Effect of staining beverages on color stability and surface roughness of additively manufactured permanent resin materials

Abstract

Objective

To evaluate the effects of commonly consumed staining beverages on the color stability and surface roughness of two additively manufactured permanent resin restorative materials.

Materials and methods

Sixty disk-shaped specimens (10 mm × 2 mm) were fabricated from two additively manufactured resin materials (Saremco Print Crowntec and VarseoSmile Crown Plus). Specimens were finished with standardized polishing procedures and color values (CIE L*a*b*) and baseline surface roughness (Ra) were recorded. Samples were randomly assigned to three immersion media (tea, coffee, distilled water; n = 10 per subgroup) and stored at 37 °C for 14 days with daily solution renewal. Color measurements were repeated after 24 h and 14 days, and color differences were calculated using the CIEDE2000 formula (ΔE₀₀). Surface roughness was re-measured after 14 days. Data were analyzed using mixed-model ANOVA and correlation tests (α = 0.05).

Results

Staining solution significantly affected color change at both evaluation periods (p < 0.001), while material type had no significant influence (p > 0.05). Tea produced the highest discoloration values, followed by coffee, whereas water groups remained below acceptability thresholds. Color change increased significantly over time in tea and coffee groups. Surface roughness showed only minimal changes after immersion, with Ra values ranging from 0.438 to 0.559 μm at baseline and 0.444–0.567 μm after 14 days, with no significant effects of material or staining solution (p > 0.05). No significant correlation was found between baseline surface roughness and final color change (p > 0.05). A significant positive correlation was observed between the change in surface roughness (ΔRa) and color change (ΔE00) (p < 0.05).

Conclusions

Discoloration of additively manufactured permanent resin materials was primarily influenced by exposure to staining beverages. Tea and coffee caused clinically noticeable color changes, while surface roughness showed limited changes during short-term aging. However, a significant positive correlation between surface roughness change and color change suggests that surface degradation may contribute to staining susceptibility.

Introduction

Recent advances in digital dentistry have expanded the use of additive manufacturing technologies for the fabrication of definitive restorative materials. Additively manufactured permanent resin materials were developed to provide chairside and laboratory solutions with reduced cost, simplified workflows, and high manufacturing precision compared with conventional subtractive CAD–CAM approaches [1–3]. These materials are typically based on highly cross-linked polymer matrices reinforced with micro- or nano-scale fillers, enabling fabrication of crowns, inlays, onlays, and implant-supported restorations [4]. Early laboratory studies have reported favorable mechanical properties, biocompatibility, and marginal adaptation for additively manufactured permanent resins, suggesting that they may represent a viable alternative to traditional indirect composites [5–7]. However, their long-term esthetic performance remains a critical parameter for clinical acceptance, particularly in anterior and visible posterior regions.

Color stability is considered an essential property of tooth-colored restorative materials because discoloration may compromise esthetics and lead to patient dissatisfaction or restoration replacement [8]. Extrinsic staining may result from the adsorption or absorption of colorants originating from beverages, foods, smoking, or mouthrinses, whereas intrinsic discoloration may be associated with matrix degradation or oxidation processes [9, 10]. For resin-based materials, staining susceptibility is influenced by multiple factors, including resin matrix composition, filler content, degree of conversion, water sorption, and surface characteristics [11, 12]. Compared with subtractively manufactured CAD–CAM materials, additively manufactured resins may exhibit different optical stability due to their layer-by-layer fabrication. Interlayer interfaces, residual monomers, and variations in degree of conversion may increase water sorption and pigment diffusion, thereby enhancing discoloration susceptibility [13]. Although the color stability of direct resin composites and CAD–CAM hybrid materials has been widely investigated [14, 15], evidence regarding additively manufactured permanent resin restorative materials remains limited.

Surface roughness is a critical property that plays a key role in the optical performance and stain resistance of resin restoratives. Increased surface roughness promotes plaque accumulation and facilitates the adsorption of staining chromogens, potentially accelerating discoloration over time [16–18].

