Recycling of PP packages is a very complex and difficult task, due to the very large number of [619788]

Introduction
Recycling of PP packages is a very complex and difficult task, due to the very large number of
variables affecting the recycled polymer properties.
The high differences between the properties of the initial polymer used in products obtaining,
related to the molecular masses and their distribution, the crystallinity degrees, the type of the
dominating crystalline form, the lamellae thickness, the spher ulites’ number and dimension, the
amorphous phase characteristics, the number of the tie molecules, the entanglements, as well as the
proportion of the recycled products mixed in the separated fraction, have a strong influence on the
recycled polymer feat ures.
Also, polymer processing by extrusion, blow moulding , thermoforming or injection moulding ,
in different temperature intervals and under different shear or compressive forces will determine
supplementary alteration of the polymer features: changing i n the crystallinity degree and crystallization
form (cylindritic crystals formation) and possible thermal degradation evidenced by carbonyl, carboxyl
groups and double bonds formation.
The o btainin g products have also to fulfil specific features required in function of the type of the
packaged good and in correlation with the different brands characteristics. This means that some
packages have to be transparent, other have to be coloured in different colours , other have to be
resistant to microwaves and tem perature, other have to be resistant to oily, aqueous or alcoholic
contacts, other have to be resistant to UV irradiation, other must to exhibit high impact or strength
resistance. To obtain the requested properties, additives addition (dyes, pigments, the rmal or antioxidant
stabilizers, nucleating agents), PP copolymerization or blending of PP with random (RPP) or block
(CPP) copolymers with ethylene or butylene in different proportion, are necessary.
Supplementary, the impact of the life cycle on the poly mer, meaning its possible degradation
under UV -VIS, microwaves irradiation, temperature and moisture, shelf period, as well as the impact of
the period between the waste drops and collection when the environmental factors among them being
biological ones ( fungal and microbial attacks) will determine changes in the polymer features.
Separation of the polypropylene fraction from the polymer waste stream, even in a narrow
density range, or well selected by NIR sensors, will include the results of all the above mentioned
factors that affected the polypropylene packages.
Further, the polymer reprocessing will contribute to an extra polymer features alteration by
modification of the mix composition (mixture of PP homopolymer with different types of copolymers,

mixtures of additives, mixtures of PP with different molecular masses and distribution), by a partial
oxidation of the polymer, by the possible crosslinking reaction between the functional groups resulted
from the degradation processes, by modification of the crystallinity degree and the crystallization types,
by possible phase separation and also by additives concentration changing (mainly their dilution or
possible reaction between them).
All these aspects will be reflected in the recycled polymer properti es.
A lot of efforts were devoted to study the influence of the initial polymer features on the product
characteristics, on the environmental factors affecting the properties of the recycled polymer and on the
methods of collection, selection and separatio n of the polymeric fraction on the recycled product quality
but no/or very low attention was paid to check the influence of the mixing of polymers (PP) processed
by different technologies on the final properties of the recycled product.
Processing by diffe rent technologies means in fact different initial properties of the polymer
(different molar mass: lower for injection molding moulding and higher for thermoforming and blow
moulding ), different additives and different thermal and mechanical regimes applied.
This study presents the results obtained by differential scanning calorimetry analysis (DSC) of
some samples obtained from the real waste stream collection (conventional sample s) as well as of
selected polymers from this stream based on the proces sing technology (Blow mould mix, Injection
mould mix, Thermoformation mix) and of different brands packages from each above mentioned
classified fractions. The conventional sample was analysed before and after labels and impurities
separation. Also the sam ple in pellets form or extruded in granules form were analysed . Based on the
thermal data, morphological features of the recycled polypropylene were determined and prediction of
the maximal Young modulus were was made.

Experimental
Material and sample preparation
Materials
Conventional sorted post -consumer PP was provided by SITA Suez Environment Company,
Rotterdam, The Netherlands in 2015. This fraction was separated from household plastic waste by using
NIR identification technique. After sorting by N IR, the material streams were inspected manually and
impurities and films were removed from the stream.

