Experimental Investigation on the Combination of Enzyme-Induced Calcium Carbonate Precipitation and Organic Materials for Underground Backfilling Preparation

Abstract

This paper proposes a technique for producing underground backfilling materials using enzyme-induced calcium carbonate precipitation (EICP) technology to address the growing ecological security concerns caused by coal mining. To augment the mineralization impact of EICP, diverse levels of organic substances, including yeast extract, peptone, and skimmed milk powder, were incorporated into the cementing solution to offer a greater number of nucleation sites for the precipitation of calcium carbonate. The results indicate that (1) based on visual observations, all the sand columns remained intact after cementation, demonstrating a good cementation effect; (2) unconfined compressive strength (UCS) test findings demonstrated that the introduction of organic components effectively augmented the strength of EICP. Among these materials, skimmed milk powder exhibited the most significant effect, resulting in a 66.01% increase in the UCS of EICP at a concentration of 6 g/L. Peptone also showed a positive impact, albeit to a lesser extent, while yeast powder had a relatively lower effect; (3) The utilization of scanning electron microscopy (SEM) revealed a significant diversification in the crystal morphology of calcium carbonate when combined with organic materials through the EICP process. An X-ray diffraction (XRD) test confirmed the presence of calcite and vaterite. This finding implies that the molecular structure of calcium carbonate is enhanced by the inclusion of organic materials.

1. Introduction

Coal mining generates underground goaf, which poses a significant risk of geological disasters, including land collapse, groundwater depletion, and a host of ecological and environmental problems. Statistical data reveal that the land subsidence area caused by coal mining has already exceeded 4000 km², with an estimated loss of 2.04 t of groundwater for every 1 t of coal extracted [1,2,3]. The Northwest District serves as the primary coal production base in China, with five major coal production bases established in Shendong, Ningdong, Northern Shaanxi, Huanglong, and Xinjiang, as illustrated in Figure 1. These regions collectively contribute to one-third of China’s coal production. The northwestern region’s challenges, including a dry climate, sparse vegetation, and limited water resources, result in a meager 3.9% contribution to the country’s overall water resources. The intensive mining activities have severely impacted local water resources, with groundwater levels dropping by more than 15 m in areas exceeding 306.8 m² in the Yushen mining area alone. The conflict between a fragile ecological environment, acute water scarcity, and high-intensity mining continues to deepen. The ecological problems faced by coal mining in various regions of the world are very similar, taking the waste of water resources caused by mining as an example. Hill et al. set up 11 monitoring points in the coal mining area of the Northern Appalachian Plateau Region of western Pennsylvania and found that the decrease in groundwater level caused by mining is a common phenomenon [4]. Karaman et al. targeted the southern part of the Illinois Basin in northwest Saline County, Illinois, where longwall coal mining water level drops may reach tens of meters. They proposed a new one-dimensional flow equation to estimate aquifer parameters with minimal cost. In this way, the groundwater levels of longwall coal mining could be predicted [5]. Howladar focused on the Barapukuria coal mining area, Dinajpur, Bangladesh. Through direct field investigation, questionnaire survey, and laboratory analysis, Howladar understood the impact of underground coal mining on the water environment of the mining area and confirmed that the water level in the mining area was almost depleted. From 2001 to 2011, the overall water level decreased by more than 5 m [6]. Robertson studied the governance and sustainability of groundwater in Australian coal mining areas [7].

