Introduction

In the past decades, the use of conventional materials such as metals has been involved in several daily life applications. However, nowadays we have looked for ways to incorporate polymers to replace conventional materials. The advantage of using polymers is their processability, low cost and productivity. However, one of its disadvantages are its mechanical properties; so it is necessary to incorporate a filler to improve them. This is because they need to have a high strength/high Young’s modulus depending on the application that is going to be given [1].

The current tendency is to replace petroleum-derived polymers with materials coming from renewable sources and friendly to the environment. Poly(lactic acid) (PLA) is a polyester made of block 2-hydroxypropionic acid. It is known to be a compostable and biodegradable thermoplastic that derives from renewable sources such as sugar where the PLA is obtained [2]. The use of PLA has been relevant due to its applications in food packaging and is widely used in the biomedical field. Recently it has had an important participation due to its potential to replace oil derivatives [3]. The PLA has low mechanical properties and to improve PLA properties, fiber glass has been used as filler to increase its stiffness to double and 3 times its impact resistance using 20% fiberglass [4]. In addition, it has been tested with natural cellulose fibers to enhance mechanical performance by 42% when 20% fibrous material is used. This result showed that applications of PLA can be issued to manufacture materials that resist high temperatures [5]. Carbonaceous material blends with fibers have been involved in the modification of PLA nanocomposites, highlighting the betterment of poly(lactic acid) compatibility with the filler and resulting in an increase in mechanical and thermal properties [6]. Studies on improving the thermal stability and crystallinity of PLA have also been conducted using reactive copolymers such as synthesized PSMG and PSG. In case of the PLA molecular weight spotlight, it increases significantly with the addition of these copolymers and the PLA crystallization behavior is strongly influenced by the copolymer chains [7]. Ternary PLA blends nanocomposites have been studied to set forth new types of nanomaterials with good mechanical, thermal and bactericidal properties.

Metal oxides have been used as fillers to modify poly(lactic acid) nanocomposites and to increase their range of applications. Mainly, applications that have had these modifications are approached on the food packaging area. This is because in modern life its protection is essential and guarantees the quality of the product during transport to distant places [8]. Recently, zinc oxide nanoparticles (ZnO NPs) have been included to enhance some important properties in food packaging, such as UV light barrier, water vapor barrier and antibacterial properties. The ZnO NPs incorporation improved the water vapor barrier and mechanical properties but its thermostability decreased [9]. Mechanical and thermal properties are important in engineering applications. However, plenty of the problem of nanoparticles incorporation into polymeric matrices is their dispersion. Therefore, SiO2 systems have been carried out with superficial modifications to study the dispersion effect on PLA properties. It has been observed that the nanoparticles dispersion shows improvements in the crystallization rate and PLA crystallinity due to surface energy and interfacial energy between nanoparticles and the lateral crystals surface [10]. A coupling agent which has been involved in modifying the dispersion of SiO2 nanoparticles is 3-aminopropyltriethoxysilane (3-APTES). Although the 3-APTES use is complex due to its multilayer deposition and the irregular morphology that it generates, it is extensively used to modify the metal oxide nanoparticles surface charge and improve its stability in solvents and polar matrices [11,12,13]. A recently study demonstrated that the chemical modification of metal oxides (as TiO2) with aminosilanes has a direct effect on the non-isothermal crystallization of the PLA; mainly in the rate at with which PLA chains are accommodated in the first steps [14]. Besides, modifying the surface charge using 3-APTES has been important for carbon dioxide adsorption on mesoporous silica, which can be extended to the gas selective films manufacture [15]. A similar aminosilane to 3-APTES used for surface modification is 3-aminopropyltrimethoxysilane (3-APTMS) which is employed by its adhesion promotion. The 3-APTMS molecule has three methoxy groups and is able to polymerize in the presence of water [16]. A study showed that the reactivity with the silicon oxide layer and the polymerization process of aminosilanes depend on the number of possible bonding sites and the 3-APTMS reacted the most intensively with the silicon dioxide compared with others aminosilanes [17]. Also, the modification of the silicon dioxide surface by 3-APTMS strongly depends on the type solvent used. Results of a study showed that ethanol forms thin 3-APTMS coatings on silicon dioxide surfaces [16].

