3.1. XRD Analysis
In an attempt to understand how the amount of the external liquid affects the mechanochemical synthesis of Cu
3(BTC)
2, a mixture of ethanol and deionized water, ranging from 0 μL to 1500 μL, was added to the solid reactants prior to being ground for 10 min. To compare with similar studies [
9,
20,
22], the ratio of the liquid volume to the mass of the reactants, as defined by η [
27], was calculated and varied from 0 μL/mg to 0.777 μL/mg in the current study, as shown in
Table 1. Anhydrous Cu(OAc)
2 rather than hydrated Cu(OAc)
2⋅H
2O, which is commonly used as the metal salt in most of the published studies, was chosen in order to exclude the influence of internal liquid—water from hydration on the reaction products.
Figure 1 includes the XRD patterns for the initial reactants and the final products with various amounts of liquid (the liquid is always referred to as the external one from this point, unless noted otherwise). For the sample without any liquid added (NG), its XRD pattern (labeled as “None”) shows very broad peaks, indicating that the products after the NG process are mainly amorphous phases. Based on the locations of the characteristic peaks in the XRD patterns, coupled with the FT-IR results from our previous study [
8], it can be confirmed that the products in this sample contain Cu
3(BTC)
2, though they have a low degree of crystallinity. Unreacted H
3BTC also likely exists in this sample after grinding because the peak at 2θ = 24.6° in its XRD pattern overlaps with the strongest peak of H
3BTC near this location, indicative of the aforementioned possibility. As shown by the other XRD patterns in
Figure 1, the samples with liquid added prior to grinding (LAG) have much more defined and narrower peaks, which is a clear indication of a much higher degree of crystallinity. The three pronounced peaks located at 2θ = 11.9°, 13.8° and 19.4° in these XRD patterns are consistent with those reported for Cu
3(BTC)
2 [
9,
10,
18], which confirms the successful formation of crystalline Cu
3(BTC)
2 by LAG. It is also noted that among all the samples being studied, the one with 1000 μL of liquid shows the highest intensity for the strongest peak at 2θ = 11.9°. A quantitative analysis of the full width at half maximum (FWHM) of this characteristic peak was conducted for all the LAG samples to estimate their crystallite size using the Scherrer equation based on Bragg’s law. The corresponding results in
Table 1 illustrate the continuous improvement in the crystallinity of the products when the amount of added liquid increases. The crystallite size of the sample prepared with 50 μL of liquid, for instance, is about 20 nm. It then reaches 34 nm and 38 nm when 400 μL and 1000 μL of liquid are added, respectively. However, the sample prepared with 1500 μL of liquid shows a somewhat decreased crystallite size of 30 nm. It is also noteworthy that the samples with 800 μL and 1000 μL of liquid display a close similarity in their microstructure and textural properties, as shown in
Figures S1 and S2. Therefore, only the latter is detailed in this paper.
In general, the successful synthesis of MOFs, such as Cu
3(BTC)
2, involves three elementary steps occurring in parallel and/or in series: (i) the deprotonation of ligands and dissociation of metal salts, (ii) the assembling of metal clusters, and (iii) the complexation of metal ions/clusters by the ligands to assemble a coordination motif, often referred to as secondary building unit (SBU). In the case of Cu
3(BTC)
2, a paddlewheel-shaped SBU is built up of four benzene-1,3,5-tricarboxylate linkers coordinated with two copper metal centers. As explained in our previous study [
8], copper (II) acetate or its monohydrate is often preferred over other copper salts in the mechanochemical synthesis of Cu
3(BTC)
2. This is because of the fact that copper (II) acetate already adapts to a paddlewheel structure and, therefore, is thermodynamically favored to form Cu
3(BTC)
2 over other copper salts. After the secondary building units are formed in the reaction, the MOFs will then be constructed by repeating such units in three dimensions to form crystalline structures with pores dispersed in between.
