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Colloids and Surfaces A: Physicochem. Eng. Aspects 348 (2009) 254–262

Contents lists available at ScienceDirect

Colloids and Surfaces A: Physicochemical andEngineering Aspects

journa l homepage: www.e lsev ier .com/ locate /co lsur fa

n analysis of the complexation between poly(aspartic acid) and polyethylene glycol)

.E. Nita, A.P. Chiriac ∗, I. Neamtu, M. Bercea, M. PintiliePetru Poni” Institute of Macromolecular Chemistry, Polymeric Materials, Grigore Ghica Voda Alley No. 41 A, 700487 Iasi, Romania

r t i c l e i n f o

rticle history:eceived 26 May 2009eceived in revised form 21 July 2009

a b s t r a c t

The compatibility between poly(aspartic acid) and poly(ethylene glycol) for the formation of an inter-polymer complex (IPC) was investigated by dynamic rheology and evaluation of zeta potential values. Thehomogeneity of the realized IPC was observed by near infrared chemical imagistic (NIR-CI) technique.

ccepted 21 July 2009vailable online 29 July 2009

eywords:oly(aspartic acid)oly(ethylene glycol)

The data were sustained and underlined by the assessment of the compatibility between the polymericcompounds.

© 2009 Elsevier B.V. All rights reserved.

nterpolymer complexear infrared chemical imagistic

. Introduction

The polymer complexation is one convenient route for theevelopment of new polymeric materials due to their commercialpplications and academic viewpoints. The complexation methods usually cheaper and less time-consuming for the creation of newolymeric materials with improved properties than the develop-ent of new monomers and/or new polymerization routes. An

dditional advantage is that the properties of the materials can beailored by combining the polymeric components and by changinghe composition of the mixture [1–5]. From the thermodynamicallyiewpoint, the polymer complexation is considered as a favorablevent promoted by a negative free energy of association [2,6,7].

Depending on the nature of the association, the major classesf the interpolymeric complexes (IPCs) are stereo-complexes typ-

cally formed through van der Waals forces between polymersith identical chemical structure and complementary stereoiso-erism, polyelectrolyte (poly-ionic) complexes prepared by mixing

he oppositely charged polyelectrolyte, hydrogen-bonded com-lexes stabilized through hydrogen bonds between a polyacidnd a polybase, and charge-transfer complexes obtained througholymers with electron-donor and electron-acceptor groups. The

nterpolymer complexes stabilized by hydrogen bonds are formedetween polymers containing electron-donating protons, typicallyoly(carboxylic acids), and polymers containing electron-donatingroups. The hydrogen-bonded complexes are generally formed in

∗ Corresponding author.E-mail address: achiriac1@yahoo.com (A.P. Chiriac).

927-7757/$ – see front matter © 2009 Elsevier B.V. All rights reserved.oi:10.1016/j.colsurfa.2009.07.040

the aqueous media. Their stability depends on many environmen-tal factors such as temperature, nature of the solvent, pH, or ionicstrength. Additionally, this type of interpolymer complexation pro-cess is reversible in the nature. It is well known that intermolecularinteractions in the hydrated and polymer complexes in which thereare hydrogen-bonding donor and acceptor groups, sometimes, gov-ern the structure, physical properties, molecular motion, and so on[8–10].

The near infrared chemical imagistic (NIR-CI) was used toprovide qualitative and quantitative analysis of localized andspace-averaged chemical compositions. NIR-CI technique makesthe fusion between near infrared spectroscopy and image analy-sis and it is already used in pharmaceutical applications to revealthe extent of the ingredient blending, particle size distribution, thepresence of polymorphs, and the trace of contaminants. Thus, themethod was used to visualize the spatial distribution of the chem-ical compounds in a sample provided by a chemical image. Thesample measurement implies the generation of the hyperspectraldata cubes containing thousands of spectra, which are after thatprocessed through NIR-CI analysis [11–13]. Jovanovic analyzed themixtures between lysozyme and trehalose using the contrast in thechemical images [14]. Gendrin used the method for the content pre-diction of the active pharmaceutical ingredient and two excipientsin the pharmaceutical solid dosage forms [15]. The use of the NIRspectroscopic techniques for powder blend uniformity analysis has

been reported by several authors using the off-line analysis of thesamples taken from different blender locations at various blend-ing times and on-line or in-line monitoring of the powder mixing[16–21]. Some recent papers concerned with quantitative analysis,pointed out this analysis is a prerequisite for complete resolution of

hysicochem. Eng. Aspects 348 (2009) 254–262 255

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Table 1Mw and [�] for the analyzed PEG samples.