The understanding of PLA crystallization behavior is crucial for the control of its degradation rate, thermostability, mechanical, barrier properties and crystal nucleation kinetics [18, 19]. Studies on PLA non-isothermal crystallization include nanoclays and linear low-density polyethylene (LLDPE) where the results indicate that the nanoclays presence improves the PLA crystallization in heating, as well as the plasticizer (LLDPE) presence improves the PLA chains mobility [20], this phenomenon of facilitating the PLA chains mobility due to another polymer embedded has also been observed previously in PET/PLA blends [21]. There are different strategies to promote crystallinity in order to increase the PLA crystalline content. That is, through the heterogeneous nucleation effect, the PLA chains mobility increases. There are studies where it has been tested by adding above 10% acetyl triethyl citrate in PLA matrices obtaining good results [22]. However, particle size of filler has a share in the crystallization process; micro-sizes improve the crystallization rate and PLA growth rate while a large nanometric particles number retard the crystal initial growth, probably due to PLA molecules reduced its mobility [23]. Other PLA non-isothermal studies with various additives indicated that polysaccharides can be used as cheap fillers without changing the PLA crystallization [24]. An effect bit studied on transport and PLA relaxation properties is the nanoparticles morphology that are incorporated into the matrix. When spherical and rod-shape zinc oxide morphologies are used as fillers in PLA matrices, high agglomerate formation occurs when the spherical shape is used. While rod-shaped morphology maintains a better dispersion that also improves PLA optical properties [25].

Among variables that mainly affect mechanical and thermal properties are the nanostructure morphology, agglomerates formation in the polymer matrix and the coupling agent amount on the metal oxide surface. Even when the same particle size is used, the results reported by each research group present contrasts. This research seeks to demonstrate that not only the particle size but also the surface area has an important role in the mode that the polymer chains interact with the nanoparticles. Two silicon dioxides (SiO2) with different surface area and similar particle size were used with 3-APTMS organic coating to modify the metal oxide surface and avoid aggregates formation in a PLA matrix. Modifications were made in the coupling agent amount on the surface to observe the coating effect on the PLA/SiO2 nanocomposite behavior and improve PLA mechanical properties without influence its thermal properties.

Materials and methods

Materials

To prepare PLA/SiO2 nanocomposites, commercial PLA (3D Market, 3 mm) and silicon dioxide nanoparticles supplied by US Research Nanomaterials Inc were used. In this work, two surface areas were employed. It was used SiO2 (99.5%, 15–20 nm, S- type, spherical, 170–200 m2/g) labeled as S-SiO2 and SiO2 (99%, 20–30 nm, 180–600 m2/g) labeled as P-SiO2. Additionally, distilled water, (3-aminopropyl) trimethoxysilane, chloroform provided by J. T Baker and Petri dishes were employed.

Chemical modification of SiO2 nanoparticles

SiO2 nanoparticles were modified superficially by a silanization process. The coupling agent was added in different proportions, SiO2:APTMS, (10:4, 10:2, 10:1) for 2 nanoparticles types. The proportions and specific surface area measured by N2-BET method are shown in Table 1. For the incorporation of SiO2 nanoparticles in the ethanol for all experiments, 30 min of agitation in magnetic stirring were used, with 30 min of sonication at 60 Hz in an ultrasonic bath, until a total of 2.5 h were completed. Subsequently, the (3- Aminopropyl) trimethoxysilane was added, and at 10-min intervals, 1 ml of water was added to promote hydrolysis in the reaction, stirring at 400 rpm for 6 h. The suspension was washed by centrifugation twice with water and five time with methanol at 300 rpm for 10 min per wash, in order to remove the unreacted agents. The drying was carried out in an oven at 80 ºC. The dry powders were stored in vials for further testing.

Table 1 Coupling agent ratio used on silicon dioxide surface
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Z potential and size particle

The particle size distribution as well as obtaining the Z potential of different modified SiO2 samples was performed on a Delsa Nano C Particle Analyzer (Beckman Coulter). For particle size samples, modified SiO2 samples were suspended in water. While for Z potential test, the pH was varied from 3 to 11, in order to monitor the modified SiO2 nanoparticles behavior.