In additively manufactured materials, the layer-by-layer fabrication process, post-curing protocols, and surface finishing procedures may collectively influence surface roughness [19]. Although several recent studies have reported baseline surface roughness or color stability values for additively manufactured resin materials [20, 21], most investigations have focused on single surface parameters and evaluated them at a single time point. Moreover, limited information is available regarding the combined evaluation of surface roughness and color stability under clinically relevant staining conditions. Consequently, data simultaneously addressing time-dependent changes in surface roughness and color stability of additively manufactured permanent resin restorative materials following exposure to commonly consumed staining beverages remain scarce.

Therefore, the aims of this in vitro study were to (1) compare the color stability of two additively manufactured permanent resin restorative materials following immersion in staining solutions, (2) evaluate baseline and time-dependent changes in surface roughness, and (3) investigate the relationship between surface roughness changes and color stability. The null hypotheses were that material type and staining conditions would not influence color stability or surface roughness, that these surface properties would not change over time, and that no correlation would exist between surface roughness changes and color stability.

Materials and methods

Study design

This controlled in-vitro study evaluated the color stability and surface roughness (Ra, arithmetic mean roughness) of two additively manufactured permanent resin restorative materials following immersion in staining solutions. The experimental design included two factors: material (two levels) and staining solution (three levels). Color measurements were performed at baseline (T0), after 24 h (T1), and after 14 days (T2), while surface roughness was assessed at baseline (T0) and after 14 days of immersion (T2) to evaluate time-dependent changes in surface characteristics.

Prior to the study, a power analysis was performed using G*Power software (version 3.1.9.7; Heinrich Heine University, Düsseldorf, Germany) to determine the minimum required sample size. Based on previous study evaluating color change of resin-based materials following immersion in staining solutions, a medium-to-large effect size (f = 0.40) was assumed [15]. With an alpha level of 0.05 and a statistical power of 80%, the minimum required sample size was calculated as 8 specimens per subgroup. To compensate for potential specimen loss or measurement variability, 10 specimens per group were included in the present study.

Specimen fabrication

Two additively manufactured permanent resin restorative materials were tested:

• SPC: Saremco Print Crowntec (Saremco Dental AG, Rebstein, Switzerland)

• VCP: VarseoSmile Crown Plus (BEGO, Bremen, Germany)

The composition, manufacturer information, and lot numbers of the tested materials are presented in Table 1. The two additively manufactured permanent resin materials were selected based on their widespread clinical use and differences in resin matrix composition. The tested materials differ in their manufacturer-reported resin matrix composition, including methacrylate-based and UDMA-based resin systems, which may influence water sorption and discoloration behavior. These compositional differences enabled comparison of materials with distinct resin chemistries under identical experimental conditions.

Table 1.

Composition and manufacturer information of the additively manufactured resins used in the study

Material Name	Manufacturer	Country	Composition	Lot Number
Saremco Print Crowntec	Saremco Dental AG	Switzerland	Methacrylate-based resin matrix with inorganic fillers, photoinitiators, and pigments	F298
VarseoSmile Crown Plus	Bego GmbH	Germany	UDMA-based dimethacrylate resin with ceramic fillers, photoinitiators, and pigments	602,021

For each material, thirty disk-shaped specimens (10 mm diameter × 2 mm thickness) were designed using the manufacturer’s proprietary CAD software and fabricated using a third-party DLP 3D printer (Trox, Tolard, Türkiye). Printing parameters were applied according to the resin manufacturers’ recommended settings compatible with the printer. The layer thickness was set at 100 μm, and specimens were printed in a horizontal orientation (0°). After printing, all specimens were cleaned in ≥ 96% isopropyl alcohol using an ultrasonic bath for three minutes to remove residual uncured resin. Subsequently, specimens were post-cured in an Otoflash light-curing unit (NK-Optik GmbH, Baierbrunn, Germany) for 2 × 2000 flashes, corresponding to approximately 10 min of post-curing, with a light intensity of approximately 10 mW/cm², following the manufacturer’s recommended protocols.

All specimens were visually inspected under magnification to confirm the absence of surface defects or printing irregularities.