The above-mentioned XRD results of Cu
3(BTC)
2 show that the addition of a liquid prior to grinding facilitates the formation of crystalline Cu
3(BTC)
2 during the mechanochemical synthesis. This could be explained by examining how those elementary steps of the reaction are affected when liquid is added. From a thermodynamic point of view, the presence of liquid facilitates the deprotonation of H
3BTC ligands and dissociation of Cu(OAc)
2 salts by solvation since such processes are much more thermodynamically favored to occur in the quasi-liquid state of reactants over their solid-state. The liquid serves as a reservoir for the deprotonated anionic ligands and cationic metal ions. It is also noted that, based on their solubilities, Cu(OAc)
2 and H
3BTC are both saturated with the liquid added to each sample of this study. Therefore, the complexation of Cu
3(BTC)
2 SBU and eventually the formation of three-dimensional crystalline structures are also thermodynamically favored under such conditions where the MOF-forming components are saturated. From a kinetic point of view, the presence of liquid enhances the mobilities of these MOF-forming components and consequently improves the reaction rate as well as the crystallinity of Cu
3(BTC)
2. Such thermodynamical and kinetic interpretations are consistent with what we observed from the XRD results. As shown in
Figure 1, the NG sample has an incomplete formation of Cu
3(BTC)
2 after 10 min of grinding, while all the LAG samples have the opposite results. Moreover, the former is amorphous, indicating that only a short range of repeating SBUs exists in the sample. On the other hand, the latter are all well-defined crystalline structures, and their crystallite size increases from 20 nm (50 μL is added) to 38 nm (1000 μL is added) as a result of the thermodynamically and kinetically favored conditions for LAG vs. NG. Notably, the sample with 1500 μL of liquid shows a decrease in the crystallite size. It was observed that this sample appeared as a slurry after grinding, while all the other samples remained powdery. This may indicate the possibility of a different reaction pathway than LAG under this particular condition.
3.2. SEM Analysis
The SEM images were collected to further analyze the effect of the amount of liquid on the morphology of as-synthesized Cu
3(BTC)
2.
Figure 2 includes a group of such images for the samples with 0, 400 and 1000 μL of liquid added prior to grinding. Under low magnification, as shown in
Figure 2a,c,e, all three samples contain agglomerates. The occurrence of agglomerates is common in ground samples, which experience ball/powder collision, repeated deformation, and fracture and, therefore, contain many fresh surfaces. As a result, ground samples tend to agglomerate.
In mechanochemistry, agglomerates are often called secondary particles [
30], as they are agglomerated from smaller primary particles, as illustrated by a schematic diagram in
Figure 3. In most cases, the primary particles are either a single crystal or polycrystal in nature. The average size of the crystallites in these particles can be estimated by the Scherrer equation based on the XRD results, as discussed earlier. The term of “particle” is referred to as the counting units of the samples rather than their morphology since mechanochemical synthesis does not lead to powder samples, the shape of which is as well-defined as a solvothermal one.
Figure 2b,d,f show the more detailed morphology of the primary particles for the three aforementioned samples. The NG sample (
Figure 2b) is characterized by many flake-like primary particles in the agglomerates. This suggests repeated deformation caused by ball/powder collision during grinding. When 400 μL of liquid is added to the sample, the majority of the resultant primary particles adopt whisker-like shapes, as shown in
Figure 2d. They are estimated to be a few hundred nanometers in diameter and are the finest among these three samples. When 1000 μL of liquid is present, rod-like primary particles are dominant in the agglomerates, as shown in
Figure 2f. The cross-sectional areas of these rods are approximately 1 μm in diameter, which are much larger than those seen in the sample synthesized with 400 μL of liquid.