Nuclear magnetic resonance of modified SiO2 nanoparticles

29Si NMR and 13C NMR spectra were obtained in a Bruker Ascend (400 MHz) instrument operating at 400 (29Si) and 100 (13C) MHz. For 13C analysis, parameters were a scan number (NS) of 16 and a pulse length of 8.5 microseconds.

Scanning electron microscopy and surface area analysis

An EVO HD LS Zeiss electron microscope was used to obtain SiO2 nanoparticle micrographs. In addition, an EDS X-MaxN X-ray detector was used to obtain the X-ray scattering data. To correctly measure the SiO2 samples, the SiO2 nanoparticles were previously coated with a gold plating, because the nanoparticles contain an organic coupling agent on the surface. The surface area of the modified SiO2 samples was determined by the N2-BET method using a surface area and porosimetry analyzer, Micromeritics, ASAP 2010.

Preparation of PLA/SiO2 nanocomposites

A ratio of 1% modified SiO2 nanoparticles in PLA was used for the production of films. First, a quantity of poly(lactic acid) was dissolved in sufficient chloroform, modified SiO2 nanoparticles were added, and the system was stirred and sonicated constantly to assure mixture. Subsequently, suspensions were placed in Petri dishes and kept in a controlled environment at room temperature to keep the evaporation of the solvent as homogeneous as possible.

Non-isothermal crystallization of PLA/SiO2 nanocomposites

Non-isothermal crystallization was carried out on a TA instruments model Q2000 differential scanning calorimeter (DSC) in a dry nitrogen atmosphere. About 5 mg of the samples were melted at 200 ºC and held for 10 min to erase the thermal and mechanic memory and were then cooled at constant rates of 2.5, 5, 10 and 20 ºC/min. The exothermal curves of heat flow as function of temperature were also recorded to analyze the crystallization process.

Non-isothermal crystallization kinetics

In accordance with Avrami equation, this considers a constant crystallization rate temperature, then we have following Equation

$$ X_{t} = 1 - e^{{Z_{t} t^{n} }} $$
(1)

where Xt represents the degree of relative crystallization, the exponent n refers to a constant mechanism and its value is subject to a type of nucleation and growth process parameters. Zt represents composite rate constant, which involves nucleation and growth parameters, and the crystallization time is represented by t. Assuming differential crystallization changes, the relative crystallization is represented by Eq. 2

$$ X_{t} = \frac{{\mathop \smallint \nolimits_{{t_{0} }}^{t} \left( {dH_{c} /dt} \right)dt}}{{\mathop \smallint \nolimits_{{t_{0} }}^{{t_{\infty } }} \left( {dH_{c} /dt} \right)dt}}*100 $$
(2)

The time at the onset and end of the crystallization process is represented by t0 and t∞, respectively. Differential enthalpy changes are symbolized by dHc and these are integrated in a time range. With the crystallinity and time data, Zt and n parameters were calculated using a fit in Eq. 3. The fit was obtained changing to a double logarithmic form:

$$ \log \left( { - \ln \left( {1 - X_{t} } \right)} \right) = \log \left( {Z_{t} } \right) + n \log \left( t \right) $$
(3)

Assuming a non-isothermal character of analyzed process, the Zt parameter from Jeziorny’s model shows a dependence with the cooling rate, ϕ. This suggests the non-isothermal crystallization can be represented by equation:

$$ \ln \left( {Z_{c} } \right) = \ln \left( {Z_{t} } \right)/\varphi $$
(4)

As a result to consider the non-isothermal process as small isothermal steps, this fact is modeled by the Ozawa Equation:

$$ 1 - X_{t} = e^{{ - K\left( T \right)/\varphi^{m} }} $$
(5)

The cooling function is represented by the term K(T), the Ozawa exponent is symbolized by m, the crystal growth depends on this exponent. Unfortunately, Avrami and Ozawa equations are inconvenient to analyze the non-isothermal crystallization process of polymeric systems. For a certain values of crystallinity degree, both the Avrami and Ozawa equation (Eq. 1 and Eq. 5, respectively) can be combined to produce another non-isothermal analysis. The combined model is known as model of Mo, and it is represented by the follow equation:

$$ \ln \left( \varphi \right) = \ln \left( {F\left( T \right)} \right) - a\ln \left( T \right) $$
(6)

and

$$ F\left( T \right) = \left[ {K\left( T \right)/Z_{t} } \right]^{1/m} $$
(7)

The cooling rate to reach a crystallinity degree at unit crystallization time is represented by F(T). The “a” parameter corresponds to coefficient of Avrami’s and Ozawa’s exponent, i.e., a = m/n.