Based on the specific characteristics of the packages form s, the obtained conventional PP fraction was
classified in sub -fractions in function of the pr ocessing technology.
The average distribution of the different types of PP was determined to be: 58 % thermoformed and
blow molded PP; 42 % injection molded PP from which 52 % is white PP, 29 % is transparent PP and
19% have other colors.
In the separated sub -fractions there were identified packages with different composition (mixture
among PP and PP copolymers having ethylene groups, block or random distributed on the chain) that
were coded as it is specified in Figure 1.

Figure 1 Classification of Conventional post -consumer PP stream with the code fraction and composition of different types
of specific packaging. HP= homopolymer, CP=copolymer

After separation from post -consumer stream, the conventional PP fraction was cleaned by washing with
water and a small amount of liquid detergent (Persil for colored clothes, to avoid the presence of
peroxides), at 90 oC, for 50 min. , by using a household washing machine of type Indesit WIA 121,
using the standard washing program number 1 and stopping the washing process before centrifugation.
The polymer fraction was washed within a jute bag to prevent the ingress of small pieces of plastic to
the water exhaust system of washing machine.

After washing, the products were manually cut, having the possibility to separate the labels. Also,
aluminum residues were removed during this step.
Then, the fractions were shredded at 10 mm particles size, this one being optimal for the second
cleaning step. Washing process is more effective at the flake l evel by comparing to the product level.
An industrial mixer type Hobart A200 was used . 1 kg plastic flakes, 4 L water at 80 oC, 30 ml detergent
(Neutral, containing sodium lauryl sulfate) were used for washing process, at a rotation speed of 107
rpm for 10 min. After mixing, a supplementary portion of 10 L of water was added into the washing
machine, facilitating the separation process of PP and impurities still present into the fraction. The
impurities were separated by sieving with a 2 mm mesh size and th en the flakes were rinsed by wa ter at
80oC and dri ed overnight in the lab .
Aiming to eliminate the impurities , as much as possible, the polymeric flakes were then introduced into
a spinning machine (Hermion BV, Waalvijk, The Nederlands) that allows elimination of smaller
particles than 2 mm, by using a sieve of 2mm mesh and 3 000 rpm rotation speed. Then , the polymeric
fraction was dried in an oven at 60 oC for 22 h, including ventilation.
A second size reduction was performed by using the same shred der and a sieve with mesh size of 6 mm,
in order to easier homogenize the mixture of polymers.
Homogenizing step was carried out by using a co -rotating twin screw extruder (ZSK 18 MEGAlab from
Coperion) to obtain granules . These make easier injection molding. The temperature profile for
compounding process is presented in Table 1 .
Table 1 . The temperature profile for compounding process for Reference samples

The reference samples were obtained following the producers’ recipe , starting from the virgin polymers
as it is prese nted in Table 2 , by injection mold with , or without extrusion. The composition was similar
with packages obtained both by injection mold and respectively by thermoforming and the composition
of the mix of these fraction s is similar with the conventional post -consumer stream (Table 1) .

Table.2 . Reference sample codes, composition and processing
Sample code Sample characteristics
4A PP100% (HP)
6A 70%HP+30% RCP Blue
7A 70%HP+30% RCP White Extruded
8A 70%HP+30% RCP White Not Extruded
9A 50%HP+50% BCP Extruded

Methods of analysis
DSC method was used to determine the thermal features of the conventional PP fraction s and sub –
fractions and to compare them with those of the reference samples.
NETZSCH DSC 200 F3 Maia® instrument, with a heat flux system sensor , the measurement range
from 0 mW to ±600 mW, temperature accuracy <0.1 K, Enthalpy accuracy <1 % was used . The thermic
regime applied during samples analysis was as follows: (1) cooling from the room temperature t o (-20

oC) with a rate of 10 oC/min., (2) maintaining the sample at ( -20 oC), for 5 min. to equilibrate it (3)
heating up to 230 oC with a rate of 10 oC/min.; (4) maintaining the sample at (230 oC), for 5 min. to
equilibrate it ; (5) cooling the sample up t o (-20 oC) with the rate of 10 oC/min; (6) heating with the same
rate of heating up to the room temperature. The measurements were made in nitrogen atmosphere.