PEG sample Mwa [�]b

PEG 2000 2,000 0.0935PEG 4000 4,000 0.1211PEG 10000 10,000 0.2348

L.E. Nita et al. / Colloids and Surfaces A: P

he chemical and physical properties of the mixture [22]. Koehlersed NIR imaging to visualize and quantify the spatial distributionf the active ingredient in a tablet [23]. Correlation of physical prop-rties and technological functionality of powder blends with theirhemical heterogeneity was the approach described by Hammondnd Clarke [24].

There are few studies concerning the evaluation of polymerlends using NIR-CI. Furukawa evidenced the potential of NIR-I for qualitative and quantitative non-destructive evaluation ofhe homogeneity of the polymeric blend based on poly((R)-3-ydroxybutyrate) and poly(l-lactic acid) [25].

Regarding the polymeric blends, it is important to know if theiromponents are compatible and if their mixture is homogeneous.he formation of a blend is governed by the appearance of the inter-olecular complexation which determines the homogeneity of the

lends.Poly(aspartic acid) (PAS) belonging to the family of synthetic

olypeptides, it is a biocompatible and biodegradable water-solubleolymer. Due in part to the carboxylic groups, the poly(asparticcid) has some similarity in chemical properties with poly(acryliccid) [26]. As biocompatible compound, with no toxic or mutagenicffect, poly(aspartic acid) can be used in medicine, cosmetics andood industry. It is also considered as a sustainable and environ-

entally friendly chemical product due to its biodegradability thatakes it particularly valuable from the viewpoint of the environ-ental acceptability and the waste disposal [27–30].

Poly(ethylene glycol) (PEG) is an interesting non-ionic polymerictructure because it is soluble in both water and several organicolvents, due to the presence of both hydrophobic and hydrophilicegments. Since this polymer is soluble in many different solvents,t is widely used in both industrial and biological applications [31].he mild action of PEG on the biological activity of the cell compo-ents explains the success of this polymer in the biotechnologicalpplications. PEG is also used as drug delivery matrix and as coatingo avoid the immune responses to the implants [32,33].

In our previous papers it was presented the preparation of an IPCealized by the interpolymer complexation via hydrogen bondingetween poly(aspartic acid) and poly(vinyl alcohol) [34–37]. The

PC was subsequently used for the bioactive substances entrap-ent, respectively it was doped with silver nanoparticles. Theiscibility and compatibility between the polymeric componentsas evidenced by dynamic rheology and zeta potential analyses. At

he same time, the influence of the polymer structure and the ratioetween the components brought additional data considering theydrogen-bonded complexation.

In this paper it is evaluated the homogeneity of an IPC basedn poly(aspartic acid) and poly(ethylene glycol) using NIR-CI tech-ique. Data is sustained by the assessment of the compatibilityetween the polymeric compounds through dynamic rheology andeta potential analyses.

. Materials and methods

.1. Materials

Poly(aspartic acid) was synthesized through a reaction inwo steps. First its precursor it was prepared, respectivelyoly(succinimide) (PSI), by thermal polycondensation in dodecaneFluka Chemika provenience) of l-aspartic acid (Fluka BioChemikarovenience), at 180 ◦C, 6 h, with o-phosphoric acid (analytical

eagent of 85%, Chemical Co. provenience) as catalyst. Second stepas constituted of in situ hydrolysis in alkaline medium of PSI asdodecane suspension, at 20–24 ◦C for 7 h. The prepared polymeras the molecular weight of about 15,110 and the polydispersity

ndex of 1.317.

PEG 35000 35,000 0.5134

a Fluka producer specification.b Intrinsic viscosity determined in aqueous solution of 1%, at 30 ◦C.

Poly(ethylene glycol) (PEG), Fluka Germany provenience, usedwithout further purification) with four molecular weights (Mw) inorder to cover several orders of weight extent respectively 2000 Da,4000 Da, 10,000 Da and 35,000 Da (denoted PEG 2000, PEG 4000,PEG 10000 and PEG 35000 in the present paper), it was studied. InTable 1 are registered the PEG samples with the producer specifica-tion on Mw and the correspondingly values for intrinsic viscosities[�] determined in aqueous solution at 30 ◦C.