The crystallization phenomenon is evaluated through the change in the activation energy, the mathematical method of Kissinger [26, 27] has been widely used in this process. This method correlates changes of the crystallization peak temperature as a function of the cooling rate obtained by a fitted value of ∆E. However, the method has evidenced that the Kissinger equation is mathematically inapplicable to quantify activation energy of processes that occur upon cooling [28]. Friedman and Vyazovkin [28, 29] proposed an isoconversional method to determinate the correct behavior of ∆ E. In this research work, the Friedman method [30] was used to calculate the effective activation energy. Besides, it was studied as a function of the degree of crystallinity and its temporal evolution, this behavior is showed to the following equation:

$$ \ln (dX/dt)_{X,i} = A - \frac{{\Delta E_{X} }}{{RT_{X,i} }} $$
(8)

Dynamic mechanical analysis (DMA) of PLA/SiO2 nanocomposites

Viscoelastic properties were measured using a dynamic mechanical analyzer (DMA-8000 Perkin-Elmer) in tension mode with displacement amplitude of 0.1 mm under constant strain. Specimens used were rectangular sheets measuring 2.5 mm in width, 0.5 mm in thickness and 22 mm in length. The temperature dependence of the storage modulus, loss modulus and Tan δ (phase angle δ is the difference between the dynamic tension and dynamic deformation of a viscoelastic material subjected to a sinusoidal oscillation and allows for the observation of transitions, such as Tg, in which the value of Tan δ against the temperature is 0, i.e., where one can observe a maximum on the graph) was measured at 10 across a temperature range from 30 to 100 ºC at a heating rate of 3 ºC/min. To avoid discrepancies in estimation of Tg, the equipment software provided by Perkin-Elmer was used to calculate the transition. The purpose of this analysis was to obtain information regarding with the influence of the organic coating on the integration of particles into polymeric matrix.

Mechanical properties of films

The mechanical test consisted of tension test for the determination of the stress at break and the elasticity modulus. To determinate the tensile strength of films, the test were performed according to the ASTM standard method, D-8822-09 (ASTM, 2009) on a TAXT texture machine Plus (Stable Micro System Ltd., UK). Young’s modulus and the tensile stress of PLA/SiO2 nanocomposites were performed in a universal machine (Instron 3369). A 50 kN load was used maintaining a rate of 25 mm/min.

Results

Z potential and size particle

To corroborate the chemical modification made on silicon dioxide nanoparticles, Z potential tests in the pH range of 3 to 11 were performed. Changes in the Z potential are due to the nanoparticle surface charge. Highly negative or positive Z potential values suggest good colloidal stability in aqueous solutions [31]. That is, a higher surface charge implies a high repulsion between nanoparticles; so in polar matrices good behavior is expected. As seen in Fig. 1, the nanoparticles chemical modification was effective due to the change in the Z potential of samples. In Fig. 1a, it can be seen that at pH 7 values, charges are balanced in three samples. In addition, it is observed that the isoelectric point displacement is influenced by the coupling agent amount on the surface. Figure 1b shows similar behavior in three samples, this due to the surface area is large and crosslink sites are not affected by the coupling agent amount used, which is produced to a similar isoelectric point shift in porous nanoparticle specimens. In both silicon dioxide types, the presence of amino groups on the surface implies a high dispersion in the polymer matrix of PLA. Surface modifications of metal oxides to improve their stability in biopolymer films have already been reported a better results, mainly in mechanical properties when low percentages of silanized particles are used [32].

