Fracture resistance of nanocomposite 3D-printed resins designated for teeth fabrication: An in vitro analysis before and after thermal aging

Introduction

Artificial teeth for removable dentures are manufactured from various materials, including acrylic resin, ceramics, 3D-printed materials, and resin composites.^1–3 Conventionally, prefabricated denture teeth are made of acrylic resin, making them prone to fracture or chipping, particularly in situations in which a complete denture opposes natural teeth or an implant-supported overdenture.^4–6 With growing demand for artificial teeth with enhanced fracture resistance, various approaches have been proposed, including the use of different monomers, cross-linking agents, and organic and inorganic fillers in polymer matrices.^7,8 Despite these advancements, denture-teeth fractures continue to be a persistent issue, highlighting the need for the development of denture teeth fabricated using innovative methods capable of withstanding higher loads and forces.^8,9

Digital dentures can be produced by using subtractive or additive manufacturing techniques.³ In the additive process, a photopolymerized liquid resin is used to build removable prostheses layer-by-layer.^3,4,10 This method offers several benefits, including the significantly lower cost of 3D printers compared with milling machines, which facilitates its broader adoption in clinical practice.³ Unlike subtractive milling, 3D-printing generates less material waste.^3,11,12 Moreover, 3D-printed denture teeth are typically manufactured from methacrylate-based photopolymerized resin, a material specifically designed for processing through 3D-printing technology.^11–14 This method provides flexibility and precision, and improves functionality in the fabrication of removable dentures, making it a modern alternative to traditional techniques.

Gad et al., ⁸ studied the fracture resistance of a specific type of 3D-printed teeth (NextDent), and showed that they exhibited greater fracture resistance than traditional prefabricated teeth. However, their strength decreased after exposure to thermal cycling. Similarly, Chun et al.,¹⁰ examined another variety of 3D-printed resin teeth (Dentca) and reported that their fracture resistance was comparable to that of prefabricated teeth. These studies^8,10 identified the potential of 3D-printed resins and highlighted the need to improve their strength, especially after thermal aging (TA). The absence of nanoparticle (NP) reinforcement in previous research left a gap in the exploration of how NPs can enhance durability.¹³ Therefore, exploring the incorporation of different NPs may be an effective approach for improving the mechanical properties of 3D-printed resin teeth. Owing to the capacity of 3D-printed resins for reinforcement, zirconium dioxide nanoparticles (ZNPs) and silicon dioxide nanoparticles (SNPs) have attracted considerable interest. When added to a resin matrix, ZNPs, which are well known for their antibacterial properties, increase the mechanical strength and wear resistance of dental composites.^4,13–16 Similarly, SNPs enhance the hardness, fracture toughness, and elastic modulus of dental materials owing to their large surface area and compatibility with resin matrices.¹⁵ By resolving the drawbacks of conventional materials, previous studies^4,13 have shown that the addition of these NPs to interim resins has yielded encouraging results, resulting in long-lasting and resilient interim restorations.

The incorporation of ZNPs into 3D-printed dental resins has been investigated as an effective approach to enhance mechanical properties, particularly due to zirconia’s high strength, toughness, and resistance to crack propagation.^17,18 The reinforcing effect of ZNPs is strongly dependent on their concentration and dispersion within the resin matrix. Recent studies on 3D-printed and conventional denture base resins have shown that low to moderate concentrations of ZNPs (approximately 0.5–1 wt.%) significantly improve flexural strength, hardness, and fracture resistance by promoting effective stress transfer across the filler–matrix interface.^13,17,19 Increasing the concentration to 2–3 wt.% may further enhance certain mechanical properties; however, this effect is often material-dependent and may be accompanied by increased viscosity and potential processing challenges in 3D printing systems.²⁰ At higher concentrations (≥5 wt.%), studies have reported particle agglomeration, reduced interfacial bonding efficiency, and deterioration of mechanical performance due to stress concentration sites within the resin matrix.¹⁸ Furthermore, excessive ZNP loading may negatively affect printability, surface quality, and dimensional accuracy of additively manufactured dental materials. Therefore, based on current literature, ZNP concentrations in the range of 0.5–2 wt.% are generally recommended for 3D-printed dental resins, as they provide a balance between mechanical reinforcement and material processability while minimizing adverse effects associated with nanoparticle aggregation.¹⁸

The incorporation of SNPs into 3D-printed dental resins has been widely investigated as a strategy to enhance mechanical performance. Recent studies on 3D-printed denture base resins have demonstrated that low concentrations of SNPs (approximately 0.25–0.5 wt.%) are optimal for improving flexural strength and surface properties, with 0.5 wt.% showing the most significant enhancement in some resin systems.²¹ Similarly, investigations on 3D-printing resins incorporating silica nanoparticles have reported the use of 1–2 wt.% concentrations, which resulted in improved degree of conversion and mechanical properties without adversely affecting print accuracy.²² Although SNP concentrations can range widely (0.25–15 wt.%), lower concentrations are generally preferred to ensure homogeneous dispersion and effective stress transfer within the resin matrix.¹⁵ Therefore, based on current literature, SNP incorporation in low to moderate concentrations (approximately 0.25–2 wt.% for 3D-printed resins) is considered optimal for enhancing mechanical performance while minimizing adverse effects related to particle aggregation and reduced material stability.¹³

