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Article

The Effect of Different Beverages on the Color Stability of Nanocomposite 3D-Printed Denture Base Resins

1
College of Dentistry, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia
2
Department of Dental Education, College of Dentistry, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31411, Saudi Arabia
3
Department of Substitutive Dental Sciences, College of Dentistry, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia
*
Authors to whom correspondence should be addressed.
Prosthesis 2024, 6(5), 1002-1016; https://doi.org/10.3390/prosthesis6050073
Submission received: 16 July 2024 / Revised: 22 August 2024 / Accepted: 28 August 2024 / Published: 30 August 2024

Abstract

:
Background: Nanocomposite resins have been widely used in modern denture manufacturing. However, their long-term color stability is a concern for both dental professionals and patients. Purpose: to evaluate the effect of different beverages on the color stability of 3D-printed denture base resins modified with zirconium dioxide nanoparticles (ZrO2NPs). Methods: A total of 440 specimens were fabricated and distributed into 11 groups (n = 40/group). The control group of heat polymerized (PMMA) and five groups of two different 3D-printed resins (NextDent and ASIGA) as experimental groups with various concentrations of ZrO2NPs added to the 3D-printed resins (0.5 wt%, 1 wt%, 3 wt%, 5 wt%) in addition to one unmodified group per resin. Specimens per group are sorted into four subgroups (n = 10) according to tested beverages, as follows: coffee, tea, cola, and mineral water. Before immersion, all the specimens were exposed to 5000 thermal cycles. Color changes (ΔE00) were assessed prior (T0) and following immersion for 6 days (T1) and 12 days (T2) using a spectrophotometer. Color difference values were calculated by using CIEDE2000 color difference. Data was analyzed by ANOVA and post hoc Tukey test with a significant level of less than 0.05. Results: Tea produced the highest color change for both NextDent and ASIGA materials, whereas water caused the least color change on PMMA at T2. Increasing the immersion time resulted in more color changes, with tea and coffee showing significant differences. PMMA had considerably less color change than 3D-printed resins. The color change of 3D-printed increased after adding ZrO2NPs. Conclusions: Beverage type and immersion time have an impact on the color stability of unmodified and ZrO2NP-modified denture base resins with significant change after immersion in tea and coffee.

1. Introduction

Complete edentulism is considered to be one of the most common conditions that affects geriatric patients [1]. The most prevalent treatment for edentulous patients is the construction of a complete denture [2,3]. Accordingly, denture base materials are undergoing continuous improvements to achieve the best outcome satisfying the patients’ needs and expectations [4].
PMMA is commonly used in fabricating complete dentures [4]. It has great properties such as light translucency, biocompatibility, low cost, and ease of manipulation. Regardless, it has a variety of limitations, including high polymerization shrinkage, weak flexural strength, and inferior surface properties, resulting in denture stomatitis due to biofilm deposition and adherence of Candida albicans [4,5]. Also, they have poor color stability intraorally due to their porosity [6,7].
Advancements in the denture fabrication process have been developed technologically, leading to the production of digitally fabricated dentures using Computer-Aided Design/Computer-Aided Manufacturing (CAD/CAM) technology, overcoming some of the limitations of conventionally fabricated dentures [8]. One of the recent digital techniques is 3D printing technology. This technique builds the prosthesis in successive layers, eliminating the need for conventional molds [9,10]. Thus, the denture fabrication process became easier with significant improvement in denture accuracy and adaptation [9,10,11]. In addition, it saves a considerable amount of time, and the reproduced prostheses are highly accurate, hence making the CAD/CAM fabrication technique a promising method toward manufacturing dentures [11].
Multiple studies tested the effect of incorporating modified zirconium dioxide nanoparticles (ZrO2NPs) into PMMA of different sizes and concentrations [12,13,14,15,16,17]. Zirconium dioxide was found to increase the surface area of the material, thus improving its strength [6]. Denture base material needs to match the underlying tissue in its color and appearance as well as having adequate color stability to meet the patient’s expectations. Different factors could affect the color stability of denture base resins, which might be intrinsic or extrinsic factors [18,19,20]. The presence of residual monomers and porosity are considered intrinsic factors that have an influence on color stability, causing color change in the denture base material [20]. Extrinsic factors involve time-dependent processes such as eating habits.
According to the authors’ knowledge, the effects of coffee, tea, cola, and mineral water on the color stability of 3D-printed denture bases have not been studied before resins modified with ZrO2NPs. Therefore, the aim of this in vitro study was to investigate the effects of coffee, tea, cola, and mineral water on the color stability of 3D-printed denture resins modified with ZrO2NPs. The null hypothesis states that there is no significant difference in the color stability of 3D-printed denture base resins modified with ZrO2NPs after immersion in different beverages.

