Riccardo
Catalano
a,
Danielle L.
Slomberg
a,
Céline
Picard
b,
Nicolas
Hucher
b,
Vladimir
Vidal
a,
François
Saint-Antonin
c,
Jean-Claude
Hubaud
d,
Jerome
Rose
a and
Jerome
Labille
*a
aAix Marseille Univ, CNRS, IRD, INRAE, Coll France, CEREGE, Aix-en-Provence, France. E-mail: labille@cerege.fr
bNormandie Univ, UNILEHAVRE, FR3038 CNRS, URCOM, 76600 Le Havre, France
cCEA, LITEN, Minatec Campus, Grenoble, France
dHélioscience, Marseille, France
First published on 14th October 2021
Engineered nanomaterials (ENMs) can be used in cosmetics as UV blockers. For these products, the exposure-driven risk for humans and the environment is related to the ENM release during or after use, and thus to the original surface properties and aggregation state of the ENMs. Moreover, as the ENM dispersion in the product also affects the efficiency to screen UV rays, optimizing the formulation can lower the ENM load. Characterizing the ENM behaviour directly in a cosmetic formulation is thus crucial to better assess their risk and develop safer-by-design products. However, the complexity of such a multiphasic system limits in situ characterization using most common analytical tools. Here, we present a novel methodology based on two-dimensional X-ray absorption (2D-XRA) imaging to characterize the dispersion state of ENMs directly in a sunscreen product. Two commercial nano-TiO2 UV filters, displaying different surface coatings, were used to prepare contrasting sunscreen formulations at increasing ENM concentration. Cryogenic scanning transmission electron microscopy (Cryo-STEM) was also used for comparison to evaluate the advantages and limitations of both methods in this context. 2D-XRA proved to be a powerful and rapid technique to analyze both UV filter dispersion in the formulation and the overall product homogeneity. This was enabled by thresholding areas of contrasting ENM densities in the 2D-XRA image, which reflected ENM aggregates, fine ENM dispersions, or voids with a lower UV protection. Image analysis also allowed semi-quantitative evaluation of the relative area of each density range, and of the aggregate size in terms of projected area. In comparison, Cryo-STEM provided a larger magnification than 2D-XRA, which enabled visualisation and sizing of the ENM primary particles, plus the distinction of the emulsion oil and water phases thanks to EDX coupling, but with a smaller and less representative volume of analysis and a higher cost in time and energy. This work is a step forward in measuring ENM behavior in situ in a complex multiphasic matrix constituting a nano-enabled product. Such knowledge at the original stage of the product life cycle is crucial to better predict the ENM fate along with use and end of life, and eventually, develop safer-by-design nano-enabled products.
Environmental significanceAnalysing the nanomaterial (ENM) dispersion state in a cosmetic product, without altering the original matrix, is crucial to assess the exposure driven risk during and after use. Here, we present a novel methodology based on 2D X-ray absorption imaging to analyse, in situ, the aggregation state of ENM UV filters in a sunscreen emulsion. Our results demonstrate that this methodology is able to rapidly characterize, semi-quantitatively, the ENM dispersion and homogeneity in the formulation and can be a useful tool to optimize the UV filter type and concentration with regard to the product efficacy. Eventually, this can help to develop sunscreens with a lower ENM load, still maintaining an acceptable sun protection factor, but with a lower environmental footprint. |
Cosmetic products, like sunscreens, often contain nanoparticulate TiO2 or ZnO minerals, used mainly as UV filters. They are preferred over the corresponding micron-sized particulate filters because of their better screening efficiency and transparency on the skin.5 During use, these ENMs may penetrate the human skin,6 causing cytotoxicity,7–10 or be released into aquatic and soil environments during bathing activities or showering,11 with potential hazards to the surrounding ecosystems.4,12 The European Commission's regulation program, Registration, Evaluation, Authorization and Restriction of Chemicals (REACH), is currently working on the regulation of products containing nanomaterials. The regulatory process normally requires basic physico-chemical characterization of the product (stability; purity; molecular weight; crystal structure) and, when necessary, a toxicological evaluation (in vivo/in vitro toxicity tests).13,14
Since the risk associated with these ENMs is related to the sunscreen composition and to the ENM content in the formulation, optimizing the mineral filter performance and concentration is crucial to anticipate and minimize this risk.11 One way to obtain a cosmetic product with a lower ENM content without affecting its efficiency (solar protection factor – SPF) is to enhance the particle dispersion and stability in the formulation medium.15 It was observed that a finer nano-UV filter dispersion can be twice as efficient as a formulation containing aggregated nano-UV filters.16 Consequently, the determination of nanoparticle size and dispersion state (i.e. aggregation; agglomeration) in a cosmetic formulation is a key step to optimizing the product efficiency and thus minimizing the UV filter load and environmental footprint after release. Although the physico-chemical characterization of raw nanomaterials prior to their integration into a cosmetic product is relatively straightforward,17 it is more challenging to characterize the final nano-enabled product because of the matrix complexity, which makes many routine approaches unsuitable.