Fig. 1
figure 1

Z potential of different modified and unmodified silicon dioxide nanoparticles

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Table 2 shows particle sizes for two silicon dioxide species. On the one hand, it is observed that the size of the agglomerate in spherical nanoparticles decreases due to the coupling agent amount on the surface that promotes their dispersion. An increase in the size of agglomerates is observed in porous nanoparticles (P-SiO2 series) because the amino group amount on the surface is independent of the coupling agent ratio.

Table 2 Size of different modified and unmodified silicon dioxide nanoparticles
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Nuclear magnetic resonance of modified SiO2 nanoparticles

The nuclear magnetic resonance (NMR) spectrum characterization for 13C and 29Si is shown in Fig. 2. Signals at 43, 23 and 9 ppm attributed to 3 carbons from the propyl group from the coupling agent are shown in Fig. 2a, b. These three carbon signals are represented and schematized as 1, 2 and 3 in Fig. 2e. The 4 signals of 29Si are found in Fig. 2c, d, the first signal located at −59 ppm corresponds to silicon T2, while the second signal found at−69 ppm belongs to silicon T3. The third signal located at -103 ppm corresponds to a silicon Q3 and the fourth signal located at −112 ppm belongs to a signal Q4. The signals corresponding to silicon are schematized in Fig. 2e. In Fig. 2c, an inversion is observed in the signals Q3 and Q4, this means that the attaching of the coupling group is being carried out on the nanoparticle surface. The above indicates that the silane functional group replacement is performed in the –OH groups that are exposed in the silicon dioxide nanoparticle. In Fig. 2d, there is no change in signals Q3 and Q4 depending on the coupling material amount. However, the presence of the 3 carbons corresponding to the propyl group in Fig. 2b implies that the silane group is present in the nanoparticle, so the silanization reaction is taking place inside the silicon dioxide. The above is corroborated by the study of Z potential of porous nanoparticles (P-SiO2 series) where it is observed that the nanoparticle surface charge distribution is independent of the coupling agent amount used.

Fig. 2
figure 2

Nuclear magnetic resonance of different modified and unmodified silicon dioxide nanoparticles employed in this study

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Analysis of SiO2 nanoparticles by scanning electron microscopy

After carrying out the organic coating on the surface of the different silicon dioxide particles, SEM micrographs of the modified nanoparticles were obtained. Figure 3 shows the morphology of the organic coatings as well as the bulk particle size histograms. The micrographs show a similar size among them, this is in agreement with the similarity of the sizes reported by the manufacturer. Histograms show that the organic coating causes the particle size to maintain invariant. However, the coupling agent could induce the folds formation on the nanoparticle surface, which are manifested as an increase in the available surface area. ImageJ software was used to estimate the size distributions in the micrographs

Fig. 3
figure 3

SEM micrographs and size histograms for modified SiO2 nanoparticles

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Non-isothermal crystallization analysis of PLA/SiO2 nanocomposites

The non-isothermal behavior of the PLA and its SiO2 nanocomposites were studied under different cooling rates (2.5, 5, 10 and 20 ºC/min). The temperature-dependent crystallization thermograms are shown in Fig. 4. Crystallization thermograms begin to widen and tend to move at higher temperatures as the cooling rate increases. The crystallization phenomenon is a process in which polymer chains tend to form ordered domains, known as crystalline domains. These domains are formed due to the polymer chains have to enter a crystalline network with an increase in the energy of the medium. It is observed in Fig. 3 that having low cooling rates (φ), nucleation centers will be formed in relatively long times. That is, there is not enough time to have stable nucleation centers at high temperatures in all specimens. It is appreciated that the thermal behavior is similar in all samples having small variations in the crystallization temperature, these data are displayed in Tables 3 and 4.

Fig. 4
figure 4

Non-isothermal crystallization thermograms for composites of neat PLA and its nanocomposites under different crystallization cooling rates

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Table 3 Effect of cooling rate under the non-isothermal process for tested composites (part 1)
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Table 4 Effect of cooling rate under the non-isothermal process for tested composites (part 2)
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The crystallization kinetics was achieved by integrating the thermograms of the nanocomposites. The temperature behavior appears to correlate with time owing to the functionality between the temperature of nanocomposites and the period necessary to reach the crystalline state. The stages of crystallinity in nanocomposites made up of silanized particles of varied coupling agent ratio and different surface area are shown in Fig. 5.