2. Materials and Methods

A total of 440 square specimens were divided into 11 main groups. Each main group consists of 40 specimens (n = 40). Two 3D-printed resin materials, “NextDent” and “ASIGA”, are divided into five groups, each according to the concentration of ZrO2NPs added, and one group for heat polymerized polymethyl methacrylate acrylic resin as a control group. One group of each 3D-printed resin (the unmodified group) remained without the addition of ZrO2NPs. The other four groups of NextDent and ASIGA each had ZrO2NPs added in different concentrations (0.5 wt%, 1 wt%, 3 wt%, and 5%wt). All these groups were divided into four subgroups for each immersion solution (coffee, tea, Coca-Cola, and mineral water) Figure 1. Power analysis was used to determine the study’s sample size. By calculating a research power of 80%, a 5% level of significance, and a margin of error of 5% was applied for the study using the calculations provided by the World Health Organization.

2.1. Preparation of Resin/Nanoparticle Mixture

The Silane-coupling agent is 3-(Tri-methoxysilyl) propyl methacrylate silane (TMSPM, Sigma Aldrich, St. Louis, MO, USA) was applied to ZrO2NPs as described in Rahman et al. study [21]. The silanized ZrO2NPs were weighed using an electronic scale, then loaded in various amounts as follows: 0.5 wt%, 1 wt%, 3 wt% and 5 wt% to the tested 3D-printing resins (“NextDent” and “ASIGA”). Liquid resins, including ZrO2NPs, were mixed for 30 min, as discussed in previous articles in Figure 2 [17].

2.2. Fabrication of Heat-Polymerized Acrylic Resin Specimens

Heat-polymerized poly methyl methacrylate (PMMA) specimens were manufactured using the conventional process of denture fabrication as a control group [4]. Wax patterns were fabricated using a square metal framework of (10 mm × 10 mm × 2 mm) dimensions. Then, wax was invested in a dental stone inside a flask to prepare for dewaxing. After packing, a heat polymerization apparatus was used to finalize polymerization, where the specimens were heated at 73 °C for 90 min, followed by heating at 100 °C for 30 min Figure 2 [4].

2.3. Fabrication of 3D-Printed Specimens

An open-source CAD system was used in designing 3D-printed specimens by saving the design as a standard tessellation language (STL) file and printing it using both NextDent and ASIGA 3D-printing machines (Dentsply Sirona, New York, NY, USA). Before adding the nanoparticles, the pure resin was put in a 3D mixer machine and blended for 120 min. The bottle was stirred for 30 min after the nanoparticles were added before starting the printing process. The printer was set to print each layer at 50 μm layer thickness and at a perpendicular orientation [22]. It was then subjected to 405 nm UV radiation. Following printing, each specimen was washed with 99.9% isopropyl alcohol. The post-curing process took 20 min for ASIGA specimens and 10 min for NextDent specimens, as per the manufacturer’s instructions Figure 2 [23].

2.4. Specimens Finishing and Polishing

The excess resin was removed by low-speed rotary instruments. Silicon carbide grinding papers (800, 1500, and 2000 grit) were used in finishing the specimens. Then, polishing was done using a 0.050 μm-suspension and a polishing cloth on a polishing machine under wet conditions by one operator to guarantee standardized pressure applied on all specimens during polishing [24].

2.5. Thermocycling Procedure

The thermocycling machine ran 5000 thermal cycles in total, simulating intraoral temperature variations over a half-year at a range of 5 to 55 °C with dwell times of 30 s and dripping times of 5 s [25].

2.6. Immersion Protocol

To reduce methodological variations, the same operator prepared four commonly consumed beverages for this study: coffee, tea, Coca-Cola, and mineral water Table 1. In different containers, each specimen was hung and submerged in the solution. Every jar was labeled with the sort of solution it contained and kept at room temperature, and fresh solutions were replaced daily. In order to replicate the use of the drink over a period of six months, each subgroup was first stored for six days, then subsequently for twelve days, which corresponded to 12 months of consumption (a 24 h storage period was used to simulate this period) [26].