Surface finishing

To standardize surface topography, the upper surfaces of all specimens were finished under continuous water irrigation using silicon carbide abrasive papers in the following sequence: 600-, 800-, and 1200-grit. Each abrasive step was applied for 30 s under consistent manual pressure. The same operator performed all procedures using standardized movements and polishing duration to minimize variability. The polishing protocol was applied to standardize surface topography and minimize variability between specimens rather than to simulate clinical polishing procedures. The opposite surface was left unpolished and was not used for subsequent measurements.

Following surface finishing, specimens were ultrasonically cleaned in distilled water for 10 min to remove abrasive residues and then stored in distilled water at 37 °C for 24 h to allow completion of post-curing water uptake prior to baseline measurements. Surface roughness and color measurements were performed by a single calibrated operator blinded to group allocation to reduce measurement bias.

Baseline color measurement

Color measurements were performed using a spectrophotometer (VITA Easyshade V, VITA Zahnfabrik, Bad Säckingen, Germany) operating in the CIE L*a*b* color space under standardized D65 illumination and 10° observer conditions [22]. To minimize background interference, measurements were conducted over a standardized white calibration tile.

Each specimen was positioned in a custom-fabricated silicone mold to ensure reproducible alignment during measurements. Three consecutive readings were obtained for each specimen, and the mean L*, a*, and b* values were recorded as baseline color values (T0).

Surface roughness measurement (Ra)

Surface roughness measurements were performed using a contact profilometer (Perthometer M2, Mahr GmbH, Göttingen, Germany). The stylus tip radius and applied load complied with ISO 21920-2:2021 recommendations [23]. For each specimen, three linear measurements were conducted across the center of the polished surface under a constant load, using a cutoff length of 0.8 mm and a traverse speed of 0.5 mm/s. The evaluation length was set at 4.0 mm, and measurements were performed in accordance with ISO 21920-2:2021 guidelines. Three consecutive measurements were performed for each specimen, and the arithmetic mean was recorded as the Ra value.

Baseline surface roughness measurements were obtained prior to immersion in staining solutions (T0). Surface roughness measurements were repeated after 14 days of immersion (T2) using the same profilometric parameters and measurement locations identified by reference markings and standardized specimen positioning to assess time-dependent changes in surface topography.

Staining procedure

Specimens from each material were randomly allocated to one of three staining media (n = 10 per material per solution) using a computer-generated randomization procedure to ensure unbiased group allocation:

• Black tea: 2 g of tea leaves infused in 100 mL of boiling distilled water for 10 min and subsequently filtered

• Coffee: 2 g of instant coffee dissolved in 100 mL of hot distilled water

• Control: Distilled water

Each specimen was individually stored in a sealed glass container containing 20 mL of the assigned solution and incubated at 37 °C. To prevent fluctuations in pH and staining concentration, all solutions were renewed daily throughout the immersion period. The staining solutions and immersion protocols were prepared according to previously published studies evaluating discoloration of resin-based materials [10, 15]. The immersion period was set at 14 days to simulate extended clinical exposure to staining beverages, as previously reported in color stability studies of resin-based restorative materials [10, 15].

Color measurements were repeated after 24 h (T1) and 14 days (T2). Prior to each color measurement, specimens were rinsed with distilled water and gently dried with absorbent paper. Surface roughness measurements at T2 were performed following completion of the staining protocol and prior to final color measurements.

Color difference calculation

Color differences relative to baseline were calculated using the CIEDE2000 (ΔE₀₀) formula between T0 and each subsequent time point (T1 and T2) [24].

Here, ΔL′, ΔC′, and ΔH′ represent the differences in lightness, chroma, and hue, respectively. The weighting functions S_L, S_C, and S_H adjust the contribution of each color component to the overall calculation. The parametric correction factors k_L, k_C, and k_H were set to 1 in the present study. The term Rₜ denotes a rotation function that accounts for the interaction between chroma and hue differences in the blue region of the color space [25].

The resulting color differences were evaluated according to the 50:50 perceptibility threshold (PT = 0.8) and acceptability threshold (AT = 1.8) established for tooth-colored restorative materials (ΔE₀₀ values) [8].