In recent years, enzyme-induced calcium carbonate precipitation (EICP) technology has continuously attracted more attention in geotechnical engineering applications. EICP generates ammonium ion and carbonate ion through urea hydrolysis catalyzed by urease, and carbonate ion combines with calcium ion in a solution to generate calcium carbonate precipitation, thereby strengthening the soil [8,9,10,11,12]. The effectiveness of soybean urease in the treatment of sandy soil was examined in an experimental study conducted by Wu et al. They examined the influence of temperature and pH on the activity of soybean urease and evaluated the reinforcement effect through various experiments, such as ultrasonic testing and unconfined compression strength (UCS) testing [9]. Similarly, to increase the stability of silty soil, Gao et al. used soybean urease to accelerate the creation of calcium carbonate. The test results demonstrated that the silty soil did not experience blockage and exhibited a significant improvement in strength [11]. Additionally, a mortar crack healing test was carried out by Dakhane et al. utilizing the hydrolysis reaction of urea catalyzed by plant-derived urease. The findings of their study validate the practicality of employing EICP for crack repair [12]. It is widely recognized that ureolytic bacteria play crucial roles in microbially induced calcium carbonate precipitation (MICP) [13,14]. Urease, produced by these bacteria, enables the rapid decomposition of urea. Moreover, the bacteria’s negatively polarized surface facilitates the assimilation of positively polarized Ca²⁺ ions, leading to the creation of calcium carbonate. However, the EICP process does not involve bacterial participation, resulting in a lack of nucleation sites for calcium carbonate generation. Scholars have recently devoted their attention to addressing this particular issue. To fortify the silty soil of the Yellow River, Yuan et al. utilized organic components like skimmed milk powder, glutinous rice flour, and brown sugar within the EICP technique. The results demonstrated that the combination of organic materials with EICP resulted in a significant 33% enhancement in strength compared to traditional EICP methods [15]. The incorporation of organic substances can enhance the utilization of organic material components as sites for nucleation, facilitating the continuous accumulation and formation of new crystals. This process helps optimize the crystal structure of calcium carbonate and compensates for the limited number of nucleation sites and the low efficiency of traditional EICP in terms of reinforcement [15]. Khodadadi et al. introduced calcium carbonate “seeds” into the soil to serve as nucleation sites, thereby enhancing the reinforcement effect [16]. Additionally, specific research studies have suggested that particular bacteria, even though they lack the capability to generate urease, can still function as sites for nucleation [17]. EICP, as a new type of environmentally friendly geotechnical technology, has increasingly widespread engineering applications. For example, in terms of dust control, EICP technology has also shown strong capabilities [18]. In terms of erosion resistance, Ossai et al. evaluated the feasibility of using EICP to control runoff erosion of sandy soil on sloping farmland [19]. It has shown certain advantages in enhancing slope stability [20], mitigating liquefaction [21], and enhancing foundation-bearing capacity [22]. Guo et al. used MICP technology to mineralize solid waste coal gangue to prepare underground backfilling materials, and systematically analyzed the bonding effect of biomineralized coal gangue from the macro and micro perspectives. Finally, it was preliminarily concluded that the study on biomineralization technology for preparing underground backfilling materials was successful [23]. However, there are currently few studies mentioning the use of EICP technology for underground backfilling.

Therefore, in order to achieve optimal coal mining while reducing adverse environmental consequences such as coal waste pollution, land subsidence, and groundwater depletion caused by mining activities. This article decides to use environmentally friendly EICP technology to mineralize sand bodies as underground backfilling materials. At the same time, considering the successful development and application of continuous extraction and continuous backfilling coal mining methods under water bodies [24], it is proposed to use “parallel mining and backfilling” methods to backfill mineralized sand bodies.

2. Test Materials and Methods

2.1. Test Materials

The soil samples employed in this experiment were procured from the Yushen mining area. In accordance with the specifications outlined in GB/T 50123-2019 (Standard for Geotechnical Test Methods) [25], the soil samples collected from the designated sampling area underwent thorough testing to ascertain their fundamental physical properties. Figure 2 depicts the grading curve which visually represents the distribution of particle sizes in the soil. The majority of the samples exhibit sizes ranging from 0.5 to 1 mm, and the coefficient of non-uniformity (Cu) is measured at 3.08, indicating coarse sand with inadequate grading. In addition, the parameters of the sand, such as maximum and minimum dry density, organic carbon, and salt content, are shown in Table 1. X-ray diffraction analysis of sand samples showed that the main component was silica. MDI Jade 6.5 software was used for phase identification.

The organic materials used in this experiment were yeast extract, peptone, and skimmed milk powder, all of which were purchased from the Sinopsin Group. The cementation solution was urea and calcium chloride, and the solution was configured with deionized water. Urease was extracted from soybeans [26] as follows: dried soybeans were ground through a 120-mesh screen, then dissolved in deionized water, stirred for 30 min, centrifuged at 30 °C and 4000 r/min for 15 min, and finally filtered to obtain crude urease liquid. Urease activity was detected by a conductivity meter [27].