2.7. Color Measurements

A color reflectance spectrophotometer equipped with computer software was used to measure the color of each specimen before exposure to beverage solutions. This data served as the baseline. The colorimeter was calibrated based on the manufacturer’s recommendations prior to the commencement of any measurement session. Samples were placed on a standard black background plate, and background lights were switched on for all measurements. The spectrophotometer’s viewport was used to position each specimen, and measurements of the L*, a*, and b* values of each sample were made. The L*, a*, and b* data mean values were computed after the measurement procedure was done three times [27]. After being submerged in the drinks, the samples underwent two evaluations. One assessment was finished after six days of immersion (T1) and another after twelve days (T2). On the day of the assessment, the samples were removed from the staining solution and allowed to dry. The second color evaluation (T1) was then carried out as previously indicated. The identical procedure was then used for the (T2) third color assessment. The materials’ color difference values (ΔE00) between baseline and different immersion durations were calculated using the CIEDE2000 color difference formula, as described in previous studies [28,29]. The study assessed the perceptibility and acceptability of CIEDE2000 values. According to Ren et al. [30], 1.72 CIEDE2000 units was the 50% perceptibility threshold, and 4.08 CIEDE2000 units was the 50% acceptability threshold for denture base acrylic resin materials. These were considered perceptibility and acceptability thresholds in the current study.

2.8. Statistical Analysis

Normality was checked by using the Shapiro-Wilk test, and insignificant results from the test provided that the data was normally distributed. Hence, parametric tests were used for inferential analysis. One-way ANOVA was used to study the relationship between a scale and a categorical variable having more than 2 categories, followed by Tukey’s post hoc test. Two-independent samples t-test was used to study the relationship between a scale and a categorical variable having two categories. p-values < 0.05 were set significantly.

3. Results

Table 2 demonstrates the color change in relation to time and type of solutions used in the study, while Figure 3 shows images of tested groups after immersion in different beverages. The effect of the tested beverages on the color stability of PMMA was similar at T1, while at T2, the water showed the least color change significantly (p = 0.02). The duration of immersion with all tested beverages at T1 and T2 did not reveal any significant difference in the color stability of PMMA.
For NextDent, tea and coffee resulted in the highest values of color change at T1 and T2 with all ZrO2NPs concentrations. The unmodified group with tea showed the highest color change in comparison to other beverages, at T1 and T2, without significant difference to T1 coffee. Increasing the immersion time resulted in a higher color change that was significant with tea and water, respectively (p = 0.003, 0.02). At 0.5% ZrO2NPs, coffee resulted in significantly higher color change than all other beverages at T1 and T2, with significant changes between the two immersion times (p = 0.004). Tea comes second after coffee with regards to color change, while Cola and water showed similar effects on color at both immersion times. At concentrations of 1% and 3% ZrO2NPs tea showed the highest color change at T1 and T2 than other beverages, followed by coffee without significant differences between them except at 1% T2. At 5% ZrO2NPs, the effects of tea and coffee were similar at both immersion times. The color change increased with increasing the immersion time, with all beverages showing significant differences at 3% and 5% ZrO2NPs, while the difference was not significant with water at 0.5% and 1% ZrO2NPs and coffee at 1% ZrO2NPs Table 2.
When coffee was used as an immersion solution, at the time “T1”, the lowest average was found in the control group, while the maximum average was at a 5% concentration level. The variation in the averages at time “T1” was statistically significant, and in pairwise comparison, the control group had a significantly different average compared to each concentration level. Similarly, at time “T2”, the lowest average was found in the control group, while the maximum average was at a 5% concentration level. The variation in the averages at time “T2” was statistically significant and in pairwise comparison, the control group had a significantly different average compared to each concentration level. In the case of using cola as an immersion solution, it was found that at time “T1”, the variation caused by concentration level was statistically significant. The minimum average was found at 3% concentration level, while the maximum was at 0%. On the other hand, at time “T2” there was no significant variation in averages found due to the change in the concentration level Table 3. In the case of using tea as an immersion solution, it was found that at time “T1” and “T2”, the variation caused by concentration level was statistically significant. At the time “T1”, a minimum average was found in the control group, while the maximum was at 0.5% concentration. At the time “T2”, the minimum average was found in the control group, while the maximum was at 1% concentration level Table 3. When water was used as an immersion solution, it was found that at time “T2”, the variation caused by concentration level was statistically significant. The minimum average was found in the control group while the maximum was at 0.5% concentration Table 3.
For ASIGA, tea resulted in the highest values of color change at T1 and T2 with all ZrO2NPs concentrations. At 0% ZrO2NPs, tea significantly showed the highest color change in comparison to other beverages at both T1 and T2. Increasing the immersion time resulted in a lower color change that was significant with cola and water, respectively (p = 0.016, 0.002). At 0.5% and 5% ZrO2NPs, the effects of tea and coffee were similar at both immersion times. At concentrations of 1% and 3% ZrO2NPs, tea significantly showed the highest color change at both immersion times than other beverages, followed by coffee, except at 1% ZrO2NPs T1, there was no significant difference between all beverages. The color change increased with increasing the immersion time, with all beverages showing significant differences at 3% ZrO2NPs with all beverages. The difference was not significant with cola at 0.5% and 1% ZrO2NPs and water at 0.5%, 1%and 5% ZrO2NPs (Table 2).
When coffee was used as an immersion solution, at the time “T1”, the lowest average was found in the control group, while the maximum average was at a 5% concentration level. The variation in the averages at “T1” was statistically significant. Similarly, at time “T2”, the lowest average was found in the control group, while the maximum average was at a 5% concentration level. The variation in the averages at time “T2” was statistically significant Table 3. In the case of using cola as an immersion solution, it was found that at time “T2”, the variation caused by concentration level was statistically significant. The minimum average was found at 0.5% concentration level while the maximum was at control and 5%. On the other hand, at “T1” there was no significant variation in averages found due to the change in the concentration level Table 3. In the case of using tea as an immersion solution, it was found that at times “T1” and “T2”, the variation caused by concentration level was statistically significant. At the time “T1”, the minimum average was found in the control group, while the maximum was at 3% concentration. At the time “T2”, the minimum average was found in the control group, while the maximum was at 3% concentration level Table 3. When water was used as an immersion solution, it was found that at time “T1”, the variation caused by concentration level was statistically significant. The minimum average was found at a 5% concentration level, while the maximum was at a 0% concentration level (Table 3).
The combined effect of factors “concentration, time, liquid” on the change in color was analyzed using a three-way ANOVA. It was found that the combined effect of “concentration and time”, “concentration and liquid”, and “time and liquid” were statistically significant Table 4.