Statistical analysis

All statistical analyses were performed using IBM SPSS Statistics v29 (IBM Corp., Armonk, NY, USA). Data normality was assessed using the Shapiro–Wilk test. Homogeneity of variances was evaluated using Levene’s test. For repeated-measures analyses, the assumption of sphericity was assessed using Mauchly’s test, and when violated, the Greenhouse–Geisser correction was applied. Baseline surface roughness (Ra) values were compared using a two-way ANOVA considering material type and staining solution. Changes in surface roughness over time (T0 vs. T2) were analyzed using a mixed-model ANOVA with time as the within-subject factor and material type and staining solution as between-subject factors. In this model, time was treated as a repeated-measures factor to evaluate time-dependent changes within specimens.

Color difference (ΔE₀₀) values were analyzed using a mixed-model ANOVA with time (T1 and T2) as the within-subject factor and material type and staining solution as between-subject factors. Time was considered a repeated-measures factor, while material type and staining solution were included as fixed between-subject factors. Post-hoc comparisons were performed with Bonferroni adjustment.

The relationships between baseline Ra, changes in Ra (ΔRa), and ΔE₀₀ values at the final evaluation period were assessed using Pearson or Spearman correlation analyses, as appropriate. The level of statistical significance was set at α = 0.05.

Results

Color change (ΔE₀₀)

Mean color change values for all groups are presented in Table 2. The distribution of ΔE₀₀ values over time and their relationship with clinical perceptibility and acceptability thresholds are illustrated in Fig. 1. At the early evaluation period (T0–T1), specimens immersed in tea exhibited the greatest discoloration, followed by coffee, while the water groups showed minimal color change. This trend was consistent for both materials.

Table 2.

Mean ΔE₀₀ values (Mean ± SD)

Material	Solution	ΔE00 (T0–T1)	ΔE00 (T0–T2)
SPC	Tea	1.97 ± 0.49a	7.16 ± 0.86a
SPC	Coffee	1.50 ± 0.27b	6.65 ± 0.93b
SPC	Water	0.48 ± 0.21c	1.28 ± 0.30c
VCP	Tea	2.07 ± 0.32a	7.88 ± 0.88a
VCP	Coffee	1.33 ± 0.24b	6.80 ± 1.37b
VCP	Water	0.65 ± 0.28c	1.51 ± 0.25c

Different superscript lowercase letters within each column indicate statistically significant differences (p < 0.05)

Fig. 1.

Color change (ΔE₀₀) of additively manufactured permanent resin materials after immersion in staining solutions, with clinical thresholds. Bar chart showing mean ΔE₀₀ ± standard deviation values for SPC (Saremco Print Crowntec, Saremco Dental AG, Switzerland) and VCP (VarseoSmile Crown Plus, BEGO, Germany) after 24 h (T1) and 14 days (T2) of immersion in tea, coffee, and distilled water. Horizontal dashed lines indicate the perceptibility threshold (PT = 0.8) and acceptability threshold (AT = 1.8) for tooth-colored restorative materials. Error bars represent standard deviation. Different letters indicate statistically significant differences between groups (p < 0.05)

At the final evaluation period (T0–T2), overall color change increased markedly in the tea and coffee groups, whereas water continued to show very low discoloration values. Tea produced the highest discoloration values in both materials, with coffee showing slightly lower but still substantial color change. In contrast, the water groups showed color changes above perceptibility thresholds but below acceptability thresholds.

Color change was significantly influenced by the staining solution at both time points (p < 0.001), whereas the material type did not significantly affect discoloration (p > 0.05 at T1; p > 0.05 at T2). No significant interaction between material and staining solution was observed at either time point (p > 0.05). Detailed comparisons between groups are summarized in Table 3.

Table 3.

Mixed-model ANOVA results for ΔE₀₀

Time	Factor	F	df	p-value	Partial η²
T1	Material	0.17	1,54	0.683	0.003
T1	Solution	107.97	2,54	< 0.001	0.800
T1	Material × Solution	1.63	2,54	0.206	0.057
T2	Material	2.75	1,54	0.103	0.048
T2	Solution	302.15	2,54	< 0.001	0.918
T2	Material × Solution	0.65	2,54	0.527	0.023

Between-subject effects derived from mixed-model ANOVA

Surface roughness (Ra)

Baseline and post-staining surface roughness values, as well as the calculated changes in roughness, are shown in Table 4. Surface roughness values exhibited only minor fluctuations after immersion in all staining solutions.