Fig. 5
figure 5

Relative crystallinity behavior of PLA and its nanocomposites as function of crystallization time

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The obtained crystallization period (tc) for different crystallinity stages as well as the apparent crystallization period (∆tc) are grouped in Tables 3 and 4. The parameter ∆tc can be deduced by the discrepancy between the apparent beginning and the end while the crystallization temporal evolution occurs.

A dainty change in the non-isothermal crystallization process of the polymer was observed when it was reinforced with the nanoparticles. In addition, the required time during the crystallization process was shortened when a cooling rate of 5 ºC min−1 was maintained. While, at high cooling rates, the crystallization time evolution remained unchanged. It should be noted that the unmodified and modified SiO2 nanoparticles act as nucleation centers, since they promote the process and increase the crystal formation rate. However, also the crystalline part of the polymer begins to be arranged and to constitute its own nucleation centers when this type of materials are subjected to a controlled temperature drop. The absence of sufficient time in all the nanocomposites was considered to appreciate the crystallization phenomenon because it occurs suddenly at high cooling rates without presenting an alteration in the maximum crystallization temperature (Tp).

Non-isothermal crystallization kinetics

The unfavorable use of the Avrami and Ozawa equations has been previously seen to study the phenomenon of non-isothermal crystallization in polymeric systems. We have opted to plot the data of Eq. 3 of the Avrami model and carry out the Jeziorny fit (Eq. 4), in order to kinetically parameterize the non-isothermal crystallization process of the PLA and its nanocomposites. Table 5 summarizes the kinetic parameterization by estimating n, Zc and Zt. Within crystallization mechanisms, a metric considered to evaluate crystal growth is the value of n. Normally, it acquires values between one and four. Three is a suggested value to explain a three- dimensional growth, as in the case of the nanocomposites analyzed in this work. These nanocomposites exhibited an increasing behavior for values of Zc when an ascending value of φ is preserved for each of the samples. The above suggests that the crystallization rate is higher when a faster φ is evaluated as opposed to when a slower φ are used. It should be noted that notwithstanding the use of both nanoparticles series, pure PLA showed higher crystallization rates.

Table 5 Non-isothermal kinetic parameters from the Jeziorny model for PLA and its composites with S-SiO2 and P-SiO2
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By applying Eq. 6 to the crystallization data, we obtained a good linear dependence between ln F(T) and ln φ. This observation confirms the applicability of the Mo model to PLA and its nanocomposites (modified and unmodified silicon dioxide nanoparticles). The results are shown in Table 6 and Fig. 6. It can be seen in Fig. 6a that the nanocomposites M1 and M3 together with the neat PLA show similar crystallization rates when the relative crystallinity reaches 0.70. By outperforming this value, the M3 nanocomposite improves its crystallization rate. It is also appreciated that the S-SiO2 and M2 nanocomposites present low crystallization rates compared to pure PLA, with the M2 nanocomposite presenting a lower nucleating capacity in PLA. In Fig. 6b, we observe that the nanocomposites maintain their crystallization rate until a relative crystallinity of 0.50 is reached. Outstripping this value, we observe that the crystallinity rate of the M5 nanocomposite decreases. These results indicate that the nucleation capacity decreases when a 10:2 ratio of coupling agent is used on the silicon dioxide surfaces.

Table 6 Non-isothermal kinetic parameters from the Mo model for PLA and its composites with S-SiO2 and P-SiO2
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Fig. 6
figure 6

F(T) versus crystallinity behavior of PLA and its composites with a S-SiO2 and b P-SiO2

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Effective activation energy from non-isothermal analysis

The reference on the effect of adding SiO2 nanoparticles to the polymer matrix was obtained by the Friedman isoconvertional method (Eq. 8) based on the non-isothermal crystallization data. Through this method, we can visualize in energy terms the impact of the inclusion of modified and unmodified nanoparticles in the crystallization process through the behavior of the activation energy. This effect on crystallization can be seen in Fig. 7.