The improvement in mechanical properties of 3D-printed nanocomposite resins is mainly attributed to their role as reinforcing ZNPs and SNPs within the polymer matrix.^13,22 These nanoparticles enhance mechanical behaviour through effective stress transfer from the relatively compliant resin matrix to the stiff inorganic particles, thereby increasing resistance to deformation and fracture. In addition, their nanoscale size allows them to occupy intermolecular spaces within the polymer network, restricting polymer chain mobility and contributing to increased stiffness and hardness.^13,15,22,23 Crack deflection and crack pinning mechanisms are also considered important, particularly for ZNPs, which possess high fracture toughness and can hinder crack propagation, leading to improved fracture resistance.^24,25

Although the incorporation of NPs into 3D-printed resins has been explored as a strategy to enhance their mechanical properties, most previous studies have focused on general resin formulations or standardized specimen geometries that do not adequately replicate the clinical configuration of denture teeth. Furthermore, the available literature provides limited and inconsistent evidence regarding the influence of specific nanoparticles particularly ZNPs and SNPs at different concentrations on the mechanical performance of 3D-printed resins intended for denture tooth fabrication. In addition, there is a lack of studies evaluating these modified materials under clinically relevant conditions, including anatomically shaped specimens and simulated aging processes such as thermal cycling. More importantly, direct comparisons between 3D-printed nanocomposite denture teeth and conventionally manufactured prefabricated teeth, which serve as the current clinical standard, remain scarce. This gap limits the ability to determine whether nanoparticle modification can produce materials with comparable or improved mechanical performance for clinical application. Therefore, this study aimed to evaluate the fracture resistance and elastic modulus of 3D-printed denture teeth modified with ZNPs and SNPs at different concentrations, and to compare their performance with prefabricated teeth before and after thermal aging.

The study tested three null hypotheses: first, that incorporating zirconium dioxide (ZrO₂) and silicon dioxide (SiO₂) nanoparticles into 3D-printed denture-tooth resins would have no significant effect on their fracture resistance or elastic modulus; second, that thermal aging would not significantly influence these mechanical properties in any of the tested materials; and third, there is no significant interaction effect between nanoparticle type, nanoparticle concentration, and thermal aging on the fracture resistance and elastic modulus.

Methodology

The sample size for this in-vitro study was estimated using an online power and sample-size calculator, based on the mean and standard deviation values reported in previous studies that evaluated the fracture resistance of 3D-printed resin teeth.^8,26 These studies provided the closest available estimates of variability for the primary outcome measure. Using their reported mean difference and standard deviation as input parameters, the calculation was performed with a significance level of 5% (α = 0.05), a statistical power of 80% (1–β = 0.80), and a margin of error of 5%. The resulting output indicated that a minimum of ten specimens per subgroup would be sufficient to detect a statistically meaningful difference under these conditions. A total of 220 specimens were fabricated and subdivided as follows: 20 prefabricated teeth, 100 ASIGA, 100 NextDent. The prefabricated group (n = 20) consisted of mandibular molar teeth (Major Dent-V, MAJOR Prodotti Dentari S.P.A., Moncalieri (TO), Italy). For the printed groups, two types of photopolymerized resins were used to create the 3D-printed resin teeth (n = 100/resin): NextDent C&B MFH (NextDent, 3D Systems, Soesterberg, The Netherlands) and ASIGA (Asiga DentaTOOTH, Shade A1, ASIGA, Erfurt, Germany). Half of the prepared specimens (N = 110) were tested without thermocycling while another half (N = 110) were tested after thermocycling (Figure 1).

Figure 1. Diagram illustrating the study design.

In this study, 3D-printed groups were reinforced with two types of NPs: ZNPs (Shanghai Richem International Co., Ltd., Shanghai, China) and SNPs (AEROSIL R812; Evonik-Degussa, Essen, Germany). Each NP type was incorporated into the resin fluid at two different concentrations (0.5 wt.% and 1 wt.%). The NPs were treated with silane coupling agent [3-(trimethoxysilyl) propyl methacrylate (TMSPM) (Shanghai Richem International Co., Ltd. China)] which contains bifunctional groups capable of forming a chemical bridge between inorganic fillers and organic resin matrices. The silanization process was performed by dissolving 0.3 g of TMSPM in 100 mL of acetone, followed by the addition of 30 g of nanoparticles and continuous stirring to promote the hydrolysis of alkoxy groups into silanol groups.^13,19,27 These silanol groups then react with hydroxyl groups present on the nanoparticle surface, forming stable siloxane (Si–O–Si or Zr–O–Si) bonds, while the methacrylate end of the silane co-polymerizes with the resin matrix during curing.^28,29

For nanocomposites preparations, 3D printed resins containers were shaken using shaker (NextDent LC- 3DMixer, B. V., Soesterberg, the Netherlands) for 1 h according to manufacture r recommendation for assurance of normal distribution fluid resin composition within each container.³⁰ The silanized NPs were carefully weighed using a digital balance (S-234; Denver Instruments, Gottingen, Germany) to ensure precise measurements.^15,16 Subsequently, the required amount of NPs was gradually added to the fluid resin while continuously stirring on a magnetic stirrer (Cimarec Digital Stirring Hotplates, SP131320-33Q; Thermo Fisher Scientific, Waltham, MA, USA) at 60°C for with 300 rpm 30 minutes. After the initial thermal mixing, the mixture was allowed to stir at room temperature for an additional 8 hours, enabling complete nanoparticle integration and stabilization of the nanocomposite prior to printing.¹³ For each 3D printed resin type, five groups were prepared and classified according to nanoparticle (NP) type and concentration into one control group without reinforcement and four experimental groups containing different NP concentrations (0.5 wt.% ZNP, 1 wt.% ZNP, 0.5 wt.% SNP, and 1 wt.% SNP).