4. Discussion

Denture base resin manufacturing can benefit from 3D printing technology, and NPs can be used as a reinforcing agent to create nanocomposites that have superior qualities to the original materials. It is necessary to strike a balance between mechanical qualities and aesthetics. Therefore, care must be made to prevent any negative effects on the aesthetics qualities when choosing a filler concentration that will enhance the mechanical properties.
This in vitro study examined the impact of various beverages on the color stability of 3D-printed denture base resins treated with ZrO2NPs. A significant difference in the value of the color stability of the tested 3D-printed denture base resins modified with ZrO2NPs after immersion in different beverages was reported. Thus, the null hypothesis of the current study was disapproved.
When the denture is in clinical use, it is subjected to an oral environment with thermal stresses. Therefore, the specimens were subjected to thermal cycling for 5000 cycles, simulating the changes that happened in the oral cavity in half a year of clinical use [25]. The color stability of denture base resins is an important factor that affects their esthetic appearance and patient satisfaction. In this study, the color stability of 3D-printed denture base resins modified with ZrO2NPs was evaluated after immersion in different beverages, including coffee, tea, cola, and distilled water. The beverages were selected based on the daily consumption frequency, and they have often been used in previous in-vitro studies [19,20]. The specimens were stored in beverage solutions for the entire study period to simulate prolonged exposure [19].
Color changes can be evaluated either through visual assessment or by using certain instrumentation. Colorimeters and spectrophotometers are commonly used to evaluate color changes in dental materials, as they eliminate subjective interpretations and enable the detection of minor color alterations [31]. The Commission Internationale de l’Eclairage (CIE) L*, a*, b* is a constant color scale that comprises all the colors visible to the human eye. Therefore, it is a suitable instrument for evaluating color changes in dental materials [32]. The perceptibility and acceptability of the CIEDE2000 values were assessed in this research. According to this study, the PMMA group’s color changes were negligible in all tested beverages and remained below the acceptability and perceptibility thresholds. The ASIGA and Nextdent groups displayed more noticeable, substantial color changes in coffee and tea, over the perceptibility threshold but still below the acceptable limits, with the exclusion of Nextdent 1% ZrO2NPs group in tea.
Our findings highlighted that tea showed the highest color change, followed by coffee, cola, and water, respectively. This could be attributed to the presence of Tannic acid in both tea and coffee, which is known to be highly chromogenic [33]. The discoloration caused by these beverages is the result of brown pigmentation being triggered by the water-soluble tannic acid [34,35]. The highest color change seen in tea was in agreement with many previous studies [33,36,37,38,39]. On the other hand, other studies found that coffee showed higher staining values than tea [36,40,41]. This difference might be due to the difference in methodology design, the immersion period or lack of addition of ZrO2NPs to the tested specimens.
The results of the current study showed color change in specimens immersed in cola but less than in tea and coffee. When exposed to cola, denture-based acrylic resin materials may experience color changes due to low PH values [19,40,42,43]. In addition to low PH, caramel additives and colorant substances, can also lead to staining [40,43]. These findings agree with Keyf et al. [42] and Aldulaijan [39] results. The reduced staining effect of cola in comparison to tea and coffee, which are also considered acidic, may be due to the absence of yellow colorant in cola and the inclusion of carbonated water, which acts as a buffering agent to reduce the acidity [39,44,45]. Lastly, mineral water showed the least color change, likely due to its neutral pH and lack of colorant substances [18,19,46]. This aligns with previous research indicating that water absorption and solubility behavior are influenced by the hydrophilicity of the resin matrix. This is why specimens immersed in water had less color change [19,47]. This finding was in agreement with Keyf et al. [42].
