Color Stability of Digital and Conventional Maxillofacial Silicone Elastomers Mixed with Nano-Sized Antimicrobials: An In Vitro Study

Abstract

Background/Objectives: Maxillofacial silicone prostheses’ long-term color stability remains a challenge. This study aimed to evaluate and compare the color stability of conventional and digital maxillofacial silicone elastomers mixed with nano-sized antimicrobial additives (ZnO nanoparticles and chlorhexidine salt-CHX) at various concentrations over a 10-week period. Methods: A total of nine groups (n = 10) of maxillofacial silicone elastomers were prepared. These included a control group (no additives), conventionally pigmented silicone, digitally pigmented silicone (Spectromatch system), and silicone mixed with ZnO or CHX at 1%, 3%, and 5% by weight. Specimens were fabricated in steel molds and cured at 100 °C for 1 h. Color measurements were performed at baseline and after 1, 4, 6, and 10 weeks using a Minolta Chroma Meter (CIELAB system, ΔE₀₀ formula). Data were analyzed using two-way ANOVA and Tukey HSD post hoc tests (α = 0.05). Results: Color changes (ΔE₀₀) ranged from 0.74 to 2.83 across all groups. The conventional pigmented silicone group showed the highest color difference (ΔE₀₀ = 2.83), while the lowest was observed in the ZnO 1% group (ΔE₀₀ = 0.74). Digital silicone and all antimicrobial-modified groups exhibited acceptable color stability (ΔE₀₀ < 3.1). Time significantly affected color difference, with the largest change occurring during the first four weeks (p < 0.05), followed by stabilization. Regression analysis confirmed high color stability over time for all groups except the conventional pigmented group. Conclusions: This is one of the first studies to directly compare digital and conventional pigmentation methods combined with nano-antimicrobials in maxillofacial silicones. Maxillofacial silicone elastomers mixed with up to 5% ZnO or CHX maintained acceptable color stability over 10 weeks. Digital pigmentation is similar to conventional methods. The incorporation of nano-antimicrobials offers significant microbial resistance and improved color retention.

1. Introduction

Restoring the form and function of soft tissue maxillofacial deformities is known as maxillofacial prosthetics or facial prosthetics, which significantly aid patients in regaining confidence, normalcy and reintegration into community [1,2]. Silicone elastomers are widely used in constructing such prosthetics because of their durability, biocompatibility, and ease of use [3,4].

Despite advancements in material science, the long-term aesthetic performance of maxillofacial prostheses remains a major clinical concern [4]. Patients often report dissatisfaction due to color mismatch or discoloration over time, which can lead to social withdrawal and psychological distress. Since these prostheses are typically worn for extended periods in dynamic environments, exposed to ultraviolet radiation, perspiration, sebum, and cleansing agents, the materials used must maintain chromatic stability under such conditions [4]. Therefore, identifying strategies to preserve color fidelity is not merely a technical issue but a critical component of patient-centered rehabilitation. Incorporating antimicrobial additives that also enhance aesthetic longevity addresses both functional and psychosocial aspects of prosthetic use.

Digital technologies and accompanied tools have revolutionized maxillofacial prosthodontics [5,6,7,8]. These tools, especially those based on computer-aided design and manufacturing (CAD/CAM), have improved the way data are collected and prostheses are produced [9]. One such advancement is digital skin tone matching involving scanning a patient’s skin and generating precise color recipes. The result is a highly accurate and reproducible skin tone that eliminates much of the guesswork involved in traditional, manual coloring techniques [8]. In dentistry, nanomaterial-based biosensors represented advancement in oral health diagnostics and therapeutics [9]. In maxillofacial prosthodontics, recent case reports showed successful digital production of facial prostheses by means of 3D printing [10,11].

