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