One of the main experimental issues is related to the oily nature of the product, which impedes the complete drying of the sample. Therefore, size, structure and chemical analyses using transmission electron microscopy (TEM) in standard mode are not possible, because this works under a complete vacuum, and can eventually lead to sample aspiration which could damage the instrument.18 Dilution of the cream with an organic solvent, followed by evaporation of the volatile components, is often used prior to the analysis in order to avoid this effect with conventional TEM or SEM.19,20 Such a sample preparation changes the ENM dispersion state and its interaction with the formulation ingredients, which is not compatible for characterizing the final sunscreen product. To avoid sample aspiration or drying during TEM analysis, Butler et al.21 used high-pressure freezing substitution of the creamy medium with a suitable resin. The resulting images allowed the finer characterization of particle size, shape and aggregation state. However, this experimental set-up is very time-consuming and the resin addition could likely change the interaction of the nanoparticles with the surrounding medium. Recently, Philippe et al.,22 performed a TEM analysis on different commercial sunscreens in cryogenic mode. This technique is suitable for obtaining finer electron microscopy images of nanoparticles in sunscreen formulations without altering the original composition of the product.23 Nevertheless, although Cryo-TEM is able to give insight on the size and shape of primary particles and aggregates, the images cannot be representative of the entire product structure (i.e. nanoparticle aggregation or agglomeration state; inhomogeneities), as a high resolution often implies a limited analyzed area. It is thus crucial to use a methodology which does not alter the original formulation matrix, gives a resolution on the order of the UV filter aggregate size, and enables the analysis of a representative area of the product.
Tyner et al.18 compared more than 20 analytical methods to characterize nanomaterials in sunscreen formulations. They concluded that four of them were capable of providing insight on some specific ENM characteristics without changing the composition of the original product. Laser-scattering confocal microscopy (LSCM) is able to give insight on the presence of nanoparticles and their average dispersion state, but due to the diffraction-limit resolution of optical microscopy and low optical contrast, the particles cannot be detected or sized accurately. X-ray diffraction (XRD) is suitable for characterizing the crystalline structure and size of the coherent domain of primary particles. Variable pressure scanning electron microscopy (VPSEM) provides surface characterization of the sample, and coupling with a back-scattering detector gives a contrast function of the atomic number, which leads to a better visualization of Ti or Zn-based ENMs in the sample. Finally, atomic force microscopy (AFM) is able to detect nanomaterials in the formulation and give insight on morphological features, even though phase imaging is required for bulk characterization. Because AFM is really sensitive to topographical changes, height analysis can be complicated due to artifacts arising from sample preparation.
The present work was aimed at developing a novel methodology based on two-dimensional X-ray absorption (2D-XRA) imaging to characterize the aggregation and dispersion state of nanoparticles directly in a sunscreen product together with the formulation homogeneity. Different sunscreen formulations were prepared in-house in order to obtain contrasting case studies that were analyzed by this method. The sun protection factor (SPF) of each formulation was measured in order to evaluate the impact of the filter dispersion on the SPF and if the latter could be used as a possible indicator of the formulation homogeneity. Cryo-STEM was also used to measure the particle size, shape and dispersion state in the emulsion in order to give insights on the advantages and limitations of both methods for sunscreen characterization.