2.2. Test Schemes

The test scheme was shown in Table 2. The overall process of the experiment is shown in Figure 3. The experiment was divided into an initial stage (urease preparation), middle stage (grouting treatment), and final stage (mineralization effect test). Crude urease extracted from 40 g/L soybean powder solution was used in the EICP test, and urease activity was 5.2 mM/min. Sand columns obtained from the supernatant of 40 g/L soybean powder solution have the highest strength, and urease slurries obtained by centrifugation are not prone to blockage, which can better balance the curing effect and economy [8,9]. As per the findings of Yuan et al. [15], the concentrations of peptone, yeast powder [28,29], and skimmed milk powder [30,31] in the three organic materials were established at 2 g/L, 4 g/L, and 6 g/L, respectively. The cementation solution concentration was 1 mol/L of urea and calcium chloride. The pH was adjusted to 9.0 with a low concentration of NaOH solution, and the grouting rounds were set to 5 rounds. In each scheme, the volume of each injected solution was 50 mL, which was about 1.5 times the pore volume of the sand column. Three parallel samples were set for each scheme.

The grouting procedure entailed injecting the grout into the sand column from the lower part of the sample using a peristaltic pump. The grouting speed was carefully adjusted to 1 mL/min [32]. The sand column had a height of 7.0 cm and a diameter of 3.5 cm. The loading quality of the sand column was controlled at 105 ± 1 g. The solution was configured according to the corresponding scheme. The urease solution was injected first, and then the cementation solution and organic materials were injected after an interval of 2 h. This was repeated once a day for 5 days. After the grouting was finished, it was left to stand at room temperature for 2 days, and then the sand column was taken out together with the mold and placed in a drying box at a constant temperature of 105 °C for drying until the weight no longer changed. The mold was taken out and dismantled for various tests.

2.3. Evaluation of Mineralization Effect

After the mineralization stage, the reinforcement effect was evaluated and analyzed via UCS, calcium carbonate content, SEM, and XRD of the sand column.

2.3.1. UCS Test

The UCS test of the sand column was conducted using a DDL.100 strain control triaxial instrument manufactured by Sinotest Equipment Co., Ltd., Nanjing, China. The test followed the procedure described in [25], and the loading rate was adjusted to 1.27 mm/min [33] until the sample failed.

2.3.2. Determination of Calcium Carbonate Production

The amount of calcium carbonate produced was determined via the pickling method [34] and divided into upper, middle, and lower parts to evaluate the uniformity of cementation. Samples of 3–6 g were taken from each part to test the content of calcium carbonate.

2.3.3. SEM and XRD Analysis

A scanning electron microscope with a built-in energy spectrometer was used (SEM, model Phenom ProX, Phenom-Word BV Company, Eindhoven, The Netherlands); the test acceleration voltage was adjusted to 10 KV; and the samples were subjected to vacuum gold spraying treatment before the test. The model of the equipment used in the XRD test was Germany Bruker model D8 Advance, with a scanning angle between 4° and 90° and a scanning speed of 10°/min. MDI Jade 6.5 software was used for phase identification.

3. Results

3.1. UCS Test

Figure 4 illustrates the UCS test conducted on the sand column. The sand mineralization scheme demonstrates that all the sand columns underwent cementation, resulting in an excellent cementation effect and integrity. The failure modes of sand columns were diverse. Generally speaking, specimens with lower strength were more prone to local failure, while specimens with higher strength were more prone to splitting and shear failure. In the traditional EICP experiment, scheme A did not incorporate organic materials, leading to the sand column displaying patterns of local failure, as depicted in Figure 4a. This indicates that the uniformity of cementation in the EICP sand column was poor. In the experiment of EICP combined with organic material peptone and yeast powder, some sand columns showed shear failure patterns in the lower left corner, as shown in Figure 4b; some samples showed local damage, as shown in Figure 4c,d; and some sand columns exhibited splitting failure, as shown in Figure 4e,f. However, when EICP was combined with skimmed milk powder, the predominant form of destruction in the sand column was shear destruction, as shown in Figure 4g,h. This indicates that the presence of organic materials can enhance the mineralization effect of EICP, with skimmed milk powder having a more significant effect.