The characteristics of denture base resins affect how they stain, with liquid sorption most likely being the primary process. Research has demonstrated a connection between denture base material hygroscopic expansion, water sorption, and discoloration [40,48]. Water-absorbing resins are also likely to absorb other liquids that include staining agents [40,48]. The resin’s polymer matrix expands as a result of water absorption, leaving gaps that staining materials may penetrate and, therefore, discolor the material [40,48]. Without expanding, water sorption might take place if the resin is porous [40,48].
In this study, compared to heat-polymerized PMMA, both groups using 3D-printed resins showed greater color change. The layer-by-layer printing technique, in which photopolymerization happens with each printed layer, is responsible for the increased color differences in 3D-printed resins [49]. These layers may trap air, creating gaps that increase the water sorption capacity of 3D-printed resins. In terms of monomer conversion rate, the polymerization process also explains the color change [50]. Unreacted monomers from inadequate polymerization of 3D-printed resins can seep out of the material, causing water diffusion and staining susceptibility [51]. The findings of the studies by Shim et al., Gruber et al., and Falahchai et al. align with each other, indicating agreement with the study results [52,53,54]. Conversely, the study conducted by Alfouzan et al. presents conflicting results in which the conventional denture base materials exhibited less color stability when compared to the 3D-printed group [55].
When ZrO2NPs are introduced to 3D-printed resins, our research shows a significantly greater increase in color change when compared to the unmodified group. This increased color change is most likely caused by the optical characteristics of ZrO2NPs and their distribution in the resin matrix. Zirconia particles may induce further color changes because of their porous structure, which facilitates stain penetration [56,57]. Furthermore, zirconia particles could be abrasive, which would enhance surface roughness and increase the material’s susceptibility to discoloration [58,59,60]. This result was in line with the findings of Ren et al., Kanat-Ertürk, Ellakany P et al., and Gad et al. findings [56,57,61,62]. These findings, however, are not consistent with those published by Azmy et al., who found that the heat-polymerized acrylic resin treated with various kinds of nanoparticles displayed less color changes than the unmodified group [19].
In this study, prolonging the exposure of specimens to the beverages resulted in increased staining readings of the acrylic resin denture base material. This finding is consistent with other studies [35,63,64,65]. Additionally, Zuo et al. [66] found that heat-polymerized resin denture base materials showed different degrees of staining or discoloration when immersed in coffee, cola, tea, and red wine, with the discoloration being time-dependent and escalating with longer immersion periods.
The limitation of this study is that it is an in vitro study and utilizes a single printing orientation and a single kind of nanoparticle. In addition, there was no dynamic stress. The specimens did not replicate the arrangement of a denture, and thermal cycling only simulated six months of intraoral use. Therefore, this paper recommends experimenting with various denture configurations, varied nanoparticles with various concentrations, and printing orientations, as well as subjecting the materials to mechanical and thermal stressors comparable to those seen in the intraoral environment.
Understanding how different beverages affect the properties of 3D-printed denture base resins can help clinicians make informed decisions about patient care and improve the longevity and esthetics of dental prostheses. Further studies are needed to evaluate the long-term clinical performance of these materials under oral conditions.

5. Conclusions

The color stability of the 3D-printed denture base resins was significantly affected by immersion in all tested beverages and by prolonging the immersion duration. Tea and coffee exhibited the highest color change with both materials. 3D printed resins exhibit higher color change compared with heat-polymerized resin. Adding ZrO2NPs to 3D printed resins increased the color change of the 3D printed resins following beverage immersion.

