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A novel approach to accelerate bacterially induced calcium carbonate precipitation using oxygen releasing compounds (ORCs)
Author’s Accepted Manuscript A novel approach to accelerate bacterially induced calcium carbonate precipitation using oxygen releasing compounds (ORCs) Mostafa Seifan, Ali Khajeh Samani, Aydin Berenjian www.elsevier.com/locate/bab
PII: DOI: Reference:
S1878-8181(17)30375-4 https://doi.org/10.1016/j.bcab.2017.10.021 BCAB645
To appear in: Biocatalysis and Agricultural Biotechnology Received date: 13 July 2017 Revised date: 11 October 2017 Accepted date: 27 October 2017 Cite this article as: Mostafa Seifan, Ali Khajeh Samani and Aydin Berenjian, A novel approach to accelerate bacterially induced calcium carbonate precipitation using oxygen releasing compounds (ORCs), Biocatalysis and Agricultural Biotechnology, https://doi.org/10.1016/j.bcab.2017.10.021 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
A novel approach to accelerate bacterially induced calcium carbonate precipitation using oxygen releasing compounds (ORCs) Mostafa Seifan, Ali Khajeh Samani, Aydin Berenjian* School of Engineering, Faculty of Science and Engineering, The University of Waikato, Hamilton, New Zealand *Corresponding author: Dr. Aydin Berenjian, School of Engineering, Faculty of Science and Engineering, The University of Waikato, Hamilton, New Zealand. T: +64 7 858 5119; M: +64 21 081 79872. [email protected]
Abstract In the present study, a mixture of oxygen releasing compounds (ORCs) was designed in an attempt to continuously supply dissolved oxygen (DO) in the oxygen-limiting conditions and evaluate bacterially induced calcium carbonate (CaCO3) production. The biomineralization of CaCO3 was adversely affected in the presence of calcium peroxide (CP) and zinc peroxide (ZP), whereas urea-hydrogen peroxide (UP) and magnesium peroxide (MP) were found to be significant on enhancing the biosynthesis of CaCO 3. The optimal values for UP and MP obtained from central composite face-centered (CCF) were 1800 mg/L and 8.3 mg/L, respectively. As compared to the control samples, the bacterially induced CaCO3 precipitation was not only enhanced but also accelerated when the optimum concentrations of ORCs were supplemented in the fermentation media. Moreover, the morphology of the precipitated CaCO3 was affected in the presence of ZP, while no such effect was observed when the media were supplemented with CP, UP or MP. The results of this study can be used in many natural and engineered applications such as the constructional purposes for designing a more efficient bio self-healing concrete. The other applications of this innovative technology are the removal of heavy metals, radionuclides and calcium ions contaminants from the environment.
Keywords: Bacteria; Calcium carbonate; Oxygen releasing compound; Bio self-healing concrete; Optimization; Morphology
1
Introduction
Concrete is the most used material for the modern day construction and plays a crucial role in global economy. Concrete is used in many applications including buildings, dams, ports, bridges and roads as it is durable, resilient, versatile, fire-resistant and relatively inexpensive. However, concrete has a high tendency to crack as it shrinks, and the crack extends over age. Generally, cracks have a negative effect on the concrete’s lifespan by paving the path for water and aggressive chemicals to seep into the structure. To date, attempts have been continuously made to stop or at least slow down the crack extension by the application of conservative 1
techniques. However, these methods are unreliable, requires periodic inspection and more importantly, they cannot reach the inner parts of small and deep cracks (Seifan et al., 2016a). Since CaCO3 is the most compatible material with the concrete compositions, its production through an innovative biotechnological approach has been proposed to address the concrete crack formation issue. Biomineralization of CaCO3 can be achieved through biologically controlled mineralization (BCM) and biological induced mineralization (BIM). The mineral particles are deposited in a specific location during BCM and the process is highly regulated and independent of environmental conditions, while BIM process usually occurs in an open environment (Bazylinski and Moskowitz, 1997). The effectiveness of BIM process highly depends on the concentration of dissolved inorganic carbon, nucleation site, pH, temperature and Hartree energy (Eh) (Barton and Northup, 2011; Hammes and Verstraete, 2002; Seifan et al., 2016b). However, in addition to these factors, the performance of a bio self-healing concrete and CaCO3 precipitation rely on the presence of oxygen (Seifan et al., 2017). Despite the recent progresses in designing a biotechnological protocol for the crack treatment, CaCO3 precipitation can only occur on the surface areas of the concrete. Achal et al. (2013) performed an investigation to determine the possibility of CaCO3 production by Bacillus sp. in mortar samples. Their results showed that the production of CaCO3 was only limited to the outer parts of the specimen and biomineralization was occurred up to 27.2 mm from the surface. In another investigation, Rodriguez-Navarroet et al. (2003) demonstrated the effect of CaCO3 biomineralization using Myxococcus xanthus on deteriorated ornamental stone. Although the authors noted that the newly formed CaCO3 crystals were strongly attached to the substrate, the biomineralization was limited to a depth of hundred micrometers. Over the recent years, X-ray computed tomography (X-ray µCT) recognizes as a non-destructive technique in material sciences, particularly for porosity analysis. Wang et al. (2014) employed X-ray µCT to prove the feasibility of bacterial incorporation as a promising approach for self-healing concrete. It was found that the amount of CaCO3 precipitation decreases with the increase of crack’s depth. Considering the positive effect of oxygen on bacterial growth and CaCO3 production, the lack of oxygen might be the reason to limit mineral precipitation inside the cracks and pores. To be industrially applicable, a prompt action is in demand to address the current problem associated with the bioself-healing approach. The successful utilization of oxygen releasing compounds (ORCs) has been reported for bioremediation applications such as removal of contaminants biodegradation from ground water (Vogt et al., 2004) and saturated soil (Cassidy and Irvine, 1999). It is, therefore, believed that the use of ORCs can be a solution to address the shortage of oxygen in deeper parts of the concrete. ORCs are mainly composed of chemicals which liberate oxygen in the presence of water or moisture, and provide the molecular oxygen needed for the aerobic microbial metabolic activity. Once a crack occurs in concrete, water or moisture penetrate into the deepest parts of cracks enabling the ORCs to generate oxygen for bacterial germination and possibly CaCO 3 biosynthesis. Therefore, the main aims of the present study are to (i) screen the effect of different oxygen releasing compounds on bacterially induced CaCO3 precipitation and (ii) determine the critical level of ORCs to maximize the biosynthesis of CaCO3 in oxygen-limiting conditions.
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2 2.1
Material and methods Chemicals
Bacto™ Peptone and glucose were obtained from Becton Dickinson (NJ, USA). Calcium chloride anhydrous, urea, yeast extract, calcium peroxide (CP), zinc peroxide (ZP), magnesium peroxide (MP) and urea-hydrogen peroxide (UP) were purchased from Sigma-Aldrich (St. Louis, MO, USA).
2.2
Microorganism and inoculum preparation
Bacillus sphaericus NZRM 4381 and Bacillus licheniformis ATCC 9789 were used for CaCO3 production studies (Seifan et al., 2016c). To rehydrate the isolates, the sterilized growth medium was used with the following composition: peptone (0.5% w/v), glucose (0.5% w/v) and yeast extract (0.05% w/v). The medium was incubated in a shaker incubator (120 rpm and 37°C) for 24 h. One milliliter of revived bacterial culture was then spread directly onto nutrient agar and incubated at 37°C for 48 h. The harvested cells were suspended in a normal saline solution (sodium chloride 0.9%) and kept in a water bath at 80°C for 10 min to inactivate the vegetative cells and produce spores. The cell debris was then removed by centrifuging the spore suspension at 3000 rpm for 12 min.
