicted mass given a specific absotbance

value. For example, an IR peak absorbance of 4 at 1730 cm" yields a 95% confidence

intemai for predicted mass of 37 to 46 pg. This prediction does not take into account

the error variance of the measured absorbance (the error in the value of 4 in this

example).

Figure 27 shows calibratïon cuve obtained using the online method. Again Beer's

law is shown to be obeyed and good correlation coefficients were obtained.

Online Calibtation for PS and PMMA For Three Replicates

i +PS y = 0.0192~ + 0.08 rZ = 0.973

Figure 27: Odine Calibration of PS and PMMA

4.3.3. The EEect of Molecular Weight

The performance of the solvent evaporative interface (SEI) may be affected by the

molecular weight of polymer. For example, a solution of high molecular weight

polymer has a high viscosity which may affect the performance of the uitrasonic

nozzle. If the nozzie produces larger droplets then the existing distance between the

n o d e tip and the collection nage wili be imdEcient for complete evapoation.

Therefore, the polymer film thickness will then become non-uniform due to solvent

build up on the substrate. To examine this effect, several samples of very nanow

molecular weight distribution polystyrenes with molecdar weights ranging fkom

1x10' to 1.6x106 g/mol were analyzed using the interface. R e d t s are show in

Figure 28 as a plot of the area under the spectraî peak at 699 cm" used for PS versus

the molecular weight of the polystyrene anaiyzed. Resuits fkom both deconvolution of

the conventional spectnun and fiom obtaining the area under the valley portion of the

second derivative spectnim (see description in the experimental section) demonstrate

that the molecular weights above 200x10~ al1 provide the same results. However,

below that molecular weight the area noticeably decreases. This indicates m a s loss

and is attributed to the deposition of low molecdar weight species on the SEI w&

possibly because at the same residual solvent level the drying droplets wouid be more

adherent to the wails (Le. the solvent-polymer mixture would be more Iikely to have a

glass transition temperature below the temperature in the evaporation chamber). Also,

polymer molecules (such as those in a low molecular weight taii of chromatogram)

present at low concentrations can f o m small dned particles wtiich would be entrained

in the exhaust of the SEI-

PS Molecular Weight Series Th ree Replicates

1 1

O 200 460 600 800 1Wû 1200 1460 1600 l

i * 1 Mohcular M g M of Poiystyirno x i 0 j Î

l i I Figure 28: The Effect of the Molecular Weight on the Performance of SEI

4.3.4. Assessrnent of Beer's Law Deviations

It was recently suggested [26] that the characteristic band of polystyrene at 699 cm-'

wavenumber does not show a linear response with concentration 1261. Such a

deviation fkom Beer's law may indicate the presence of a factor other than

concentration influencing the absorbance. For example, the deviation may be due to

the interaction of the phenyl ring with neighboring fiinctional groups and so the

absorbance obtahed may be significantly dependent upon the morphology or

composition of the film. To examine this possibility, the band ratio of the peak at 699

to that at 3026 cm ' (phenyl CH peak) was compareci for different compositions

(Figures 28, and 29). The reason for selection of the phenyl CH peak is its strong IR peak. It is also shown later (in Figure 37) that the IR peaks of pheny, and aliphatic

CH groups (in PS) demonstrate a linear calibration curve as does the peak k m

phenyl ring at 699 cm".

Three compositions and three replicates were evaluated. As shown in Figures 29 and

30, the resuits did not show any significant variations in the band ratio of pure and

blend samples in the centrai portion of the chromatograms. The variations bctwcea '

the compositions at the tails of the chromatograms (020 - t48.6 min) were not

considered signincant because of the error inherent in ratioing values where the

denominator is neariy zero.

Polystyrene Peak Sensitivity Pure and 50% PS Blerid with PMMA

17.8 18.8 19.8 M.8 21 -8

aiution tirne, min

Figure 29: The band ratio cornparison of PS bfhred peaks for 75% blend and puré

samples

The results in Figures 29 and 30 also show that there is less variation in the ara ratio

for higher compositions than for lower composition. This was also atîributed to the

higher SNR of polystyrene idkared peaks obtainable with the higher composition.

There is more error invoived in the peak area caiculations of low SNR responses.