Author Contributions

Conceptualization, A.K. and M.M.G.; methodology, A.K., S.H.A. and J.A.A.; software, A.M.A. (Ali M. Alsalem), A.M.A. (Ahmed M. Alessa) and M.M.G.; validation, A.K., S.M.F. and M.M.G.; formal analysis, A.M.A. (Ali M. Alsalem) and S.Q.K.; investigation, J.A.A. and M.M.G.; resources, S.H.A., A.K., A.M.A.(Ahmed M. Alessa) and S.M.F.; data curation, J.A.A., A.K. and S.Q.K.; writing—original draft preparation, S.H.A., A.K., J.A.A. and A.M.A. (Ali M. Alsalem).; writing—review and editing, A.K., P.E., M.M.G. and S.M.F.; visualization, A.M.A. (Ali M. Alsalem) and J.A.A.; supervision, P.E., M.M.G. and S.M.F.; project administration, M.M.G., S.M.F., A.K. and S.H.A.; funding acquisition, M.M.G. and A.M.A. (Ahmed M. Alessa). All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding authors.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Flowchart of specimen distribution.
Figure 1. Flowchart of specimen distribution.
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Figure 2. Study design and flowchart.
Figure 2. Study design and flowchart.
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Figure 3. Representative photographs of tested groups after immersion in different beverages.
Figure 3. Representative photographs of tested groups after immersion in different beverages.
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Table 1. Beverage preparation protocol.
Table 1. Beverage preparation protocol.
Beverage Brand NamePreparationImmersion
Time
Temperature
CoffeeNescafe Classic (nestle Co., Araras, Brazil)2 g of coffee was dissolved in 200 mL of distilled boiling water for 2 min then filtered to remove the dustThe solutions were renewed daily.
Each solution was prepared to replace the previously used solution.
Each subgroup was stored for 6 days.
then stored for 6 additional days, 12 days totally
37 °C
TeaLipton Yellow
Label Lipton Co.,
Dubai, United Arab Emirates)
2 g of tea was dissolved in 200 mL of distilled boiling water for 2 min then filtered to remove the dust
ColaCoca-Cola (Coca-Cola Co., Ritadh, Saudi Arabia)Ready-made
Carbonated water, high fructose corn syrup, caramel color, phosphoric acid, natural flavors, caffeine.
WaterBerain (Berain Co., Riyadh, Saudi Arabia)Ready-made.
Average Composition (Milgram/Liter)
Cations: calcium 22 ppm, magnesium 3 ppm, sodium 17 ppm, potassium 5 ppm, iron 0.01 ppm.
Anions: bicarbonates 50 ppm, carbonates < 1 ppm, sulfates 9 ppm, chlorides 35 ppm, fluorides 1 ppm, nitrates 0.1 ppm
Table 2. Mean, SD, and significance of color changes (ΔE00) at a given ZrO2NP concentration in relation to the time of immersion and type of solution.
Table 2. Mean, SD, and significance of color changes (ΔE00) at a given ZrO2NP concentration in relation to the time of immersion and type of solution.
MaterialZrO2NPs %TimeCoffee
Mean (SD)
Cola
Mean (SD)
Tea
Mean (SD)
Water
Mean (SD)
p-Value
PMMA T10.67 (0.3)0.77 (0.4)0.79 (0.3)0.55 (0.3)0.429
T20.71 (0.3) A,B,C0.77 (0.3) A,D0.75 (0.2) B,D0.36 (0.3) C0.02 *
p-value0.8031.000.760.199