2.3
Fermentation process and experimental design
In our previous study, it was shown that the highest concentration of CaCO3 precipitation is achieved when the fermentation medium is composed of calcium chloride (40 g/L), urea (65 g/L) and yeast extract (2 g/L) (Seifan et al., 2016c). In the present study, the fermentation experiments were carried out in 200-mL Erlenmeyer flasks (short vertical neck without baffle) containing the optimum medium. The flasks were then inoculated with 4.5% (v/v) of isolates, maintained at 35°C and 100 rpm for 108 h. To screen the most CaCO3 producing ORCs, different concentrations of ORCs were added to the fermentation medium. In order to enhance the CaCO3 biosynthesis, the optimum concentrations of significant variables from the screening stage were determined using a response surface methodology (RSM) with a central composite face-centered (CCF) design matrix. A statistical software package (MODDE pro, V11, Umetrics, Umeå, Sweden) was used for the experimental design, statistical analysis of the data and building of the quadratic model. Table 1 presents the full experimental design with regard to their concentrations. The data obtained from RSM were then fitted via the response surface regression procedure using the second order polynomial equation. The screening data were analyzed using IBM SPSS statistics package version 24 (USA). The significance level (p-value) of 0.05 was used to determine whether the variables are significant.
2.4
Analytical experiments
The concentration of soluble Ca2+ in the media was determined by a benchtop photometer (Palintest, Gateshead, The UK). To extract the precipitated CaCO3 crystals, the fermentation media were vacuum filtered through a 0.2 µm membrane filter paper (Advantec, Tokyo, Japan) at the end of the fermentation. The precipitates were washed with distilled water (three times) to remove impurities, oven dried for 24 h at 70°C. Samples were kept
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in a desiccator until morphological observation and crystal characterization. During the fermentation, the concentration of dissolved oxygen (DO) and pH of the solutions were monitored every 24 h using a DO meter (Hach sensION6, Colorado, USA) and a benchtop pH meter (Eutech instrument pH 150, Shanghai, China).
2.5
Morphological observation
Bioprecipitates were examined by scanning electron microscope (SEM, Hitachi S-4700, Tokyo, Japan) to observe the morphology of induced CaCO3 precipitation. Moreover, energy dispersive X-ray spectroscopy (EDS) was used to recognize the composition of bioprecipitate. The precipitates were well-grinded by a mortar and pestle and mounted on an aluminum stub using double-sided carbon tape. To prevent surface charging by the electron beam, the stub was sputter-coated with platinum using a Hitachi (E1030, Tokyo, Japan) sputter coating unit. Image scanning and EDS analysis were performed at accelerating voltage of 5 KeV and 15 KeV, respectively.
2.6
Crystal characterization
X-ray diffraction (XRD) was used to characterize the precipitated CaCO3. The well-grinded bioprecipitate crystals were back-packed into a sample holder and mounted onto the instrument sample changer. The XRD analysis was conducted using a Panalytical Empyrean diffractometer (Almelo, The Netherlands) with CuKα radiation generated at 45 kV and 40 mA. The step size was set to 0.0530°, and the data was recorded over a scan range (2θ) of 15°–75°.
3
Results
The fermentation media in the presence or absence of ORCs were prepared and incubated to evaluate the capability of CaCO3 precipitation. The results obtained at the screening and optimization studies are presented in the following sections.
3.1
ORCs and CaCO3 precipitation
The effect of ORCs on bacterially induced CaCO3 precipitation was determined at the screening stage. Four different types of peroxide, namely calcium peroxide (CP, 1.67–6.67 mg/L), urea-hydrogen peroxide (UP, 133.33–3333.33 mg/L), zinc peroxide (ZP, 3.33–33.33 mg/L) and magnesium peroxide (MP, 6.67–46.47 mg/L) were evaluated for their oxygen releasing ability. CP was selected as it can increase the pH of the media and possibly the formation of CaCO3. UP as a nitrogen source was used to support the bacterial growth and facilitate the biosynthesis of CaCO3 through ureolysis pathway (nitrogen cycle). ZP and MP were chosen due to their metallic nature, the capability of steadily releasing oxygen, and possible effect on the mechanical properties of concrete. The ANOVA results indicate that the data obtained in screening stage were significantly different (p-value of 0.000). Fig. 1 shows the effect of different ORCs on the bacterial production of CaCO 3. Based on the results, presence of UP and MP enhanced the CaCO 3 precipitation in the fermentation media (p-
4
value<0.05), whereas the addition of ZP showed an inhibitory effect on the bacterial precipitation of CaCO 3 (pvalue>0.05). The statistical results also show that the presence of CP had no significant (p-value<0.05) effect on the biosynthesis of CaCO3 as compared to UP and MP. The highest concentration of CaCO3 (33.85 g/L) was achieved when 6.67 mg/L of MP was added to the fermentation medium. However, the increase in MP dosage from 6.67 to 33.33 mg/L resulted to a 19% decline in the biomineralization of CaCO3. A significant decrease (10-fold) in CaCO3 precipitation was observed when the concentration of MP further increased to 46.47 mg/L. Contrariwise, there was no significant difference in the amount of CaCO3 precipitation when the fermented medium was supplemented with different dosages of UP (p-value = 0.11). Based on the results, a 10-times increase in UP concentration only resulted in 5% decline in the biomineralization of CaCO 3.
3.2
Optimization of significant ORCs using response surface methodology
It is particularly important to study the variables interaction at various concentrations, since toxicity is experienced by the cells, especially at a high concentration of peroxides. The screening study showed that CP and ZP significantly inhibited the bacterial precipitation of CaCO3. Therefore UP and MP were selected for the optimization stage to further evaluate their effect on enhancing the bacterially induced CaCO 3 precipitation. To investigate the optimum levels of ORCs on bacterial CaCO3 production, RSM using a CCF design matrix was used. The statistical analysis data containing the regression coefficients for the model are given in Table 2. As shown in Eq. 1, the quadratic model for the bacterial precipitation of CaCO3 was regressed for predicting the CaCO3 precipitation as a function of significant peroxides (UP and MP). (1) where Y, X1 and X2 are the predicted CaCO3, UP and MP concentrations, respectively. The statistical analysis of the quadratic regression model shows that the model is highly significant (p-value < 0.000) with R2 value of 0.985. The R2 value indicates that 98.5% of the sample variation for the response (CaCO3) is explained by the independent variables, and this also implies that the model is not explained only 1.5% of sample variation. Based on the results, the linear interaction of variables is significant on the response, whereas the quadratic term of X12 is found to be insignificant on CaCO3 production. The statistical significance of the quadratic model was checked by F-test, and the results of ANOVA are listed in Table 3. The results indicate that the Fischer’s F-test is highly significant (p-value < 0.000) for the regression. Lack of fit test is a good indication to evaluate the accuracy of the model. When the mathematical model is well fitted to the experimental data, the mean squared lack of fit reflects only the random errors inherent to the system (Bezerra et al., 2008). This means that a non-significant lack of fit and a significant regression confirm the high accuracy of the fitted model to the experimental data. Therefore, the model was further assessed for its suitability by examining the lack of fit, and the results show that the lack of fit is not significant for the model (p-value = 0.165). This indicates that there was only 16.5% chance that a lack of fit could occur due to the noise.
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3.3
Experimental verification
To determine the optimum level of ORCs, the regression equation was solved while remaining inside the experimental region. Independent fermentation runs were carried out with the optimum levels of ORCs predicted by the model to verify the optimization results. The fermented medium was supplemented with the optimum concentrations of ORCs (1800 mg/L UP and 8.3 mg/L MP). The results indicated that the average value of CaCO3 concentration obtained experimentally was only 4.5% lower than the predicted value by the model. The variations of DO and pH during CaCO3 biosynthesis in the optimum sample were checked under a biological fume hood cabinet and the results are shown in Fig. 2. The DO concentration was monitored during the fermentation to investigate the effect of ORCs on DO variation. The result in Fig. 2a shows that the DO trend was consistent for the sample with ORCs and control experiments, while the DO level was significantly higher in the presence of ORCs than the control experiment. The concentration of DO started to decrease after 24 h of the fermentation period. After 48 h, the DO concentration rose and reached to a peak level. Overall, the addition of ORCs brought about 12.5% increase in DO concentration for the first 48 h of the fermentation, whereas the average level of DO was 3.3-times higher than the control run during the rest of the fermentation. The variation of pH was also monitored during the fermentation with ORCs, and the results are exhibited in Fig. 2b. The same strategy was noticed for the pHs in the presence of ORCs and control samples. However, the pH of control solution was higher than the medium supplemented with ORCs for the first 35 h of incubation. The pHs began to gradually decrease until 72 h, and followed an increase and reached the values of 8.51 and 8.10 for the sample containing ORCs and control, respectively. The results also disclosed that the solution supplemented with ORCs had the higher pH after 35 h of fermentation as compared to the control sample. This might be attributed to the presence of ORCs which bring about a rise in pH by producing strong bases compounds, such as Ca(OH)2 and Mg(OH)2, which facilitates bacterial CaCO3 precipitation.