1 Poîystyrene Peak Sensitivity f 1

1 1

I Pure and 75% PS B l e d with PMMA

I 4 ,

17.8 18.8 19.8 20.8 21.8 k

eiution the, min l t

-- - - - - - -

Figure 30: The band ratio cornparison of PS hfkired peaks for 50% blend and pure

samples

The deconvolution technique c m also affect sensitivity- The characteristic band at

699 cm-' is located in the fmger print (600-1500 cm-') region, and overlaps several

smaller peaks. Therefore, the baseline fit needs careful attention. The PeakFit

software selects the best baseline according to the second derivative of the spectnim.

The location (wavenumber) and the number of the IR peaks in the region were

detemiined based on the 2** derivative plot. The peaks are located exclusively h m

the local minima (called a valley) in the second derivative data With this information

the iext step would be baseline correction. The general principle is that baseline data

points tend to exist where the second derivative of the data is zero. Therefore the

baseline can be passed through these. The options for the baseline fûnctions included

linear, quadratic, cubic, logarithmic, exponential, power, hyperbolic and non-

parametric. For the majority of this work the linear, the hyperbolic, and the

exponential baseliae selections were used.

4.3.5. The composition of Polyrner Blends and Total Mass Collected

The linear regression FTIR calibration equations fkom the data shown in Figure 26

were applied to quanti@ the polymer blend composition across the SEC

chromatograms for a series of PSPMMA blend ratios. For each sample, the solvent-

amealed polymer FTIR film spectnun of each SEC fiaction was analyzed for PS a d

PMMA mass content. The weight percent PMMA in each fkt i sn was then

calculated fiom these individual values. Figure 3 1 shows the r e d i s of tbee replicate

analyses as data points compared with the solid line indicating wt.% PMMA

calculated fÏom the previously determineci DR[ chromatograms (Equations 34 and

35). Aiso shown in this figure are the nomalized chromatograms for PMMA and PS.

wt% PMMA

18 20 22 24 Elution Time [min]

Figure 31: Calculated 5050 PSFMMA blend composition using LR external

calibration expressed as weight percent PMMA of annealed SEC fractions obtained

fiom the solvent-evaporation interface. The heavy solid line indicates the weight

percent PMMA calculated from DR1 data. Data points are h m each of three replicate

SEC experiments [ 1 51

Agreement is excellent between the blend composition across the SEC

chromatognims calculated fiom the independent DR1 signals and the FTIR

quantitation. The shapes of the composition curves agree for al1 blend sampIes even at

long retention times where the total mass of the polymer is less than 10 pg.

With the use of extemal caiibration standards, the percent recovery of the solvent-

evaporation interface can be e h a t e d fiom addition of the individual M o n

masses. For the 5050 blend samples of Figure 3 1, an average value of 1 0 1.4% of the

expected mass over the collection time was found for the three replicates. This ciearly

indicates that within experimentai precision, the entire sample was deposited on the

Ge collection disks by the SEI and lends confidence to the use of the intemal

caiibration approach discussed below for the PLS modeling.

Further analysis of the accuracy of the FTIR quantitation was evaluated by comparing

the DR1 expected blend composition to that determined by extenial caiibration.

....... let 0 75% PMMA

a 50% PMMA

A 25% PMMA

Elution Time [min]

Figure 32: LR extemal caiibration relative percent e m r in wt.% PMMA prediction

Cl SI

Figure 32 shows the relative percent error (Equation 36) of the calcuiated wt.%

PMMA for each fiaction across the SEC blend chromatograms for average blend

compositions of 25,SO and 75%. Figure 33 shows the weight percent &ta that served

as the basis for Figure 32. Across the rnajority of the SEC chromatogram, the relative

error in FTIR predicted W.% PMMA is within the 110% range. That is, values

determined by FTIR using extemal caiibration generally a g d with those obtained

fiom the

9 z h

f

18 20 22 24

Elution Time [min]

Figure 33: Compazison of wt.% PMMA across the SEC chromatograms determined

by FTIR LR external cdibration (data points) and DRI (solid iines) Cl 51 .,..

4.4. Use of the Solvent Evaporation Interface with Internai Caiibration

In contrast to extemal caiibration where cast films were used, with internai calibration

the DM chromatograms combined with the mass injected provides the caiibration

curve. The objective was to use internai caiibration with Linear regression to anaiyze

annealed films fiom the SEI and with PLS to analyze both annealed and as-collected

(un-amealed) films. The following sections examine r e d t s fiom each of these three

cases.