Table 4.

Surface roughness (Mean ± SD)

Material	Solution	Ra T0 (µm)	Ra T2 (µm)	ΔRa (µm)
SPC	Tea	0.529 ± 0.121	0.531 ± 0.126	0.0026 ± 0.0178
SPC	Coffee	0.559 ± 0.083	0.567 ± 0.075	0.0086 ± 0.0477
SPC	Water	0.502 ± 0.085	0.504 ± 0.071	0.0023 ± 0.0257
VCP	Tea	0.456 ± 0.072	0.463 ± 0.081	0.0071 ± 0.0221
VCP	Coffee	0.442 ± 0.034	0.449 ± 0.037	0.0071 ± 0.0093
VCP	Water	0.438 ± 0.041	0.444 ± 0.043	0.0060 ± 0.0091

The magnitude of roughness change was very small across all groups, generally remaining within a narrow range. Neither the type of staining solution nor the material appeared to influence the extent of surface roughness alteration. No statistically significant differences were observed in roughness change for staining solution, material, or their interaction (all p > 0.05). Statistical outcomes for roughness changes are presented in Table 5.

Table 5.

Mixed-model ANOVA results for ΔRa

Factor	F	df	p-value	Partial η²
Material	0.11	1,54	0.736	0.002
Solution	0.12	2,54	0.888	0.004
Material × Solution	0.08	2,54	0.922	0.003

Between-subject effects derived from mixed-model ANOVA

Relationship between surface roughness and color change

The relationship between baseline surface roughness and final color change is summarized in Table 6. No meaningful association was observed between the initial roughness values and the degree of discoloration after staining when all specimens were evaluated together (p > 0.05). This pattern remained consistent when each material was analyzed separately, with no significant correlations detected for SPC or VCP (both p > 0.05).

Table 6.

Correlation between surface roughness and color change

Group	Baseline Ra vs. ΔE00 r	p-value	ΔRa vs. ΔE00 r	p-value
All specimens	0.13	0.31	0.41	0.002
SPC	0.27	0.15	0.38	0.018
VCP	0.07	0.72	0.36	0.026

However, when the change in surface roughness (ΔRa) was considered, a statistically significant positive correlation with color change (ΔE00) was observed for all specimens (p < 0.05). Similar trends were also identified for both SPC and VCP materials, indicating that increases in surface roughness over time were associated with greater discoloration.

Discussion

This study evaluated the effects of different staining solutions on the color stability and surface roughness of two additively manufactured resin-based restorative materials. The findings demonstrated that discoloration was strongly influenced by the staining medium, whereas surface roughness remained largely unchanged over time. Moreover, no relationship was found between baseline surface roughness and the extent of color change. However, a significant correlation between changes in surface roughness and color change suggests that dynamic surface alterations may contribute to the staining behavior of additively manufactured resins. Regarding the study hypotheses, the first null hypothesis was partially rejected. While staining solution significantly influenced color stability, material type and baseline surface roughness did not show a significant effect on discoloration. The second null hypothesis was accepted, as surface roughness values did not significantly change over time following immersion in the tested solutions.

Both materials showed significant discoloration after immersion in tea and coffee, while specimens stored in water exhibited minimal color change. These findings are consistent with previous reports demonstrating that beverages such as tea and coffee have a high chromogenic potential and can markedly alter the optical properties of resin-based restorative materials [9, 10, 15, 26]. The greater discoloration observed in tea may be attributed to its high tannin content and strong pigment affinity for organic resin matrices [9, 10, 27, 28].

Unlike conventionally fabricated composite resins, additively manufactured materials are produced using a layer-by-layer polymerization process, which may create interlayer interfaces and variations in degree of conversion throughout the material [2, 5, 6]. These structural characteristics may influence water sorption and pigment penetration, potentially affecting color stability. In addition, printing parameters such as layer thickness may further influence surface topography, interlayer bonding, and light scattering behavior. Thicker layers may lead to more pronounced interlayer interfaces and increased surface irregularities, which may facilitate pigment accumulation and discoloration. In contrast, thinner layers may improve surface uniformity and reduce staining susceptibility [6, 20, 21]. Furthermore, post-curing procedures play a critical role in improving polymerization efficiency and reducing residual monomers in additively manufactured resins [5, 6]. Insufficient post-curing may increase water uptake and staining susceptibility.