2.2. IPC preparation

The complex PAS/PEG was prepared by direct mixing for 60 minof the stock aqueous solutions of 1% concentration, in the differentPAS/PEG ratios (vol.%) respectively 0/100, 20/80, 50/50, 80/20 and100/0. Thus, the total polymer concentration in the mixture wasmaintained constantly during each experiment.

The water was purified using an Ultra Clear TWF UV System.The polymer mixtures in solution were then poured into the Petridishes at the room conditions and the films were obtained bycasting.

2.3. Methods and equipments

2.3.1. Zeta potential estimationThe zeta potential measurements were performed in aque-

ous solutions (1 g/dL) with a ZETASIZER NANO ZS instrument byapplying laser light diffusion method (Malvern Instruments, UK).The instrument works with the technique of laser Doppler elec-trophoresis (4 mW He–Ne, 633 nm). Electrophoretic mobilities (�)of the particles were measured and converted to zeta potential (�)using the Smoluchowski equation:

� = ��

εand k˛ >> 1

where � is the viscosity, ε the dielectric constant of the medium, kand ˛ are Debye–Huckel parameter and the particle radius, respec-tively. The average of five measurements is presented as the meanvalue for the zeta potential. Also, the difference between the mea-surements and their average is less than 2.5%.

2.3.2. Dynamic rheological testingThe dilute aqueous solutions (1%) of the components and their

mixtures in the above specified ratios were tested with a Bohlin CVOrheometer equipped with a Peltier device for the temperature con-trol. The measurements were performed using the parallel-plategeometry. Both plates are from stainless steel, with a gap of 0.5 �m,the upper plate having the radius of 30 mm. For each determination,2 mL of the mentioned solutions are poured on the lower plate ofrheometer. The experiments for different compositions were real-ized at the temperature 22 ◦C for small amplitude rheological tests,

at a frequency (ω) of 0.1 rad/s and shear stress (�) of 1 Pa. Pre-vious frequency sweep tests established the correctitude of theexperiments within the linear viscoelastic range of the oscillatorydeformation. All measurements were done 60 min after the mixing,to allow IPC realization and thermal equilibrium to be reached.

256 L.E. Nita et al. / Colloids and Surfaces A: Physicochem. Eng. Aspects 348 (2009) 254–262

ely. PE

pt

2

Lisiwtcrebtqti

mscclcalc

3

pgou

Fig. 1. PAS/PEG IPC zeta potential (�) data as a function of PAS/PEG ratio, respectiv

The results obtained for different preparations for the same sam-le (with respect to the same experimental protocol) were found inhe limit of errors given by the method (<1%).

.3.3. Near infrared chemical imaging (NIR-CI)NIR-CI evaluation of the compounds was realized on a SPECIM’S

td. SisuCHEMA device as completely integrated Chemical Imag-ng Workstation that acquires the full hyperspectral data from theamples within seconds and employs SPECIM’s hyperspectral imag-ng technology in the NIR range (1000–2500 nm). The sample image

as taken with the spectral camera (NIR model based on an ImSpec-or N17E imaging spectrograph and a temperature stabilized InGaAsamera) which provides 320 and 640 pixel spatial resolution at aate of 60–350 Hz). The SisuCHEMA system uses Evince as the pow-rful chemometrics and image processing software package. Thus,y the exploring of the spectral and spatial information it is assuredhe images processing and the proposing of the classifying and theuantifying of the image content. Evince also, it is able to build spec-ral calibrations and prediction models for the specific chemicalmaging applications.

Multivariate approaches were developed to extract the infor-ation from the hyperspectral images. Thus, the second derivative

pectra were calculated from the original NIR-CI data before pro-eeding with further data analyses. Also, the contrast in thehemical images was compared using the intensity of a single wave-ength, the peak-height ratio of two wavelengths, the correlationoefficient with a reference spectrum and the principal componentnalysis (PCA). The correlation coefficient method and the partialeast squares discriminate analysis model (PLS-DA) were used foronsidering the homogeneity and quantitative investigations.