4.4.1. Internai Calibration for the Composition Analysis of Annealed

Films Using Linear Regression

The SEC of polystyrene (PS) and poiy(methy1 methacrylate) (PMMA) bleds

provided chrornatograms r e f i e c ~ g a wide variation of polymer blend composition

with retention tirne. Figure 34 shows the cornparison of individually obtained

nonnalized (using Equation 16) DR1 chrornatograms of the reference PS and PMMA

samples used in this study. For ail sampies, a constant mass of polymer was injecteci

into the SEC colllllln~. Polymer blend composition was varied for ciifferent blend

samples by changing the ratio of PS to PMMA in the blend solution. The heavy line

in Figure 34 shows the weight percent PMMA calculated using the DRI signais

across the SEC chrornatogram of a 50150 blend of the PS and PMMA (Equation 34).

crg ta1 polymer

NBS706 PS sp2 PMMA

18 20 22 24 26 28 SEC Elution Time [min]

1 O0

wt% PMMA

50

O

Figure 34: Normalized DR1 chromatograms of pure PS NBS 706 ( ) and

PMMA ( . . . . ... ) used in blend SEC experiments [1 S]

The right axis indicated on Figure 34 is the calculated weight percent P W present

in a 5050 blend sample across the SEC chromatogram whereas the left is the usual

weight hction per retention time increment referring to the normalized

chromatograms. The solvent-evaporation interface was used to collect fiactions h m

each SEC chromatogram for FTiR analysis between the start and stop times indicaiai

in the Figure 34.

Interna1 Calibration Curve for PMMA

1 Aliphatic Peaks y = 0.0737~ - 0.08 9 = 0.97 '

8 Carbonyl Peak at 1730 cm-1 y = 0.0896~ + 0.14 3 = O.% j O IR Peak Ratio

- " ---../.=-2- -2 --.--a-- -I;I 3

O 10 20 30 40 50 60 70 80 PMMA lllku ftom th. nonnalizad DR1 slicos pg

Figure 3 5: Calibration alternatives for PMMA

The caiibration c m e s for PMMA and PS based on the DR1 chromatogram and FTIR

peak area at the certain IR wavenurnbers are shown in Figures 35 to 38. Ail of these

lines had multiple comlation coefficient squared values of p a t e r than 0.938 and

standard error of estimates less than 0.282. Intercept values were very small. Tbus,

obedience to Beer's law was indicated in ali cases.

Interna1 Calibration Curve for PMMA Three Replicates

- -

Figure 36: internai Calibration for PMMA

lnbmal Calibmtion Cunre for Polystyrens

Figure 37: Calibration alternatives for PS

Interna1 Calibntion Cuwe for Polystyrene Three Replicates

Figure 38: Intemal Calibration for PS

4.4.2. Intemal Calibration for the Analysis of Annealed and As-Coilected

Polymer Blend Films Using PLS

Linear regression methods codd not be used with spectra of as-collected polymer

blend films because the spectra were so distorted as to be not suitable for

',

deconvolution. However, PLS was usable for both annealed and as-coliected -. But even then it was found necessary to use the second derivative of absorbante with

respect to wavelength rather tha. the raw spectra as inputs to the me-. The

derivative was obtained with the aid of a Savitsiq-Golay second-degree five point /

smoothing routine.

Internai caiibration was required for the calibration (or ''trahing") step in PLS. In

this case DR1 chromatograms of the pure homopolymers (PS and PMMA) were used

to provide the mass of homopoiymer deposited on each disk. That information dong

with portions of the FTIR spectnun of each homopolymer film provided the needed

training data.

The portions of spectra selected for building the PLS training set are shown in Tabie

N. They were selected based on minimum overlap of the component absorbance

bands and correlation coefficient values greater than 0.90.

Table IV: PLS training set speçtral regions 1151

Spectral Range (cm-') 1 Cornpanent 1 Fmctionai Group

1 3101-3035 1 PS 1 ammatic C-H

I 1

1755-1705 1 PMMA 1 ester carbonyl

I

2981 -2962 1 PMMA methyl C-H

1612-1589 L

1277-1 122

PMMAlPS Blends

PS

713-687

Comprrhon of PLS and LR thrn R a d i e

A P M M A ~ ~ P ~ PLS + PMMA 25% PLS i

phenyl ring (stretch)

PMMA

0 PMMA75% PLS 1

D R 1

ester

PS

18 19 20 21 22 23 24

SEC Elution Tïma (min)

phenyl ring (bend)

- -

Figure 39: Cornparison of the composition prediction by DRI, LR, and PLS

techniques

Figure 39 shows a cornparison of PLS and LR (based on Figure 26) for the

measurement of composition variation with retentiou time for the three blends used.