Results and Discussion
Start ing from the idea that mixing the polymers with different molar mass will strongly affect
the thermal characteristics of the sample that are directly correlated with the crystallinity degree and
crystal types that influence at their turn the mechanical and opti cal properties of the po lymer, the
followi ng data were collected from the DSC curves :
 the melting and recrystallization temperature (Tm and Tc),
 The melting and crystallization curves characteristics (onset, endset, width at 37% and height)
 the heat of melting and crystallization ( ΔH m, ΔH c )
By using these data, the following polymer and transition characteristics were calculated:
 the crystallinity degree of the initial recycled polymer (from the melting curve) (Xm) and that of
the re -crystallized polymer (from the crystallization curve) (Xc),
 Melting and crystallization rate (vm, vc)
 Lamellae thickness
 Number of the tie molecules
 Predicted maximum Young modulus calculated both from the melting and crystallization
curves.
From these data, the follo wing information can be drawn :
The m elting temperature indicate s the crystallites ’ type of the polymer. Industrial polypropylene is
generally i -PP. It was noted that stable α -PP melts at around 155-160 oC [Varga, J., in Polypropylene:
Structure, Blends and Composites , Vol. 1, pp. 56 -115, Karger -Kocsis, J. (ed.), Chapmann & Hall: London (1995). ,
Varga, J., Journal of Macromolecular Science -Physics B41, 1121 -1171 (2002)
Padden, F. J., Keith, H. D., Journal of Applied Physics 30, 1479 -1484 (1959) ]. The reaching of different equilibria
between α and α’ crystalline forms leads to the increase of the DSC curve width. The unstable β
crystalline form melts at around 120 -130 oC [ Natta, G., Corradini, P., Nuovo Cimento, Supplemento 15, 40-51
(1960) ,42-46
Meille, S. V., Ferro, D. R., Bruckner, S., Lovinger, A. J., Padden, F. J., Macromolecules 27, 2615 -2622 (1994)
Lotz, B., Wittmann, J. J., Lovinger, A. J., Polymer 37, 4979 -4992 (1996) ]. So, the dominating crystalline form
present in the sample can be identified by checking the melting temperature (peak temperature) .

Polymorphic modification affects both stiffness and strength of the polymer. The i mpact resistance of
the β form is higher than that of the α-PP. Determination of the melting temperature gives information
on PP polymorphism and this is helpful in mechanical properties prediction.
Analyzing the DSC melting and crystallization curves, it can be noted that as in the general case of the
polymers, the crystallization peak temperature of PP is always lower than that of its melting peak. This
is due both to thermod ynamic and kinetic reasons: (1) the possibility of the polymer crystallization only
below the melting te mperature when the free energy of the crystalline phase becomes smaller than that
of the amorphous material and (2) the large size and consequently the low mobility of the polymer
molecules, that kinetically hindered crystallization. Crystallites cannot form immediately below T m , but
at much lower temperature. [Wunderlich, B., Macromolecular Physics: Crystal Nucleation, Growth,
Annealing , Academic Press: London (1979 )].

110120130140150160170180
Inj.Virg. mix Inj. VirgTransition temperature (oC)
Type of sample Tm
Tc
Conv. Blow Inj. Th.

Figure 2 Melting and crystallization temperatures for recycled and virgin samples
obtained by different processing technologies.