. Results and discussion

The preparation of the complex between a polyanionic com-ound – poly(aspartic acid) – and a polyether – poly(ethylenelycol) – which is essentially non-ionic, it is entirely justified inrder to have a multifunctional interpolymer structure with molec-lar architectures and properties optimized for further specific

G molecular weight: (A) PEG 2000; (B) PEG 4000; (C) PEG 10000; (D) PEG 35000.

applications. The complexes form between polymer containingelectron donating protons – poly(aspartic acid) – and the poly-mer containing electron-donating groups – poly(ethylene glycol).Thus, the interpolymer complex (IPC) formation is based on thepolymeric structures’ compatibility and the occurred intermolec-ular forces between the macromolecular chains especially to thehydrogen bonds formation.

3.1. Zeta potential evaluation

Fig. 1A–D illustrates the evolution of zeta potential (�) related tothe composition of the studied IPCs.

As it is well known zeta potential values, indicating the chargeof the surface, offer information on the stability of the system. Theindex of stability corresponds to zeta potential higher than +30 mVor less than −30 mV [38].

Fig. 1A–D evidences the evolution of the complexation processperformed by the addition of the successive amounts of polyetherto the polyacid aqueous solution when the concentration of thefree carboxylic groups decreases and also the zeta potential valuesdecrease. The dashed lines correspond to the individual compo-nents, in the ideal conditions and absence of the interactionsbetween them. Also, the zeta potential values are related on theratio between components – PAS/PEG – as well as on the PEG molec-ular weight.

It must be underlined the registered absolute values of zetapotential – higher than 30 mV – for all the IPCs prepared variants,which attest the stability of the complexes as well as the compati-bility between the two polymeric compounds. Also, zeta potentialvalues are – normally – directly dependent on the PAS content, thecomponent with the functional groups. Generally, the reduction ofthe PAS content induces the diminution of the zeta potential val-ues owing to the decrease of the functional groups as well as to the

formation of the hydrogen bonds.

In the ratio domain between the two polymers of aboutPAS:PEG = 50/50 and respectively PAS:PEG = 20/80 the zeta poten-tial values of the prepared IPC are maintained on a plateau. Thisbehavior was attributed to a relaxed structure of PAS, with the func-

L.E. Nita et al. / Colloids and Surfaces A: Physicochem. Eng. Aspects 348 (2009) 254–262 257

F ght: 2d

tttctae

uFb

3r

mcauctt

ig. 2. PAS/PEG IPC complex viscosity (�*) data as a function of PEG molecular weiependencies.

ional groups oriented on the surface in an adequate conformationo the formation of hydrogen bonds between the PAS carboxyl pro-ons and the PEG ether group. At the same time, the existence oflosely values of the molecular weights for both polymeric struc-ure – PAS and PEG, case depicted in Fig. 1C – it is considered as

matching characteristic to induce the optimum configurationalntropy for the IPC preparation.

Further, these considerations concerning zeta potential (�), val-es obtained by laser light diffusion method and depicted inig. 1A–D, they are corroborated with the data on the rheologicalehavior of the studied polymeric structures.

.2. Evaluation of polymer–polymer compatibility by dynamicheology

An easy and direct method to evaluate the interactions in theixed polymer solutions is the measurement of the mixture vis-

osity versus its composition. The procedure was advantageously

pplied in different studies [34–37,39–41]. The experimental val-es of the mixture viscosity have to be then compared with thealculated additive curve, which ignores the interactions betweenhe components. Any deviations of the experimental results fromhe additive curve indicate the presence of specific interactions

Fig. 3. The raw NIR spectra (A) and the second de

000 (A); 4000 (B); 10,000 (C); 35,000 (D). The dashed lines correspond to additive

between the components. Thus, the classical way of calculating anadditive curve is to measure the viscosities of the initial componentsand then, to calculate the mixture viscosity at different composi-tions. Also, the positive and negative deviations from the predictionof Raoult’s law on the composition dependence of a property ofbinary mixtures are explained in terms of structure formation uponthe mixing [42].

The complex viscosity (�*) of the IPCs realized between PAS andPEG of different molecular weights is presented in Fig. 2A–D. Themixtures are low-viscosity liquids for all the ratios between PASand PEG (regardless of the PEG molecular weight). �* shows slightpositive or negative deviation of the experimental values from theadditive dependence, reflecting the IPCs formation.

Thus, the figures with complex viscosity shape similar with theevolution of zeta potential, emphasize the difference between theexperimental viscosity data of the mixtures and the additive valuedata (the dashed lines) evidencing the compatibility as well as theassociation and former criterion between the two components in

aqueous solution.