Three parallel samples were set for each scheme, totaling 30 samples. In order to reduce the workload of analysis and ensure the rationality of the results, the intermediate values of each scheme were taken for analysis, and error bars were provided in the UCS peak intensity graph. Figure 5a,b display the stress–strain curve and UCS peak value. The stress peak in the stress–strain curve is inversely proportional to the relative strain, suggesting that a lower porosity of the sand column and higher compactness result in a more favorable cementation effect. Categorizing the stress–strain curve into four stages, namely compaction, linear increment, plastic deformation, and post-peak failure, reveals interesting insights. During the first stage, strain exhibited a rapid increase while stress remained relatively low, indicating a gradual compaction of the sample’s pores. In the second stage, stress showed a nearly linear correlation with strain, steadily increasing as strain increased. The rate at which stress increased was rapid until it reached a critical value. In the third stage, the stress–strain relationship curved downward in a convex manner, showing the state of plastic deformation until peak stress was reached. In the fourth stage, stress decreased sharply with strain after reaching peak stress, which is a typical brittle failure. In scheme A, the UCS peaks of the three parallel samples are 1.42 MPa, 1.53 MPa, and 1.68 MPa, respectively, and strain ranges from 4% to 5%. This is similar to the effects observed by Yang Fan [35], who used EICP technology to consolidate soil sites in northwest China (UCS reached 1.83 MPa), and those noted by Yasuhara et al. [36], who used EICP technology to cement sand (UCS reached 1.60 MPa). This shows that the EICP test results are reasonable.

The peak value of EICP UCS combined with organic materials ranges from 1.6 to 2.54 MPa. In contrast to traditional EICP, bonding strength witnessed a substantial surge of nearly 60%, highlighting the efficacy of organic materials in reinforcing the bonding strength of EICP. With the increase in organic material concentration, the peak value of UCS increases, but the increase in amplitude of 4% concentration is close to that of 6% concentration, indicating that a 4% concentration of organic material can result in a better strength balance effect. In addition, at the same concentration of organic materials, the peak value of UCS D > B > C indicates that the effect of skimmed milk powder is the best, the effect of peptone comes second, and the effect of yeast powder is relatively low. The above results show that EICP, combined with organic materials, can improve the strength of sand columns.

Moreover, out of the three organic materials examined in this study, skimmed milk powder exhibits the most notable impact. This observation is consistent with the findings of several scholars [12,30,31,37]. Dakhane et al. employed skimmed milk powder as a stabilizer due to its stable glycoprotein, which coordinates with the enzyme without interfering with its active site [12]. Almajed et al. proposed that the inclusion of milk powder in the EICP treatment solution enhances enzyme stability, facilitates carbonate precipitation by providing nucleation points, reduces precipitation rate, and improves precipitation morphology. As a result, this facilitates the formation of larger calcite crystals and leads to a substantial increase in unconfined compressive strength value [37].

Due to the large number of voids in the sand column and the high strain during the initial compaction stage, taking into account the deformation mechanism of the sand column, a constitutive model for the entire process of rock deformation was selected for analysis, considering initial void compaction. According to Li et al., the deformation of a sand column is divided into two parts: pore deformation and skeleton deformation. The concept of pore–strain ratio K was proposed, and the evolution equation of K was derived [38]. Statistical damage theory was introduced, and the sand column was regarded as composed of numerous microelements that follow Weibull function distribution [38]. Finally, the constitutive model of the whole deformation process of the sand column was established and its related parameters were determined.

(1)$K=\left\{\begin{array}{c}\frac{a_1}{\epsilon }\left[1-exp(-a_2\epsilon )\right],{\epsilon }_i<{\epsilon }_a\\ 1,{\epsilon }_i\ge {\epsilon }_a\end{array}\right.$

(2)$\mathsf{\sigma }=\left\{\begin{array}{c}E\left(1-K\right)\epsilon \left(1-D\right)+\left(2\mu -1\right)R_{s}D,{\epsilon }_i<{\epsilon }_a\\ E\left(\epsilon -K{\epsilon }_a\right)\left(1-D\right)+\left(2\mu -1\right)R_{s}D,{\epsilon }_i\ge {\epsilon }_a\end{array}\right.$

(3)${\epsilon }_i=\left\{\begin{array}{c}K{\epsilon }_i+\frac{\left[{\sigma }_i^{*}-\mu \left({\sigma }_j^{*}-{\sigma }_k^{*}\right)\right]}{E},{\epsilon }_i<{\epsilon }_a\\ K{\epsilon }_i+\frac{\left[{\sigma }_i^{*}-\mu \left({\sigma }_j^{*}-{\sigma }_k^{*}\right)\right]}{E},{\epsilon }_i\ge {\epsilon }_a\end{array}\right.$