From Figure 2 it could be noted that both recycled PP obtained by injection mold ing and recycled PP
obtained by thermoforming exhibit quite similar melting and respectively crystallization peak
temperatures. They are also close to the melting and crystallization temperatures of the conventional
recycled polymers. Blow molded polymers sho w the lowest melting temperature, with up to 26oC
lower, by comparing to the other samples. This could be due to the highest molecular weight of

polymers used in blow molding technology (MFI=3 ) by comparing both to that obtained by
thermoforming (MFI= 15) and to injection molding technologies (MFI=70) . Injection molded virgin
samples show the high est melting temperature for nucleated PP, but lower melting temperatures for
virgin polymers containing block heterophasic copolymer and white pigment, both of them acting as
nucleating agents. It could be stated that the presence of both copolymers and white pigment has the
dominating influence on the melting temperatures, by comparing to the influence of the molar mass.
The difference between T m and T c can give information concerning the nucleation agents’ presence.
So, it was stated that if ∆𝑇=𝑇𝑚−𝑇𝑐≈50 𝑜𝐶 the polymers are non -nucleated . β nucleated s amples
exhibit lower ΔT values as in case of blow molded samples, as well as, in that of the injected vi rgin PP
containing different percent of RCP and white pigment . The mix of the virgin PP -s exhibits a melting
temperature close to the conventional recycled polymers, probably due to the dilution of the nucleating
agents by mixing with un -nucleated PP.

 The Heat of melting can be correlated with the crystallinity degree of the recycled polymer. It
can be calculated by using the formula (1):
𝑋𝑚(%)=∆𝐻𝑚
∆𝐻𝑜∗100 (1)
Where : Xm is the crystallinity degree of the polymer; ∆𝐻𝑚 is the melting enthalpy determined by
integration of the surface under the DSC curve in the domain of melting process and ∆𝐻𝑜 is the melting
enthalpy of the 100% crystallized i-PP (207 kJ/g [Brandrup J., Immergut E.H., Grulke E.A., Abe A., Bloch D.R.:
„Polymer handbook”, 4rd ed., John Wiley & Sons, Canada 2005.
[16] Perrin -Sarazin F., Ton -That M.T., Bureau M.N., Denault J.: Polymer 2005 , 46, 1624, http://dx.doi.org/10.1016/j.polymer.
2005.09.076 ])
The crystallization heat was calculated by determination of the area under the DSC curve of
crystallization, in the crystallization temperature domain. The crystallinity degree of the re -crystallized
sample was calculated by using a similar formula with the eq.(1), where ∆𝐻𝑚 was replaced by ∆𝐻𝑐 that
is the crystallization enthalpy.

Figure 3 Correlation between the samples transition temperature
and their crystallinity degree for samples obtained by different technologies.

From Figure 3 it can be observed that the crystallinity degree of PP based materials can be identified
based both on the melting or crystallization peak temperature determination. Higher the crystallinity
degree, higher the transition temperature is. The slope of variation of the crystallinity as a function of
the transition temperature is higher for the crystallization transition and lower for the melting transition,
due to the higher polymorphism of the initial melted polymers.
100 110 120 130 140 150 160 170 180 190 2002025303540455055
Cryst. Th.
Cryst. Virg.
Melt. Conv.
Melt. Blow
Melt. Inj.
Melt. Th.
Melt. Virg.
Cryst. Conv.
Cryst. Blow
Cryst. Inj.Crystallinity (%)
Transition temperature (oC)

5101520253035404550Property
Type of sample width-m (oC)
width-c (oC)
Xm (%)
Xc (%)
Conv.R Blow R Inj. R Thermo R Inj. Virgine
Figure 4 Crystallinity degree and the width of the transition curve in melting
and crystallization process, as a function of the samples processing technology.

From Figure 4 it can be noted that the highest crystallini ty degree corresponds to the nucleated
injected virgin PP. The addition of the RCP, and of the white pigment, determined a dramatic decrease
of the materials’ crystallinity. But the lowest crystallinity degree belongs to the blow molded polymer,
due to the highest molecular weight of the polyme r and to the highest viscosity of the polymer’s melt
that hinders its crystallization. The crystallinity of the recycled fractions increases in the following
series:
X Blow mold < X Conventional polymers ≤ X Thermoformed polymers <X Injected mold polymers .

It can be noted that the crystallization degree of the conventional recycled polymers is closer to
that of the higher molecular mass fractions.
Crystallinity degree determined from the melting and crystallization curves exhibits the same
trend but a clearer selection of the polymers obtained by different processing technologies can be made
by using the crystallization curve. The last one seems to be better related with the structural ability of
the polymers to crystallize, due to the constant cooling regime applied during DSC analysis .