It is known that the size of the particles resulting from the grinding process is mainly determined by two competing events: particle breakage and agglomeration of the newly created particle fragments [
31]. Such an observation also applies to mechanochemical synthesis, where the grinding process leads not only to the pulverization of raw reactant materials, but also to the induction of chemical reactions between raw materials. The addition of a liquid to the reactants prior to grinding plays an important role in affecting the dominance level between these two competing events. When such an amount of liquid is added that particle breakage is dominant, it can result in a low degree of agglomeration in the products and, therefore, smaller primary particles. This is mainly because of the following: (i) the liquid phase wets particles and thus separates them from each other to suppress agglomeration, which then enhances particle breakage; (ii) the liquid phase also acts as a mechanical impact sink [
32], which absorbs the mechanical energy caused by the ball/powder collision and, in turn, lowers the local temperature of the particles. A lower temperature alleviates the tendency of agglomeration. This is why, when these impacts are prominent in grinding, particle breakage tends to be dominant over the agglomeration. Such a scenario can be applied to explain the sample with 400 μL of liquid, which contains smaller particles in comparison to the one without any liquid involved.
As the amount of added liquid increases beyond 400 μL and reaches 1000 μL, however, the results show that the dominance between those two events reversed as the agglomeration becomes dominant. It is believed that there are two main reasons for what caused such a change: (i) With more liquid added, the ball/powder collision continues to be further alleviated so that the mechanical impact may not be strong enough to break the agglomerated particles as frequently as is the case with a smaller amount of added liquid. (ii) In the discussion of XRD results, it was found that the crystallite size of the sample with 1000 μL of liquid was larger when compared to the one with 400 μL. This is attributed to the continuous enhancement in the mobilities of the MOF-forming components and the rate of mass transfer among those components as more liquid is added to the samples. Such enhancement occurs not only inside the primary particles, but also across the primary particles. The former mainly contributes to crystallite growth, while the latter contributes to the agglomeration of the primary particles. As a result of these combined impacts, the agglomeration of particles is believed to be favored over particle breakage under such conditions, as is seen in the sample with 1000 μL of liquid.
3.3. N2 Adsorption/Desorption Analysis
As shown in
Figure 4, the N
2 adsorption/desorption isotherms were collected at −196 °C to examine the surface areas and porous properties of the Cu
3(BTC)
2 samples. These isotherms can be categorized into three distinct groups. The first one, including the NG sample, shows little adsorption until the relative pressure
P/
P0 is close to 1, where a small rise is observed. This indicates there are no micropores (pore diameter < 2 nm) in this sample, except for a small amount of larger pores, such as mesopores (2–50 nm) or macropores (>50 nm). The second group of isotherms includes the samples with 50, 200 or 400 μL of liquid, respectively. Each of these samples exhibits a superimposition of multiple types of physisorption isotherms classified by IUPAC [
33]. For example, the initial part of the adsorption curve of these samples shows the characteristics of a Type-I isotherm, where a steep uptake in adsorption occurs at a very low
P/
P0, and then a plateau follows. Based on the IUPAC classification, this is clearly indicative of the presence of microporosity because narrow space, such as micropores, enhances the adsorbent–adsorptive (MOFs-N
2) interactions, thus enabling the filling of micropores at a very low
P/
P0. The ending part of these adsorption isotherms does not remain flat, but instead shows a notable jump, deviating from the behaviors normally expected of the Type-I isotherm but resembling what is common for a Type-III isotherm. Such a deviation suggests the presence of mesoporosity and/or macroporosity in these samples. Furthermore, the desorption part of these curves is characteristic of a Type-IV isotherm with a pronounced H2-type hysteresis loop, which is clearly attributed to meso/macro pore blocking or cativation. The third group of isotherms, including the samples with 1000 or 1500 μL of liquid, are very similar to how a Type-I isotherm behaves. In these curves, the rise at a high
P/
P0 is much smaller than in others. However, more importantly, the H2 hysteresis loop is barely seen in these isotherms, indicating little mesoporosity and macroporosity in such samples.
