Correction: A micro-CT–integrated 3D simulation framework reveals fluid transport mechanisms and void dynamics in root canal fillings

Correction to: Scientific Reportshttps://doi.org/10.1038/s41598-026-43796-y, published online 10 March 2026 The original version of this Article contains a repeated error, where the expression ‘biomaterials’ was incorrect. As a result, the title, “A micro-CT–integrated 3D simulation framework reveals fluid transport mechanisms and void dynamics in root canal biomaterials” now reads: “A micro-CT–integrated 3D simulation framework reveals fluid transport mechanisms and void dynamics in root canal fillings” Furthermore, in the Abstract, “A micro-CT–integrated three-dimensional simulation framework (3D-SALAM) was developed to address the long-standing limitations of destructive, poorly reproducible leakage tests traditionally used to evaluate the sealing performance of root canal biomaterials.” now reads: “A micro-CT–integrated three-dimensional simulation-assisted leakage analysis methodology (3D-SALAM) was developed to address the long-standing limitations of destructive, poorly reproducible leakage tests traditionally used to evaluate the sealing performance of root canal fillings.” Additionally, “This proof-of-concept study demonstrates that 3D-SALAM enables reproducible, quantitative, and mechanistic mapping of fluid dynamics in complex biomaterial architectures.” now reads: “This proof-of-concept study demonstrates that 3D-SALAM enables reproducible, quantitative, and mechanistic mapping of fluid dynamics in complex root canal filling architectures.” and, “The framework’s adaptability also extends its relevance to a wide range of porous and composite biomaterials in regenerative medicine and biomedical engineering, where void connectivity and capillary behaviour critically influence long-term performance.” now reads: “The framework’s adaptability also extends its relevance to a wide range of porous and composite fillings in regenerative medicine and biomedical engineering, where void connectivity and capillary behaviour critically influence long-term performance.” Furthermore, in the Introduction, “While the combination of micro-computed tomography and image-based numerical simulation has long been established in fields such as the geosciences and porous media research³⁵, its application to endodontic biomaterials presents distinct challenges related to anatomical complexity, material heterogeneity, wettability, and clinically relevant transport conditions.” now reads: “While the combination of micro-computed tomography and image-based numerical simulation has long been established in fields such as the geosciences and porous media research³⁵, its application to endodontic fillings presents distinct challenges related to anatomical complexity, material heterogeneity, wettability, and clinically relevant transport conditions.” Finally, in the Conclusion, “This study introduced and validated the micro-CT–integrated three-dimensional simulation framework (3D-SALAM) as a non-destructive and reproducible method to investigate how void geometry, surface wettability, and flow dynamics determine fluid transport within root canal biomaterials.” now reads: “This study introduced the micro-CT–integrated three-dimensional simulation framework (3D-SALAM) as a non-destructive and reproducible method to investigate how void geometry, surface wettability, and flow dynamics determine fluid transport within root canal fillings.” Moreover, “Beyond endodontics, the framework offers broad applicability to other porous and composite biomaterials—including restorative interfaces, bone scaffolds, and implant junctions—where fluid dynamics and interfacial stability are critical to longevity.” now reads: “Beyond endodontics, the framework offers broad applicability to other porous and composite dental materials—including restorative interfaces, bone scaffolds, and implant junctions—where fluid dynamics and interfacial stability are critical to longevity.” and, “In essence, 3D-SALAM transforms static imaging into a predictive, mechanistic tool for studying fluid–material interactions, laying the foundation for more reliable evaluation and design of next-generation biomaterials.” now reads: “In essence, 3D-SALAM may transform static imaging into a predictive, mechanistic tool for studying fluid–material interactions, laying the foundation for more reliable evaluation and design of next-generation dental materials.” Lastly, the description text of panel K was omitted from the legend of Fig. 3. The Legend now reads: “Transport behaviour in water-filled teeth under different pressure conditions. (a–c) Temporal progression of tracer concentration under applied pressure. Transport was dominated by convective flow, with rapid passage through larger interconnected voids and marked concentration gradients between high-flow pathways and adjacent stagnant regions. (h) Flowline visualisation showing the primary liquid streamlines through larger voids in contrast to slower movement along cavity margins. (i) Integral statistics of tracer concentration across the entire void space at selected time points, expressed as median, quartiles, and extremes. The box represents the interquartile range, whiskers indicate the minimum and maximum values, and the bold line denotes the median concentration. (d–f) Tracer distribution under diffusion-only conditions (no applied pressure), showing more uniform mixing across voids and reduced concentration gradients due to molecular diffusion. (g, j) Probe-based measurements of tracer concentration over time at two locations: one in a well-connected region of the void space (green) and the other in a stagnant zone (red). Under applied pressure (g), clear discrepancies emerged between the two sites, reflecting the influence of void geometry on spatially heterogeneous transport. Shaded areas indicate local variability around the measurement points. (k) Integral statistics of tracer concentration across the entire void system at selected time points, presented as median, quartiles, and extremes, illustrating temporal changes in overall distribution patterns. “ The original Article has been corrected.