Figure 40 shows the relative percent e m r fiom annealed samples.

Figure 40: PLS intemal calibration relative percent error in wt.% PMMA prediction

'. fiom annealed film spectra [15]

50 - ; 0 : -

O i 30 .' ......... -+ ........-.. -1.. ......... -<.. ......... .> ..........

ô m

t w 10 --....-...-..'--....-... s -

Although the accuracy is better in the time fiame of the PMMA maximum

concentration, significant detenninate variation is observed in the tails of the polymer

distribution. Significant overprediction of W.% PMMA is observed at both ends of

the PMMA distribution. The overprediction at short retention times is too large to fit

on the scale of Figure 40 and is not shown. It is speculated that this error is due to the

degraded signal-to-noise ratio in the second derivative spectra.

.- 5 -10 - d

-30 .

--..-.. ...... '... ........

- -. .......... ; ..........

-50 I 1 I 1 1 I 1

18 20 22 24 Elution Tirne [min]

A PLS dbration model was aiso coasmicted using the "as collected" nIm spectra

prior to solvent anneaiing and applied to the corresponding blend fiaction spectm As

shown in Figure 22' these spectra show signincant distortions in band shape and

relative band intensities due to nIm non-unûomities. The resuits of the polyrner

composition analysis are again expressed as relative percent emr in predicted wt.%

PMMA in Figure 41. Considering the si-cant spectral distortions, surprisingly

good accuracy is found for aii but the lowest percent PMMA blend sampks.

Increasing determinate variation is observed with decreasing amount of PMMA in the

overali blend. These r e d t s may overestimate the quality of the PLS qyantitation

results however, as discussed in the next section,

Elution Time [min]

Figure 41 : PLS intemal calibration relative percent error in wt-% PMMA prediction

fiom "as collected" film spectra [15]

4.5. Quantitative Analysis of the Composition of Copolymers

In the previous sections, polymer biends were used to deveIop the experïmental and

data interpretation methods, which were to be used as a basis for anaiysis of

copolymers. In order to do this, three replicates of a commercial poly(styrene-co-

methyl methacrylate) (SMM) were analyzed. The composition of the copolymer as

stated by the manufacturer was 70% styrene monomer and 30% methyl methacrylate

monomer.

The fÏrst step in this d y s i s was the evaiuafion of the UIlifomùty of monomer

distributions across the chromatogram for diffierent molecuiar weights (retention

times). These redts are demonstrated in Figure 42. Three different mathematical

approaches were tested: cornparison of the IR peak areas, second derivative vaiiey

areas, and second derivative valley heights. Al1 three methods predicted a uniform

distribution of monomers across the chromatogram for three replicates.

70B0 SMM COPOLYMER Peak Ratio Bas& on the FïiR 2nd D e r k t k Spectra

Ririee Replicates

Figure 42: Monomers distribution across the SEC Chromatogram for SMM

Co polymer

68

i 4 , ! 8 3.5 -

1

I 3 ,

2nd UV Area Ratm O O 2nd W M g h t Ratio I

, Abs. Area f?atb O O

However, there is an obvious dinerence among the techniques in the repmducibiiity

of the results. It is demonstrated in Figure 42 tbat there is a variation in height ratio of

t h e replicates. in contrast, using the IR peak area of either the original spectra or the

second denvative spectra instead of a height ratio gave a consistent and reliable

response. The analysis of variance (ANOVA) supporting these conclusions is

presented in Appendix 1.

In the second step of the analysis, the IR peak area, of two monomers (699 cm-' for

styrene monomer, and 1730 cm-' for methyl methacrylate monomer) was applied to

several caIibration curves to validate the monomer composition in three replicates.

Internal Calibration for SMM (70130) Copolymer Thme Repliates

1 i 699 Abs Peak Area y = 0.0197~ - 0.ôWO ? = 0.93 0

Figure 43: Internal Calibration for SMM copolymer based on F'IIR spectra

Five different calibration techniques were tested for the copolymer malysis. They

were as foIlows:

Caiibration 1 : Extemai Calibration for Homopolymers

The calibration curves, which already had been generated for PS and

PMMA homopolymers (Figure 26), were applied to the SMM

copolymer samples to predict monomer composition and total mas

injected,

Calibration 2: Internal Calibration for Homopolymers

The calibration curves generated based on the DR1 response of PS, and

PMMA homopolymers (Figmes 36, and 381, are applied to

characterize SMM copolymer.