Earlier works on silicone elastomers indicated the need to enhance their anti-fungal resistance and bonding strength without compromising their mechanical properties for long sustainable facial prostheses [4,12]. Additionally, facial silicone discoloration has been related to the micro-pores presented within the silicone structure. Such discoloration is a strong indication of micro-organism colonization leading to infection and bad odors. Hence, such issues have been resolved by incorporating antimicrobials of titanium dioxide (TiO₂), zinc oxide (ZnO), chlorhexidine (CHX), and aluminum oxide (Al₂O₃) into silicone materials [13,14]. Nano-oxide opacifiers, such as SiO₂, TiO₂, and ZnO, have been reported to improve color stability when used at 1–3% concentrations [15,16], while a 3% concentration of ZnO has been linked to better mechanical strength [12]. However, little is known about how these nanoparticles interact with other common additives, such as liquid pigments and flocking fibers, especially in terms of long-term color stability. Furthermore, clinical use of silicone prostheses often results in progressive discoloration, material breakdown, and microbial buildup, particularly under environmental and physiological stresses. This gap is critical because maxillofacial prostheses require both durability and aesthetic consistency, yet pigment degradation or nanoparticle-induced alterations could compromise clinical outcomes. By systematically evaluating silicone mixtures with varying concentrations of ZnO, CHX, and digital/conventional pigmentation over 10 weeks, this study bridges this gap. It provides evidence-based guidelines for optimizing antimicrobial efficacy while preserving color stability—a dual priority for prosthetic longevity and patient satisfaction.

This study aimed to evaluate the color stability of conventional and digital maxillofacial silicone elastomers mixed with various colorants and additives, including pigments and flocking fibers, ZnO-NP, and CHX, at different concentrations (1%, 3%, and 5%) over time. The null hypothesis was that the incorporation of these colorants and additives would not significantly affect the color stability of the silicone elastomers over time.

2. Materials and Methods

M511 maxillofacial silicone elastomer (Poly dimethyl silioxane-PDMS) was utilized to manufacture nine groups (n = 10) of 90 samples [13]. The first group was control where the silicone was not mixed with any additive or colorant. Group 2 included silicone elastomer mixed with color pigments and flocking (Microfibres, Bridgend, Technovent, UK). Group 3 included digital silicone elastomer of the digital e-skin system (Spectromatch, London, UK). The exact shade was determined using the Spectromatch system, the recommended proportions of pre-dosed pigments are generated by the e-skin calculator, which provided the exact pigment types and their concentration percentages relative to the total weight of the silicone. These pigments were then manually mixed into the silicone elastomer. Groups 4 to 6 included silicone elastomer mixed with nano-sized particles of ZnO-NP (BET = 67 m²/g) (ZnO, Nanostructured, Amorphous Materials, Inc., Texas, USA at three different concentrations (by weight%): 1%, 3% and 5%, respectively. Groups 7 to 9 included silicone elastomer mixed with chlorohexidine salt (CHX, Sigma, Aldrich) at three different concentrations (by weight%): 1%, 3% and 5%, respectively. The concentrations were selected based on antimicrobial efficacy, mechanical compatibility, and reported previously safety thresholds [12]. For both pigment and nanoparticle incorporation, a two-stage mixing process was employed. First, pigments or antimicrobial agents were weighed using a high-precision balance (±0.001 g) and manually blended with the base component of the silicone. This was followed by speed mixing under vacuum (Hauschild SpeedMixer, Dac150, Hamm, Germany) for 2 minto eliminate air bubbles and ensure homogeneous distribution of the additives. All weighing and mixing steps were carried out in a temperature-controlled laboratory setting (22 ± 1 °C). This process was repeated for each group to maintain reproducibility and eliminate operator bias.

Specimens were packed inside disc-shaped steel molds (10 mm diameter and 0.5 mm height). In this study, all mixing was performed by a single experienced operator, strictly adhering to the manufacturer’s protocols to ensure consistency. The materials were cured for 1 h at 100 °C and incubated at 37 °C. Color measurements were conducted using colorimeter (Minolta Chroma Meter CR-221, Osaka, Japan) according to the CIELAB coordinates with a D65 standard light source. They were performed at baseline and repeated after 1, 4, 6, and 10 weeks. Color difference (ΔE₀₀) was calculated following the equation below [17].

ΔE₀₀ = √((ΔL′/k_L * S_L)² + (ΔC′/k_C * S_C)² + (ΔH′/k_H * S_H)² + R_T * (ΔC′/k_C * S_C) * (ΔH′/k_H * S_H))

where ΔL′, ΔC′, and ΔH′ were the differences in lightness, chroma, and hue color parameters between R0, R1, and R2. The terms ΔL*, ΔC*, and ΔH* represented the differences in lightness, saturation, and hue, respectively, between colors being compared. The weighting factors S_L, S_C, and S_H were used to adjust the importance of these three color differences, considering the varying sensitivity of the human eye to different aspects of color. The parametric factors, constants k_L, k_C, and k_H, could have their values altered depending on the surface of the specimen. The effect on the hue and saturation angle in the blue region RT was also considered in the equation. Specimens were gently cleaned, rinsed in water, and ultrasonically cleaned for 5 min (Transonic T310, Camlab Ltd., Cambridge, UK) before each color measurement.

