The properties of composite materials are highly dependent on the fiber and matrix fraction and on the porosity resulting from micro voids. This paper addresses void content characterization and the constituent content of composite materials by resorting to a comparison of destructive and non-destructive methods. The work presents the detailed procedures of two destructive methods, using acid digestion of epoxy resins matrices, and compares their processes. It also presents the results of a non-destructive method, by means of Micro Computed Tomography (MicroCT). The results of both destructive and non-destructive methods are compared, and a recommendation is made based on the application and the type of composite being analyzed. The MicroCT showed better and more consistent results in detecting voids in the material, while the acid digestion tests provided better results about the fiber and matrix percentage. Exported results from the MicroCT scanning with actual locations of voids were used in numerical analysis, to examine the feasibility of using them, whether by developing models that map damage in the proximity of the void, or by developing models that predict the properties of the entire material with respect to the content, shape, and distribution in the material.

Technological advances have made it possible to examine dental resin composites using 3D nanometer resolution. This investigation aims to characterize existing dental nano-hybrid and micro-hybrid resin composites through comparing and contrasting nano-computed tomography (nano-CT) with micro-CT and high-resolution SEM images. Eight commercially available and widely used dental resin composites, 2 micro-hybrid and 6 nano-hybrid were researched. Cured samples were examined and characterized using nano-CT (resolution 450 nm) and compared with micro-CT images (resolution 2 µm). Acquired images were reconstructed and image analysis was carried out to determine porosity and pore morphology. A comprehensive comparison of scanning micrograph images unsurprisingly revealed that the nano-CT images displayed greater detail of the ultrastructure of cured dental resin composites. Filler particle diameters and its volumes were lower when measured using nano-CT, porosity being higher where analysed at higher resolution. There were large variations between the examined materials. Fewer voids were found in Tetric EvoCeram and IPS Empress Direct, the smallest pores being found in Universal XTE and Tetric EvoCeram. Nano-CT was successfully used to investigate the morphology of dental resin composites and showed that micro-CT gives a lower porosity and pore size but overestimates filler particle size. There were large discrepancies between the tested composites. Evidence of porosities and pores within a specimen is a critical finding and it might have a detrimental effect on a material’s clinical performance.

Experimental dental resin composites containing copper-doped mesoporous bioactive glass nanospheres (Cu-MBGN) were developed to impart anti-bacterial properties. Increasing amounts of Cu-MBGN (0, 1, 5 and 10 wt%) were added to the BisGMA/TEGDMA resin matrix containing micro- and nano-fillers of inert glass, keeping the resin/filler ratio constant. Surface micromorphology and elemental analysis were performed to evaluate the homogeneous distribution of filler particles. The study investigated the effects of Cu-MBGN on the degree of conversion, polymerization shrinkage, porosity, ion release and anti-bacterial activity on S. mutans and A. naeslundii. Experimental materials containing Cu-MBGN showed a dose-dependent Cu release with an initial burst and a further increase after 28 days. The composite containing 10% Cu-MBGN had the best anti-bacterial effect on S. mutans, as evidenced by the lowest adherence of free-floating bacteria and biofilm formation. In contrast, the 45S5-containing materials had the highest S. mutans adherence. Ca release was highest in the bioactive control containing 15% 45S5, which correlated with the highest number of open porosities on the surface. Polymerization shrinkage was similar for all tested materials, ranging from 3.8 to 4.2%, while the degree of conversion was lower for Cu-MBGN materials. Cu-MBGN composites showed better anti-bacterial properties than composites with 45S5 BG.

X-ray micro-computed tomography (micro-CT) is an advanced technique able to provide a comprehensive examination of the volumetric characteristics of asphalt mixtures. A key step for the air void (AV) quantification using micro-CT images is the segmentation, which is a stage of the digital image processing. The most common segmentation technique, the manual threshold (TH) selection, depends significantly on the operator skills, image homogeneity, and material complexity. These factors that can limit the reproducibility of the TH procedure. Machine learning and deep learning recently appeared as promising alternatives to solve this challenge. In this paper, images of an asphalt concrete (AC) specimen were acquired in a modern high-resolution micro-CT scanner to determine its AV content using four different segmentation tools, i.e. TH, watershed, machine learning, and deep learning. All methods presented similar results for the total AV content. The advantages and limitations of using each technique were discussed in terms of computational effort, user-friendliness, and accuracy of the results. Machine learning and deep learning were identified as powerful tools for AC segmentation, being accurate and easy to adjust, however taking longer data processing times.

Innovative strategies for periodontal regeneration have been the focus of research clusters across the globe for decades. In order to overcome the drawbacks of currently available options, investigators have suggested a novel concept of functionally graded membrane (FGM) templates with different structural and morphological gradients. Chitosan (CH) has been used in the past for similar purpose. However, the composite formulation of composite and tetracycline when cross-linked with glutaraldehyde have received little attention. Therefore, the purpose of the study was to investigate the drug loading and release characteristics of novel freeze gelated chitosan templates at different percentages of glutaraldehyde. These were cross-linked with 0.1 and 1% glutaraldehyde and loaded with doxycycline hyclate. The electron micrographs depicted porous morphology of neat templates. After cross-linking, these templates showed compressed ultrastructures. Computerized tomography analysis showed that the templates had 88 to 92% porosity with average pore diameter decreased from 78 to 44.9 μm with increasing concentration. Fourier transform infrared spectroscopy showed alterations in the glycosidic segment of chitosan fingerprint region which after drug loading showed a dominant doxycycline spectral composite profile. Interestingly, swelling profile was not affected by cross-linking either at 0.1 and 1% glutaraldehyde and template showed a swelling ratio of 80%, which gained equilibrium after 15 min. The drug release pattern also showed a 40 μg/mL of release after 24 h. These doxycycline-loaded templates show their tendency to be used in a functionally graded membrane facing the defect site.