3.4
Morphological observation
Crystal shapes of CaCO3 particles are distinguishable by SEM. The morphology of CaCO3 crystals is more complex in the enzymatic systems, and it can be affected in the presence of the enzyme. Sondi and Matijević (2001) reported the regulatory effect of the enzyme on the morphology of the CaCO3 crystals. Morphologies of the CaCO3 crystals precipitated in the presence of various ORCs during the screening and optimization studies, are summarized in Figs. 3 and 4. Based on the results obtained at screening study (Fig. 3), it was visually confirmed that different shapes of crystals, including small rounded body and rhombohedral, were precipitated. As depicted in Fig. 3a-c, the mixture of CaCO3 particles consisting of vaterite and calcite was induced in the media containing MP, UP, and CP. However, the majority of crystals precipitated in the presence of ZP were rhombohedral (calcite). It is worth noting that the average size of induced vaterite particles was ~10–30 µm, while different sizes of calcite crystals were observed at the screening stage. It was found that the size of calcite particles was mainly 20–40 µm in the presence of MP and UP, and 5–15 µm when CP and ZP were added to the fermentation media. As expected, a combination of vaterite and calcite was induced at optimization stage, and the SEM micrographs for the optimum sample are shown in Fig. 4.
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The collected dry biosynthesis products were also examined using EDS analysis to observe the elemental compositions. As shown in Fig. 5, the EDS spectra for the optimum sample (containing ORCs) closely resembled the pure CaCO3, indicating the formed crystals were either calcite, vaterite and/or aragonite. Since aragonite particles were not detected by SEM and XRD, it can be concluded that the precipitated crystals are calcite and vaterite.
3.5
Characterization of crystals
The XRD peaks are appropriate indicators for qualitative and quantitative determination of bacterially induced CaCO3 precipitation. Therefore, the precipitated CaCO3 powders at screening study were subjected to XRD measurement and the patterns are shown in Fig. 6a. Interestingly, the presence of different ORCs at the screening stage resulted in a different portion of CaCO3 polymorphs. The highest portion of calcite was precipitated in the solution containing ZP, while the lowest concentration of calcite induced in the medium supplemented with MP. The comparison between UP and CP revealed that the solution containing CP, induced a higher portion of calcite than UP. It was also found that no aragonite was induced during the fermentation process. On the other hand, the addition of MP to the fermentation medium led to induce the highest portion of vaterite precipitation. The investigation also indicates that a higher portion of vaterite was induced in the solution with UP as compared to CP. However, no vaterite particles were detected when ZP was added to the fermentation medium. XRD analysis was also performed for the optimization media and the spectra are given in Fig. 6b. As expected, a combination of vaterite and calcite was induced when the optimum concentrations of ORCs were added to the fermentation solution (Fig. 6c).
4
Discussion
4.1
ORCs and CaCO3 precipitation
The applications of ORCs, including sodium percarbonate or metal peroxides, have been reported to support in situ aerobic biosynthesis (Cassidy and Irvine, 1999; Narendranath et al., 2000). In this sense, the aerobic biodegradation of contaminants by the addition of ORCs has been proposed under oxygen-limiting conditions (Heitkamp, 1997; Koenigsberg and Sandefur, 1999). However, the aerobic fermentation can be affected by many physical, chemical and biological conditions that influence the overall CaCO3 biosynthesis efficiency. Our previous study demonstrated that aeration has a positive effect on the bacterial production of CaCO 3 by providing a higher level of DO (Seifan et al., 2017). In general, the ORCs significantly affect the quantity of released oxygen and the pH (Walawska et al., 2007). The introduction of pure oxygen rather than air in the fermentation media can significantly increase the DO concentration (Tsai et al., 2009), and consequently, this contributes to enhancing the biomineralization efficiency. However, maintaining DO concentration greater than its critical level would be toxic for microorganisms (Kazzaz et al., 1996), and bacterially induced CaCO3 precipitation is affected accordingly. The ORC materials tend to release oxygen at a controlled rate to enhance the aerobic biomineralization processes by providing more oxygen. Eqs. 2–3 show the chemical reactions of peroxides towards the production of hydrogen peroxide and subsequently oxygen liberation, where M represents the divalent metal (Cassidy and 7
Irvine, 1999; Kao et al., 2003). As shown in the Eq. 2, hydrogen peroxide is produced by the reaction between peroxide (ORC) and water. This process is subsequently followed by decomposition of hydrogen peroxide into oxygen (Eq. 3). (2) (3) It has been reported that oxygen is required to initiate and maintain the bacterial activity for the biomineralization of CaCO3 which is induced through urea hydrolysis or oxidation of organic carbon pathways (Tziviloglou et al., 2016). Considering the poor solubility of oxygen in the water, the bio self-healing approach for concrete crack treatment is only limited to the surface areas where a sufficient amount of oxygen is available. To address this issue, we proposed the addition of ORCs. However, the addition of various ORCs results in the production of different CaCO3 concentrations. It was found that UP and MP are significant ORCs on enhancing CaCO3 precipitation, while CP and ZP have a negative effect on CaCO3 biomineralization. Zhang et al. (2016) reported that CP can increase the bacterially induced CaCO3 precipitation in the presence of Bacillus species. However, our data show that UP and MP have more significant influence on producing CaCO3. This might be due to the rapid oxygen-releasing rate of CP at the early stage of the fermentation (Lee et al., 2014), which leads to exceeding its critical level, and consequently, CaCO3 precipitation is inhibited. As depicted in Fig. 1, among the investigated ORCs, the presence of ZP in fermentation media results in the drastic decline in bacterial CaCO3 precipitation. As compared to the control experiment, a considerable reduction in CaCO3 precipitation was observed due to the presence of the lowest concentration of ZP (3.33 g/L). This shows that the availability of ZP has the most detrimental effect on the biomineralization process. Previously, Rothenstein et al. (2012) reported that the presence of zinc in culture media can affect the growth rate of Halomonas halophila. It is hypothesised that the zinc is extracellularly bound to the cells and consequently affects the CaCO3 precipitation. On the other hand, a low concentration of UP and MP resulted in a slight increase in CaCO3 precipitation. Due to a low solubility and slow reaction rate of MP with water, it has the slowest oxygen-releasing capability (Camci-Unal et al., 2013) which provides a sustained release of oxygen during the fermentation. Dissolution of UP in water not only releases oxygen, but also provides a higher supply of urea which is essential to inducing carbonate during biosynthesis. However, a greater amount of urea than it can be consumed by bacteria to initiate the biomineralization process, remains unused. Overall, the screening results suggest that UP and MP are the most promising sources for the support of bacterial production of CaCO 3, and therefore an optimization study was performed for further enhancement of CaCO3 biosynthesis.