Caiibration 3: Oniine Calibration for Homopolymers

The SEC \vas bypassed. A high volume (2ml) of homopolymer

solution was injected into the SEI chamber to generate the polymer

films. The solution flow rate was I d m i n . The polymer films were

deposited in 20-second intervals. Different concentrations (0.1, 0.2 and

0.3 mg/ml) of PS and PMMA solutions were separately injected. LR

was used to generate the caiibration c w e s (Figure 27) fiom the FTIR

spectra of the annealed samples.

.. Calibration 4: Internal Calibration for Copolymer

The copolymer intemal calibration curves fiom FTIR spectra are

demonstrated in Figures 43. SMM copolymer was tested as a

homopolymer regardless of existing calibration sets for PS or PMMA

homopo lpe r s .

Caiibration 5: Intemal Calibration for Copolymer based on second derivative spectra:

The copolymer internai calibration curves fiom FTiR second

denvative spectra are shown in Figures 44. To evaluate the adequacy

of deconvolution and baseline correction techniques, a new calibration

cuve was generated fiom the FTlR second derivative spectra and L R

The results of these caiibration techniques are shown in Tables V and VI.

Surprisingly, the three different caiibration techniques predicted a similar

composition for the copolymer. The predicted average composition was

approximattely 68% styrene, based on the homopoiymer calibration sets.

lnternal Calibmtion for (70/30) SMM Copolymer B a d on the 2nd Derivative

For Thme R a p T ï

Figure 44: Intemal Calibration based on second denvative of F l ï R spectra

The vendor's estimate of the styrene content of this commerciai copolymer is 70% a

value close to the results of this study. Consequently, h m the compositional

viewpoint the accuracy and precision of these methods are saîisfactory. There w&

less than 2% styrene standard deviation in precision and less than 4% styrene emor in

the accuracy of the composition prediction of the three methods.

Table V: Cornparison of the calibraiion techniques based on the homopolymers

Calibration Technique

External Calibration for Homopolymers

Monomer Total Mass

Predicted for Sample 1 (pg)

Totai Mass Predictedfor

Sample 2 (MI Totai Mass

Predicted for Sample 3 (w)

Average Predicted M-w

Theoreticai Mass Injected

M!

PS

293.4

371.1

346.2

336.9

350

Online Calibration for Homopolymers

Styrene % in Repiicate 1 Sîyrene % in Replicate 2

Sîyrene % in Replicate 3

Average Styrene ./.

Compositional MD%

PS

279.7

353.9

330. 1

321.2

350

PMMA

1 17.3

168

152.1

145.8

150

Internd Crilibration for Homopolynm

67.7

66.3

66.2

PMMA

133.7

180.2

168-3

160.7

150

PS

412.2

521.5

486.5

473 -4

350

67.9

PMMA

195. I

262.8

245.5

234.5

150

71 -4

69.9

1-9

66.7

1.2

66.5

66.5

67

1.2

68.8

69.5

Table VI: Comparison of the caiibration techniques based on the copolymer

Calibration Technique

Monorner

4.6. Quantitative Analysis of Total Mass

Interna1 Calïbration for

Total Mass Predicted for Sampte 1 (pg)

Total Mass Predicted for Sample 2 Org)

Total Mass Predicted for Sample 3 (pg) Average Predicted

M a s YI3 Theoreticai Mass

Injected I

An additional evaluation of the FTIR accuraçy is provided by observing the

integrated m a s accuracy across the SEC chromatogram relative to the expected DR1

valu= muation 3 8). \

Internai Calibration for S M M Copoiymer

SMM Copoïymer

PS 1 PMMA

4.6.1. PS and PMMA Blends

~ u c d ~ r i t a + 2- Dcriniivt Spccai

PS 1 PMMA

The previous data (Figures 37-39) was presented in temis of the calculated weight

395.3

5 19.3

484.8

466.5

500 I

397.9

504.1

470

457.3

500 1

percent of one blend component, PMMA as a h c t i o n of retention time in the SEC.