Recent studies have also investigated the color stability of additively manufactured resin materials and reported varying degrees of discoloration depending on material composition and aging conditions. Gad et al. demonstrated that 3D-printed denture base resins showed significant color changes following artificial aging, emphasizing the susceptibility of additively manufactured polymers to environmental factors [16]. Similarly, Acar et al. reported that CAD–CAM and additively manufactured resin materials exhibited increased staining after immersion in chromogenic beverages [13]. These findings support the results of the present study, where tea and coffee produced clinically noticeable discoloration in both tested materials.

Despite compositional differences between the tested materials, no significant differences in color stability were observed. This finding may suggest that factors such as degree of conversion, filler characteristics, and water sorption could play a more dominant role than resin matrix composition alone. Water sorption may increase free volume within the polymer network and may facilitate the diffusion of chromogenic molecules into the resin matrix [11, 12, 29]. This mechanism explains the time-dependent increase in ΔE₀₀ values observed in the present study and aligns with previous research indicating that discoloration of resin-based materials is largely driven by pigment absorption and internal diffusion rather than superficial deposition alone [9, 10]. Importantly, specimens stored in water exhibited color changes above perceptibility thresholds but below acceptability thresholds, indicating limited clinical relevance in agreement with established thresholds in dentistry [8, 10].

In contrast, the ΔE₀₀ values observed in tea and coffee groups exceeded the acceptability threshold, indicating clinically unacceptable discoloration [8, 10, 15]. These findings suggest that exposure to commonly consumed staining beverages may significantly compromise the esthetic performance of additively manufactured resin restorations [9, 15, 26]. From a clinical perspective, ΔE₀₀ values exceeding perceptibility thresholds may be noticeable to patients, whereas values above acceptability thresholds may necessitate restoration replacement [30, 31]. Therefore, clinicians may consider patient dietary habits and material selection when planning restorations fabricated using additive manufacturing technologies, particularly for patients with frequent consumption of chromogenic beverages.

Despite the pronounced discoloration, surface roughness values showed only minor changes after immersion in all staining solutions. However, correlation analysis revealed a significant association between changes in surface roughness (ΔRa) and color change (ΔE00). This finding suggests that even small alterations in surface topography may contribute to discoloration of additively manufactured resin materials. Similar findings have been reported where composite materials demonstrated significant color change without concurrent alterations in surface topography [9, 13, 32].

Surface roughness is known to influence plaque accumulation and bacterial retention when exceeding specific threshold values [16]. However, the small variations in Ra observed in this study remained within a narrow range and are unlikely to be clinically relevant. These results suggest that staining may occur through a combination of pigment sorption within the resin matrix and subtle surface alterations that facilitate pigment retention [10]. These findings suggest that intrinsic material properties may play a more important role in discoloration than surface finishing procedures alone [30, 33].

No significant correlation was found between baseline surface roughness and the magnitude of color change. However, a significant positive correlation was observed between the change in surface roughness and color change, indicating that surface degradation over time contributes to staining susceptibility. These findings suggest that dynamic surface changes may be more important than initial surface characteristics in determining discoloration behavior [9, 31]. Even smoother specimens in the present study exhibited comparable levels of discoloration, reinforcing the concept that internal material properties such as matrix hydrophilicity and polymer network characteristics play a more critical role in stain uptake than initial surface texture [34, 35].

However, previous studies have reported conflicting findings regarding the effect of staining solutions on surface roughness and discoloration. Some investigations demonstrated significant increases in surface roughness following exposure to staining beverages, suggesting that chemical degradation and softening of the resin matrix may contribute to discoloration [32, 35]. In contrast, other studies reported minimal or no changes in surface roughness despite noticeable color changes, indicating that pigment absorption within the resin matrix may play a more dominant role [9, 13]. Similarly, studies evaluating additively manufactured resins have also reported inconsistent findings regarding surface roughness changes after aging. While some authors observed minimal surface alterations following immersion in staining media, others reported increased roughness after long-term aging or mechanical wear. These inconsistencies may be attributed to differences in material composition, aging protocols, polishing procedures, and measurement techniques. Therefore, variations in experimental conditions may explain the differences observed between studies.