NextDent0%T11.73 (0.38) A0.88 (0.51) B1.94 (0.54) A0.44 (0.32) B0.000 *
T22.22 (0.74)1.33 (0.5) A2.99 (0.7)0.87 (0.38) A0.000 *
p-value0.0980.0780.003 *0.02 *
0.5%T12.67 (0.37)0.62 (0.27) A1.38 (0.46) B1.03 (0.86) A, B0.000 *
T23.45 (0.59)1.4 (0.22) A2.24 (0.44)1.18 (0.36) A0.000 *
p-value0.004 *0.000 *0.001 *0.624
1%T12.11 (0.85)0.46 (0.19) A2.93 (0.68)0.73 (0.38) A0.000 *
T23.17 (1.85) A1.17 (0.28) B4.11 (0.82) A0.42 (0.28) B0.000 *
p-value0.1350.000 *0.004 *0.068
3%T11.6 (0.21)0.26 (0.12) A2.92 (0.81)0.48 (0.33) A0.000 *
T22.91 (0.69)1.26 (0.24) A4.01 (0.9)0.96 (0.38) A0.000 *
p-value0.000 *0.000 *0.011 *0.014 *
5%T12.68 (0.94) A0.52 (0.4) B2.55 (0.53) A0.37 (0.15) B0.000 *
T23.91 (1.27) A1.5 (1.03) B3.66 (0.51) A0.91 (0.39) B0.000 *
p-value0.034 *0.017 *0.000 *0.001 *
ASIGA 0%T11.15 (0.16) A0.82 (0.26) B1.51 (0.31)0.96 (0.22) A, B0.000 *
T21.2 (0.41)0.53 (0.18) A1.64 (0.42)0.61 (0.17) A0.000 *
p-value0.7390.016 *0.4550.002 *
0.5%T11.32 (0.29) A0.60 (0.41) B1.47 (0.43) A0.64 (0.40) B0.000 *
T22.27 (0.63) A0.36 (0.18) B2.5 (0.96) A0.69 (0.16) B0.000 *
p-value0.001 *0.1240.01 *0.713
1%T10.98 (0.22)1.18 (1.64)1.81 (0.41)0.83 (0.68)0.141
T21.94 (0.55)0.61 (0.2) A3.04 (0.49)0.52 (0.37) A0.000 *
p-value0.000 *0.3110.000 *0.254
3%T10.96 (0.3)0.34 (0.14) A1.88 (0.64)0.35 (0.08) A0.000 *
T22.13 (0.48)0.73 (0.15) A3.83 (0.87)1.17 (0.36) A0.000 *
p-value0.000 *0.000 *0.000 *0.000 *
5%T11.39 (0.41) A0.39 (0.09) B1.68 (0.48) A0.25 (0.11) B0.000 *
T22.66 (0.41) A,B0.77 (0.36) C3.26 (0.94) A1.36 (2.25) B,C0.000 *
p-value0.000 *0.008 *0.000 *0.159
* Statistically significant at 0.05 level of significance. Same Capital alphabets in each row showed statistical insignificance difference.
Table 3. Mean, SD, and significance of color changes (ΔE00) of specimens immersed in different solutions at a given time and concentration.
Table 3. Mean, SD, and significance of color changes (ΔE00) of specimens immersed in different solutions at a given time and concentration.
ImmersionMaterialT1T2Material T1T2
CoffeePMMA0.67 (0.3)0.71 (0.3)PMMA0.67 (0.3) A,B0.71 (0.3) A
ND 01.73 (0.38) A,B2.22 (0.74) A,B,CASIGA 01.15 (0.16) C,D,E,F1.2 (0.41) A
ND 0.52.67 (0.37) C,D3.45 (0.59) A,D,E,FASIGA 0.51.32 (0.29) C,G,H,I2.27 (0.63) B,C,D
ND 12.11 (0.85) A,C,E,F3.17 (1.85) B,D,G,HASIGA 10.98 (0.22) A,D,G,J1.94 (0.55) B,E
ND 31.6 (0.21) B,E2.91 (0.69) C,E,G,IASIGA 30.96 (0.3) B,E,H,J2.13 (0.48) C,E,F
ND 52.68 (0.94) D,F3.91 (1.27) F,H,IASIGA 51.39 (0.41) F,I2.66 (0.41) D,F
p-value0.000 *0.000 *p-value0.000 *0.000
ColaPMMA0.77 (0.4) A,B,C,D0.77 (0.3) PMMA0.77 (0.4) 0.77 (0.3) A,B,C,D
ND 00.88 (0.51) A,E,F,G1.33 (0.5) ASIGA 00.82 (0.26) 0.53 (0.18) A,E,F,G,H
ND 0.50.62 (0.27) B,E,H,I,J1.4 (0.22) ASIGA 0.50.60 (0.41) 0.36 (0.18) E.I
ND 10.46 (0.19) C,F,H,K,L1.17 (0.28) ASIGA 11.18 (1.64) 0.61 (0.2) B,F,I,L,K
ND 30.26 (0.12) I,K,M1.26 (0.24) ASIGA 30.34 (0.14) 0.73 (0.15) C,G,J,L
ND 50.52 (0.4) D,G.J,L,M1.5 (1.03) ASIGA 50.39 (0.09) 0.77 (0.36) D,H,K,L
p-value0.007 *0.064p-value0.1630.004 *
TeaPmma0.79 (0.3) A0.75 (0.2) Pmma0.79 (0.3) 0.75 (0.2) A