Commercial name | Supplier | Composition | Function |
---|---|---|---|
SEPIPLUS 400 | SEPPIC | Polyacrylate; polyisobutene polysorbate 20; water; sorbitan; isooctadecanoate | Gelling agent |
EASYNOV | SEPPIC | Octyldodecanol; octyldodecyl xyloside; PEG30 dipolyhydroxystearate | Emulsifier |
CETIOL LC | AMI CHIMIE | Coco-caprylate/caprate | Emollient |
TEGOSOFT P | EVONIK | Isopropyl palmitate | Emollient |
EUXYL PE 9010 | SCHUELCKE | Phenoxyethanol; ethylhexylglycerin | Cosmetic preservative |
A total of seven sunscreen formulations were prepared using this procedure, which include the two UV filters incorporated at three different concentrations (2.8; 5; 10 wt%), and a blank formulation free of UV filter. In the formulations prepared with 10 wt% UV filter, 10 g of the dry UV filter powder were incorporated. In the formulations prepared with a lower amount of UV filter (2.8 and 5 wt%), the weight difference was balanced by adding the same mass of ultrapure water.
![]() | (1) |
UV transmitting poly(methyl methacrylate) (PMMA) plates (50 × 50 mm) with a 5 μm medium roughness were used as a substrate that mimics skin. Between 1.2 and 1.4 mg cm−2 of cream was spread on the substrate, accurately weighing the amount deposited before and after evaporation occurred. By using light finger pressure, the cream was spread over the entire surface until a homogeneous distribution was achieved and the sample was left to settle for 15 min at room temperature to ensure self-leveling of the formulation. A bare PMMA plate was used as a blank for UV transmittance. The transmittance of each sample was measured in the UV range (400–290 nm) using a spectrophotometer (Kontron UVIKON – UVK lab) equipped with an integrating sphere. For each sunscreen sample, the measurements were repeated 9 times at different locations of the PMMA plate.28
In addition to this qualitative characterisation, the local ENM concentration in each area of the sample image could be quantitatively determined, using the calculated X-ray transmission through the sample, as follows. The transmission of X-rays through a slab of thickness d is given by eqn (2):29
T = exp(−nμad) | (2) |
μa = 2r0λf2 | (3) |
![]() | (4) |
To further quantify the ENM aggregation and dispersion state of the samples, when some large aggregates were revealed as discrete units in the 2D projection map, their average area (1–25 μm2) was determined using the particle size calculator feature of ImageJ. For this analysis, only the concentration domains higher than the expected nominal concentration in the sample were considered. In samples with 5 or 10 wt% nominal concentration, we considered the domains >10 wt%, while in samples with 2.8 wt% nominal concentration, we considered both domains 5–10 and >10 wt%.
Finally, the standard deviation of the greyscale distribution histogram was also calculated for each sample, after blank subtraction, and tested as a possible indicator of the sunscreen homogeneity.
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Fig. 1 Contact angle measurements (θ) between different liquids and the T-Lite (a) or T-S (b) nanoparticle pellets, using the sessile drop method (3 replicates). |
Nanoparticulate UV filters | Interfacial Lifshitz–van der Waals component (γLW) | Lewis base component (γ−) | Lewis acid component (γ+) | Surface free energy (γs) (mN/m) |
---|---|---|---|---|
T-S | 21.3 ± 2.0 | 3.9 ± 1.5 | 0.4 ± 0.4 | 23.1 ± 1.8 |
T-Lite | 35.3 ± 1.4 | 0.1 ± 0.1 | 0.4 ± 0.2 | 35.7± 1.5 |
The interfacial Lifshitz–van der Waals component of the surface free energy (γLW) describes the likelihood of a compound surface to establish apolar interactions,31 while the Lewis base component value (γ−) describes the likelihood to interact with polar components. γLW is lower for T-S ENM (21 mN m−1) compared to that for T-Lite ENMs (35 mN m−1), while γ− is lower for T-Lite ENMs (0.1 mN m−1). These differences can reasonably be ascribed to the respective organic coatings of the two ENMs. The carboxylic groups of the T-S ENM stearic acid coating can likely act as an electron donor (Lewis base) and favor interactions with polar molecules. The T-Lite ENMs, instead, contain a dimethicone (polydimethyl siloxane) coating free of any electron donor (or acceptor) moiety, which does not favor polar interactions. Although we do not have any information about the stearic acid chain orientation or the nature of interactions with the nanoparticle surface, Paunov et al.32 estimated that a stearic acid coating on calcium carbonate particles brings intermediate surface hydrophobicity, which enables stable dispersion in both water-in-oil and oil-in-water emulsions. These relative polarities agree with the slight differences in affinity for the ultrapure water, or the oil phase, observed between the two ENMs. Due to their more polar aspects, the T-S ENMs, although still maintaining a hydrophobic character, showed a slightly higher affinity for ultrapure water (θTS–w = 93.9°) compared to the T-Lite ENMs (θTLite–w = 106.9°). In contrast, the wettability with the oil phase was likely favored by the apolar interactions present at the T-Lite ENM surface.