The samples obtained by waste collection are more heterogeneous from morphological point of view,
due to their different provenience . It is well known that sometimes, at industrial level, the product is
cooled rapidly i n order to increase productivity. The fact that crystallization occurs under no
equilibrium conditions wa s clearly demonstrated by the skin -core morphology of injection molded
polymers [ Karger -Kocsis, J., Csikai, I., Polymer Engineering and Science 27, 241-253(1987) ]. This
aspect was evidenced in our study too, in case of the injection molded polymers that exhibit a
supplementary melting (endothermic) peak at 121 -130oC, characterized by a low peak height and
attributed to β -PP crystals formation. Interes ting, the presence of the injection molded polymers in the
Conventional recycled mix can be identified by this secondary melting process evidenced at 120 -130oC.

Figure 5 DSC curves for melting of different fractions of recycled PP obtained by different processing
types

Characteristics of the melting or crystallization curve (onset, endset, width and height) can be correlated
with the multiple crystallization -melting eq uilibria, meaning the presence of different forms of
crystallites or crystals perfection processes.

The higher width of the DSC curves in the case of the high molecular mass polymers (blow molded
ones) and in the case of the virgin white nucleated injecti on molded polymers is more pronounced in the
melting curve. In the crystallization curve, the same trend is maintained but the differences are lower.
The crystallinity degree shows similar behavior of the conventional fraction with the thermoformed
polymer s, as in case of melting temperature. Also, the conventional sample exhibit s lower crystallinity
by comparing to that of the injection molded virgin mix, evidencing possible degradation of the
polymers during the life cycle. The formed OH, carbonyl or carb oxyl groups hinder the crystallization.

 Melting and crystallization rate were calculated by using formula (2):
𝑣𝑚 (𝐽∗𝑔−1∗𝑚𝑖𝑛−1)=∆𝐻𝑚
∆𝑡 (2)
Where ∆𝑡 is the duration of the melting process, calculated as ΔT/heating rate.
The obtained data were plotted as a function of the processing technologies and compared to the
DSC curve width, in Fig.6 .

020406080100120140Property
Type of samples Width-m (oC)
vm (J*g-1*min-1)
Width-c (oC)
vc (J*g-1*min-1)
Conv. Blow Inj. Th Inj. virg. Inj. virg. mix
Figure 6. Rate of crystallization calculated from melting (vm) and respectively from the
crystallization curve (vc), correlated with the DSC curve width and processing type of samples

From Figure 6 it can be noted that the rate of melting is correlated with the dispersity of the
crystallite types. Higher type numbers of crystallites, lower melting rate, due to the multiple
simultaneous equilibria. Crystallization rate show s the same trend as the melting rate, but the
differences between samples obtained by different technologies are better evidenced by the last
one.
The main goals of development in nowadays industry are both to increase the stiffness of PP above
current levels and to improve the impact resistance or even more, to prepare materials having
simultaneously large stiffn ess and fracture resistance. Large impact resistance is usually achieved by
copolymerization and blending but rarely by nucleation.
Lamella thickness is a very important parameter, directly correlated both with modulus, meaning the
polymer stiffness, and with i ts fracture (impact) resistance. While the polymer impact resistance
depends only on the lamella thickness [ Karger -Kocsis, J., Csikai, I., Polymer Engineering and Science
27, 241 -253(1987)
22. Wang, S. W., Yang, W., Xu, Y. J., Xie , B. H., Yang, M. B., Peng, X. F., PolymerTesting 27, 638 –
644 (2008)
23. Addink, E. J., Beintema, J., Polymer 2, 185 -193 (1961)

24. Phillips, P., J., Mezghani, K., in Polymeric Materials Encyclopedia , Vol. 9,pp. 6637 -6649 Salamon,
J. C. (ed.), CRC Press: B oca Raton. FL (1996) ], modulus depend s both on lamella thickness and
crystallinity.
Each lamella can be built up from several macromolecular chains and one chain can participate to the
formation of different lamellae. The number of the tie molecules (chain s connecting lamella) is
inversely proportional to lamella thickness [ Nitta, K. H., Takayanagi, M., Journal of Polymer Science
Part B -Polymer Physics 37, 357 -368 (1999)
56. Nitta, K. H., Takayanagi, M., Journal of Polymer Science Part B -Polymer Physics 38, 1037 -1044
(2000) ] and influence s the strength and fracture resistance of the polymer too.