To quantify the observations from N
2 isotherms, several porosity-related calculations were performed. Using the multipoint BET model, the specific surface areas (SSA) of these samples were determined, and the results are shown in
Figure 5a. Because of the fact that the BET model is built on the assumption of monolayer-multiplayer adsorption at a low
P/P0 and also that micropore filling occurs exclusively at this range of relative pressures, the BET results can be regarded as a useful fingerprint for microporosity in the samples. It can be seen that the BET surface areas are very low when no liquid is added to the sample prior to grinding, whereas they are significantly improved when liquid is added. These BET values continue to increase from 315 m
2/g to 851 m
2/g when the amount of liquid changes from 50 μL to 1000 μL; however, they are followed by a drop to 621 m
2/g when 1500 μL of liquid is present. The same trend can therefore be predicted for the microporosity in these samples because of the correlation between the BET surface areas and microporosity. The corresponding results are summarized in
Table 1.
In addition to the specific surface areas, the pore volumes were also calculated using the N
2 adsorption isotherms. The total pore volume was determined from the N
2 adsorption isotherms at
P/P0 = 0.99, while the micropore volume was determined at
P/P0 = 0.40, where the pressure was low so that the adsorption in the meso/macro pores would not have started. The results are shown in
Figure 5b, from which several important observations can be made as follows: (i) The total pore volume is significantly larger for the LAG samples than that for the NG ones; (ii) the total pore volume reached a maximum of 0.47 cm
3/g when 400 μL of liquid was added. However, the mesoporosity/macroporosity accounts for a large portion of the total porosity in this sample and those with less than 400 μL, as illustrated by the trend line in
Figure 5b; (iii) for the sample with 1000 μL, microporosity is larger than that for the samples with 400 μL or less, and also becomes much more dominant, accounting for approximately 90% of the total porosity; and (iv) the trend mentioned in (iii) reverses when the amount of liquid increases to 1500 μL.
To further understand the nature of mesoporosity/macroporosity in these samples, the mesopore/macropore size distributions of these samples were derived from the adsorption isotherm by using the Barrett–Joyner–Halenda (BJH) model. As shown in
Figure 6, the three groups of samples categorized above, based on their isotherms, show distinct mesoporosity/macroporosity distribution characteristics—consistent with the BET and pore volume calculation results. First, the NG sample does not exhibit any peaks within the range of either the mesopores or macropores. This indicates that the very minimal amount of porosity in this sample is likely from the features, the size of which is beyond the calculation limits of the BJH model (~100 nm). Second, the samples with 400 μL or less liquid show pronounced peaks in the BJH pore size distribution. For the sample with 50 μL, the distribution has a broadened peak between 25 and 45 nm. For the sample with 200 μL, however, the curve includes two peaks at 18 and 42 nm, respectively. More importantly, these two peaks are better defined in terms of width and height. The same trend continues to be seen in the sample with 400 μL, which shows one dominant peak near 66 nm. The narrow width and the large height of these peaks indicate that the mesopores and/or macropores are more ordered structures from the interior of the samples rather than some features on the surface of the samples. Third, the results show that the prominent mesoporosity and macroporosity almost diminish from the samples prepared with 1000 and 1500 μL of added liquid.
3.4. Mechanistic Analysis of the Effect of Liquid on Porosity Formation
When evaluating all the results described above, it is clear that the mechanochemically synthesized Cu3(BTC)2 samples in this study exhibit hierarchical porosities and that the external liquid plays an essential role in controlling the formation of such porosities. Microporosity originates from structurally intrinsic pores because they are generated when metal centers and organic ligands are assembled through coordination. This is why micropores are formed inside the primary particles of crystalline Cu3(BTC)2. As a result, it is expected that microporosity has a positive correlation with the degree of crystallinity of these particles.