Finally, using residual strength $R_e$ instead of $R_s$, combined with the Mohr–Coulomb strength criterion, the final calculation is as follows:

When strain is less than ${{\epsilon }_a,\epsilon }_i<{\epsilon }_a$

(4)$\mathrm{m}\left(ln\mathsf{\epsilon }-\mathit{ln}\left({\epsilon }_c+0.1\right)\right)=ln\left[-ln\left(\frac{\sigma -\left(2\mu -1\right)R_e}{\left\{1-a_1\left[1-exp(-a_2\epsilon )\right]\right\}E\epsilon -\left(2\mu -1\right)R_e}\right)\right]$

When strain is greater than ${\epsilon }_a,$ ${\epsilon }_i\ge {\epsilon }_a$

(5)$\mathrm{m}\left(ln\mathsf{\epsilon }-\mathit{ln}\left({\epsilon }_c+0.1\right)\right)=ln\left[-ln\left(\frac{\sigma -\left(2\mu -1\right)R_e}{\left\{\epsilon -a_1\left[1-exp(-a_2{\epsilon }_a)\right]\right\}E-\left(2\mu -1\right)R_e}\right)\right]$

Elastic modulus $E$ and Poisson’s ratio $\mu$ were calculated from the stress–strain curve of the linear elastic stage. ${\epsilon }_c$ is the peak strain and $a_1$ is the intersection point between the stress–strain curve in the linear elastic stage and the transverse axis, where m can be considered as the slope and is initially set to 14.2. Finally, the stress–strain fitting curves of samples A, B3, C3, and D3 were successfully obtained, as shown in Figure 6. Taking the D3 sand column with the best reinforcement effect as an example, the fitting explanation was given by fitting the equation at its linear elastic stage; calculating $E=1520\mathrm{K}\mathrm{P}\mathrm{a}$, $R_e=295\mathrm{K}\mathrm{P}\mathrm{a}$, $a_1=1.40$, ${\epsilon }_c=2.98\%$, $a_2=6.20$; and finally fitting the stress–strain curve throughout the entire process using Origin 2018 (9.5) software.

3.2. Calcium Carbonate Content

The content of calcium carbonate in the sand columns is shown in Figure 7. The content of calcium carbonate in scheme A was 5.48%, while the content of calcium carbonate in scheme EICP combined with organic materials was significantly higher than that in scheme EICP alone, reaching a maximum of 8.88%, which indicates that organic materials can promote the formation of calcium carbonate to some extent. For the same organic material, the higher the concentration of organic material, the higher the content of calcium carbonate, but the increase of 6% is close to that of 4%, which indicates that the concentration of 4% organic material can achieve a better balance effect of calcium carbonate. A comparison of schemes B, C, and D showed that under the same concentration, the calcium carbonate content of the schemes was D > B > C, indicating that skimmed milk powder had the largest incremental effect on calcium carbonate, followed by peptone and yeast powder.

Comparing Figure 5 and Figure 7, it is found that the calcium carbonate content and UCS peak value can be mutually verified, and the scheme with the highest UCS peak value has the highest calcium carbonate content. Yuan et al. introduced organic substances into EICP and carried out a comparison with EICP in isolation. Despite calcium carbonate content experiencing a minimal increase of less than 1%, strength exhibited a significant improvement, resulting in an enhanced strength enhancement efficiency of 32% [15]. In this paper, the strength enhancement efficiency of calcium carbonate was similar. It may be that under the condition of organic material stimulation, the distribution uniformity of calcium carbonate in the sand column increases and the crystal structure of calcium carbonate was optimized.

