The following sections present the data on the physical and mechanical properties of the CRMs studied, followed by the porosity results obtained (gas adsorption test (N2) and by means of the SEM image analysis process), exploring for each case their correlation, linkage, or general incidence.
3.2. Porosimetry by N2 Adsorption
Gas adsorption (N
2) is an appropriate technique to characterize pore sizes and distribution mainly in the range of mesopores (from 2 to 200 nm) [
37], gel pores (<10 nm), and capillary pores (10 to 50 nm) [
41,
42]; Therefore, for an investigation in mortars, this can be considered the most approximate, accurate, and adequate. Gas adsorption measurements have been extensively used to determine the surface area and pore size distribution of an important variety of solid materials—among which construction materials are also included [
36]. On the other hand, total pore volume and pore size distribution are also common techniques used to describe the porosity of materials; the latter being a distribution of pore volume with respect to pore size [
39]. The results of the different variables (besides porosity) obtained by this technique are presented below.
The N
2 adsorption isotherms for the samples studied (ratio of the amount of adsorbed molecules with respect to the pressure at constant temperature) are shown in
Figure 5 (the letter “A” at the end of the name corresponds to the adsorption phase; and the letter “D” to desorption, respectively)—sample CRM30 could not be included due to contamination of the sample. It can be seen that CRM100 reports the highest adsorbed amount for all pressures with respect to the rest of the samples, and in the same figure (upper left enlargement) it can also be appreciated that for low pressures (beginning of the curves) and in general, the adsorbed amount presents an increase related to the highest amount of CA in the CRMs, where the UM (0% CA) is the one that presents the lowest values. With regard to high pressures (end of the curves), which is observed in the upper right enlargement of the same figure, the amount adsorbed continues to be higher for CRM100 (65.9 cm
3/g); for the rest of the mortars, adsorption caused similar amounts (values from 32.35 to 35.84 cm
3/g)—the UM being the one with the highest amount. According to the way the hysteresis was presented, it can be said that to remove the gas from the sample, lower pressure was necessary; however, for relative pressures of 0.5 (approx.) in all samples, the amounts of gases decreased, so desorption becomes slower. From the data provided in the isotherms, the surface area of the solid, the size and its descriptive pore parameters, its distribution, etc. were calculated.
With this technique, it is feasible to measure the surface area of solids; and for which the data in
Figure 5 [
43] are used, in particular those of the low relative pressure region (P/P
o from 0 to 0.30). The calculation is carried out using the BET method, since it is a used and established approach to determine the surface area of solid materials, especially those with different open porosity [
37].
The results obtained are shown in
Figure 6. In this figure it can be observed that the surface area values present, in general terms, an increase related to the increase of the percentage of CA in the CRMs. CRM100 has the highest surface area with respect to UM, with a difference of 5.05 m
2/g (73% higher). According to the above, and due to its greater surface area, it can be affirmed that CRMs have greater porosity, which increases as a function of the CA content [
36]. In a previous study, similar behavior was observed (case of concrete with recycled concrete aggregates); in which the surface area increased in relation to the increase in the percentage of recycled aggregate in the mixes (and higher than the reference concrete) [
41].
Total pore volume and pore size distribution are two common techniques also used to describe the porosity of materials [
39].
Figure 7 shows the pore size distribution curves, which indicate the accumulated pore volume as a function of the average pore diameter of the different CRMs studied and the reference UM (adsorption and desorption phase, respectively).
Figure 7a shows that CRM100 is the one that contains significantly higher pore volume, with an accelerated increase of pore volume in the pores with diameters between 20 and 150 nm; while the rest of the mortars contain about 48% lower volume; the general trend of pore volume increase is a function of the percentage of CA in the CRMs. In the desorption phase (
Figure 7b), the same order in the behavior of the CRMs is presented; however, the decrease in volume is reflected in smaller pore diameters included between 10 and 70 nm.
The above graphs provide the porosity of the CRMs, which is expressed as cumulative pore volume (cm
3/g) and are presented in
Table 5. The above porosity values have a similar trend to the values obtained by means of the open porosity test (
Table 4). By the N
2 adsorption technique, the average superior difference of CRM100 with respect to the rest of the mortars is 48% (both in the adsorption and desorption phase), while that obtained by open porosity is 40%.