ND 01.94 (0.54) B,C2.99 (0.7) A,BASIGA 01.51 (0.31) A,B,C,D1.64 (0.42) A,B
ND 0.51.38 (0.46) A,B2.24 (0.44) AASIGA 0.51.47 (0.43) A,E,F,G2.5 (0.96) B,C,D
ND 12.93 (0.68) D,E4.11 (0.82) C,DASIGA 11.81 (0.41) B,E,H,I3.04 (0.49) C,E,F
ND 32.92 (0.81) D,F4.01 (0.9) C,EASIGA 31.88 (0.64) C,F,H,J3.83 (0.87) E,G
ND 52.55 (0.53) C,E,F3.66 (0.51) B,D,EASIGA 51.68 (0.48) D,G,I,J3.26 (0.94) D,F,G
p-value0.000 *0.000 *p-value0.000 *0.000 *
WaterPmma0.55 (0.3) A,B,C,D,E0.36 (0.3) APmma0.55 (0.3) A,B,C,D,E0.36 (0.3)
ND 00.44 (0.32) A,F,G,H,I0.87 (0.38) B,C,D,EASIGA 00.96 (0.22) A,F,G0.61 (0.17)
ND 0.51.03 (0.86) B,F,J,K1.18 (0.36) B,F,GASIGA 0.50.64 (0.40) B,F,H,I,J0.69 (0.16)
ND 10.73 (0.38) C,G,J,L,M0.42 (0.28) A,C,HASIGA 10.83 (0.68) C,G,H,K0.52 (0.37)
ND 30.48 (0.33) D,H,K,L,N0.96 (0.38) D,F,IASIGA 30.35 (0.08) D,I,K,L1.17 (0.36)
ND 50.37 (0.15) E,I,M,N0.91 (0.39) E,G,H.IASIGA 50.25 (0.11) E,J,L1.36 (2.25)
p-value0.0350.000 *p-value0.001 *0.206
* Statistically significant at 0.05 level of significance. Same Capital alphabets in each column showed statistical insignificance difference.
Table 4. Three-way ANOVA results of NextDent and ASIGA resins.
Table 4. Three-way ANOVA results of NextDent and ASIGA resins.
Properties Type III Sum of SquaresdfMean SquareFSig.
NextDentColor changes
E00)
Intercept1125.04211125.0423113.1900.000 *
concentration × time12.55752.5116.9490.000 *
concentration × liquid105.797157.05319.5170.000 *
time × liquid8.16832.7237.5340.000 *
concentration × time × liquid3.956150.2640.7300.754
Error138.7703840.361
Total1813.010432
Corrected Total687.968431
ASIGA Color changes (ΔE00)Intercept625.6131625.6131883.4850.000 *
concentration × time24.84554.96914.9600.000 *
concentration × liquid41.981152.7998.4260.000 *
time × liquid18.60336.20118.6690.000 *
concentration × time × liquid8.238150.5491.6530.058
Error127.5483840.332
Total1041.190432
Corrected Total415.577431
* Statistically significant at 0.05 level of significance.
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Almansour, S.H.; Alkhawaja, J.A.; Khattar, A.; Alsalem, A.M.; Alessa, A.M.; Khan, S.Q.; Ellakany, P.; Gad, M.M.; Fouda, S.M. The Effect of Different Beverages on the Color Stability of Nanocomposite 3D-Printed Denture Base Resins. Prosthesis 2024, 6, 1002-1016. https://doi.org/10.3390/prosthesis6050073

AMA Style

Almansour SH, Alkhawaja JA, Khattar A, Alsalem AM, Alessa AM, Khan SQ, Ellakany P, Gad MM, Fouda SM. The Effect of Different Beverages on the Color Stability of Nanocomposite 3D-Printed Denture Base Resins. Prosthesis. 2024; 6(5):1002-1016. https://doi.org/10.3390/prosthesis6050073

Chicago/Turabian Style

Almansour, Sara H., Juhana A. Alkhawaja, Abdulrahman Khattar, Ali M. Alsalem, Ahmed M. Alessa, Soban Q. Khan, Passent Ellakany, Mohammed M. Gad, and Shaimaa M. Fouda. 2024. "The Effect of Different Beverages on the Color Stability of Nanocomposite 3D-Printed Denture Base Resins" Prosthesis 6, no. 5: 1002-1016. https://doi.org/10.3390/prosthesis6050073

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