In order to evaluate the uniformity of calcium carbonate distribution in the sand column, the calcium carbonate content was measured in the upper, middle, and lower areas of the sand column, following the methods of Cao et al. [39]. Figure 8 show cases the findings, with calcium carbonate content represented on the horizontal axis and the sand column area (top, middle, and bottom) on the vertical axis. As the data points progress towards the right, calcium carbonate content demonstrates a gradual rise. In scheme A, the difference between the top and bottom reaches 3.1%, which is a large gap, indicating that the distribution uniformity of calcium carbonate in traditional EICP is poor. The disparity in calcium carbonate levels between the upper and lower portions of calcium carbonate in schemes B, C, and D is less significant compared to scheme A. This suggests that the inclusion of organic materials enhanced the even distribution of calcium carbonate within the sand columns. The discrepancy in calcium carbonate content between schemes B1, B2, and B3 and C1, C2, and C3 is approximately 2% and 2.5%, respectively. Similarly, the difference in calcium carbonate content between schemes D1, D2, and D3 is around 1%. This indicates that skimmed milk powder has the most substantial impact on the uniformity of calcium carbonate distribution in sand columns, while peptone and yeast powder also contribute to improving the uniformity of calcium carbonate distribution. Furthermore, in all schemes, it is evident that calcium carbonate content is generally higher at the bottom compared to the top and middle sections. This is due to the injection of grouting into the bottom of the sand column and the more extensive distribution of solution at the bottom caused by gravity. As a result, calcium carbonate content is higher at the bottom than that at the top and middle sections.

3.3. SEM/XRD

SEM images of the sand are shown in Figure 9. Figure 9a shows the original sand grains. It can be seen that the sand grains have distinct marks and corners, and the grain surfaces are relatively smooth. Figure 9b shows the EICP-cemented sand particles. The surface of the sand particles is covered with crystal particles, which cement the loose sand particles into a whole, but the crystal particles do not form an obvious stacking form and are distributed evenly on the surface of the sand particles. The sand cemented by EICP combined with peptone is depicted in Figure 9c, where the resulting crystal particles exhibit a denser clumpy aggregation form. The SEM of EICP combined with yeast powder is shown in Figure 9d, and the surface of the sand particles is distributed with calcium carbonate crystals of different sizes. The SEM images of EICP combined with skimmed milk powder are shown in Figure 9e. The crystal particles present multiple couplings, including not only a cluster aggregation form but also a rod form. In Figure 9c–e, calcium carbonate crystal particles show different aggregation forms, which may be formed by small calcium carbonate particles wrapped around bacteria or organic materials.

Generally speaking, the smaller the crystal, the larger its specific surface area, and the tighter its filling between sand particle gaps, resulting in a more stable sand column formed by its cementation. In Figure 9, it can be seen that under SEM images of the same size, the crystal polymer formed by EICP combined with skimmed milk powder has the highest density and the smallest size, indicating a good reinforcement effect. The distribution of crystal polymers formed by EICP combined with yeast powder fluctuates greatly, forming obvious gaps and loopholes, which are similar to traditional EICP. Thus, its strength is not significantly improved compared to traditional EICP. The Figure 9c SEM image of EICP combined with peptone shows overall dense bonding signs on the surface, but the size of the bonding polymer is significantly larger than that in Figure 9e, with a smaller specific surface area, and the stability of the formed sand column is inferior to that of skimmed milk powder. Kiasari Amini et al. determined that molasses and yeast powder acting as carbon sources yielded superior strengthening effects in bioconsolidation. The SEM images and EDX analysis in their study showed similar microscopic effects to those in this paper. Without any treatment, the surface of soil particles is smooth, and after treatment, calcite crystals will be generated on the surface and joints of soil particles. At the same time, different organic materials added will also show significant differences in crystal morphology [40].

In the detection of material composition, XRD data analysis is crucial. In fact, the basic theory and functional usage of XRD can be studied further. Bosikov et al. utilized differential equations such as Fourier transform and constructed an Ewald sphere mathematical analysis model to solve the complex stacking fault problem in X-ray diffraction [41]. Elaqra et al. used XRD scanning to construct a three-dimensional void fraction image of concrete [42]. This article conducted XRD data analysis using Jade 6.5 software, and the results are shown in Figure 10. It can be seen from the top curve in Figure 10, at an angle of 10°~90°, that the main component of the original sand is silica. After mineralized treatment via EICP combined with organic materials, calcite is found in the consolidated precipitation materials. In the consolidated sand samples of EICP combined with skimmed milk powder, some vaterite was detected, but calcite still dominated. It can also be seen in the SEM in Figure 9e that the crystal shapes of calcium carbonate were diversified. Yuan et al. pointed out that the crystallinity of calcium carbonate induced by urease would change when organic materials were added as nucleation sites [15]. Wen et al. pointed out that the crystal type induced by urease in calcium carbonate is mainly calcite, and when the concentration of urease changes, the calcium carbonate crystal type will also change [43]. It can be seen that different mineralization conditions can change the mineral phase of calcium carbonate crystals [44,45].