Fig. 7
figure 7

Activation energy behavior as function of crystallinity degree for PLA and its nanocomposites. a S-SiO2 series and b P-SiO2 series

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The crystallization process rate is determined by an important parameter named activation energy [33]. This parameter is the energy required to transport molecular segments to the surface in crystallization process. The crystallization rate is determined by two main factors: nucleation and molecular mobility of polymer chains [34, 35]. The activation energy is interpreted as the ease that materials have to form crystals or the energy necessary for the chains of material to accommodate. Figure 6a–b shows that when unmodified nanoparticles are added, there is a higher activation energy value than neat PLA, in other studies a similar behavior has been observed and suggests that nanoparticles have an effect on the PLA crystal growth [36]. Sample M2 (see Fig. 7a) shows a value slightly below the PLA, which indicates an increase in the crystallization rate of PLA. It is also observed that in percentages less than 50% crystallinity, the incorporation of modified nanoparticles (M1 and M3) avoids PLA chains to order perhaps due to a molecular mobility restriction. Similarly, we observed that at the crystallization process beginning with P-SiO2 series samples, the crystal growth of PLA is prevented (see Fig. 7b). However, the behavior is maintained with slight variations, which suggests that the coating from filler does not have a significant effect on the growth of PLA crystals. Which has an advantage in terms of PLA processing.

Dynamic mechanical analysis of PLA/SiO2 films

Figure 8 shows the effect of temperature on the storage modulus and damping factor of the neat PLA and various composites with S-SiO2 (a, c) and P-SiO2 (b,d) with different 3-APTMS content on the silicon dioxide surface. Variation in modulus occurs owing to the effect of the incorporated filler.

Fig. 8
figure 8

Dynamic mechanical analysis (DMA) storage modulus curves of a PLA/S-SiO2 and b PLA/P-SiO2 composites. Dynamic mechanical analysis (DMA) damping factor curves of c PLA/S-SiO2 and d) PLA/P-SiO2 composites

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Figure 8a indicates that nanocomposites (S-SiO2 series) have a larger storage modulus than pure PLA. Firstly, when S-SiO2 was added with a surface modification of 3-APTMS with a 10:2 ratio (M2), there was a significant increase. Furthermore, it was observed that the incorporation of S-SiO2 with the least amount of coupling agent maintains similar the behavior of the virgin PLA matrix. Also, we observed that the incorporation of the unmodified nanoparticle (S-SiO2) had an improvement in the storage modulus of PLA. This is because it is known that using spherical mineral fillers tends to increase the storage modulus due to the stiffness of the filler [37].

Figure 8b shows that some of nanocomposites (P-SiO2 series) have a smaller storage modulus than pure PLA. It is again observed that when P-SiO2 was added with a 3-APTMS surface modification with 10:2 ratio (M5), there was a significant increase, although less than in the M2 sample. Furthermore, it was observed that the incorporation of P-SiO2 with the least amount of coupling agent (M6) maintains a similar behavior of the PLA virgin matrix. Furthermore, we observed that the incorporation of the unmodified nanoparticle (P-SiO2), as well as the sample with high load of coupling agent (M4), had a decrease in the PLA storage module. This could be caused by agglomeration of nanoparticles in the PLA matrix. Increasing the storage modulus, as shown in Fig. 8a, b, suggests that there may be an optimal coupling agent concentration on the surface to enhance the interaction between the PLA polymer and silica nanoparticles (samples M2 and M5).

The damping properties improvement is related to the appearance of a higher degree of molecular mobility by the polymer chains. This mobility is reflected in an increase in the area under the behavior curve of Tan δ [38]. The area under the α-relaxation peak in conformed PLA nanocomposites is approximately 60° C (see Fig. 8c–d). The area appears to widen without affecting the maximum temperatures for nanocomposites that are reinforced with nanoparticles without actually showing a specific trend regarding the coupling agent increase on the nanoparticle surface [39]. The glass transition temperature (Tg) is influenced by factors such as the nanoparticle surface and even by the dispersion along the polymer matrix [40]. In addition to this, there are studies where polymer–nanoparticle interactions play an important role in the polymers dynamics, mainly when they are in the molten state [41]. In Fig. 8c–d, it is observed that the Tg in both nanocomposites series is independent of the coupling agent amount on the silicon dioxide surface; other authors who have worked with silicon dioxide have reported similar behaviors [42]. The addition of porous silicon dioxide nanoparticles (P-SiO2 series) in the PLA matrix shows two Tan δ peaks for some composites (P-SiO2, M4 and M5) (see Fig. 8) and is appreciates that the second peak decreases as the amount of coupling agent decreases. This second peak can be attributed to the formation of a crosslinked microgel structure to the PLA matrix [43].