A prefabricated mandibular molar tooth, standardized to dimensions of 10.2 × 11.1 × 7.3 mm, were scanned using desktop scanner (E3; 3Shape A/S, Copenhagen, Denmark) to create a standard tessellation language (STL) file. The STL file was subsequently exported to the designated 3D printer.^8,13 As detailed in Figure 1, all 3D printed specimens were fabricated using two different additive manufacturing systems according to the manufacturer-recommended printing protocols. The first group was printed using the ASIGA MAX (Asiga, Alexandria, NSW, Australia), which operates using digital light processing (DLP) technology with a 385-nm UV light source. The second group was fabricated using a NextDent 5100 (NextDent, 3D systems Vertex Dental B.V., Soesterberg, Netherland) with a 405-nm UV LED light source. Printing parameters were set to print specimens with 0-dgree printing orientations and 50 μm layer thickness, and the exposure time was set at approximately 5–6 s per layer according to the manufacturer’s recommendations. After printing, post-processing process included removal of printed object from the platform followed by cleaning, post curing and support structure removal.^31–33 Once printing was completed, the specimens were cleaned with 99.9% isopropyl alcohol to remove uncured resin. After cleaning, specimens underwent post-processing using the post-curing units of each printing system with the recommended post-curing process and conditions.^13,15,16 The post-polymerization protocol for ND was using curing unit (LC-D Print Box, 3D systems Vertex Dental B.V., Soesterberg, Netherland) for 15 min with wavelength measured 360–435 nm and ASIGA underwent for (Asiga Flash UV Curing Chamber) for 4000 flashes with wavelength 480–530 nm. Support structures were removed after post-curing, as complete light polymerization is necessary to achieve the final degree of conversion and mechanical stability of the resin, thereby reducing the risk of deformation or surface damage during support removal.³⁴ Supports were removed using a low-speed diamond disc under continuous water irrigation to reduce heat generation and prevent microcrack formation, as recommended in studies evaluating finishing procedures of resin-based materials.^31,33 Residual support areas were then refined using fine-grit diamond burs followed by sequential wet polishing with silicon carbide papers of increasing grit sizes (320, 600, and 1200) to achieve a uniform surface finish.³¹ Final polishing was completed using rubber polishing instruments and acrylic polishing paste to enhance surface smoothness and optimize mechanical performance.^35,36

Printed teeth and prefabricated teeth were randomly divided into two groups according to thermal aging. Half of specimens (N = 110) were randomly selected and stored in water for 48 h at 37°C and then immediately tested. While the other half of the specimens (N = 110) were randomly selected and subjected to 5000 TA cycles. The TA process was performed using a Thermocycler (Thermocycler THE-1100, Mechatronik GmbH, Feldkirchen-Westerham, Germany). Five thousand cycles are roughly equivalent to 6 months in the oral cavity, based on the assumption that intraoral restorations can be subjected to abrupt temperature changes 20 times per day.^28,37 So, in this study, specimens were subjected to 5000 cycles at 5°C and 55°C with a dwell time of 30 s and transfer time of 4 seconds.^13,38,39

A stainless-steel ball indenter with a 7 mm radius was used to load the specimens at the occlusal surfaces using a universal testing apparatus (Instron model 5965, Massachusetts, United States) with a 5 kN load cell at a loading rate of 1 mm/min until failure occurred (Figure 1). A 1.5 mm-thick rubber sheet was positioned between the occlusal surface and indenter to reduce contact damage and aid in distributing the load.^13,39

Fracture resistance was recorded as the maximum load at fracture and expressed in Newtons (N). The elastic modulus was calculated from the linear portion of the load–deflection curve obtained from the universal testing machine as described in previous study.⁴⁰

Essential data on the fracture behaviour of the modified 3D-printed denture teeth were obtained through fracture-site analysis using scanning electron microscopy (SEM; TESCAN VEGA3 LM model, TESCAN Orsay Holding, Kohoutovice, Czech Republic). To ensure optimal image quality, the fractured samples were cleaned and prepared by coating nonconductive polymer or resin materials with a thin layer of conductive gold (Quorum, Q150R ES, UK). This coating, applied at an accelerating voltage of 20 kV, prevented charging effects and enhanced image clarity. The specimens were then placed in the SEM chamber for analysis. Key fracture characteristics such as initiation sites, crack-propagation patterns, and interactions between the polymer matrix and reinforcing particles were identified. The NPs, with an average size of 40 nm and surface area of 9 m²/g, were analyzed using both SEM and transmission electron microscopy (TEM).

Fourier transform infrared (FTIR) analysis is an essential tool for examining the bonding interactions between NPs and the polymer matrix because it offers comprehensive details on the chemical structure and functional groups present in the material. FTIR analysis assisted in identifying any changes in the molecular bonding caused by the addition of NPs. The specimens were placed inside an FTIR spectrometer for transmission spectroscopy (Hartmann & Braun, MB series), and two readings were obtained per specimen. FTIR spectra were obtained at a resolution of 4 cm⁻¹, spanning a wavenumber range of 4000 to 400 cm⁻¹. The resultant spectra showed distinctive peaks corresponding to certain functional groups; thus, the bond types and any matrix chemical changes caused by the presence of NPs could be identified.