Krigbaum and Wall [43] have developed the theoretical equa-tion for the ideal mixed polymer solutions; in our case, the mixtureviscosity between the two polymers is the average of their viscosi-ties, taken separately. In the examination of the mixed PAS and PEG

rivative spectra (B) of the neat PEG and PAS.

2 hysicochem. Eng. Aspects 348 (2009) 254–262

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iddstto

Iopd

3

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Table 3The predicted values of PEG and PAS content found in the prepared IPCs.

Molecular weight of PEG [Da] PAS/PEG [%] PAS% PEG%

2000 50/50 57 4380/20 88 12

4000 50/50 56 4480/20 91 9

10,000 50/50 65 35

58 L.E. Nita et al. / Colloids and Surfaces A: P

olutions there are evidenced deviations from the ideal behaviorhat reflect the chain mobility as well as the interactions that areoing to establish and range between slight and strong, as a functionf measured deviation.

The positive deviation (the IPC PAS/PEG(Mw = 10,000) case – Fig. 2C)s the indicative for the interpolymer complex structure, formeremonstrating the considerable enhancement of short range orderue to stronger cohesive interaction between the two-like con-tituent species to unite them. The negative deviation is attributedo the adhesive forces between polymeric chains during prepara-ion of an interpolymer association with a compact structure basedn attractive forces [44–47].

The compatibility between PAS and PEG in order to achieve anPC demonstrated by the zeta potential and the dynamic rheol-gy data are in the next stage completed and the homogeneity ofrepared IPC is evidenced and proved by NIR-CI analysis as non-estructive method.

.3. NIR spectra of the neat PEG and PAS

The raw NIR spectra and the second derivative spectra of theeat PEG and PAS in the 1100–2500 nm regions are illustrated inig. 3A and B, respectively. Hilton demonstrated the utility of theIR region to evidence the absorption bands of the hydroxyl groups

48]. Also, Le Fevre and Miller determined the molecular weightf poly(ethylene glycol)s using the OH bands near to 1400 and100 nm [49,50].

The first overtone bands of the CH stretching vibrations and theecond overtone of the C–O stretching vibration were registered inoth the PAS and PEG spectra. For both compounds PAS and PEG,he OH groups were identified as the first overtone absorption at428 nm. The second and the third overtones of the CH bands arehe prominent bands at 2308 and 1735 nm. The prominent bands at434 nm (for PEG) and 2480 nm most likely belong to the OH band.he above assignment leaves the peak at about 1800 nm as the CHtretch overtone [51].

The assignments of the NIR bands of PEG and PAS are listed inable 2. Although there are many common bands, the intensities ofome bands substantially differ from each other. The spectral dif-erences between PEG and PAS are more clearly seen in the second

erivative spectra, especially in the 2100–2500 nm regions. How-ver, the bands of PEG and PAS are somehow overlapped, evenn the second derivative spectra. Thus, it is difficult to performhe evaluation of the distribution and the prediction of the IPComponents by simply using the intensity at a fixed wavelength.

able 2he wavelength and the assignments of the NIR bands for PEG and PAS.

avelength/nm PEG PAS

227 CH2 second overtone CH2 second overtone733 – CH2 first overtone739 CH2 first overtone –800 CH stretch overtone –804 – CH stretch overtone941 OH band –063 OH band –280 – NH combination308 – CH2 stretching + CH

deformation combination370 CH2 stretching + CH

deformationcombination

392 – CH2 stretching + CHdeformation combination

435 CH2 stretching + CHdeformationcombination

–

482 OH band –

80/20 84 16

35,000 50/50 62 3680/20 97 3

Consequently, the multivariate analysis of the NIR-CI data it wasadopted.

3.4. Evaluation of homogeneity using statistical analysis byNIR-CI

The conventional, non-imaging NIR spectroscopy analyzes thesample in the bulk and determines an average composition acrossthe entire sample. The NIR imaging (NIR-CI), on the other hand, pro-vides information about the spatial distribution of the componentsinto the sample. The possibility to visualize the spatial distributionof the chemical species throughout the sample enables to deter-mine the degree of the chemical and/or physical heterogeneitywithin a given sample.