The XRD spectrum of the sand column sample mainly displays the crystalline phases of SiO₂ and calcite. Calcite occupies an absolute dominant position in the mineralized samples, and vaterite is also present in part in the mineralized group of EICP combined with skimmed milk powder, while it is not present in the other groups. In Figure 9b–d, it can be seen that the crystal form of calcite is cubic and rod-shaped. From the perspective of thermodynamic stability, calcite is relatively stable and has high mechanical strength. Therefore, the strength of mineralized calcium products is also high, which improves the overall strength of the cemented sand column. Macroscopically, it exhibits excellent unconfined compressive strength. Compared to calcite calcium carbonate, vaterite calcium carbonate exhibits a more spherical distribution, as shown in Figure 9e, although its stability is lower than that of calcite. It has a larger specific surface area, better solubility and dispersion, and better biocompatibility and safety. Therefore, vaterite filling in sand columns also has great application prospects. EICP combined with skimmed milk powder can induce calcite and vaterite crystals, which undoubtedly have a more favorable mineralization effect. Therefore, from a macro perspective, the UCS and calcium carbonate data performance of this combination was the best.

4. Discussion

4.1. Mechanism Analysis

In terms of the role of organic materials in EICP, it is theoretically speculated that these materials serve as nucleation sites for calcium carbonate. In addition, Kiasari Amini et al. mentioned that organic matter can stimulate indigenous bacterial growth [40], while Khaleghi et al. [46] and Gat et al. [47] also explicitly proposed that non-urease-producing bacteria can serve as nucleation sites in biomineralization, enhancing the effectiveness of biomineralization. Therefore, reasonable analysis shows that the organic materials added to EICP in this paper can also stimulate the growth of indigenous bacteria in sand columns. The negatively charged surface of the bacteria attracts positively charged calcium ions in the cementation fluid, leading to the utilization of the bacteria as nucleation sites for the generation of calcium carbonate precipitation. Figure 11 illustrates the action mechanism of soil solidification by EICP combined with organic materials. Loose sand particles slowly bond into a sturdy block under the action of EICP combined with organic materials. Yuan Hua et al. incorporated organic materials, such as skimmed milk powder, glutinous rice flour, and brown sugar, into EICP to compensate for the deficiency of nucleation sites and the low reinforcement efficiency of conventional EICP [15]. The experimental results and mechanism analysis are similar to our research results, which also verifies the rationality of the research results in this paper.

4.2. Further Prospects

4.2.1. Research on Biomineralization of Coal-Based Solid Waste

The development and utilization of coal resources not only leads to water loss and ecological water level decline in mining areas, but also generates a large amount of coal-based solid waste and CO₂. According to statistics [48], in recent years, the annual production of fly ash in China was about 650 million tons, the annual production of coal gangue was about 659 million tons, the annual production of blast furnace slag was about 160 million tons, and the annual production of magnesium slag was about 5.8 million tons. Coupled with historical stocks, the amount of coal-based solid waste in China is huge. Therefore, if EICP technology can be used to mineralize coal-based solid waste and successfully apply it to underground backfilling, the results of this paper will prove highly meaningful.

4.2.2. Research on the Self-Healing Function of Biomineralized Materials

Under load disturbance, the interior of a sand column is prone to damage and microfractures. As an environmentally friendly material, biomineralized materials have powerful functions and wide applications, and many scholars have attempted to produce self-healing sample cracks [49,50]. Therefore, the authors aim to further the self-healing function of biomineralized materials by preparing underground backfilling materials, studying the mechanism of self-healing bacteria, and exploring their impact on the underground ecological environment in order to expand the ecologically friendly function of microbial mineralization materials in mining areas.