From a clinical perspective, the results suggest that additively manufactured resin restorations may be prone to discoloration when exposed to chromogenic beverages, even when their surfaces remain structurally stable [15, 17]. Patients with high consumption of tea or coffee may therefore experience noticeable aesthetic changes over time. Preventive strategies may include polishing protocols, material selection, and patient dietary counseling. However, the continuous immersion protocol used in this study does not directly replicate intraoral conditions. Although this method has been widely used to simulate accelerated aging and prolonged exposure to staining beverages, 24 h of immersion has been suggested to correspond approximately to one month of clinical exposure depending on beverage consumption frequency [15, 26]. Therefore, the 14-day immersion period may represent several months of clinical service; however, these findings should be interpreted with caution when extrapolating to clinical conditions.

This study was conducted under controlled laboratory conditions and did not simulate complex intraoral factors such as salivary pellicle formation, pH fluctuations, thermal changes, or mechanical abrasion from toothbrushing, all of which may influence staining and surface behavior in vivo. Only two materials and a limited immersion period were evaluated. Surface finishing procedures were performed manually without mechanical force standardization, which may introduce operator-dependent variability. Furthermore, only polished surfaces were investigated, which may have masked the intrinsic effects of the layer-by-layer fabrication process. Printing parameters such as layer thickness and build orientation were standardized in this study; however, variations in these parameters may also influence surface roughness and discoloration behavior. In addition, specimens were not subjected to daily brushing or rinsing during the immersion period, which may not fully reflect clinical conditions and may influence staining behavior. Future studies should include longer aging protocols, additional staining agents, different printing parameters, and evaluation of both polished and as-printed surfaces. The potential effectiveness of repolishing procedures in reversing discoloration should also be investigated.

Despite these limitations, this study has several strengths. The simultaneous evaluation of color stability and surface roughness allowed a comprehensive assessment of staining behavior. Additionally, the inclusion of two widely used additively manufactured permanent resin materials and standardized polishing procedures enhanced the reliability and clinical relevance of the findings. Furthermore, the evaluation of both baseline and time-dependent surface roughness changes provided additional insight into the relationship between surface characteristics and discoloration.

Conclusions

Within the limitations of this study, discoloration of additively manufactured resin materials was significantly affected by the type of staining solution, with tea and coffee producing pronounced color changes. Surface roughness remained relatively stable after immersion, and no association was found between baseline roughness and discoloration. However, a significant correlation between changes in surface roughness and color change suggests that subtle surface degradation may contribute to staining behavior. Clinically, these findings indicate that patients with high consumption of chromogenic beverages such as tea and coffee may experience noticeable discoloration of additively manufactured restorations over time. Therefore, material selection, patient dietary counseling, and periodic polishing procedures may be considered to maintain long-term esthetic outcomes.

Abbreviations

ANOVA

Analysis of Variance

AT

Acceptability Threshold

CAD–CAM

Computer-Aided Design / Computer-Aided Manufacturing

CIE

Commission Internationale de l’Éclairage

CIEDE2000 (ΔE₀₀)

Color Difference Formula (CIEDE2000)

ΔE₀₀

Color difference value

ΔRa

Change in surface roughness

ISO

International Organization for Standardization

PT

Perceptibility Threshold

Ra

Arithmetic Mean Surface Roughness

SPC

Saremco Print Crowntec

SPSS

Statistical Package for the Social Sciences

T0

Baseline measurement time

T1

24-hour measurement time

T2

14-day measurement time

VCP

VarseoSmile Crown Plus

Authors’ contributions

Ünlü, Ö: Conceptualization, Data Curation, Formal analysis, Methodology, Investigation, Writing - Original Draft, Writing- Review and Editing.Sakallı, S: Conceptualization, Data Curation, Writing- Review and Editing.Yıldırım Manav, E: Conceptualization, Methodology, Data Curation, Investigation, Writing- Review and Editing, Supervision.

Funding

None.

Data availability

Data available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

Ethical approval was not required for this study, as it did not involve human participants or animals.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.