4.2
Optimization of significant ORCs for CaCO3 precipitation
Adequate oxygen supply to the cells is often critical in aerobic fermentation; however, the excessive release of oxygen by ORCs might adversely affect the bioprocesses (Spain et al., 1989). Furthermore, it has been noted that the irreversible cell damage can occur as a result of temporary oxygen depletion (Lee, 1992). Therefore the optimization was carried out to propose an optimum concentrations for the selected ORCs which can provide a continuous supply of oxygen, and facilitates the bacteria to induce CaCO3 under oxygen-limiting conditions. The CCF design matrix used in the present investigation enabled us to study and explore the effect of various 8
concentrations of potent ORCs on CaCO3 precipitation. The regression analysis of the experimental design listed in Table 2 reflects that all single factor and quadratic model terms, excluding X12, are significant (pvalue<0.05) on bacterial precipitation of CaCO3. A p-value of less than 0.05 also shows that the interactive term of X1X2 significantly affects the biosynthesis of CaCO3. As compared to the control sample, the results for optimization study demonstrate that the biosynthesis of CaCO3 enhanced and the presence of the optimum concentrations of MP and UP resulted in an increase in CaCO3 concentration from 22.99 g/L to 34.39 g/L. This confirms that the optimization was successfully achieved. The comparisons between observed and predicted CaCO3 concentration showed a good correlation between the experimental results and the fitted model. The error associated with repetitions was determined based on the replicates of the central points. The analysis of variance results indicate an R2 value of 0.985 which ensures a satisfactory adjustment of the model to the experimental data. As given in Table 3, the significant regression and the non-significant lack of fit also suggest that the model has been well fitted to the experimental data. As depicted in Fig. 7, a 3D response surface plot was constructed to illustrate the synergistic effects of the influential ORCs and to provide a visual interpretation for the location of the optimal concentrations. The shape of the corresponding plot shows the mutual interaction between variables is significant, and CaCO3 precipitation is considerably affected by the concentration of UP and MP. The data indicate that the low and high concentrations of both UP and MP adversely affect the biomineralization of CaCO 3. The oxygen released by the low concentrations of ORCs could not meet the cell requirement, and the high levels of ORCs showed toxicity by releasing an excessive amount of oxygen than required by bacteria. The precipitation of CaCO 3 was enhanced with increases in the concentrations of UP and MP to approximately 3300 and 12 mg/L, respectively. However, further increases in the concentration of UP and MP led to a decrease in CaCO3 concentration. The high concentrations of UP and MP cause the oxygen releasing process to take place too quickly, and the resulted supersaturation state inhibits the bacterial activity. Another possible explanation for the inhibitory effect of high concentrations of UP and MP is due to oxygen toxicity which causes inhibition of metabolism and respiration in microorganisms (Haugaard, 1968).
4.3
Experimental verification
In order to validate the optimization results, verification experiments were performed at the predicted values derived from the model. The review of the optimization as a contour curve plot given in Fig. 7 shows the relative effects of UP and MP on CaCO3 precipitation. To evaluate the performance of optimized ORCs on the biomineralization process, the critical parameters such as DO and pH were monitored. The validation experiments showed that there is an increase in bacterial precipitation of CaCO3 as compared to the control run, and it has only a negligible difference with the value predicted by the model. More importantly, the optimized sample could accelerate the biomineralization of CaCO3. The presence of ORCs resulted in a 22.5% increase in CaCO3 precipitation at 72 h of fermentation. Taking into account that the majority of the concrete cracks are generated at the early age, an ideal bio self-healing compound requires to activate immediately upon crack formation and fill the entire crack in a short period of time. Moreover, it has been noted that the ORCs are able to last from four months to over a year (Koenigsberg and Sandefur, 1999). Therefore the addition of proposed
9
optimum ORCs as a supplementary bio self-healing agent can enhance the concrete performance by efficiently filling the concrete cracks upon their formation. The bacterial metabolic activity has an important role in the biomineralization process, and it can be affected by the level of DO. As shown in Fig. 2a, the samples containing the optimum concentrations of UP and MP have a higher level of DO throughout the fermentation as compared to the control samples. The higher DO level during fermentation not only boosts the cell populations, but also contributes to bacterial growth in oxygenlimiting conditions. These higher nucleation sites provide a favourable condition to further increase CaCO3 precipitation due to the controlled and continuous supply of oxygen which meets the requirement for bacteria to initiate the biomineralization process. The bacterial cell has an important role in the biosynthesis of CaCO3 precipitation. Stocks-Fischer et al. (1999) reported that the bacterial cells serve as nucleation sites in the biomineralization process. Eqs. 4–9 represent the bacterially induced CaCO3 precipitation process through urea hydrolysis pathway (Burne and Chen, 2000; Seifan et al., 2016b). →
(4) (5) (6) (7) (8) (9)
In general, a higher concentration of bacterial cells increases the urease concentration which catalyses the hydrolysis of urea into carbonate (Okwadha and Li, 2010). Therefore urea hydrolysis has a direct relationship with bacterial cell concentration, and this has a direct effect on CaCO3 precipitation. On the other hand, one of the most common issues associated with the presence of ORCs is the sudden release of oxygen, which may affect the bacterial metabolism and CaCO3 precipitation capacity. Since MP content in the optimized sample has a low solubility in water, it guarantees a gradual and continuous release of oxygen (Barbara Walawska et al., 2007). pH is another significant parameter on biomineralization of CaCO3 by affecting the bacterial urease activity (Gorospe et al., 2013). Our results also confirm the effect of pH on biomineralization of CaCO3. It was noticed that the control experiment had a higher pH, and more CaCO3 was precipitated over the first 35 h of fermentation. However, the optimized sample had higher pH and more CaCO3 precipitation as compared to the control for the rest of fermentation period. This is due to the fact that carbonate tends to dissolve rather than precipitate at a low pH level (Loewenthal. R.E and Marais. G.V.R, 1978). The increase of H+ in solution caused a decline in pH for both optimized and control experiments due to CO 2 dissolution. On the other hand, after 72 h of fermentation, the produced OH- neutralized H+ in fermentation medium through the dissolution of NH3(g) and, consequently, pH increased (Becker et al., 2003; Li et al., 2013). Overall, a greater pH fluctuation was observed in the control solution during the dropping of pH, while in both fermentation runs, the pH increased more steadily. Over the oxygen liberating period, the reaction between ORCs and water results in increase in pH, and this leads to stabilizing the pH variation.
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4.4
Morphological observation and crystal characterization
The EDS spectrum taken for the bioprecipitates clearly showed that the main compositions are Ca, O, and C. A high degree of similarity between the pure CaCO3 and precipitated crystals is another indication that the presence of ORCs can successfully facilitate the CaCO3 biosynthesis process. Bioprecipitation of CaCO3 may result in the production of different polymorphs, including calcite, vaterite, aragonite, and two hydrated crystalline phases, monohydro calcite and ikaite (Kaur et al., 2013). It has been noted that the production of the polymorphs depends on bacterial strains, growing environments, and their chemical nature (González-Muñoz et al., 2010; Wei et al., 2015). Taking into account that CaCO3 polymorphs have different mechanical and physical properties (i.e., density, hardness and solubility), and they may be used in various applications, it requires determining whether the presence of ORCs will change the CaCO3 polymorphs. For the bio-concrete application, the precipitation of vaterite is preferred rather than calcite. Vaterite has a lower density than calcite, and this contributes to occupy more space and the efficiency of the bio-concrete will be increased. Bacterial cell wall characteristics and growth medium composition are the main factors influencing the bacterially induced CaCO3 morphology. Furthermore, a number of previous studies have demonstrated the role of bacterial extracellular polymeric substance (EPS) in the bacterial production of CaCO3 polymorphs (Braissant et al., 2003; Kawaguchi and Decho, 2002). Specifically, Bosak and Newman (2005) noted that the presence of EPS encourages the precipitation of vaterite particles rather than calcite. In our investigation the results obtained by XRD and SEM disclosed that the presence of ZP has an effect on the CaCO3 morphology and vaterite formation is suppressed. This might be due to the changes in nucleation energy caused by extracellular attachment of zinc onto the bacterial cell wall. This result corresponds with the finding of Rothenstein et al. (2012) who observed that the availability of zinc in a fermentation solution had an effect on the morphology of induced CaCO3 precipitation.
5
Conclusion
In this investigation, we proposed a simple, active and long-term protocol to not only enhance but also accelerate the bacterially induced CaCO3 precipitation up to 34.39 g/L. The experimental results clearly show that the CaCO3 precipitation and cell growth are significantly enhanced by the addition of optimum concentrations of UP (1800 mg/L) and MP (8.3 mg/L). It is believed that the optimum concentrations of ORCs are promising to enhance the bio self-healing concrete performance. The addition of proposed compounds can activate and support the biomineralization process in oxygen-limiting areas such as deep cracks and interior parts of the concrete matrix.
Acknowledgments This investigation was financially supported by The University of Waikato, New Zealand.
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Competing interests The authors declare that they have no conflict of interest.
Ethical approval This study does not contain any studies with human participants or animals performed by any of the authors.