After fabrication and initial measurement, all specimens were stored individually in sealed, sterile polyethylene containers to prevent contamination and to minimize environmental variability. The containers were incubated at 37 °C. Each container was labeled to ensure accurate sample tracking across time intervals. No exposure to UV light, chemical disinfectants, or excessive handling was permitted during the storage period. This approach was taken to maintain standardization and reduce potential confounding variables influencing color stability.

To ensure accuracy and reproducibility in color measurements, the colorimeter was calibrated against a white standard background before each measurement session according to the manufacturer’s recommendations. The same operator conducted all color measurements to minimize inter-operator variability. For each specimen, three separate readings were taken at different surface points, and the average ΔE₀₀ value was recorded.

Significant differences in color difference between the test groups and time intervals were analyzed using 2-Way ANOVA (release 16, SPSS Inc., Chicago, IL, USA) (p < 0.05). Normality of data distribution was assessed using the Shapiro–Wilk test. All data were subjected to Levene’s test of homogeneity of variance (α = 0.05), following the assumption of equal variances. Equal variances were assumed (p > 0.05) and Tukey HSD post hoc test was used to analyze significant differences within test groups.

3. Results

The color difference values’ (ΔE₀₀) range was 0.74–2.83. Two-way ANOVA showed a significant intercept between silicone additives and time storage (

Table 1. Two-way ANOVA analysis of the ΔE₀₀ suggesting significant effect of silicone mixtures and time (p < 0.05).

Dependent Variable: SCORE
Source	Type III Sum	df	Mean Square	F	Sig.
Groups_2wayANOVA	95.302	8	11.913	16.632	0.000
Time storage_2Way_ANOVA	11.329	3	3.776	5.272	0.002
Groups_2wayANOVA AND time storage_2Way_ANOVA	44.807	24	1.867	2.607	0.000
Error	180.494	252	0.716
Total	862.824	288

), as well as a significant effect of silicone additives (

Table 2. Mean (SD) values color difference values (ΔE₀₀) between the different groups.

Group		ΔE00
No.	Description
1	Control (no colorants)	1.41 (0.72) a
2	Colored (pigments and flocking)	2.83 (1.22) b
3	Spectromatch	1.29 (1.56) a
4	ZnO1%	0.74 (0.34) a
5	ZnO3%	1.09 (0.58) a
6	ZnO5%	1.38 (0.64) a
7	CHX1%	1.65 (0.95) a
8	CHX3%	0.94 (0.93) a
9	CHX5%	1.18 (0.77) a

Different superscript letters indicate heterogeneous subsets (p < 0.05).

), and time storage (

Table 3. Mean (SD) values of color difference (ΔE₀₀) across all silicone groups over the 10-week storage period.

Time Storage Period	Mean (SD)
1 week	1.66 (1.39) a
4 weeks	1.12 (0.89) b
6 weeks	1.27 (1.02) b
10 weeks	1.39 (0.87) b

Different superscript letters indicate heterogeneous subsets (p < 0.05).

) (p < 0.05). Previously reported perceptible and acceptable color difference values of dark skin following ΔE₀₀ formula were 1.2 and 3.1, respectively [18].

Conventional silicone mixed with pigments and colorants (Group 3) exhibited the highest color change (ΔE₀₀ = 2.83), which was significantly different when compared to the remaining study groups (p < 0.05) (Table 2). It was perceptible (ΔE₀₀ > 1.2), yet acceptable (ΔE₀₀ < 3.1). Regardless, digital maxillofacial silicone elastomer and conventional silicone elastomer mixed with additives at different concentrations were color stable, as the color difference of some groups was perceptible but acceptable (ΔE₀₀ < 3.10) (Figure 1).

Color difference dropped after four weeks’ storage from 1.66 to 1.12 (p < 0.05) and it was stable to the end of the 10-week storage period (p > 0.05) (Table 3). Regardless, the difference was acceptable among the whole study period (ΔE₀₀ < 3.1). Quadratic regression between silicone groups and time storage (R²) showed fairly good-to-excellent fit (R² = 0.70–1.00), indicating stabilization of color change over time for all groups except for the colored group (R² = 0.02) (Figure 2).