The means and standard deviations of the data were calculated for a descriptive analysis by using SPSS v.23. The normality of the data was assessed using the Shapiro–Wilk test, with nonsignificant results indicating that the data followed a normal distribution. Consequently, parametric tests were applied for an inferential analysis. A two-sample t-test was used to evaluate the effect of TA on fracture resistance. To explore the effects of the NP concentration on the fracture resistance and elastic modulus, a one-way analysis of variance (ANOVA) was performed. If the ANOVA results were significant, pairwise comparisons were conducted using Tukey’s post hoc test. A three-way ANOVA was used to examine the interaction effects of the NPs, their concentration levels, and their properties. Statistical significance was set at p < 0.05.

Results

Table 1 shows the three-way ANOVA of the three variables (NP type, material type, and impact of TA) and their interactions for fracture resistance. The combined interaction effect showed a significant interaction only between TA and the material type (P < 0.001) while no significant when combined with other variables (P > 0.05).

The fracture resistance results are summarized in Table 2 and Figure 2. For ND pre-TA, in comparison to pure resin, the addition of both SNPs and ZNPs significantly increased the fracture resistance (p < 0.001) except 0.5%ZNPs (p > 0.05) which showed the lowest fracture resistance value (1047.5 ± 100.6 N). In between NPs groups, SNPs showed significant increase compared to ZNPs while SNPs groups demonstrated an insignificant difference in fracture resistance compared to the prefabricated teeth (p > 0.05). For ND post-TA, in comparison to pure resin, the addition of both SNPs and ZNPs significantly increased the fracture resistance (p < 0.001) except 0.5%ZNPs (p > 0.05) which showed the lowest fracture resistance value (984.5 ± 81.9 N). In between NPs groups, 0.5 wt.% SNPs with the highest fracture resistance value (1387.1 ± 101.4 N) significantly showed an increase in the fracture resistance compared to all reinforced groups and demonstrated an insignificant difference in fracture resistance compared to prefabricated teeth (p > 0.05). In terms of the TA effect on ND, the fracture resistance was significantly decreased (P < 0.05) except the prefabricated (p = 0.087) and 0.5%SNP (P = 0.656).

Figure 2. Fracture resistance of prefabricated and 3D-printed resins before and after thermal aging.

For ASIGA pre-TA, the pure resin exhibited the highest fracture resistance value (2346.6 ± 162.9 N). In comparison to pure resin, the addition of both SNPs and SNPs showed no insignificant increase in fracture resistance (p > 0.05). In between NPs groups, no significance was found between all groups (p > 0.05); however, all reinforced groups and the pure group showed a significant increase in fracture resistance compared to the prefabricated group which showed the lowest fracture resistance value (1517.1 ± 121.9 N).

For ASIGA post-TA, the results showed the same behavior before TA, no significant differences were found between groups (p > 0.05) except 0.5%SNPs which showed a decrease fracture resistance recorded the lowest value (1352.9 ± 116.4 N). In comparison to the prefabricated group, all reinforced groups showed a significant increase in fracture resistance (P < 0.001) except 0.5%SNPs (p = 0.921) and the prefabricated group showed the lowest fracture resistance value (1352.9 ± 116.4 N). In terms of the TA effect on ND, the fracture resistance was significantly decreased per respective group (P < 0.05) except for the prefabricated group (p = 0.087).

The statistical T-test analysis for fracture resistance in Table 3 highlights the material-specific differences per respective NP type and concentration. Pre-AT, ASIGA significantly showed an increase in the fracture resistance (p < 0.05). Post-TA, significant differences in the fracture resistance were observed between the ND and AS materials across all NP-incorporated groups (p < 0.05), except for the pure resin (p = 0.387) and 1 wt.% SNPs (p = 0.657) groups.

Table 4 shows the three-way ANOVA of the three variables (NP type, material type, and impact of TA) and their interactions for the elastic modulus. The results showed a significant interaction between all variables (P < 0.05) and when the three variables were combined (P = 0.007).

The elastic modulus results are summarized in Table 5 and Figure 3. The prefabricated teeth significantly showed the highest elastic modulus values pre-TA (5002.0 ± 172.8 MPa) and post-TA (4255.5 ± 100.5 MPa). For ND pre-TA, the addition of SNPs and ZNPs significantly decreased the elastic modulus when compared with the pure resin (p < 0.001) and the lowest elastic modulus value was recorded with 1%ZNPs (1772.0 ± 128.8 MPa). In between NPs-reinforced groups per NPs type, there were no significant differences between SNPs groups (p = 0.064) as well as ZNPs groups (p = 0.072). When comparing NPs type, ZNPs showed a significant decrease in elastic modulus and the highest elastic modulus value was found with 1%SNPs (2048.2 ± 132.8 MPa) and the lowest values with 1%ZNP (1772.0 ± 128.8 MPa). For ND post-TA, in comparison to the prefabricated group, the elastic modulus of pure and NP-modified groups were significantly decreased (P < 0.001). While no significant differences between the pure and NP-modified groups (p < 0.05) and the pure group showed the highest elastic modulus value (376.6 ± 35.6 MPa). In terms of the TA effect, the elastic modulus of prefabricated, pure, and NP-modified groups was significantly decreased per respective NP type and concentration (p < 0.05).