References Achal V., Mukerjee A., Sudhakara Reddy M., 2013. Biogenic treatment improves the durability and remediates the cracks of concrete structures. Constr. Build. Mater. 48, 1-5. Barton L.L., Northup D.E., 2011. Microbes at Work in Nature: Biomineralization and Microbial Weathering, in: Barton L.L., Northup D.E (Eds.), Microbial Ecology, John Wiley & Sons, Inc., Hoboken, NJ, pp. 299-326. Bazylinski D.A., Moskowitz B.M., 1997. Microbial biomineralization of magnetic iron minerals: microbiology, magnetism and environmental significance. Rev. Mineral. Geochem. 35, 217223. Becker A., Becker W., Marxen J.C., Epple M., 2003. In-vitro Crystallization of Calcium Carbonate in the Presence of Biological Additives - Comparison of the Ammonium Carbonate Method with Double-Diffusion Techniques. Z. Anorg. Allg. Chem. 629, 2305-2311. Bezerra M.A., Santelli R.E., Oliveira E.P., Villar L.S., Escaleira L.A., 2008. Response surface methodology (RSM) as a tool for optimization in analytical chemistry. Talanta. 76, 965-977. Bosak T., Newman D.K., 2005. Microbial kinetic controls on calcite morphology in supersaturated solutions. J. Sediment. Res. 75, 190-199. Braissant O., Cailleau G., Dupraz C., Verrecchia E.P., 2003. Bacterially induced mineralization of calcium carbonate in terrestrial environments: The role of exopolysaccharides and amino acids. J. Sediment. Res. 73, 485-490. Burne R.A., Chen Y.Y.M., 2000. Bacterial ureases in infectious diseases. Microbes. Infect. 2, 533542. Camci-Unal G., Alemdar N., Annabi N., Khademhosseini A., 2013. Oxygen-releasing biomaterials for tissue engineering. Polym. Int. 62, 843-848. Cassidy D.P., Irvine R.L., 1999. Use of calcium peroxide to provide oxygen for contaminant biodegradation in a saturated soil. J. Hazard. Mater. 69, 25-39. Gorospe C.M., Han S.H., Kim S.G., Park J.Y., Kang C.H., Jeong J.H., So J.S., 2013. Effects of different calcium salts on calcium carbonate crystal formation by Sporosarcina pasteurii KCTC 3558. Biotechnol. Bioproc. E. 18, 903-908. González-Muñoz M.T, Rodriguez-Navarro C., Martínez-Ruiz F., Arias J.M., Merroun M.L., Rodriguez-Gallego M., 2010. Bacterial biomineralization: new insights from Myxococcusinduced mineral precipitation. Geol. Soc. London 336. 31-50. 12
Hammes F., Verstraete W., 2002. Key roles of pH and calcium metabolism in microbial carbonate precipitation. Rev. Environ. Sci. Biotechnol. 1, 3–7. Haugaard N., 1968. Cellular mechanisms of oxygen toxicity. Physiol. Rev. 48, 311-373. Heitkamp M.A., 1997. Effects of oxygen-releasing materials on aerobic bacterial degradation processes. Bioremediat. J. 1, 105-114. Kao C.M., Chen S.C., Wang J.Y., Chen Y.L., Lee S.Z., 2003. Remediation of PCE-contaminated aquifer by an in situ two-layer biobarrier: Laboratory batch and column studies. Water. Res. 37, 27-38. Kaur N., Reddy M.S., Mukherjee A., 2013. Biomineralization of calcium carbonate polymorphs by the bacterial strains isolated from calcareous sites. J. Microbiol .Biotechn. 23, 707-714. Kawaguchi T., Decho A.W., 2002. A laboratory investigation of cyanobacterial extracellular polymeric secretions (EPS) in influencing CaCO3 polymorphism. J. Cryst. Growth. 240, 230235. Kazzaz J.A., Xu J., Palaia T.A., Mantell L., Fein A.M., Horowitz S., 1996. Cellular oxygen toxicity: Oxidant injury without apoptosis. J. Biol. Chem. 271, 15182-15186. Koenigsberg S.S., Sandefur C.A., 1999. The Use of Oxygen Release Compound for the Accelerated Bioremediation of Aerobically Degradable Contaminants: The Advent of Time-Release Electron Acceptors. Remed. J. 10, 3-29. Lee C.-S., Le Thanh T., Kim E.-J., Gong J., Chang Y.-Y., Chang Y.-S., 2014. Fabrication of novel oxygen-releasing alginate beads as an efficient oxygen carrier for the enhancement of aerobic bioremediation of 1,4-dioxane contaminated groundwater. Bioresource. Technol. 171, 59-65. Lee J.M., 1992. Biochemical engineering. Prentice Hall Englewood Cliffs, NJ. Li W., Chen W.S., Zhou P.P., Zhu S.L., Yu L.J., 2013. Influence of initial calcium ion concentration on the precipitation and crystal morphology of calcium carbonate induced by bacterial carbonic anhydrase. Chem. Eng. J. 218, 65-72. Loewenthal. R.E, Marais. G.V.R, 1976. Carbonate chemistry of aquatic systems: theory and application. Ann Arbor Science. Narendranath N.V., Thomas K.C., Ingledew W.M., 2000. Urea hydrogen peroxide reduces the numbers of Lactobacilli, nourishes yeast, and leaves no residues in the ethanol fermentation. Appl. Environ. Microb. 66, 4187-4192. Okwadha G.D.O., Li J., 2010. Optimum conditions for microbial carbonate precipitation. Chemosphere. 81, 1143-1148. Rodriguez-Navarro C., Rodriguez-Gallego M., Chekroun K.B., Gonzalez-Muñoz M.T., 2003. Conservation of ornamental stone by Myxococcus xanthus-induced carbonate biomineralization. Appl. Environ. Microb. 69, 2182-2193. Rothenstein D., Baier D., Schreiber T.D., Barucha V., Bill J., 2012. Influence of zinc on the calcium carbonate biomineralization of Halomonas halophila. Aquat. Biosyst. 1, 8-31.
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Seifan M., Samani A.K., Burgess J.J., Berenjian A., 2016a. The Effectiveness of Microbial Crack Treatment in Self Healing Concrete In: Berenjian A., Jafarizadeh-Malmiri H., Song Y. (Eds.), High Value Processing Technologies. Nova Science, pp. 97-123. Seifan M., Samani A.K., Berenjian A., 2016b. Bioconcrete: next generation of self-healing concrete. Appl. Microbiol. Biotechnol. 100, 2591-2602. Seifan M., Samani A.K., Berenjian A., 2016c. Induced calcium carbonate precipitation using Bacillus species. Appl. Microbiol. Biotechnol. 100, 9895-9906. Seifan M., Samani A.K., Berenjian A., 2017. New insights into the role of pH and aeration in the bacterial production of calcium carbonate (CaCO3). Appl. Microbiol. Biotechnol. 101, 3131– 3142. Sondi I., Matijević E., 2001. Homogeneous precipitation of calcium carbonates by enzyme catalyzed reaction. J. Colloid. Interf. Sci. 238, 208-214. Spain J.C., Milligan J.D., Downey D.C., Slaughter J.K., 1989. Excessive Bacterial Decomposition of H2O2 During Enhanced Biodegradation. Ground Water. 27, 163-167. Stocks-Fischer S., Galinat J.K., Bang S.S., 1999. Microbiological precipitation of CaCO3. Soil. Biol. Biochem. 31, 1563-1571. Tsai T.T., Kao C.M., Surampalli R.Y., Chien H.Y., 2009. Enhanced bioremediation of fuel-oil contaminated soils: Laboratory feasibility study. J. Environ. Eng. 135, 845-853. Tziviloglou E., Van Tittelboom K., Palin D., Wang J., Sierra-Beltrán M.G., Erşan Y.Ç., Mors R., Wiktor V., Jonkers H.M., Schlangen E., De Belie N., 2016. Bio-based self-healing concrete: from research to field application. In: Hager M., Van der Zwaag S., Schubert U.S. (Eds), Selfhealing Materials. Springer, New York LLC, pp 345-386. Vogt C., Alfreider A., Lorbeer H., Hoffmann D., Wuensche L., Babel W., 2004. Bioremediation of chlorobenzene-contaminated ground water in an in situ reactor mediated by hydrogen peroxide. J. Contam. Hydrol. 68, 121-141. Walawska B., Gluzińska J., Miksch K., Turek-Szytow J., 2007. Solid inorganic peroxy compounds in environmental protection. Pol. J. Chem. Technol. 68-72. Wang J., Dewanckele J., Cnudde V., Van Vlierberghe S., Verstraete W., De Belie N., 2014. X-ray computed tomography proof of bacterial-based self-healing in concrete. Cem. Concr. Compos. 53, 289-304. Wei S., Cui H., Jiang Z., Liu H., He H., Fang N., 2015. Biomineralization processes of calcite induced by bacteria isolated from marine sediments. Braz. J. Microbiol. 46, 455-464. Zhang J.L., Wang C.G., Wang Q.L., Feng J.L., Pan W., Zheng X.C., Liu B., Han N.X., Xing F., Deng X., 2016. A binary concrete crack self-healing system containing oxygen-releasing tablet and bacteria and its Ca2+-precipitation performance. Appl. Microbiol. Biotechnol. 1-12.