4. Discussion

Discoloration of maxillofacial silicone elastomers is a visual manifestation of the material’s degradation over time, often influenced by external environmental exposure or internal chemical instability. In this study, we investigated the color stability of both conventional and digitally pigmented maxillofacial silicone elastomers mixed with nano-sized antimicrobial agents (ZnO-NP and CHX) at different concentrations over a 10-week period. The study rejected the null hypothesis, confirming that both the type of silicone mixture and time had a statistically significant effect on color stability (Table 1, Table 2 and Table 3). This is in harmony with other studies [3,15,16,19].

Historically, color difference was calculated based on the CIELAB system, after which, due to its inherent limitations, the International Commission on Illumination introduced the CIEDE2000 formula in 2001, denoted as ΔE₀₀. It was developed to provide a more accurate representation of perceived color differences, particularly in industrial and clinical settings. Compared to the traditional CIELAB formula, CIEDE2000 accounts for perceptual non-uniformities in lightness, chroma, and hue, thereby aligning more closely with human visual perception [17]. Numerous clinical and in vitro studies have since adopted ΔE₀₀, establishing perceptibility and acceptability thresholds for dental and maxillofacial materials [18].

The overall color change (ΔE₀₀) values across all groups ranged from 0.74 to 2.83, with significant interaction between additive type and time (p < 0.05, Table 1). The highest color difference was observed in Group 2, the conventional silicone mixed with pigments and flocking, which recorded a ΔE₀₀ value of 2.83. Although this change was perceptible (ΔE₀₀ > 1.2), it remained within the clinically acceptable threshold (ΔE₀₀ < 3.1) for dark skin tones as previously reported [18]. This high value is attributable to the presence of red pigments, which are known to degrade more rapidly under ambient light than yellow or sienna pigments [20,21].

In contrast, the digitally pigmented silicone group (Group 3) using the Spectromatch system exhibited a low mean color difference (ΔE₀₀ = 1.29), which, though perceptible, was also within clinically acceptable limits. This aligns with the reported advantages of digital pigmentation, including precision and repeatability, which help maintain color fidelity over time [8,11].

Interestingly, all groups that included ZnO-NP or CHX at varying concentrations (Groups 4–9) demonstrated superior color stability compared to the pigmented conventional group. The lowest color difference was recorded for Group 4 (ZnO1%), with a mean ΔE₀₀ of only 0.74, followed closely by CHX 3% (Group 8) at 0.94. These findings suggest that nano-sized antimicrobial particles, in addition to their primary microbial resistance function, may enhance color stability by reducing pigment degradation or stabilizing the silicone matrix, a conclusion in line with earlier systematic reviews [15,19].

Furthermore, the control group (Group 1), with no additives or pigments exhibited a ΔE₀₀ of 1.41, implying that even unpigmented silicone undergoes perceptible changes over time. This can be attributed to ongoing post-polymerization reactions and sub-product release, which not only affect dimensional stability but also alter chromatic properties. While the addition of nano-sized particles did not significantly influence this intrinsic polymerization, they did contribute to mitigating further color change.

Time had a clear effect on color stability. Color difference decreased significantly from 1 week (ΔE₀₀ = 1.66) to 4 weeks (ΔE₀₀ = 1.12), indicating an early phase of post-curing stabilization (p < 0.05). Beyond 4 weeks, color changes plateaued with no significant differences observed at 6 and 10 weeks, suggesting a stabilization in the chemical and physical behavior of the materials. The initial reduction in ΔE₀₀ values observed between weeks 1 and 4 across most groups may indicate ongoing post-polymerization and surface stabilization phenomena, particularly involving unreacted polymer chains and residual by-products. These processes could influence light reflectance and pigment alignment, resulting in perceptible changes in chromatic parameters. The early stabilization seen after week 4 suggests that the silicone matrix reaches a steady chemical state, which is less susceptible to further environmental alteration under controlled storage. This pattern was further supported by quadratic regression analyses, which showed high coefficients of determination (R² = 0.70–1.00) for all groups, except the colored conventional group (Group 2), which exhibited erratic color change over time (R² = 0.02) (Figure 2). The R² value of 1.00 for ZnO5% indicates an extremely predictable and stable color profile, reinforcing the role of ZnO as a beneficial additive for long-term prosthesis aesthetics. The enhanced color stability noted in groups containing ZnO and CHX may be attributed not only to their antimicrobial effects but also to their potential role as UV absorbers and stabilizers within the silicone matrix. ZnO, in particular, is known for its capacity to scatter ultraviolet and visible light, potentially shielding internal pigments from photo-degradation. Moreover, its high surface area (BET = 67 m²/g) facilitates effective integration into the silicone network, reducing porosity and oxidative degradation pathways. These findings support the dual-function hypothesis of nanoparticles, serving both mechanical and aesthetic preservation roles in maxillofacial prosthetics [12,15].