As the SPF value is proportionally correlated to the UV absorbance,33 this trend cannot be biased by the calculation method. Furthermore, it is unlikely that this trend was due to differences in the T-S and T-Lite ENM primary particle sizes, because this would not lead to such a dependence on the ENM concentration. We assume that such a difference in SPF arises from various aggregation states of the nanoparticulate UV filters in the formulation. It is well-known that particle aggregation increases with particle concentration and leads to a lower sunscreen screening efficacy.34 Aggregation phenomena can indeed cause inhomogeneities in the UV filter distribution in the formulation, creating voids with low filter content that are more transparent to UV radiation. As such, T-S aggregation at the highest UV filter load resulted in an SPF 25% lower compared to that of T-Lite. With the aim to test the ability of 2D-XRA to evidence such contrasting formulation structures, the seven samples were analysed using this technique. The large field of view images are presented in Fig. 3 through the unmodified 8bit mosaics.
In each greyscale image, darker shades correspond to regions with higher X-ray absorption, while brighter shades correspond to lower X-ray absorption zones. Denser materials, like TiO2, are stronger X-ray absorbers compared to the aqueous or oily sunscreen components. The black dots with a size of a few micrometers (red circles) in sunscreens (b–g) can thus be easily associated with ENM aggregates, as they are not detected in the blank sunscreen free of ENMs (a). Based on these images, at each ENM concentration, the T-Lite sunscreens contain less micro-sized aggregates than the T-S sunscreens. The darker regions are more homogeneously dispersed in the T-Lite formulation than in the T-S formulation, indicating a finer dispersion of the ENMs in the former. Meanwhile, for a given UV filter nature, the particle distribution observed at 2.8 and 5 wt% appeared similar, and at the highest concentration tested, 10 wt%, the homogeneity of the dispersion was dramatically affected. In TS-10 (g), this is associated with increasing particle aggregation. In TLite-10 (d), although the presence of discrete micron-sized aggregates was not observed at this magnification, the dispersion itself appeared less homogeneous compared to those with lower T-Lite concentrations, with a marbling-like aspect in the center of the sample and nanoparticle accumulation along the meniscus. This nanoparticle accumulation at the air–cream interface was also observed in TLite-5 and in all the T-S samples. This suggests a higher affinity of the ENMs for the air phase than for the sunscreen medium. Such surface accumulation was already observed in aqueous colloidal dispersions with hydrophobic particles, usually accompanied by particle aggregation/coagulation,35 and this accumulation would likely increase at higher particle concentrations. The fact that ENM aggregation and concentration at the meniscus were already observed at the lowest particle concentration in TS-2.8 suggests that this ENM is less stable in the formulation compared to the T-Lite ENM. These qualitative observations are in accordance with the contact angle and SPF measurements obtained (Fig. 1 and 2), which attests to the utility of 2D-XRA as a rapid screening method to assess both the dispersion state of mineral UV filters in a sunscreen formulation and, indirectly, the emulsion homogeneity.
It is important to underline that the images obtained by 2D-XRA are 2D projections of a 3D sample, where each pixel thus results from the sum of the projected voxels. The TiO2 ENMs are the most X-ray absorbing components in the formulation. Moreover, the other components constituting the blank formulation were subtracted. Thus, the greyscale distribution obtained in 2D reflects the ENM concentration and aggregation state in the total volume analysed, so that any local ENM large aggregation generates an increase of X-ray absorption, leading to a map region with an ENM density higher than the nominal sample concentration. Conversely, any map regions with lower X-ray absorption can be interpreted as containing a low ENM density, i.e. voids with under-protection against UV-rays.