Figure 3. Elastic modulus of prefabricated and 3D-printed resins before and after thermal aging.

For ASIGA pre-TA, the pure resin and NP-modified groups showed a significant decrease in elastic modulus when compared with the prefabricated group (p < 0.001). In comparison to the pure group, the addition of both NPs showed a significant decrease in elastic modulus with 0.5%SNP and 1%ZNPs and 0.5%SNPs showed the lowest elastic modulus value (1951.1 ± 161.9 MPa). While no significant differences between pure resin and other NP-modified groups (pure vs. 1%SNPs and pure vs. 0.5%ZNPs, p > 0.05). in between NP-modified groups, 1%SNPs and 0.5%ZNPs significantly showed higher elastic modulus compared with 0.5%SNPs and 1%ZNPs and the highest values were recorded with 0.5%ZNPs (2639.0 ± 93.0 MPa) followed by 1%SNPs (2608.1 ± 94.1 MPa). For ASIGA post-TA, the elastic modulus was significantly decreased in pure and NP-modified groups when compared with the prefabricated group (p < 0.001). While no significant differences between the pure and NP-modified groups (P > 0.05) and 1%ZNPs showed the highest elastic modulus value (390.0 ± 25.1 MPa). In terms of the TA effect, the elastic modulus of prefabricated, pure, and NP-modified groups was significantly decreased per respective NP type and concentration (p < 0.05).

The statistical T-test analysis for elastic modulus in Table 6 highlights the material-specific differences per respective NP type and concentration. Pre-AT, pure ASIGA significantly showed a decrease in the elastic modulus compared with pure NextDent (p = 0.003). While NP-modified ASIGA groups showed a significant increase in elastic modulus except at 0.5 wt.% SNPs (p = 0.998). Post-TA and Pre-AT, pure ASIGA significantly showed a decrease in the elastic modulus compared with pure NextDent (p = 0.032*). While no significant differences in the elastic modulus were observed between the ND and AS materials across all NP-incorporated groups (p > 0.05).

Figure 4 shows the entire range of the infrared spectrum, 4000–500 cm⁻¹, demonstrating the bonding of AS and ND with different types of NPs at varied concentrations. The FTIR spectra of the AS and ND materials revealed characteristic bonds attributed to carbonyl groups. All the groups of specimens exhibit the C-H bond at approximately 2900 cm⁻¹ and C=O double bond at approximately 1703 cm⁻¹. The most significant difference between the AS and ND groups was observed in the spectral region of 1144–1034 cm⁻¹ in the FTIR spectrum. This range corresponded to the stretching vibrations of the C–O–C (ether) functional group. The differences in this region indicate that the chemical environment or bonding characteristics of the C–O–C group vary, suggesting structural or compositional differences between the materials.

Figure 4. FTIR spectra of modified pure and nanoparticle-incorporated resins.

(A) Modified pure and nanoparticle-incorporated ASIGA specimens. (B) Modified pure and nanoparticle-incorporated NextDent specimens. The important bands are labelled in each set of specimens.

Figures 5–7 display the SEM images of both the occlusal and fracture surfaces. The fracture behavior of the occlusal surface showed more crack propagation in the NP-reinforced groups than in the pure-resin smooth fracture and absence of cracks. Prefabricated teeth (Figure 5) include a smooth occlusal surface and smooth fracture line. An additional note regarding 3D-printed teeth is the stepwise effect, representing printing layers on curved surfaces, such as cusp tips and cusp slopes (Figures 6 and 7). While comparing the two groups, pure ND and AS exhibited deep and multiple cracks. NP- incorporated AS are showing multiple and long propagated crack as compared to NP- incorporated ND. These SEM findings are useful while evaluating the mechanical strength of two types of specimens. Some cracks followed the line between the printed layers, which may be a reason for the weakened strength of printed teeth compared with prefabricated teeth that showed a smooth occlusal surface (absence of the staircase effect). In the cross-sectional surface analysis, most of the groups reinforced with NPs showed a rough surface with some lamellae as well as prefabricated teeth, whereas the pure teeth showed a smooth fracture side. Compared with AS groups the ND cross-sections showed higher surface roughness with several lamellar surfaces as marked with white arrows (Figure 7).

Figure 5. Representative SEM images of prefabricated teeth.

a) Occlusal surface, b) fracture surface.

Figure 6. Representative SEM images of 3D-printed teeth for both materials showing the occlusal surface.

Figure 7. Representative SEM images of 3D-printed teeth for both materials showing the fracture surface.

The cracks propagations are highlighted with red arrows while lamella structures are marked with white arrows.

Discussion

The aim of this study was to examine the fracture resistance and elastic modulus of 3D-printed denture-teeth pre- and post-TA with the addition of ZNPs and SNPs. The first and second null hypotheses were rejected because of the significant effect of NP addition and TA on the fracture resistance and elastic modulus when compared with the prefabricated teeth. For the third null hypothesis concerning fracture resistance, the hypothesis of no interaction between thermal aging and material type was rejected, indicating a statistically significant interaction effect. In contrast, the null hypotheses involving interactions with nanoparticle concentration were accepted, as these interactions were not statistically significant. Thus, although nanoparticle incorporation influenced the materials at the main‑effect level, its interaction with other variables did not meaningfully affect the outcomes under the conditions tested. These findings indicate that the observed changes in material performance were primarily associated with the combined influence of thermal aging and material type, rather than synergistic interactions involving nanoparticle concentration.