Previous research has identified acceptable ΔE₀₀ thresholds for dark and light skin tones to be 3.1 and 2.1, respectively [18]. All experimental groups in this study, including those with intrinsic pigmentation or antimicrobial agents, remained within these thresholds after 10 weeks. These results affirm the feasibility of incorporating up to 5% ZnO-NP or CHX into clinical formulations without compromising aesthetic outcomes.

The implications of these findings extend to the broader context of prosthesis maintenance and replacement cycles. Clinicians frequently encounter patient dissatisfaction related to discoloration, often necessitating premature replacement of otherwise intact prostheses. The demonstrated enhancement in color stability, particularly in groups incorporating ZnO and CHX, suggests that integrating such nano-additives may reduce the frequency of prosthesis remakes due to aesthetic degradation. This could lead to improved patient quality of life and reduced treatment costs. Moreover, this study supports the rationale for further exploration of nanotechnology in functionalizing maxillofacial silicones, not only for antimicrobial protection but also for maintaining long-term visual appearance.

Furthermore, the superior performance of the digitally pigmented silicone group highlights the growing importance of precision-based approaches in maxillofacial rehabilitation. Unlike traditional manual mixing, which is prone to variability and subjective color matching, digital systems standardize pigmentation protocols and reduce inter-operator differences. These benefits are particularly critical in cases requiring high aesthetic accuracy, such as orbital or nasal prostheses, where minor chromatic mismatches can have disproportionate psychological and social impacts on the patient. The difference in performance between digital and conventional pigmentation methods underlines the value of precise formulation protocols. Digital systems, such as Spectromatch, leverage colorimetric calibration and algorithmic pigment dosing, which reduce human error and inconsistencies in color matching. The relatively lower ΔE00 in digital samples (1.29) compared to conventionally pigmented samples (2.83) may also reflect better pigment dispersion and compatibility with the silicone matrix. These results validate the transition to digital pigmentation techniques, particularly in scenarios demanding high-fidelity color reproduction such as orbital or midfacial prostheses [8,11].

As the adoption of digital workflows becomes more widespread, integrating evidence-based material modifications, such as nanoparticle reinforcement, into these systems may define a new standard for aesthetic and functional prosthetic care. Clinicians often rely on visual assessment during prosthesis follow-up, making even perceptible color changes a matter of concern. The findings of this study highlight the need for material selection strategies that prioritize not only initial aesthetics but also long-term performance. The incorporation of 3% or 5% ZnO and CHX into silicone formulations emerges as a practical intervention that can be implemented without altering clinical workflows. As discoloration is a leading cause of prosthesis replacement, adopting these additives may extend prosthesis lifespan and reduce overall treatment burden for both patients and healthcare systems [1,2,4]. While pigment degradation is well-documented [21,22], this study highlights the stabilizing role of digital skin tone matching systems and nanoparticles. Although pigments can theoretically provide chromatic stabilization, their performance is heavily influenced by the type of silicone, curing method, and environmental exposure.

Comparing with other studies remains challenging due to differences in protocols, exposure conditions, and measurement standards [23,24,25,26]. However, the current investigation provides consistent internal controls, repeated measures, and strong statistical validation, offering robust evidence for material performance over time. Study limitations include a relatively short 10-week observation period and testing under controlled lab conditions, which may not fully replicate clinical settings. Despite these limitations, the study provides a valuable basis for future research, including long-term evaluations and incorporation of antimicrobials into digital elastomers used in maxillofacial prosthodontics.

5. Conclusions

This study confirmed that maxillofacial silicone elastomers mixed with nano-sized antimicrobial agents up to 5% by weight demonstrated acceptable color stability over a 10-week period. Digital pigmentation methods are similar to conventional ones in terms of chromatic fidelity. Future formulations of facial prostheses should consider incorporating ZnO or CHX, not only for their antimicrobial properties but also for their role in maintaining long-term aesthetic quality. Digital workflows, when feasible, should be prioritized due to their reproducibility and enhanced color retention. These findings can guide clinicians in selecting materials and workflows that balance microbial control with long-term color retention, especially in patients with high aesthetic demands. The integration of such strategies into digital prosthesis manufacturing may streamline production while enhancing patient satisfaction and prosthesis lifespan. Further research is needed to validate the results clinically.