## 2 Materials and Methods
To analyze the microstructural evolution within the interphase between the hardening overlay made of cement mortar and the existing concrete substrate, the exposure time was kept as low as possible in order to reduce the total duration of the experiments. Using the described setup, each scan took approximately 110-120 min. It was an acceptable timescale for the study of the microporosity changes in the concrete within the interface. Thus, the measured microporosity value is the average of this time period. An initial attempt to scan a sample just after preparation gave unsatisfactory results, which was due to a faster evolution of the microstructure than the scanning time. A decrease in the total scan duration is possible by reducing the exposure time and the number of projections, although this would result in increased artefacts and reduced contrast in the reconstructed images. Therefore, the scanning parameters were chosen in order to minimize the scan duration while at the same time keeping a sufficiently high quality of the images. In addition, the short scanning time allowed a reduction of the thermal load to the sample due to the higher temperature in the micro-CT chamber during the scan compared with the ambient temperature (up to 28 \({}^{\circ}\)C). This minimized water evaporation and unnatural changes within the fresh paste. A reconstruction of the obtained projections was made using NRecon 1 (Version 1.7.0.4, SkyScan, Kontich, Belgium) based on the Feldkamp algorithm [60]. To analyze the same test specimen at different time periods, it is important to use the same parameters during the scanning and reconstruction. After reconstruction, the 3D images were set together according to the reference scan (at 3 h) using 3D registration in DataViewer 1 (Version 1.5.2.4, SkyScan, Kontich, Belgium). In order to avoid the boundary effect [61], only a part of the 3D image was used for further analysis in CTAnalyzer 1 (Version 1.16, SkyScan, Kontich, Belgium). The microstructural changes occurring within a volume of interest (VOI) were evaluated by analyzing the same portion of each sample at different ages and then comparing the variations of microporosity in the tomographic images along the sample height. For that purpose, rectangular VOIs were accurately selected at identical positions from each 3D dataset. The width of the VOIs was equal to 1000 \(\times\) 1000 voxels (voxel size = 8.0 \(\upmu\)m), while the vertical extent was limited to 1250 slices. From a statistical point of view, the examined volumes can be considered representative for the overlay (the main objective of this study), taking into account the size of the air voids and aggregates in the overlay. The porosity analysis was followed by filtering and binarization of the images for a predetermined threshold value (the same for all scans), due to which it was possible to calculate the microporosity \(\phi\) defined as  
\[\phi=\frac{V_{V}}{V_{T}} \tag{1}\]  
Figure 2: View of **(a)** the X-ray micro-CT (micro-computed tomography) with a sample placed on a tripod; **(b)** the scheme of the sample element prepared for tests using the micro-CT method; **(c)** a fragment of the 3D image of a microstructure subjected to further analysis. where \(V_{V}\) is the volume of void-space (micropores), and \(V_{T}\) is the total or bulk volume of material, including the solid and void components. Due to the size of the sample and the duration of the measurement, the obtained resolution only allows microporosity to be measured. [PERSON] et al. (2017) clearly showed that the measured porosity content and pore connectivity are strongly affected by the voxel size, and in particular that the segmented porosity decreases with increasing voxel size. Thus, the obtained values of microporosity will be lower compared to the overall macroscopic porosity values.