The selection of ZNPs and SNPs type and concentrations was based on previous reports demonstrating their ability to enhance the mechanical and physicochemical properties of dental resins including recently developed 3D‑printed formulations when incorporated at appropriate concentrations compared with unmodified materials.^41,42 Alshamrani et al.⁴¹ and Alhotan et al.⁴² reported that adding SNPs or ZNPs significantly enhanced the mechanical and thermal stability of photopolymer resins. While the higher NPs concentrations could disrupt polymer cross-linking, reducing the elastic modulus as reported by Yan et al.⁴³ Our results align with these reports, highlighting the importance of maintaining optimal nanoparticle concentrations (0.5–1 wt%) to achieve a balance between strength and flexibility.

In this study, the incorporation of SNPs at varying concentrations into 3D-printed denture teeth increased the fracture resistance at immediate testing prior to TA in 3D-printed ND materials. This enhancement occurred by reinforcing the polymer matrix, which increased stiffness, reduced crack propagation, and boosted toughness through mechanisms such as crack deflection and energy dissipation.^18–20 The findings of the present study are consistent with previous reports^13,39,44 that showing that incorporating low concentrations of SNPs into 3D-printed interim resins can enhance their mechanical properties without negatively affecting the printing process. In addition, previous study¹³ has been investigated the flexural properties of 3D-printed resins containing 0.5 and 1 wt.% SNP concentrations. The results indicate that the addition of 1 wt.% SNP significantly improved the strength of 3D-printed resins.

ZNPs have been recommended for incorporation into dental composites to improve their mechanical qualities, as ZNPs are well known for their remarkable hardness and capacity to reinforce resin composites.^13,16,39 This investigation demonstrates that ZNPs improve the fracture resistance of 3D-printed ND only at 1 wt.% before TA. The improvements in fracture resistance resulting from ZNP integration demonstrating the ability of ZNPs to enhance the mechanical properties of polymer-based materials.^13,16 The primary mechanism proposed is the ability of ZNPs to interact with polymer chains, distribute applied stress, and inhibit fracture formation.¹⁶ Additional reason is attributed to the stiffening effect of zirconia, which reinforces the polymer matrix by promoting crack deflection and energy dissipation.^41,45

Before thermal aging, the ND resin showed a greater improvement in fracture resistance than the AS resin when the same concentration of SNPs was incorporated. Although both materials benefited from SNP addition, ND exhibited a particularly notable increase at 1 wt.% SNP. Compared with a previous study, where the fracture resistance of AS was reported as 1305.7 ± 197.4 N, the present study demonstrated substantially higher values, exceeding 2,000 N for AS both with and without nanoparticle reinforcement. Similarly, earlier work reported a fracture resistance of 867.8 ± 108.4 N for ND,⁸ whereas the current findings showed an increased value of 1097.8 ± 167.7 N. These differences may be attributed to the inherently stronger mechanical properties of AS, potentially higher cross-linking density, and variations in matrix–nanoparticle compatibility, which may make AS less reliant on external reinforcement than ND.^12–14 This interpretation is further supported by FTIR results, where shifts in the C–O–C regions suggest differences in polymer–filler interactions between the two materials.

No significant differences were found between the prefabricated teeth and the ZNP-reinforced AS resin. Although ZNPs were incorporated into the AS formulation, the resulting improvement in fracture resistance was less pronounced than that observed in ND. This is likely due to the inherently superior baseline mechanical properties of the AS resin, which already exhibits higher fracture resistance and therefore shows a smaller relative gain following nanoparticle reinforcement. Previous studies investigating the fracture strength of different dental materials have shown similar findings, in which resin materials with higher intrinsic fracture strengths demonstrate less improvement when reinforced with NPs.^{41,42,44–46}

It is important to investigate the strength of dental materials following artificial aging as many products experience decay in their strength after aging. The use of both thermally aged and non-thermally aged groups is essential to distinguish between the initial mechanical properties of materials and their behaviour after simulated oral aging.³⁷ Non-aged specimens represent baseline performance immediately after fabrication, whereas thermocycling simulates intraoral temperature fluctuations and associated degradation processes.^28,37 Previous studies have shown that thermal cycling can significantly reduce mechanical properties such as hardness and flexural strength due to hydrolytic degradation, water sorption, and internal stress development within polymer-based materials.²⁹ Moreover, thermal aging has been reported to alter the structural integrity and surface characteristics of dental materials, thereby influencing their long-term clinical performance.⁴⁷ Therefore, comparing pre- and post-thermocycling conditions provides a comprehensive evaluation of both the immediate performance and durability of materials, which is particularly important when assessing the reinforcing effect of nanoparticles in 3D-printed resins. In this study, the effect of thermal stress on the mechanical properties of the materials revealed significant differences between the pure and NP-modified groups in their fracture resistance. In pure groups, thermal stress generally led to a substantial reduction in the fracture resistance. This reduction in fracture resistance is attributed to the development of micro-cracks and other defects arising from repeated expansion and contraction under temperature changes.⁴³ These internal stresses lead to material weakening, making the material more prone to fracture. Additional factor that could be considered is the water sorption during thermal aging. 3D-printed denture teeth., water sorption plays a significant role in weakening the printed resin structure over time. When these materials absorb water, the polymer matrix undergoes plasticization, leading to reduced stiffness and softening of the intermolecular bonds.⁴⁸ This process compromises the integrity of the printed tooth, making it more susceptible to crack initiation and propagation under occlusal loading.⁴⁹ Owing to the addition of the NPs, the thermal stress caused thermal stability in the nanocomposite materials to some extent, thereby sustaining the properties of the materials and maintaining their elastic modulus.^41–43