Signincant variance between quantitation methods for different compositions is

shown in the data plotted in Figure 45. Table VII summarizes both accurstcy and

1

371 -8

502.2

468 -7

447 -6

500 I

precision of the integrated rnass results for the polyrner blends.

I

383.7

504.8

469.4

452.6

500 I

50 Quantitation Method + PS Extemal

40 -- calibration + PMMA Extenial

Poiymer 30 -' caiibration

Mass % + PS PLS Annealeci Error 20 -. + PMMA PLS

Annealeci 10 -- * PS PLS Unanneaied

0 -- --- PMMA PLS Unannealeci

I I -1 O 1 I 1 1

(25%) (50%) (75%) % PMMA in Blend

Figure 45: Cornparison of integrated polymer mass results (Equation 38) fimm

different quantitation methods [15]

It s&ms that the SNR directly affects the integrated mass accuracy: there is a srnalier '. error percentage at higher PS compositions. The higher the composition, the stronger

the FTïR peaks and the higher the SNR. A h , there is much better accuracy for

PMMA than PS. From the data analysis aspect, this improved accurafy is a d t of

superior IR peak selection and badine fitting. PMMA has a saong IR band at 1730

cm-' with a flat baseline and clear window, but on the othrr hand the strongest PS

characteristic band is located at 699 cm-' overlapped with several smaîier pealrs

which make analysis difficult even for PLS. Overall, when annealed films were use&

the calibration methods predicted the integrated mass of samples with average 9%

PMMA error standard deviation precision and an accuracy averaging 4% PMMA.

As shown in Table VII, when "as collected" f i b were used the inaccuracy is much

larger.

Table W: Comparison of accuracy (Equation 38) and precision of integrated

polymer mass for both blend components ushg different quantitation methods [15]

4.6.2. SMM Copolyrner

Caiïbration Approach

Linear regression PLS

anneaieci PLS

as collected

The integrated mass prediction results for the SMM copolymer were not as good as

the composition prediction ones. With the exception of the homopoiymer oniine

calibration technique. the calibration methods predicted the total mass of samples

wit5 average 8.5% error standard deviation precision and less than average 15% \ relative standard deviation accuracy (Table Vm).

Comparison of results fiom the Calibration sets 4 and 5 demonstrate how well the

best baseiine was fit to the FTIR spectra using PeakFit software. There is about 3%

difference in the Relative Standard Error percenage between the second derivative

approach and the deconvolution technique. This suggests that the accuracy of peak

deconvoiution and baseline fitting methodology is good.

PS Accuracy

Yo 9-3

Up to 56% error was observed in the total mass prediction using the online calibraiion

technique. This error was moa probably due to sample dilution in the mobile phase

("chromatogram spreading") following injection.

PS Piccision %MD

2.6

PMMA Accutacy

Yo 2.1

18.1

24.4

PMMA Pi.cction %RSD

4.2

3 -3

13.0

2.9

3 -2

3 -6

3 -3

Table Vm: Cornparison of accuracy (Equation 38) and precision of integraïeci

polymer mass for SMM Copolymer using Merent quantitation rnethods

Calibration Approach #le External

Calibration & Hornopolymer

#2* Online Calibration & Homopolymer

#3. Internal Calibration & Homopolymer #4, Internal

Calibration & Copolymer #Se Internal

Calibration & Copolymer 2"* derivative Average*

The online calibra caicuiation of the average

Methacrylate Methacy-hte Accuracy% Precidon

%RSD

Styrene Accuracy

O h

8.5

Styrene Precision YoRSD

ion results (Calibration Approach #2) are not included in the 12.2 8.7 15

5 . CONCLUSIONS The present study has reached the foilowing conclusions about the applicability of the

SEC/FTIR equipped with SEI technique for quantitative analysis o f polymer blends

and copolymers.

Although a srnail volume flow celi offers continuous monitoring of polyma

solutions for FTIR detection [27, 281, its application in SEC is limitted due to low

polymer concentration and strong i-d absorbtion bands of the mobile phase.

The solvent evaporative interface (SEI) cunently offers the only practical method

for using FTIR in SEC. Such an interface ailows full use of the mid-idtard

spectral range by providing analyte film fke Erom solvent interfierence. Although

this detection approach has k e n used only for qualitative analysis [26,29,30, and

311, the results of this work have shown that it can be successfiilly used for the

quantitative analysis of polymer blends and copolymers, as weii.