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Fig.1 The effect of oxygen releasing compounds on bacterially induced CaCO3 precipitation.
Fig. 2 The variations of DO and pH for the amended fermentation medium containing the optimum concentrations of selected ORCs.
15
Fig. 3 SEM micrograph of CaCO3 crystals at the screening stage for the medium supplemented with a) MP, b) UP, c) CP and d) ZP.
Fig. 4 SEM micrograph of CaCO3 precipitation when the media was supplemented with the optimum concentrations of ORCs.
16
Fig. 5 EDS spectra for the pure CaCO3 crystal and the particle precipitated in the media supplemented with optimum concentrations of ORCs.
Fig. 6 XRD spectra of bacterially induced CaCO3 precipitation in the a) screening study, b) optimization study, and c) media supplemented with optimum concentrations of ORCs.
17
Fig. 7 Response surface plot shows the synergistic effects of influential ORCs (UP and MP) on bacterial induced CaCO 3 precipitation; a review of the optimization. Table 1 Experimental conditions of the central composite face-centered (CCF) design and responses indicating both original and scaled factors. Factors a X1 (mg/L)
X2 (mg/L)
Observed CaCO3 (g/L)
Predicted CaCO3 (g/L)
1
333.33 (-1)
6.67 (-1)
34.19
34.71
2
4333.33 (+1)
6.67 (-1)
34.39
33.32
3
333.33 (-1)
33.33 (+1)
4.08
5.92
4
4333.33 (+1)
33.33 (+1)
15.17
15.42
5
333.33 (-1)
20.00 (0)
33.49
31.12
6
4333.33 (+1)
20.00 (0)
34.26
35.18
7
2333.33 (0)
6.67 (-1)
34.36
34.91
8
2333.33 (0)
33.33 (+1)
13.66
11.57
9
2333.33 (0)
20.00 (0)
32.34
34.05
10
2333.33 (0)
20.00 (0)
34.19
34.05
11
2333.33 (0)
20.00 (0)
34.07
34.05
Run
a
Values are expressed as real and scaled levels, X1 = Urea-hydrogen peroxide (UP) and X2= Magnesium peroxide (MP)
Table 2 Statistical analysis from the central composite face-centered (CCF) design experiments. Term
Coefficient
Standard Error
p-value
Constant
34.05
0.99
3.95e-07
18
X1
2.03
0.79
0.050
X2
-11.67
0.79
2.56e-05
X12
-0.89
1.22
0.494
-10.81
1.22
0.000
0.97
0.037
2
X2
X1 X2
2.72 2
2
2
X1: UP, X2: MP, R =0.985, R (Adj.)=0.969 and Q =0.865
Table 3 Analysis of variance of the quadratic model for the central composite face-centered (CCF) design. Source
DF
SS
MS
SD
F value
p-value
Regression
5
1206.40
241.28
15.53
64.52
0.000
Residual
5
18.69
3.74
1.93
-
-
Lack of Fit
3
16.58
5.53
2.35
5.22
0.165
Pure error
2
2.12
1.06
1.03
-
-
Total corrected
10
11.07
-
-
1225.10
122.51
DF degree of freedom, SS sum of squares, MS mean sum of squares, SD standard deviation
Highlights
Higher DO levels provided for the bacterial cells in the oxygen-limiting conditions.
Optimization of ORCs accelerated bacterially induced CaCO3 precipitation.
Crystal morphologies changed in the presence of ORCs.
19
PII: DOI: Reference:
S1878-8181(17)30375-4 https://doi.org/10.1016/j.bcab.2017.10.021 BCAB645
To appear in: Biocatalysis and Agricultural Biotechnology Received date: 13 July 2017 Revised date: 11 October 2017 Accepted date: 27 October 2017 Cite this article as: Mostafa Seifan, Ali Khajeh Samani and Aydin Berenjian, A novel approach to accelerate bacterially induced calcium carbonate precipitation using oxygen releasing compounds (ORCs), Biocatalysis and Agricultural Biotechnology, https://doi.org/10.1016/j.bcab.2017.10.021 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
A novel approach to accelerate bacterially induced calcium carbonate precipitation using oxygen releasing compounds (ORCs) Mostafa Seifan, Ali Khajeh Samani, Aydin Berenjian* School of Engineering, Faculty of Science and Engineering, The University of Waikato, Hamilton, New Zealand *Corresponding author: Dr. Aydin Berenjian, School of Engineering, Faculty of Science and Engineering, The University of Waikato, Hamilton, New Zealand. T: +64 7 858 5119; M: +64 21 081 79872. [email protected]
Abstract In the present study, a mixture of oxygen releasing compounds (ORCs) was designed in an attempt to continuously supply dissolved oxygen (DO) in the oxygen-limiting conditions and evaluate bacterially induced calcium carbonate (CaCO3) production. The biomineralization of CaCO3 was adversely affected in the presence of calcium peroxide (CP) and zinc peroxide (ZP), whereas urea-hydrogen peroxide (UP) and magnesium peroxide (MP) were found to be significant on enhancing the biosynthesis of CaCO 3. The optimal values for UP and MP obtained from central composite face-centered (CCF) were 1800 mg/L and 8.3 mg/L, respectively. As compared to the control samples, the bacterially induced CaCO3 precipitation was not only enhanced but also accelerated when the optimum concentrations of ORCs were supplemented in the fermentation media. Moreover, the morphology of the precipitated CaCO3 was affected in the presence of ZP, while no such effect was observed when the media were supplemented with CP, UP or MP. The results of this study can be used in many natural and engineered applications such as the constructional purposes for designing a more efficient bio self-healing concrete. The other applications of this innovative technology are the removal of heavy metals, radionuclides and calcium ions contaminants from the environment.