Regarding the size distribution (diameter) of pores defined by IUPAC (International Union of Pure and Applied Chemistry), pores can be classified into: micropores (pore < 2 nm), mesopores (between 2–50 nm) and macropores (pore > 50 nm) [
36,
37].
Figure 8a shows that the highest porosity percentages of all mortars are found in the macropore zone, with an average difference of 25%, with respect to mesopores and 62% of micropores; in which the rest of the gas was introduced. However, in the desorption phase (
Figure 8b), it is indicated that the highest porosity is represented by mesopores, with an average difference with respect to macropores of 27%, and 64% with respect to micropores.
Research on two types of mortars with 100% CA (with fine aggregate and coarse aggregate) reported that the mortar with fine aggregate (similar particle sizes to this study), showed higher porosity in general than the mortar with coarse aggregate (particles larger than 150 μm). Regarding the distribution of pore sizes, the mortar with fine aggregate presented a lower amount of macropores and a higher amount of mesopores with respect to the reference mortar. The above was attributed to the own porosity of the CAs (these influence the microstructure of the mortar when it is finely ground) [
17]. Therefore, this research presented similar behaviors to those obtained here—in particular with desorption data.
From complementary information obtained from the gas adsorption technique, and in particular from the pore size distribution curves (
Figure 7), several categories of pore radius can be identified. In
Table 6 (adsorption and desorption phase, respectively), the results of the maximum radius (
rmax), minimum radius (
rmin), average radius (
rave), medium radius (
rmed) and critical radius (
rcri) are provided; a description of each is given below.
The rmax and rmin establish the maximum and minimum radius corresponding to each variable; these were obtained directly from the reports provided by the test equipment. The rmax values are in the range of 87.74 to 103.57 nm (adsorption phase), and 91.92 to 122.47 nm (desorption phase); while those of rmin, established radius in the range of 0.91 to 0.92 nm (adsorption phase), and 0.91 to 1.63 nm (desorption phase). As can be seen in the table, these did not show any relationship with respect to the CA content.
The rave was obtained by dividing by two the average diameter value calculated with the equation 4V/A (where V = cumulative pore volume, and A = cumulative pore area). The data are obtained with the BJH method (diameters between 17 and 3000 Å). The values obtained show similar behavior to the porosity calculated by N2 adsorption, which is an increase with the percentage of CA (without considering those of the UM sample), and with similar values in mortars with CA substitutions of up to 50%, as well as a notable increase in the mortar with total replacement of the NA.
The
rmed corresponds to the radius determined by a Lagrange interpolation of the closest points corresponding to 50% of the total volume of each sample [
44,
45]; obtaining these from the pore size distribution of the test.
Table 6 shows that the
rmed varies from 29.22 to 37.89 nm, and from 16.88 to 21.52 nm (adsorption and desorption phase, respectively) for the different study variables.
The
rcri, or critical pore, is the term given to the corresponding radius that causes the onset of the maximum slope in the curve of pore radius versus the pore volume differential (
dV/
dlogD). This pore radius is usually an indicator of the microstructure of the material and is used to detect a variety of materials [
44]. The method for its determination consists of detecting the maximum peak in the pore size versus
dV/
dlogD curve [
14,
45,
46]. This also indicates the minimum radius of continuous pores within the material [
47]; that is, it establishes the space capable of being filled without forming any other adsorption pathway [
45,
46].
Figure 9 shows the graphs—for adsorption and desorption stages—in which the maximum peak of the curve (with respect to the ordinate axis) is observed; when crossed with the abscissa axis, it establishes the
rcri. As an example, that of the variable MCR100 is shown in
Figure 9a).
Using the data of the mechanical properties of the CRMs (
Table 4), a correlation analysis and equation fitting were performed in order to establish the dependencies of these with respect to the different porosity variables obtained by the N
2 adsorption technique (
Table 6). The criteria established to define the adjusted equation were as follows: (a) A coefficient R
2 as close to 1 (R
2 ≅ 1), (b) The type of equation selected should generate a curve plot coincident to the points of the related variables.
For the properties of
fm,
E and
density of the CRMs, it was established that the best fit was with the variable of rave porosity (in the adsorption phase); the type of fitting equation was that of a second-degree polynomial equation (see
Figure 10). In this equation, the R
2 values and the equations for fitting the data for the three CRM properties are indicated, with a range of validity of application established between CRM10 and CRM100. In the three equations, the UM sample is isolated from the analysis, as it establishes inconclusive values for the study, which may have their origin in aspects inherent to the test or to its degree of precision (nm).