Lamellae thickness can be calculated from the thermal DSC melting data, by using Gibbs Thom pson
equation (3):
1−2∗𝜎𝑒
∆𝐻𝑣𝑜∗𝑙=𝑇𝑚
𝑇𝑚𝑜 (3)
Where: Tm is the melting temperature; 𝑇𝑚𝑜 is the temperature at the melting equilibrium (418K); ∆𝐻𝑣𝑜 is
the equilibrium enthalpy of fusion per unit volume expressed in kJ/ cm3 (136.6 kJ/m3); l is the lamella
thickness (nm); 𝜎𝑒 is the free energy of the folded surface of lamella (0.122J/ m2) [Wunderlich, B.,
Macromolecular Physics: Crystal Nucleation, Growth, Annealing , Academic Press: London (1979)

Wunderlich, B., Thermal Analysis of Polymeric Materials , Springer: Berlin
(2005 )
Yoshitomo Furushima*†, Masaru Nakada†, Masataka Murakami†, Tsuneyuki Yamane†, Akihiko Toda‡,
and Christoph Schick§
Macromolecules , 2015 , 48 (24), pp 8831 –8837
].
The obtained values are presented in Table 3 .
Table 3. Lamella thickness and number of the tie molecules (proportional with 1/ l)
Sample Type of sample lmax
(nm) 1/l

code obtaining (µm-1)
10A Conv entional +imp urities 20.905 47.83
11A Conv ventional -impurities
granulat ed 20.408 49.00
12A Conv entional -Impurities Flakes 21.533 46.43
13A Blow mix 13.616 73.44
14A Persil 13.178 75.88
15A Injection molded Mix 20.905 47.83
16A Injection molded 50% HPP -50%
RPP 21.162 47.25
17A Injection molded 80%HPP -20%
RPP 23.221 43.06
18A Thermoforming Mix 21.696 46.09
19A Thermoforming 70%HPP -30% RPP
microwave 20.312 49.232
20A Thermoforming 70%HPP -30%RPP
aq 20.169 49.58
4A HPP 100% V irgin 22.911 43.64
6A 70%HPP -30 % R PP blue V irgin 20.312 49.23
7A 70%HPP -30% R PP white extr uded
Virgin 14.538 68.78
8A 70%HPP -30%RPP white not –
extruded Virgin 14.942 66.92
9A 50% HPP -50% R PP V irgine 22.551 44.34
5A Mix V irgin 50%(70 %HPP -30%
RPP)+50%(50 %HPP -50%RPP ) 20.604 48.53

It can be observed that the thinner lamellae were obtained in the case of polymers obtained by blow
molding technology and in the case of the reference samples contai ning R CP and white pigment. The
other samples have a lamellae thickness around 20 -23 nm. Correspondingly, the tie molecules number