Following TA, the 3D-printed resins with 1 and 0.5 wt.%SNP maintained superior mechanical properties and were comparable to the performance of traditional prefabricated resins and higher than pure control in ND 3D-printed resins. In AS 3D-printed resins, 0.5 wt.% of SNP revealed higher strength than the prefabricated teeth and the pure control. These findings indicate that the incorporation of an optimal amount of 0.5 wt.% concentrations can enhance the ability of 3D-printed teeth to endure thermal stresses in the oral environment, positioning them as a feasible alternative to conventional prefabricated resins.⁴² The enhancement in the mechanical performance of nanocomposite 3D-printed teeth can be partly attributed to the incorporation of ZNPs and SNPs nanoparticles which contribute to reduced water sorption and improved structural stability.⁴² The incorporation of nanoparticles into resin matrices can reduce water sorption because the fillers occupy free volume within the polymer network and limit the diffusion pathways available for water molecules. When nanoparticles particularly those treated with silane coupling agents are well-bonded to the resin matrix, they enhance cross-link density and reduce polymer porosity, thereby lowering the material’s affinity for water.^19,42 Another mechanism by which nanoparticles decrease water sorption is through the introduction of more hydrophobic surfaces within the resin such as SNPs, when properly silanized, create a less hydrophilic composite structure that resists water uptake.¹⁹ Such findings agree with previous studies indicating that the addition of SNP increased the fracture resistances of 3D-printed resins even after TA.^39,44 After TA in the ZNPs groups, the incorporation of 1 and 0.5 wt.% of ZNPs in ND 3D-printed resin was associated with higher fracture resistance than pure control but not prefabricated teeth. While in AS 3D-printed resins, ZNPs incorporation did not offer additional strength following TA compared to pure control, but the fracture resistance was higher than prefabricated teeth. The results found in this study may indicate that the incorporated NPs were more effective in maintaining the fracture resistance of the 3D-printed resins when compared to the pure control and prefabricated teeth.

For the elastic modulus, all the groups experienced significant reduction in their elastic modulus pre-TA compared to the prefabricated teeth, suggesting that the addition of NPs may alter the stiffness of the polymer network. The highest elastic modulus in the ND control group (3097.5 ± 115.9 MPa) indicates that the base resin formulation provides higher rigidity, which is reduced upon NP incorporation.^12,41 This decline aligns with the findings who reported that excessive ZNPs concentrations may disrupt polymer cross-linking, leading to reduced stiffness. Also, there is frequently a nonlinear relationship between the mechanical properties of composite materials and their filler content.²² Such an explanation could be applied as well when the elastic modulus values of the SNPs groups are observed. However, our findings contraindicate other studies showing that the addition of 1 wt.% SNP significantly improved the elastic modulus of 3D-printed resins compared with the control groups without the NPs.^39,44 This may suggest that other parameters could affect how NPs may influence the elastic modulus of dental materials. This study revealed that TA significantly reduced the elastic modulus for pure control and experimental groups of 3D-printed resins, and prefabricated teeth. This significant reduction is mainly related to the 3D-printed resins rather than the incorporated NPs. The reduction in elastic modulus observed after thermal aging can be attributed to several degradation mechanisms affecting resin-based dental materials. Exposure to a moist environment and repeated thermal fluctuations increased the amount of water sorption and promotes water diffusion into the polymer matrix, leading to plasticization of the resin network and a consequent reduction in stiffness and structural stability over time.^43,50,51 Similar findings were reported by Yan et al.,⁴³ and Alhotan et al.,⁴² who observed that prolonged exposure to alternating hot and cold temperatures compromises the molecular integrity of polymer-based materials. In addition, the incorporation of nanoparticles at higher concentrations may interfere with polymer chain mobility and cross-linking efficiency, resulting in a more brittle and less elastic network.⁴¹ These findings suggest that both intrinsic polymer degradation and filler–matrix interactions contribute to the observed decline in stiffness after aging, highlighting the need for further optimization of nanoparticle content to balance strength and flexibility.

Another factor that could affect the mechanical performances of 3D printed resin within the fabrication procedures is the post-polymerization conditions.^52–54 Post-polymerization conditions are critical determinants of the final physical and mechanical properties of photopolymerized dental resins.⁵³ Parameters such as light intensity, exposure duration, wavelength, and post-curing temperature significantly influence the degree of conversion (DC) and cross-link density of the polymer network.^53–55 Accordingly, optimized post-curing procedures improve polymerization efficiency and mechanical performance of 3D-printed resins, whereas inadequate post-polymerization may accelerate degradation and reduction in stiffness after aging.^53,55,56 The differences in post-curing behaviour between the ASIGA Flash unit and the NextDent LC-3D Print Box as the two curing machines do not deliver the same type or amount of energy while ASIGA uses pulsed flashes and NextDent uses continuous curing. This difference can lead to different degrees of conversion, which directly affects mechanical properties after aging. Therefore, differences in post-curing protocols between the evaluated materials may represent a potential confounding factor affecting the observed changes in elastic modulus following thermal aging.