Mechanical properties of PLA/SiO2 films

Table 7 shows mechanical properties, including tensile stress and Young’s modulus of pure PLA and its nanocomposites (S-SiO2 and P-SiO2 series). In this study, Young’s modulus and stress values for the pure PLA were 15.90 MPa and 1000.70 MPa, respectively. PLA had an increase in tensile stress when unmodified spherical silicon dioxide nanoparticles (S-SiO2) were added. Furthermore, an increase in tensile stress was noted when the coupling agent amount on the surface decreased, achieving an improvement of 40.25% for M3 sample. PLA nanocomposites of P-SiO2 series were maintained in a range of 15–17 MPa, indicating that the incorporation of this nanomaterial has tiny effect on tensile stress. However, the decrease in tensile stress in these nanomaterials was around 7%. This decrease can be attributed to a hydrolytic degradation of PLA. Other authors have proposed that the incorporation of nanomaterials (such as carbon nanotubes and silica nanoparticles) can accelerate the hydrolytic degradation of PLLA [44, 45].

Table 7 Mechanical tests for PLA and its composites with S-SiO2 and P-SiO2
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S-SiO2 nanoparticles series incorporated in the PLA matrix improve Young’s modulus to a maximum point of 1352.55 MPa for the M2 sample. This represents an improvement of 35.16% with respect to the PLA matrix. The improvement range is 17.94–35.16%, which makes the nanocomposite ideal for applications where a resistant material is required using this filler. The opposite effect in improving the resistance of the PLA matrix occurs when P-SiO2 nanoparticles series are incorporated. There are decreases in Young’s modulus with respect to the PLA between 10.59 and 51.97%. According to the results obtained with respect to Young's modulus, a trend is seen considering the specific surface area values shown in Table 1. As the surface area increases, the Young's modulus is diminished. This indicates that the material has a better elasticity and makes a difference in the effect of surface area and the coupling agent amount found on the nanomaterial surface.

Conclusions

In this research work, the effect of the surface area of silicon dioxide nanoparticles and their polarity change by means of a coupling agent on mechanical and thermal properties of PLA nanocomposites was evaluated. Within this, it was demonstrated that changing the dose of compatibilizer modifies the isoelectric point of nanoparticles, which indicates that it charges differently. When introducing them into a polymer, changes in mechanical properties were observed through an increase in elasticity when nanoparticles with high surface area were used, and an increase in stiffness when nanoparticles with low surface area were employed, reaching a maximum in the 10:2 ratio of coupling agent.

In dynamic mechanical properties, it was observed an increase in the storage modulus for both types of nanoparticles when a 10:2 ratio is used again. The glass transition temperature was kept constant and in thermal properties an increase in the crystallization rate was observed for the 10:2 ratio in both nanoparticles; there were differences when using spherical nanoparticles and a low rate disturbance when using nanoparticles with a high surface area. Finally, it was shown that the surface area does not play a role in the energy required for crystal formation but has a direct effect on mechanical properties as discussed above.

According to their Young’s modulus, the most rigid nanocomposites were those made with spherical nanoparticles, presenting an optimum when the coupling agent ratio is 10:2. In dynamic mechanical properties, for both samples regardless of the surface area, the 10:2 ratio showed a better performance, which is consistent with crystallization rates. We observe that the rate of crystal formation plays an important role in mechanical properties of formed nanocomposites by nanoparticles with low surface area. On the other hand, when nanocomposites are reinforced with high surface area nanoparticles, the amount of formed crystals is what influences mechanical properties of nanocomposites; this due to polymer chains have a different arrangement around nucleation centers.