Thus, the obtained spectral data were decomposed into a setof small number of the classification scores by PLS-DA, where thescores of PLS-DA were obtained by correlating the information ofboth the spectral variable and the response variable (the blendingratio). Fig. 4A–D illustrates the score images derived from the PAScomponent class. In the score images, the pixels with the higherand lower score values are indicated by white and dark colors,respectively. The color in the most region of the score images isgray, the intermediate color between white and dark colors. Thepredominant gray score images indicate that the IPCs are relativelyhomogeneously. However, it is very difficult to evaluate the PAS/PEGquantitative ratio into the IPC based only on these score images.

Thus, the quantitative results were obtained from the PLS-DA analysis. Through the Evince software there were defined theclasses of the spectra to be used in a reference library, and therewere performed the PLS-DA calculations in both the classificationand the concentration modes. In the case of the classification mode,each library class was assumed to be the pure component spectrafrom one chemical component and it is automatically assigned aconcentration of 1.0. The resulting PLS-DA model produces a clas-sification “score” that (optimally) varies between 0 and 1. On the

other hand, the concentration mode requires the spectra with vari-ous concentrations of the blended components. No calibration datasets are needed for the prediction in the NIR-CI data analysis, ifthe NIR data of the neat components are available for the quanti-

Table 4STD % values of the histogram for the score images of the IPCs.

Molecular weight of PEG [Da] PAS/PEG [%] PAS PEG

2000 50/50 12.9 12.980/20 7.9 8.0

4000 50/50 10.6 10.580/20 12.8 12.9

10,000 50/50 9.1 9.180/20 5.5 5.5

35,000 50/50 13.6 13.980/20 12.4 13.2

L.E. Nita et al. / Colloids and Surfaces A: Physicochem. Eng. Aspects 348 (2009) 254–262 259

S-DA

tsopsw

gst

Fig. 4. The score images of PAS/PEG IPCs derived from PL

ative analysis in the classification mode [11–16,51]. In Table 3 areummarized the predicted values of the spatially averaged contentf the two polymeric compounds PAS and PEG found into the pre-ared IPCs (data derived from PLS-DA and based on the score imageshown in Fig. 4A–D). The predicted values are in good agreement

ith the actual polymer content.

The small errors of the prediction are explained by the homo-eneity of the IPCs indicated by the standard deviation (STD) valuesummarized in Table 4. The STD values of the score image his-ogram are the same as the standard errors of the prediction (SEP)

. Mw of PEG: 2000 (A); 4000 (B); 10,000 (C); 35,000 (D).

for the response variable in the result of the Evince software. Ahistogram for the distribution of intensities (score values) in thescore image, which includes some statistical information, is a pow-erful evaluation tool. Thus, a well-mixed blend sample shows anormal distribution. The standard deviation (STD) is one of the

useful parameters indicating the overall sample homogeneity orheterogeneity. The quantitative measure is established by calculat-ing the standard deviation of the distribution of the pixel intensitiesas it is represented by the histograms of the PLS score images. Themore heterogeneously the chemical distribution is, the larger the

260 L.E. Nita et al. / Colloids and Surfaces A: Physicochem. Eng. Aspects 348 (2009) 254–262

Fig. 5. Histograms derived from the score images for PAS/PEG IPCs. Mw of PEG: 2000 (A); 4000 (B); 10,000 (C); 35,000 (D).

Table 5The predicted values of the PEG and PAS components in the IPCs and STD % values of the histogram for the score images of the IPCs.

PAS/PEGa PAS/PEG [%] PAS% PEG% STD% PAS STD % PEG PAS% average PEG % average

Reproducibility 1 50/50 65.9 34.1 8.4 8.2R 8R 9

SanhPoFtiwgba

TS

RRR

eproducibility 2 50/50 64.9 35.1eproducibility 3 50/50 65.2 34.8

a Molecular weight of PEG 10,000 Da.

TD becomes. The STD is often more important in the analysis ofrelatively homogeneous sample, instead of an obvious heteroge-eous sample, as an indicator of subtle differences in the sampleeterogeneity. Fig. 5A–D are the histograms of the score images forEG and PAS as components in the prepared IPCs. The STD valuesf the histogram are summarized in Table 4. As it can be seen fromig. 5A–D and Table 3, the histograms evidence the expected dis-ribution between polymeric compounds excepting the IPC which

ncludes PEG with molecular weight 35,000 Da. The PEG sample

ith higher molecular weight determines the decrease of homo-eneity. At the same time, it must be evidenced the good correlationetween the score images of PAS/PEG ratio found for prepared IPCsnd its STD in the case of PEG with molecular weight of 10,000 Da.

able 6TD % values of the histogram for the score images of the IPCs.