From the 6 maps obtained as shown in Fig. 4, the respective area ratios of each ENM concentration domain were quantified and are reported in Fig. 5a. The greyscale distribution plots after blank subtraction are also reported in Fig. 5b, together with the thresholds used. The ENMs in TLite-2.8 and TLite-5 appear the most finely dispersed, making it difficult to distinguish between concentration domains. In the TLite-2.8 map, a majority (71%) of the area corresponds to the domain 2.8–5 wt% (Fig. 5a), which is in good agreement with the nominal concentration of the sample. The whole greyscale distribution actually lies around the theoretical X-ray absorption value for TiO2 at 2.8 wt% (Fig. 5b). In TLite-5, still in line with the ENM nominal concentration, the greyscale distribution is shifted close to the theoretical TiO2 X-ray absorption at 5 wt% concentration (Fig. 5b). The 2D map indicates that the ENMs occur essentially in the adjacent concentration domains 5–10% (61% area) and 2.8–5% (32% area) (Fig. 4 and 5a).
On the other hand, the T-S samples do not follow the same trend. TS-2.8 and TS-5 do not show significant differences in their ENM distributions (Fig. 4 and 5b) in spite of their contrasting nominal concentrations. This is evidenced in Fig. 5, showing very similar distributions of the ENM concentration and greyscale plot for these two T-S samples. Moreover, in both maps, some large and discrete units appear, showing local areas of ENM concentration much higher than expected, as well as some large UV filter voids (16–17% of area <2.8 wt%). This is the result of the T-S ENM aggregation, which prevents homogeneous distribution in the sunscreen, even at the lowest concentration. This can be related to the lower Lifshitz–van der Waals component of T-S ENM (Table 2), which implies a lower affinity with the apolar oil phase of the sunscreen formulation, and leads thus to a lower ENM dispersion stability. Sizing of these projected aggregate areas was attempted and the values are reported in Fig. 6a. For the 2.8 and 5 wt% nominal concentrations, the T-S aggregate projected areas range between 10 and 15 μm2, while for T-Lite, much lower values are measured at around 2 μm2.
At the highest ENM nominal concentration of 10 wt%, both T-S and T-Lite sunscreens show a lack of homogeneity in the ENM distribution, including the presence of highly concentrated ENM areas (>10 wt%) and voids (<5 wt%). In both cases, the greyscale distributions lie below the theoretical value of X-ray absorption for the 10% TiO2 concentration. This means that most of the sunscreen area is under-concentrated with regard to the expected 10 wt% value. Indeed 71 and 41% of the map areas correspond to the 5–10 wt% concentration domain, while only 8 and 6% correspond to the >10 wt% domain, in the T-Lite and T-S samples respectively. For the TS sunscreen series, this comes in line with the observations made at lower nominal concentrations, showing already a lack of homogeneity due to ENM aggregation. Here, the average projected aggregate area increases to around 25 μm2, together with a larger deviation of the size value, i.e. sample heterogeneity, compared to the T-S samples with lower concentrations (Fig. 6a). However, for the more performing T-Lite series, this observation at 10 wt% contradicts the relatively high affinity of the ENMs for the oil dispersing medium. This suggests that saturation of the sunscreen formulation takes place at a high ENM load, which leads to particle aggregation and loss of dispersion homogeneity. Nevertheless, the projected aggregate area for TLite-10 still remains much smaller, around 3 μm2, than those for the T-S samples (Fig. 6a). Indeed, the TLite-10 map shows a finer distribution of the highly concentrated units on its whole area than that for TS10, which shows larger units not homogeneously dispersed.
The standard deviations of each greyscale distribution after blank subtraction are reported in Fig. 6b, as a possible rapid indicator of the global formulation homogeneity. Here, we assume that a lower standard deviation, i.e. a narrower greyscale distribution width, would indicate a more homogeneous sunscreen emulsion, containing less high density aggregates and/or less voids. As expected, at every ENM concentration studied, the values for the T-Lite samples indicate a narrower greyscale distribution, i.e. a more homogeneous sunscreen emulsion, than those for the T-S samples. Nevertheless, the standard deviation for the T-Lite samples also increases linearly with the ENM concentration, indicating a progressive decrease of the sample homogeneity. This is certainly the effect of increasing ENM load that favors the formation of aggregates and voids, as already discussed. For the T-S samples, the greyscale standard deviation remains unchanged at 2.8 and 5% w/w, whereas it increases strongly at 10% load, indicating a dramatic decrease in homogeneity. This trend is in good agreement with the aggregate projected area plotted in Fig. 6a and with the dramatic loss of SPF value in the TS-10 sunscreen (Fig. 2). This confirms the relationship between these three characteristics, and thus, that the greyscale standard deviation could be used as a preliminary indicator of the emulsion dispersion.