is higher in case of the lowest thickness lamellae. This morphology can be correlated with the
mechanical properties of the polymer s.
The maximum modulus value can be predicted by using the melting DSC data, by applying eq. (4)
[Zsuzsanna Horváth, PhD Thesis: Correlation between molecular architecture and properties in
semicrystalline polypropylene, Published by Laboratory of Plastics and Rubber Technology,
Department of Physical Chemistry and Materials Science Budapest University of Technology and
Economics H -1111 Budapest, Mûegyetem rkp. 3. H ép. 1, 2014] and where the lamella thickness was
calculated by using equation (3) and was pr esented in table 3 .:
𝐸𝑚=0.082 ∗𝑙+0.025 ∗∆𝐻𝑚 𝑚𝑎𝑥 −2.15 (4)
Where: E m is the maximum stiffness achievable (determined from the melting data); l is lamella
thickness; ∆𝐻𝑚 𝑚𝑎𝑥 is the maximum enthalpy of fusion per volume unit. We used density of crystalline
part as 936kg/m3. [Clark, E. J., Hoffman, J. D., Macromolecules 17, 878 -885 (1984 )]
Maximal m odulus value can be calculated also from the crystallization data, by using the empirical
eq.(5) [ Pukánszky, B., Mudra, I., Staniek, P., Journal of Vinyl and Additive Technology
3, 53-57 (1997) ]:
𝐸𝑐=0.02∗𝑇𝑐+0.025 ∗∆𝐻𝑐−3.2 (5)
Where: E c is the maximum stiffness achievable (determined from the crystallization data); ∆𝐻𝑐 is the
crystallization heat.

20 25 30 35 40 45 50 55400800120016002000Ec Conv
Ec Blow
Ec Inj
Ec Th.
Ec Virg. Inj.
Em Conv.
Em Inj.
Em Th
Em Blow
Em Virg. InjE (MPa)
Crystallinity (%)
Figure 7. Maximal Young modulus predicted by using DSC data both for melting (E m) and
crystallization (E c) processes versus the samples crystallinity and processing technology
From F igure 7. it can be observed that the increase of the crystallinity degree determines the increase of
the Young modulus, meaning the increase of the polymer stiffness.
It could be noted also , that the values of modulus calculated from the melting DSC curves are higher
than that calculated by using crystallization DSC curves with up to 20%, but the same trend of variation
was obtained.
Also, considering the influence of the processing technology on the modulus values, the following
hierarchy was noted:
E Blow molding <E Conventional <E Thermoforming ≈ E Injection molding < E Virgin Injection molding
Not only the crystallinity degree influences the maximal values of the Young modulus but also the
crystallite types distribution described by the DSC curve width.

5 6 7 8 9 10300600900120015001800 Ec Conv.
Ec Blow
Ec Inj.
Ec Th.
Ec Virg Inj.Ec (MPa)
Wc (oC)
Figure 8 Maximal predicted Young modulus as a function of the crystallization curve width at 37%
From Figure 8 it can be seen that the higher dispersity of the crystallites is, the lower the Young
modulus values are. The highest d ispersity was noted for packages obtained by blow molding and the
lowest one, for that obtained by Injection molding. The Conventional waste exhibits values in between,
both for modulus values and for the crystallites dispersity, being closer to the thermo formed polymers.

Conclusion
DSC measurements are very useful tools to determine materials’ thermal and morphological
characteristics and based on them, to predict the mechanical and optical properties.
This study evidenced that the processing technology of the polymers in fresh state or as recycled
material, strongly influenced the product morphology and as consequence, the predicted mechanical
properties.
Blow molded recycled polymers are characterized by the lowest melting and crystallization
temperatur e, the lowest crystallinity, the highest polydispersity, the thinner lamellae, the highest number
of the tie molecules and by the lowest maximal predicted Young modulus.

By contrary, Injection molded virgin polymers are the highest crystalline, with the lowest
polydispersity, showing the highest melting and crystallization temperature, the highest lamellar
thickness, the lowest tie number molecules and the highest maximal predicted Young modulus.
Both injection molded recycled polymers and Thermoformed recycled polymers are in between, by
comparing to the blow molded recycled polymers and injection molded virgin polymers, from all the
above mentioned points of view.
Conventional recycled polymers , containing approximately 58% thermoformed and blow molded PP
and 42% injection molded PP , behaves very similar with the recycled thermoformed polymers both
from thermal and mechanical point s of view. By comparing the Conventional recycled polymers with
the Injection molded mix of virgin polymers, the first one exhi bited a lower crystallinity with about
22%, approximately the same lamella thickness, t he crystals polydispersity higher with about 10 % and
the Young modulus lower with about 22%.
The predicted properties will be correlated with the measured ones and the morphological determined
features will be used to explain the other properties of the recycled materials.