The rave, as an evident representative parameter (central tendency) of the porosity of the CRMs, meets the expectations of its capacity to link the physical-mechanical behavior of the mortars under study to their porosity. Therefore, an increase in rave is related to losses in fm and density, with CA causing the increase in rave, which in turn produces a weaker CRM matrix structure. On the other hand, the nature of the type of equation established (second order polynomial) may suggest the existence of another variable not included in this study, which could be the cause of the nonlinearity in the equation. Finally, the existence of a significant change in the plotting of the curves between the CRM50 and CRM100 variables is notorious, and is worthy of future studies to establish the continuity of behavior for the percentages of CA between them.
As for the adsorption and
drying shrinkage properties, these established a better linkage with the
rmax porosity variable (adsorption phase), obtaining significant R
2 with second-degree polynomial type equation curves as shown in
Figure 11. As in the previous case, their application is valid for the range between CRM10 to CRM100, as well as the assumption of another variable not included in the study.
In this case, it seems that the existence of large pores in the CRM matrix is what best explains the behavior of these two properties—both intrinsically involve, in their respective behavioral phenomena, the ability of water mobility between the exterior and interior of the matrix; therefore, the existence of these large pores seems to provide the conditions that promote these behaviors, the increases in the CA in the CRM being what favors the increase in their size.
From the results of the BET surface area property with respect to the physical and mechanical properties of CRMs,
density,
E, and
absorption obtained R
2 > 0.9; while for
fm and
drying shrinkage were 0.89 and 0.79, respectively. All the fitting equations were of the second-degree polynomial type. On this occasion they are valid for all the research variables—dispersion of variables according to expectations (
Figure 12).
3.5. Correlations between Porosimetry Techniques
With the results obtained from the three different porosimetry techniques, it was determined which of these offered a better correlation with the physical and mechanical properties of the CRMs. From the previous results, it was observed that the most significant correlations between the different porosity values were presented with the data obtained from the open porosity—the simplest, most direct method and the one that establishes a more representative sample of the matrix of a mortar. The results of total porosity—the only common result comparable among the study techniques for the three techniques—are presented in
Figure 16 (porosity by N
2 is included in the adsorption and desorption phase—both very similar). In this graph, it has been chosen to present the results in percentage to simplify the comparison; thus, allowing making visible the same behavior of porosity increase between the study variables (CA content) and the techniques used.
To numerically validate the previous results of total porosity of the CRMs, taking into account the different experimental techniques of their determination, the correlations with the data obtained with the same were analyzed. It was observed that the comparison between open porosity and N
2 porosity (desorption phase) resulted in a coefficient R
2 = 0.9881 (second-degree polynomial) (
Figure 17); which shows the affinity between both techniques, and also corroborates the incidence of the use of CA in the behavior of the CRMs.
In accordance with the above, and with the objective of establishing the optimal technique to use—or in its case to establish the hierarchical order of importance in the selection of the technique when porosity is to be established, it is determined that the open porosity technique is the one that provides more reliable data (in addition to doing so with a minimum processing of the samples). Then, the N2 adsorption analysis technique should be used as a second alternative (verification of the first one, or with the contribution of special and different porosity parameters, which can help to better explain the mechanical and physical behavior of CRMs); although it is true that its requirements for laboratory equipment and its representativeness of the samples are more important and complex. Finally, as a third option, porosity by SEM image analysis would be the last of the three techniques; this limitation of choice is due to the fact that its numerical determination may involve factors such as: the choice of the image for its study, its representativeness of the complete mortar matrix, its study scale factor, its requirements of specialized laboratory equipment and its own complex sample preparation.
As additional information in this study, it is suggested that the optimum percentage of CA to be used in CRMs is 20%. Taking into account the porosity results obtained by the three techniques, it was observed that for each of them, the CRMs presented similar behavior —increased porosity, with increased CA content, particularly with the open porosity and N2 porosity techniques; however, although this information is relevant, it prevents choosing the adequate percentage of CA. Therefore, with knowledge of the physical and mechanical properties of CRMs, the fm results (property considered important or representative in mortars and concretes) were taken as an indicator for such decision. According to the information presented in the present study, it is considered that the use of up to 20% of CA in CRMs will guarantee a similar behavior to UMs, having as an added value the environmental benefits that the use of CA entails (as previously mentioned in the introduction).