Sunscreen samples were also analyzed using scanning-transmission electron microscopy in cryogenic mode, in order to compare the information provided by this analytical method to that from 2D-XRA. Cryo-STEM has already been used successfully to detect ENMs in sunscreen formulations and to provide additional information such as their primary particle size and shape.22
Here, only the TLite-2.8 and TS-2.8 samples were analyzed with Cryo-STEM, because higher ENM loads would lead to image saturation by the nanoparticles and prevent qualitative analysis. Of note, this constitutes a primary limitation of Cryo-STEM with regard to 2D-XRA. EDX analysis allows for the distinction and mapping of the three main sunscreen components: ENMs, oil and water. In both samples (Fig. 7 and 8), the presence of TiO2 ENMs is confirmed by the EDX mapping of titanium in the corresponding areas (images in Fig. 7c and f and 8c and f). Also, EDX analysis highlighted the carbon and oxygen distribution in the sample. We assume that the areas dominated by the presence of carbon are associated with the sunscreen oil phase while the areas dominated by the presence of oxygen are associated with the aqueous phase. Superimposition of different emulsion phases, which can affect the data interpretation of the STEM images, was minimized here by analyzing ultrathin sample slices (∼80 nm thickness) that allowed for a more accurate distinction of the emulsion phases. Of note, the lacey carbon background of the support grid superimposes with the carbon signal from the oil, due to the thin sample transparency, but distinction of the two contributions remains possible.
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Fig. 7 (a and c) Cryo-STEM images on TS-2.8. (b and d) Related EDX analysis of titanium, oxygen and carbon. |
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Fig. 8 (a and d) Cryo-STEM image on TLite-2.8. (b and e) EDX analysis of oxygen/carbon and oxygen/titanium images (c and f). |
In the TS-2.8 sample (Fig. 7), the presence of brighter contrasting areas is attributed to nanoparticle aggregates of ≅2 μm size, which are clearly visible in Fig. 7a, and evidenced in the Ti map in Fig. 7b. In the second slice (Fig. 7c) the ENM dispersion appears finer with the presence of smaller aggregates of <1 μm size. In both slices, the water and oil phases constituting the emulsion are clearly distinguished in the EDX maps (Fig. 7b and d) by the distinction of high carbon signal areas (oil) and high oxygen signal areas (water). The detection of titanium from ENMs only inside the areas with high carbon content (Fig. 7b and d) suggests that UV filters are concentrated in the oil phase, which is in accordance with the hydrophobic property of the ENMs. It is worth noting that in the areas (1) and (2) of the images in Fig. 7c and d, the ENMs appear more concentrated at the interface between the water and oil phases (blue arrows). ENMs may compete here with some other oil phase components (e.g. surfactants) to interact at the oil–water interface, eventually stabilizing the emulsion.36 However, confirming this mechanism would require additional analysis. Two types of T-S ENM distributions in the formulation were evidenced by Cryo-STEM, with some larger aggregates remaining stuck in their original oil dispersing medium, and some finer particles reorganized in local areas with respect to their surface affinity, i.e. at the oil/water interface.
The Cryo-STEM images for the TLite-2.8 sample are shown in Fig. 8. In order to facilitate the interpretation of the EDX analysis, the C and O signals are mapped together to highlight the emulsion structure (Fig. 8b and e), and the O and Ti signals are mapped together to visualize the ENM dispersion (Fig. 8c and f). Compared to TS-2.8, the ENMs appear more dispersed with most of the aggregates observed being <1 μm. This results in a lower detection of Ti in the EDX map, due to a lower contrast in the image compared to the O and C contributions. Some titanium agglomerates however remain visible in Fig. 8c.
Regarding the emulsion structure, the EDX maps of the two TLite-2.8 slices show that the oil and water phases are barely distinguishable and poorly reproducible, while they were clearly separate in the TS-2.8 sample. Here, one TLite-2.8 slice (Fig. 8a and c) shows a carbon signal prevailing over the oxygen one, which is attributed to the oil phase, except in the area (1) where the presence of oxygen could correspond to a water droplet. The EDX map of the other slice (Fig. 8d and e) shows a prevalence of oxygen over carbon, suggesting an excess of the water phase with regard to the oil. Unlike what was seen in the TS-2.8 sample (Fig. 7c), it is not evident in TLite-2.8 whether the ENMs are preferentially concentrated at the O/W interface. See e.g. areas (1) and (2) (Fig. 8d and e). This is in line with the difficulty in distinguishing the particles and the emulsion phases (Fig. 8e(2)).