In this study, two fracture modes are identified: brittle and ductile. The fracture mode serves as a guide for the material strength and microstructural properties.^8,9 According to SEM findings, the fracture resistance of denture teeth with a ductile fracture pattern before breakage was greater than that of teeth without this pattern, such as in the AS group. The weakened structure of the teeth, which enables them to support their weight for an extended period, appears to be the cause of such outcomes.⁸ Notably, the NextDent groups exhibited more pronounced structural degradation and surface defects following thermal cycling and staining, indicating lower resistance to aging compared to other tested resins.⁵⁷ As the material ages or is subjected to elevated temperatures, its degradation rate significantly increases.^8,9 This phenomenon was empirically confirmed by microscopic observations in form of lacking the typical embedded nanoparticles or matrix material.¹³ Similar to the findings of the current study, Chung et al.,⁹ showed that quasi-plastic materials exhibited a more gradual loss of strength than stiff materials. Furthermore, Gad et al., ⁸ illustrated that the scattered fractures in AS demonstrated that these materials have a stronger fracture resistance, which is further corroborated by their higher strengths. However, the ND materials showed a fracture mode that was characterized by an early failure dominated by brittle fractures and a lack of dispersed fractures. This implies that the strength threshold of the ND material is lower, resulting in early breaking without the progressive deformation observed in stronger quasi-plastic materials. The existence of brittle fracture modes in the ND material emphasizes the necessity of strengthening its mechanical characteristics to increase its resistance to fractures.

From a clinical perspective, the present findings suggest that NPs incorporation may enhance the mechanical performance of 3D-printed denture teeth; however, the effect appears to be influenced by both the type of nanoparticle and the resin used. Specifically, SNPs demonstrated greater improvement in strength in ND resins compared to ZNPs, while both NPs showed comparable effects in ASIGA resins at similar concentrations, highlighting the importance of material type and NPs compatibility in optimizing outcomes. As this study considered one of the early investigations exploring nanocomposite 3D-printed denture teeth, these results should be interpreted with caution due to the inherent limitations of in vitro studies. Nevertheless, the observed increase in fracture resistance indicates a potential clinical benefit in reducing the risk of denture fracture, particularly in high-stress regions. Conversely, the reduction in elastic modulus following thermal aging suggests possible long-term limitations in structural stiffness and durability, emphasizing the need for further material optimization and long-term evaluation. Within these constraints, nanoparticle-reinforced 3D-printed resins especially those containing 0.5–1 wt.% SNPs or ZNPs may be considered promising candidates for denture tooth fabrication in cases subjected to elevated occlusal forces, although additional clinical and fatigue-based studies are recommended before definitive clinical adoption. The lower elastic modulus observed, may contribute to a more favourable stress distribution under masticatory forces, potentially reducing the risk of debonding or microfracture at the tooth/base interface. These findings should be interpreted within the limits of this in‑vitro investigation, and no clinical applications can be inferred at this stage. Additional investigations particularly those evaluating wear behaviour, abrasion resistance, antagonist interactions, and long‑term functional performance are required before considering any potential clinical use of reinforced 3D‑printed denture teeth.

Despite the important findings of this study, some limitations exist such as the study focused on two types of NPs, narrow range of NP concentrations, and nanoparticle dispersion was achieved through thermal stirring and mechanical shaking, without the use of ultrasonication. Regarding the FTIR analysis, only a randomly selected subset of specimens was evaluated, which limited the ability to fully assess the degree of conversion across all samples. Consequently, the FTIR results should be viewed as supportive qualitative findings rather than a comprehensive measure of polymerization behaviour. Although thermal aging in present study, the absence of extended aging protocols and fatigue testing represents an important limitation. Without long-term aging, essential information on material performance over prolonged periods is lacking, which may lead to an overestimation of their longevity and reliability. Likewise, fatigue testing is crucial for identifying failure patterns that emerge only under repeated loading. Based on listed study limitations, future studies should investigate the effects of different nanoparticle types and concentrations in various tooth-resin systems, incorporate ultrasonication during NPs/resin mixing, and include the degree of conversion evaluation as an indicator of mechanical performance. Additionally, conducting all tests under conditions that more closely simulate the oral environment is recommended. At the printing-technology level, further research is needed to clarify the interactions between nanoparticle content, 3D-printing parameters, and the resulting fracture resistance of these materials in dental applications.

Conclusions

In conclusion, this laboratory study demonstrates that incorporating ZNPs and SNPs improved the fracture resistance of the tested denture base materials under controlled experimental conditions. Thermal aging significantly reduced the fracture resistance and elastic modulus of most nanoparticle-reinforced groups, except for specific concentrations in both materials. Among the tested formulations, AS showed the most favourable fracture resistance profile within the limits of this in-vitro setup. These findings reflect material behaviour under single-load fracture testing and short-term aging; therefore, further research including fatigue loading and long-term aging is required before drawing conclusions about clinical performance.

Ethics and consent

Ethical approval and consent were not required.