5. Conclusions

This paper presents an experimental study that aimed to examine the preparation of underground backfilling materials through a combination of EICP and organic materials. The primary research findings are summarized as follows:

• (1). Peptone, yeast powder, and skimmed milk powder all yielded positive outcomes in relation to the results of EICP. Notably, skimmed milk powder exhibited the most pronounced enhancement effect, followed by peptone, whereas yeast powder displayed a comparatively weaker enhancement effect;

• (2). Compared to traditional EICP with a strength of 1.53 MPa, the UCS of EICP combined with peptone, yeast powder, and skimmed milk powder reached 2.03 MPa, 1.60 MPa, and 2.54 MPa, respectively, with growth rates of 32.68%, 4.57%, and 66.01%. Furthermore, in traditional EICP, the proportion of calcium carbonate content is 5.48%. The calcium carbonate content of EICP combined with peptone, yeast powder, and skimmed milk powder reaches 7.44%, 6.02%, and 8.88%, respectively, with growth rates of 35.7%, 9.85%, and 62.04%. In addition, there is also a significant improvement in the uniformity of calcium carbonate, the difference in which between the top and bottom of traditional EICP is 3.1%. The range of EICP combined with peptone, yeast powder, and skimmed milk powder is around 2.0%, 2.5%, and 1.0%, respectively;

• (3). Compared to traditional EICP, the crystal morphology of calcite and vaterite varies, with different distributions, when formed using the combination of EICP and skimmed milk powder on the surface and joints of sand particles. These multiple couplings provide evidence that the combination of EICP and organic materials enhances the morphology and structure of calcium carbonate crystals.

Author Contributions

Experimental work, methodology, data curation, writing, original draft, validation, G.C.; supervision, L.M.; funding acquisition, L.M.; review and editing, I.N.; editing, A.E.O.; investigation, Z.G. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

The data can be available from the corresponding author upon reasonable request.

Acknowledgments

We thank the anonymous reviewers and the editor for their constructive comments on this manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

Footnotes

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Figures and Tables

Figure 1. Schematic diagram of five coal production bases in northwest China.

Figure 2. Particle size distribution curve of sand.

Figure 3. Experimental flow chart.

Figure 4. Failure form of sand columns in UCS test: (a) local failure; (b) local shear failure; (c) local failure; (d) local failure; (e) splitting failure; (f) splitting failure; (g) shear failure; (h) shear failure.

Figure 5. (a) Stress–strain curves for different schemes; (b) UCS peak value of different schemes.

Figure 6. Sample stress–strain curve fitting diagram of schemes: (a) sample A; (b) sample B3; (c) sample C3; (d) sample D3.

Figure 6. Sample stress–strain curve fitting diagram of schemes: (a) sample A; (b) sample B3; (c) sample C3; (d) sample D3.

Figure 7. Calcium carbonate content of different schemes.

Figure 8. The percentage of calcium carbonate in different parts of each sample scheme, with colors indicating the addition of different organic substances. Black represents no addition, blue represents peptone, green represents yeast powder, and red represents skimmed milk powder.

Figure 9. SEM imagez of sand: (a) original sand image (10 μm); (b) EICP cementation image (10 μm); (c) EICP combined with peptone cementation image (10 μm); (d) EICP combined with yeast powder cementation image (10 μm); (e) EICP combined with skimmed milk powder cementation image (10 μm).

Figure 10. XRD results: (a) original sand; (b) EICP combined with peptone; (c) EICP combined with yeast powder; (d) EICP combined with skimmed milk powder.

Figure 11. Mechanism of soil solidification by EICP combined with organic materials.

Table 1

Relevant parameters of sand.

Min Dry Densityg/cm3	Max Dry Densityg/cm3	Specific Gravity	Total Organic Carbong/kg	Total Nitrogeng/kg	Carbon-to-Nitrogen Ratio	Total Soluble Saltg/kg	Water Content%
1.51	1.74	2.52	0.23	0.07	2.71	0.35	3.27

Table 2

Experimental schemes.

Scheme Number	Treatment Method	Organic MaterialConcentration (g·L−1)	Urease ActivitymM/min	Urea mM	CaCl2 mM	pH	Grouting Rounds
A	EICP	/	5.2	1000	1000	9	5
B1	EICP + peptone	2	5.2	1000	1000	9	5
B2		4	5.2	1000	1000	9	5
B3		6	5.2	1000	1000	9	5
C1	EICP + yeast powder	2	5.2	1000	1000	9	5
C2		4	5.2	1000	1000	9	5
C3		6	5.2	1000	1000	9	5
D1	EICP + skimmed milk powder	2	5.2	1000	1000	9	5
D2		4	5.2	1000	1000	9	5
D3		6	5.2	1000	1000	9	5

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