The NG samples are mostly amorphous and, therefore, have a low degree of crystallinity. As a result, these samples contain few micropores, as illustrated schematically in
Figure 7. Their very minimal amount of porosity arises, likely from the structural features on the surface of the agglomerates. When a small amount of liquid is added, the process becomes liquid-assisted grinding (LAG). The corresponding results show that the crystallinity of the LAG samples is significantly improved. When the amount of liquid increases from 50 μL to 1000 μL, such an improvement continues, as indicated by the change in the crystallite size. As explained above, a higher degree of crystallinity of the samples leads to an increase in their microporosity, as illustrated schematically by the grids in
Figure 7. This trend for microporosity is seen within the whole range of LAG for the synthesis of Cu
3(BTC)
2 until the amount of liquid reaches 1000 μL. As for the sample with 1500 μL, the process changes from solid-state grinding to slurry grinding. It is believed that the underlying reaction mechanism has also changed, and a detailed analysis of it needs further study; however, it is currently beyond the scope of this paper.
Based on the results of this study, we believe that mesoporosity and macroporosity in the Cu
3(BTC)
2 samples arise mainly from the network space of their primary particles, as those illustrated as “inter-particle” pores in
Figure 3, and therefore, are affected by the size of these particles. In traditional porous materials, e.g., activated carbons, these spaces are most likely closed and thus are unable to contribute to porosity in the adsorption measurements. This is also what is expected of the NG sample in this study. In the case of porous MOFs, however, these spaces could be accessible through micropore channels at the proper pressure. As for those “intra-agglomerate” pores shown in
Figure 3, they are likely too large to account for any meaningful adsorption.
As discussed in the SEM
Section 3.2, there are two competing events in the LAG synthesis: particle breakage and the agglomeration of the newly created particle fragments. Which of these events is dominant will determine the size of the primary particles and their network space formed in such a process. This, in turn, will control the formation of mesoporosity and macroporosity. When particle breakage is dominant, the primary particles tend to be smaller so that the network space of these particles (referred to as “inter-particle pores”) could result in the formation of mesopores and macropores, as illustrated in
Figure 7. These pores are accessible through micropores inside the primary particles. This scenario applies to the samples with 400 μL or less of liquid in the LAG synthesis of Cu
3(BTC)
2. It is also important to realize that the size of such mesopores and macropores and their respective percentage in the total pore volumes can be tailored by controlling the amount of liquid, as indicated by the BJH results. When the amount of liquid is increased to 1000 μL, however, agglomeration is believed to be the dominant event. As a result, the primary particles become larger, and many mesopore/macropore-contributing network spaces collapse, as illustrated in
Figure 7.
3.5. H2 Adsorption Measurement
Cu
3(BTC)
2 and other MOFs are often utilized for adsorption-based applications, where preparing target MOFs with desirable porosity is essential to their performance. In this regard, it is of great benefit to realize that the formation of hierarchical porosities in MOFs could be controlled to a certain extent by adding various amounts of liquid in the LAG synthesis, as demonstrated by the Cu
3(BTC)
2 results presented herein. This strategy can be employed to synthesize the target MOFs with a desirable porosity for specific applications. In this study, the H
2 adsorption capacity of Cu
3(BTC)
2 was examined to demonstrate such a strategy. It is well-known that for a physical adsorption process, gas molecules are restrained inside the pores of adsorbents only by a weak force, such as the van der Waals force. As a result, smaller gas molecules, e.g., H
2 and CH
4, will be more effectively adsorbed into smaller pores. As shown in
Figure 8a, H
2 adsorption in the Cu
3(BTC)
2 samples is significantly improved when liquid is added, and the adsorption continues to rise until the amount of liquid reaches 1000 μL. The maximum capacity at 1.44 wt% is comparable with other reports for Cu
3(BTC)
2 under similar conditions [
34,
35].
Figure 8b was plotted to demonstrate the relationship between porosity and the H
2 adsorption capacity. It can be seen that there is a positive linear correlation between the microporosity of the Cu
3(BTC)
2 samples and their H
2 adsorption capacities, which clearly does not apply to the total porosity of the samples. Therefore, the LAG synthesis with 1000 μL, which leads to the maximum microporosity, is optimal for H
2 adsorption in the Cu
3(BTC)
2 samples.