Film thickness uniformity is the prime determinant of spectral quality. Rehctive

index variations due to film structure [25, 321 on the scale of the mid-hfiared

wave1engt.h range causes distortions, and sloping baseline [ I l , 12, and 331. The

soivent annealuig process effectively improves the quality of IR spectra and

eventuaily increases the mass accuracy.

Although it is recommended to avoid peak deconvolution for quantitative

evaluation [Il, the resdts of this study have shown that the selection of

adequate method and powerfûl software rnake it possible to use this technique for

quantitative analysis with an acceptable accuracy.

Linear regression (LR) based on the area under the infkared peaks (as the

dependent variable) is more reproducible than the height (absorbame) of the

peaks.

O The use of hear regression wîth extemal standard calibration provided superior

m a s accuracy but relative error in composition was sometimes hi& because of

difncuities in determinhg band areas.

Partial least squares with internai calibration and the use of annealed samples

provided the best overall precision and accuracy. When samples were not

anneaied, the relative error was low. However, this effect is expected to be

sample dependent because it actually uses scattering by the nIm to assist the

composition determination. While experimentai work was minimum, mass

accuracy was lest successfiil for quantitation using spectra without @or solvent

annealing of collected pol ymer films.

0 SEI ailows a hi&-precision quantitative detection of copolymer composition 6 t h

internal and extemal calibrations for the homopolymers. Superior mass accuracy

is obtained by applying internal calibration for the hornopolymers.

0 While previous studies have reported precision of SEI quantitative results to 5%

[14], the results obtained in present work have shown an error of 1.2 to 2% in the

composition prediction of copolymer.

6. RECOMMENDATIONS

0 Further development of PLS applied to "as-coliected" poiymer nIms should be

carried out to improve recovered mass values.

0 The effect of data preprocessing requires M e r study. Applying some mathematicai

hctions, Le. Multiplicative Scatter Correction (MSC), combined with PLS may be

usefùl to improve the integrated XMSS accuracy. This techaique has been foamd

practicai in near infked (NIR) spectroscopy of food products [34,35].

a Further deveiopment of the oniine calibration technique should be done. The method

resulted in good composition predictions but poor coLlected XMSS predictions.

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8. APPENDIX 1

ANOVA for IR peak area and height ratios in SMM Copolymer

Tables Al and A2 dernonstrates the resuits of the Analysis of Variances (ANOVA) with

Microsoft Excei97, for three SMM Copolymer repiicates. For two of the cases shown in

the Figure 42: peak area ratio across the chromatogram and peak height ratio across the

chromatogram.

Table Al : Single Factor ANOVA for Three SMM Copolymer repliCates Comparison of IR Peak Area Ratio (699 to 1732 cm")

F-cRI~ICAL

Statistically No Significant Difference among the Groups Gmups

Replicate 1 Replicate 2 Replicate 3

Mean Square

Source of Variation

Between Groups Wïîhin

Sum 2 1 -66227 22.1 9656 23.37863

Count 19 19 19

Groups Total

Average 1 Variance 1 -14012 0.01 5292 1.16824 0.004486 1.230454 0366767

Sum of Squares

F Mean Sauars Ratio

0.081204

1.557798 1

1.639002 . 56

Degme of Freedom

F criticrl Min. MSR to ôe

Table A2 Single Factor ANOVA for Three SMM Copolymer repiicates Comparison of IR Peak Height Ratio (699 to 1732 cm-')

F'h-m- Statistically Significant Dinerence among the Groups

1

2

54

Gmups Replicate 1

0.040602

0.028848

Soum of Variation

Count 1 Sum 19 32.9758

Mean Square

Average 1 Variance 1 -735568 O. 007334

Between Groups W a i n Groups

Sumof Squares

2.567657 1 0.191153 2.1 79143 0.028377

Replicate 2 1 19 Repticate 3 19

Degmeof Freedom

F Mem Squam Rsüo

WSR)

48.78548 41 -40373

6.587129

4.083558

F criticrl Min, MSR to be

SignilStuit

Total 1 10.67069 - 56

43.55331 I 3.168248 2

54

3.293565

0.075621

The results show that the use of peak area is more precise than peak height in quantitaîive

analysis. Inspection of Figure 42 shows that peak area fkom a 2"" derivative spectnim has

about the same precision as peak area of a conventional spectnm