The sensitivity to X-rays of the higher density of the mineral UV-filters dispersed in the formulation makes 2D-XRA imaging a powerful tool to provide more precise information compared to techniques such as multi-photon tomography (MPT) and laser scanning confocal microscopy (LSCM) used in previous studies19,21 to characterize similar colloidal systems. Although these methods are capable of providing qualitative information on the dispersion state of ENMs in a formulation at the micrometer scale, due to resolution limits, they could not provide a quantitative description of the particles or aggregate sizes and of the homogeneity of the formulation.
Ultramicrotome/Cryo-STEM analysis of the lower concentration sunscreens provided a larger magnification and thus a clearer visualization of particle aggregates and primary particles, complementing the observations made with 2D-XRA imaging. The preparation of ultrathin (80 nm) sample slices obtained using a cryogenic ultramicrotome, and coupling to EDX analysis, allowed a finer distinction of the emulsion phases and of the ENM dispersion characteristics. Notably, any eventual ENM concentration in particular areas, such as the oil/water interface, as known in Pickering-like emulsions, can be evidenced with this approach. However, due to the smaller observation field compared to that in 2D X-ray absorption imaging, Cryo-STEM could not give insight on the dispersion state and homogeneity of the overall product nor the presence of large micrometric aggregates that give evidence of a non-optimal formulation. Indeed, any variability of the ENM aggregate size when a heterogeneous sample is analyzed leads to a lack of reproducibility at this scale of observation. All these considerations taken together with the time-consuming sample preparation and imaging (2D-XRA: 2–3 h; Cryo-STEM: ∼2 days), as well as the expensive cost, suggest that Cryo-STEM should be employed only when the determination of the primary particle size and shape and precise ENM localization in an emulsion is required. However, the two techniques seem to be complementary and could be thus employed together in order to have a larger picture of the ENM fate and behavior in sunscreen formulations.
The determination of ENM UV filter aggregate size in a cosmetic formulation is essential not only for the biological/environmental risk assessment of the product, but also to optimize the product design. The relationship between the aggregation state of the ENMs in the formulation and the solar protection efficiency that was observed in the present work confirmed that more finely dispersed nanoparticles lead to a sunscreen with a higher SPF.15 In contrast, aggregation of the UV filters leads to a more heterogeneous formulation that eventually results in protection voids against UV-rays on the user's skin, which can be quantified by this method.
Two hydrophobic ENM UV-filters were selected and formulated here as case studies. They showed different affinities for the cosmetic oil dispersing medium, which was associated with contrasting dispersion states in the final formulation. The UV filter with a low polar character and higher Lifshitz–van der Waals component was better dispersed in the W/O sunscreen formulation at every concentration tested, which eventually led to more efficient UV screening compared to the formulation containing the more aggregated UV filter. In the case of 10 wt% ENMs, a concentration typically found in mineral sunscreens labeled with SPF 20, the gain in SPF reached 6 units in the sunscreen with less aggregated UV filters. Meanwhile, we could evidence that this high mineral load tended to decrease the formulation homogeneity, due to the ENMs favoring aggregation and/or over-saturation of the formulation, even with the most stable UV filter (T-Lite). These results illustrate the crucial effects of particle aggregation and formulation homogeneity on sunscreen performance. The 2D-XRA imaging methodology discussed herein is capable of rapidly quantifying these aspects inside a sunscreen, with no particular need for sample preparation. Moreover, this tool does not require any particular knowledge of the product or any calibration. Such quantitative structural analysis can be obtained simply by providing the nominal concentration of the mineral UV filter used in the product, the latter being used to calculate the theoretical X-ray absorption corresponding to an optimal UV filter dispersion.
This provides a powerful tool to fabricate sunscreens using a safe(r)-by-design approach, helping to select the most appropriate mineral UV-filter in a given matrix and its optimal concentration. Indeed, lowering the UV filter concentration and maximizing the formulation homogeneity while the product SPF is kept as high as possible would eventually allow the fabrication of sunscreens with a lower impact on consumer health and on the environment because a lower amount of active ingredient would be applied to the skin, thus reducing consumer exposure as well as the amount potentially released into the environment.
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