Keywords: Bacteria; Calcium carbonate; Oxygen releasing compound; Bio self-healing concrete; Optimization; Morphology
1
Introduction
Concrete is the most used material for the modern day construction and plays a crucial role in global economy. Concrete is used in many applications including buildings, dams, ports, bridges and roads as it is durable, resilient, versatile, fire-resistant and relatively inexpensive. However, concrete has a high tendency to crack as it shrinks, and the crack extends over age. Generally, cracks have a negative effect on the concrete’s lifespan by paving the path for water and aggressive chemicals to seep into the structure. To date, attempts have been continuously made to stop or at least slow down the crack extension by the application of conservative 1
techniques. However, these methods are unreliable, requires periodic inspection and more importantly, they cannot reach the inner parts of small and deep cracks (Seifan et al., 2016a). Since CaCO3 is the most compatible material with the concrete compositions, its production through an innovative biotechnological approach has been proposed to address the concrete crack formation issue. Biomineralization of CaCO3 can be achieved through biologically controlled mineralization (BCM) and biological induced mineralization (BIM). The mineral particles are deposited in a specific location during BCM and the process is highly regulated and independent of environmental conditions, while BIM process usually occurs in an open environment (Bazylinski and Moskowitz, 1997). The effectiveness of BIM process highly depends on the concentration of dissolved inorganic carbon, nucleation site, pH, temperature and Hartree energy (Eh) (Barton and Northup, 2011; Hammes and Verstraete, 2002; Seifan et al., 2016b). However, in addition to these factors, the performance of a bio self-healing concrete and CaCO3 precipitation rely on the presence of oxygen (Seifan et al., 2017). Despite the recent progresses in designing a biotechnological protocol for the crack treatment, CaCO3 precipitation can only occur on the surface areas of the concrete. Achal et al. (2013) performed an investigation to determine the possibility of CaCO3 production by Bacillus sp. in mortar samples. Their results showed that the production of CaCO3 was only limited to the outer parts of the specimen and biomineralization was occurred up to 27.2 mm from the surface. In another investigation, Rodriguez-Navarroet et al. (2003) demonstrated the effect of CaCO3 biomineralization using Myxococcus xanthus on deteriorated ornamental stone. Although the authors noted that the newly formed CaCO3 crystals were strongly attached to the substrate, the biomineralization was limited to a depth of hundred micrometers. Over the recent years, X-ray computed tomography (X-ray µCT) recognizes as a non-destructive technique in material sciences, particularly for porosity analysis. Wang et al. (2014) employed X-ray µCT to prove the feasibility of bacterial incorporation as a promising approach for self-healing concrete. It was found that the amount of CaCO3 precipitation decreases with the increase of crack’s depth. Considering the positive effect of oxygen on bacterial growth and CaCO3 production, the lack of oxygen might be the reason to limit mineral precipitation inside the cracks and pores. To be industrially applicable, a prompt action is in demand to address the current problem associated with the bioself-healing approach. The successful utilization of oxygen releasing compounds (ORCs) has been reported for bioremediation applications such as removal of contaminants biodegradation from ground water (Vogt et al., 2004) and saturated soil (Cassidy and Irvine, 1999). It is, therefore, believed that the use of ORCs can be a solution to address the shortage of oxygen in deeper parts of the concrete. ORCs are mainly composed of chemicals which liberate oxygen in the presence of water or moisture, and provide the molecular oxygen needed for the aerobic microbial metabolic activity. Once a crack occurs in concrete, water or moisture penetrate into the deepest parts of cracks enabling the ORCs to generate oxygen for bacterial germination and possibly CaCO 3 biosynthesis. Therefore, the main aims of the present study are to (i) screen the effect of different oxygen releasing compounds on bacterially induced CaCO3 precipitation and (ii) determine the critical level of ORCs to maximize the biosynthesis of CaCO3 in oxygen-limiting conditions.
2
2 2.1
Material and methods Chemicals
Bacto™ Peptone and glucose were obtained from Becton Dickinson (NJ, USA). Calcium chloride anhydrous, urea, yeast extract, calcium peroxide (CP), zinc peroxide (ZP), magnesium peroxide (MP) and urea-hydrogen peroxide (UP) were purchased from Sigma-Aldrich (St. Louis, MO, USA).
2.2
Microorganism and inoculum preparation
Bacillus sphaericus NZRM 4381 and Bacillus licheniformis ATCC 9789 were used for CaCO3 production studies (Seifan et al., 2016c). To rehydrate the isolates, the sterilized growth medium was used with the following composition: peptone (0.5% w/v), glucose (0.5% w/v) and yeast extract (0.05% w/v). The medium was incubated in a shaker incubator (120 rpm and 37°C) for 24 h. One milliliter of revived bacterial culture was then spread directly onto nutrient agar and incubated at 37°C for 48 h. The harvested cells were suspended in a normal saline solution (sodium chloride 0.9%) and kept in a water bath at 80°C for 10 min to inactivate the vegetative cells and produce spores. The cell debris was then removed by centrifuging the spore suspension at 3000 rpm for 12 min.
2.3
Fermentation process and experimental design
In our previous study, it was shown that the highest concentration of CaCO3 precipitation is achieved when the fermentation medium is composed of calcium chloride (40 g/L), urea (65 g/L) and yeast extract (2 g/L) (Seifan et al., 2016c). In the present study, the fermentation experiments were carried out in 200-mL Erlenmeyer flasks (short vertical neck without baffle) containing the optimum medium. The flasks were then inoculated with 4.5% (v/v) of isolates, maintained at 35°C and 100 rpm for 108 h. To screen the most CaCO3 producing ORCs, different concentrations of ORCs were added to the fermentation medium. In order to enhance the CaCO3 biosynthesis, the optimum concentrations of significant variables from the screening stage were determined using a response surface methodology (RSM) with a central composite face-centered (CCF) design matrix. A statistical software package (MODDE pro, V11, Umetrics, Umeå, Sweden) was used for the experimental design, statistical analysis of the data and building of the quadratic model. Table 1 presents the full experimental design with regard to their concentrations. The data obtained from RSM were then fitted via the response surface regression procedure using the second order polynomial equation. The screening data were analyzed using IBM SPSS statistics package version 24 (USA). The significance level (p-value) of 0.05 was used to determine whether the variables are significant.
2.4
Analytical experiments
The concentration of soluble Ca2+ in the media was determined by a benchtop photometer (Palintest, Gateshead, The UK). To extract the precipitated CaCO3 crystals, the fermentation media were vacuum filtered through a 0.2 µm membrane filter paper (Advantec, Tokyo, Japan) at the end of the fermentation. The precipitates were washed with distilled water (three times) to remove impurities, oven dried for 24 h at 70°C. Samples were kept
3
in a desiccator until morphological observation and crystal characterization. During the fermentation, the concentration of dissolved oxygen (DO) and pH of the solutions were monitored every 24 h using a DO meter (Hach sensION6, Colorado, USA) and a benchtop pH meter (Eutech instrument pH 150, Shanghai, China).
2.5
Morphological observation
Bioprecipitates were examined by scanning electron microscope (SEM, Hitachi S-4700, Tokyo, Japan) to observe the morphology of induced CaCO3 precipitation. Moreover, energy dispersive X-ray spectroscopy (EDS) was used to recognize the composition of bioprecipitate. The precipitates were well-grinded by a mortar and pestle and mounted on an aluminum stub using double-sided carbon tape. To prevent surface charging by the electron beam, the stub was sputter-coated with platinum using a Hitachi (E1030, Tokyo, Japan) sputter coating unit. Image scanning and EDS analysis were performed at accelerating voltage of 5 KeV and 15 KeV, respectively.
2.6
Crystal characterization
X-ray diffraction (XRD) was used to characterize the precipitated CaCO3. The well-grinded bioprecipitate crystals were back-packed into a sample holder and mounted onto the instrument sample changer. The XRD analysis was conducted using a Panalytical Empyrean diffractometer (Almelo, The Netherlands) with CuKα radiation generated at 45 kV and 40 mA. The step size was set to 0.0530°, and the data was recorded over a scan range (2θ) of 15°–75°.
3
Results
The fermentation media in the presence or absence of ORCs were prepared and incubated to evaluate the capability of CaCO3 precipitation. The results obtained at the screening and optimization studies are presented in the following sections.
3.1
ORCs and CaCO3 precipitation
The effect of ORCs on bacterially induced CaCO3 precipitation was determined at the screening stage. Four different types of peroxide, namely calcium peroxide (CP, 1.67–6.67 mg/L), urea-hydrogen peroxide (UP, 133.33–3333.33 mg/L), zinc peroxide (ZP, 3.33–33.33 mg/L) and magnesium peroxide (MP, 6.67–46.47 mg/L) were evaluated for their oxygen releasing ability. CP was selected as it can increase the pH of the media and possibly the formation of CaCO3. UP as a nitrogen source was used to support the bacterial growth and facilitate the biosynthesis of CaCO3 through ureolysis pathway (nitrogen cycle). ZP and MP were chosen due to their metallic nature, the capability of steadily releasing oxygen, and possible effect on the mechanical properties of concrete. The ANOVA results indicate that the data obtained in screening stage were significantly different (p-value of 0.000). Fig. 1 shows the effect of different ORCs on the bacterial production of CaCO 3. Based on the results, presence of UP and MP enhanced the CaCO 3 precipitation in the fermentation media (p-
4
value<0.05), whereas the addition of ZP showed an inhibitory effect on the bacterial precipitation of CaCO 3 (pvalue>0.05). The statistical results also show that the presence of CP had no significant (p-value<0.05) effect on the biosynthesis of CaCO3 as compared to UP and MP. The highest concentration of CaCO3 (33.85 g/L) was achieved when 6.67 mg/L of MP was added to the fermentation medium. However, the increase in MP dosage from 6.67 to 33.33 mg/L resulted to a 19% decline in the biomineralization of CaCO3. A significant decrease (10-fold) in CaCO3 precipitation was observed when the concentration of MP further increased to 46.47 mg/L. Contrariwise, there was no significant difference in the amount of CaCO3 precipitation when the fermented medium was supplemented with different dosages of UP (p-value = 0.11). Based on the results, a 10-times increase in UP concentration only resulted in 5% decline in the biomineralization of CaCO 3.