MwPEG = 2000 MwPEG = 10,00

1/1* 8/2** 1/1*

STD%PAS

STD%PEG

STD%PAS

STD%PEG

STD%PAS

SP

eproducibility 1 11.7 11.7 7.4 7.4 8.4 8eproducibility 2 13.4 13.4 7.5 7.5 8.4 8eproducibility 3 12.9 12.9 7.9 8.0 9.06 9

* PAS/PEG = 50/50.** PAS/PEG = 80/20.

34.692 ± 0.51 65.308 ± 0.51.4 8.2.1 9.1

These data sustain the conclusions derived from zeta potential anal-ysis and dynamic rheology determination. Therefore, if the valuesof STD are not so large, NIR-CI analysis will give reasonably quanti-tative results with small standard errors of prediction.

The reproducibility of the statistical analysis by NIR-CI was eval-uated for the IPC with PEG 2000, PEG 10000 and PEG 35000, withthe ratio PAS/PEG of 1:1, respectively 8:2. Thus, the samples wereexamined in three locations (by three times data acquisition) and

the data were analyzed by the PLS-DA model by using the Evincesoftware. In Fig. 6A–F the superposition of those three histogramsof the scored images of PAS component in the IPCs, are illustrated.The STD values of the histogram are summarized in Tables 5 and 6.The predicted values of PAS and PEG 10000 (resulted with the best

0 MwPEG = 35,000

8/2** 1/1* 8/2**

TD%EG

STD%PAS

STD%PEG

STD%PAS

STD%PEG

STD%PAS

STD%PEG

.2 5.5 5.5 14.5 15.1 11.5 13.6

.2 5.5 5.4 14.2 14.5 12.4 13.3

.06 5.5 5.5 13.6 13.9 12.4 13.2

L.E. Nita et al. / Colloids and Surfaces A: Physicochem. Eng. Aspects 348 (2009) 254–262 261

F G = 1:1M = 35,0

doh

4

ttces––sp

a

ig. 6. Histograms derived from the score images: (A) MwPEG = 2000 Da, PAS:PEwPEG = 10,000 Da, PAS:PEG = 8:2; (E) MwPEG = 35,000 Da, PAS:PEG = 1:1; (F) MwPEG

ata from the homogeneity viewpoint) are given in Table 5. It isbviously the good reproducibility for the running and the goodomogeneity of the studied samples.

. Conclusions

The compatibility between PAS and PEG to form an IPC byhe dynamic rheology and the zeta potential analyses was inves-igated. These data give the information about the interpolymeromplex structure: the former demonstrating the considerablenhancement of the short range order due to the stronger cohe-ive interaction between the two-like constituent species to unitein the case of polymeric compounds with close molecular weights

or the preparation of an interpolymer association with compact

tructure based on attractive forces between poly(aspartic acid) andoly(ethylene glycol).

The homogeneity of the prepared IPCs based on poly(asparticcid) and poly(ethylene glycol) was investigated by near infrared

; (B) MwPEG = 2000 Da, PAS:PEG = 8:2; (C) MwPEG = 10,000 Da, PAS:PEG = 1:1; (D)00 Da, PAS:PEG = 8:2.

chemical imaging method (NIR-CI) combined with the multivari-ate data analysis. The IPC components spatial distribution by thescore images indicates the IPCs formation. The IPCs homogene-ity was revealed by both qualitative and quantitative analysis. Thehistograms intensities in the score images confirm the IPC homo-geneity. Also, the small STD values obtained from the histogramsindicate the greater homogeneity of the prepared IPC PAS/PEG10000, when PAS and PEG have near molecular weights, as aninherent characteristic for inducing the optimum configurationalentropy for the IPC preparation.

The study envisages biomedical application of the obtained IPCby bioactive substances entrapment or by doping with the silvernanoparticles.

Acknowledgements

This research was supported by a CNCSIS-Idea Project, No466: Researches in the Field of Polymeric Matrices Design for

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62 L.E. Nita et al. / Colloids and Surfaces A: P

ensitive Structures Romania, Ministry of Education Research,009–2011.

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