3.2
Optimization of significant ORCs using response surface methodology
It is particularly important to study the variables interaction at various concentrations, since toxicity is experienced by the cells, especially at a high concentration of peroxides. The screening study showed that CP and ZP significantly inhibited the bacterial precipitation of CaCO3. Therefore UP and MP were selected for the optimization stage to further evaluate their effect on enhancing the bacterially induced CaCO 3 precipitation. To investigate the optimum levels of ORCs on bacterial CaCO3 production, RSM using a CCF design matrix was used. The statistical analysis data containing the regression coefficients for the model are given in Table 2. As shown in Eq. 1, the quadratic model for the bacterial precipitation of CaCO3 was regressed for predicting the CaCO3 precipitation as a function of significant peroxides (UP and MP). (1) where Y, X1 and X2 are the predicted CaCO3, UP and MP concentrations, respectively. The statistical analysis of the quadratic regression model shows that the model is highly significant (p-value < 0.000) with R2 value of 0.985. The R2 value indicates that 98.5% of the sample variation for the response (CaCO3) is explained by the independent variables, and this also implies that the model is not explained only 1.5% of sample variation. Based on the results, the linear interaction of variables is significant on the response, whereas the quadratic term of X12 is found to be insignificant on CaCO3 production. The statistical significance of the quadratic model was checked by F-test, and the results of ANOVA are listed in Table 3. The results indicate that the Fischer’s F-test is highly significant (p-value < 0.000) for the regression. Lack of fit test is a good indication to evaluate the accuracy of the model. When the mathematical model is well fitted to the experimental data, the mean squared lack of fit reflects only the random errors inherent to the system (Bezerra et al., 2008). This means that a non-significant lack of fit and a significant regression confirm the high accuracy of the fitted model to the experimental data. Therefore, the model was further assessed for its suitability by examining the lack of fit, and the results show that the lack of fit is not significant for the model (p-value = 0.165). This indicates that there was only 16.5% chance that a lack of fit could occur due to the noise.
5
3.3
Experimental verification
To determine the optimum level of ORCs, the regression equation was solved while remaining inside the experimental region. Independent fermentation runs were carried out with the optimum levels of ORCs predicted by the model to verify the optimization results. The fermented medium was supplemented with the optimum concentrations of ORCs (1800 mg/L UP and 8.3 mg/L MP). The results indicated that the average value of CaCO3 concentration obtained experimentally was only 4.5% lower than the predicted value by the model. The variations of DO and pH during CaCO3 biosynthesis in the optimum sample were checked under a biological fume hood cabinet and the results are shown in Fig. 2. The DO concentration was monitored during the fermentation to investigate the effect of ORCs on DO variation. The result in Fig. 2a shows that the DO trend was consistent for the sample with ORCs and control experiments, while the DO level was significantly higher in the presence of ORCs than the control experiment. The concentration of DO started to decrease after 24 h of the fermentation period. After 48 h, the DO concentration rose and reached to a peak level. Overall, the addition of ORCs brought about 12.5% increase in DO concentration for the first 48 h of the fermentation, whereas the average level of DO was 3.3-times higher than the control run during the rest of the fermentation. The variation of pH was also monitored during the fermentation with ORCs, and the results are exhibited in Fig. 2b. The same strategy was noticed for the pHs in the presence of ORCs and control samples. However, the pH of control solution was higher than the medium supplemented with ORCs for the first 35 h of incubation. The pHs began to gradually decrease until 72 h, and followed an increase and reached the values of 8.51 and 8.10 for the sample containing ORCs and control, respectively. The results also disclosed that the solution supplemented with ORCs had the higher pH after 35 h of fermentation as compared to the control sample. This might be attributed to the presence of ORCs which bring about a rise in pH by producing strong bases compounds, such as Ca(OH)2 and Mg(OH)2, which facilitates bacterial CaCO3 precipitation.
3.4
Morphological observation
Crystal shapes of CaCO3 particles are distinguishable by SEM. The morphology of CaCO3 crystals is more complex in the enzymatic systems, and it can be affected in the presence of the enzyme. Sondi and Matijević (2001) reported the regulatory effect of the enzyme on the morphology of the CaCO3 crystals. Morphologies of the CaCO3 crystals precipitated in the presence of various ORCs during the screening and optimization studies, are summarized in Figs. 3 and 4. Based on the results obtained at screening study (Fig. 3), it was visually confirmed that different shapes of crystals, including small rounded body and rhombohedral, were precipitated. As depicted in Fig. 3a-c, the mixture of CaCO3 particles consisting of vaterite and calcite was induced in the media containing MP, UP, and CP. However, the majority of crystals precipitated in the presence of ZP were rhombohedral (calcite). It is worth noting that the average size of induced vaterite particles was ~10–30 µm, while different sizes of calcite crystals were observed at the screening stage. It was found that the size of calcite particles was mainly 20–40 µm in the presence of MP and UP, and 5–15 µm when CP and ZP were added to the fermentation media. As expected, a combination of vaterite and calcite was induced at optimization stage, and the SEM micrographs for the optimum sample are shown in Fig. 4.
6
The collected dry biosynthesis products were also examined using EDS analysis to observe the elemental compositions. As shown in Fig. 5, the EDS spectra for the optimum sample (containing ORCs) closely resembled the pure CaCO3, indicating the formed crystals were either calcite, vaterite and/or aragonite. Since aragonite particles were not detected by SEM and XRD, it can be concluded that the precipitated crystals are calcite and vaterite.
3.5
Characterization of crystals
The XRD peaks are appropriate indicators for qualitative and quantitative determination of bacterially induced CaCO3 precipitation. Therefore, the precipitated CaCO3 powders at screening study were subjected to XRD measurement and the patterns are shown in Fig. 6a. Interestingly, the presence of different ORCs at the screening stage resulted in a different portion of CaCO3 polymorphs. The highest portion of calcite was precipitated in the solution containing ZP, while the lowest concentration of calcite induced in the medium supplemented with MP. The comparison between UP and CP revealed that the solution containing CP, induced a higher portion of calcite than UP. It was also found that no aragonite was induced during the fermentation process. On the other hand, the addition of MP to the fermentation medium led to induce the highest portion of vaterite precipitation. The investigation also indicates that a higher portion of vaterite was induced in the solution with UP as compared to CP. However, no vaterite particles were detected when ZP was added to the fermentation medium. XRD analysis was also performed for the optimization media and the spectra are given in Fig. 6b. As expected, a combination of vaterite and calcite was induced when the optimum concentrations of ORCs were added to the fermentation solution (Fig. 6c).
4
Discussion
4.1
ORCs and CaCO3 precipitation
The applications of ORCs, including sodium percarbonate or metal peroxides, have been reported to support in situ aerobic biosynthesis (Cassidy and Irvine, 1999; Narendranath et al., 2000). In this sense, the aerobic biodegradation of contaminants by the addition of ORCs has been proposed under oxygen-limiting conditions (Heitkamp, 1997; Koenigsberg and Sandefur, 1999). However, the aerobic fermentation can be affected by many physical, chemical and biological conditions that influence the overall CaCO3 biosynthesis efficiency. Our previous study demonstrated that aeration has a positive effect on the bacterial production of CaCO 3 by providing a higher level of DO (Seifan et al., 2017). In general, the ORCs significantly affect the quantity of released oxygen and the pH (Walawska et al., 2007). The introduction of pure oxygen rather than air in the fermentation media can significantly increase the DO concentration (Tsai et al., 2009), and consequently, this contributes to enhancing the biomineralization efficiency. However, maintaining DO concentration greater than its critical level would be toxic for microorganisms (Kazzaz et al., 1996), and bacterially induced CaCO3 precipitation is affected accordingly. The ORC materials tend to release oxygen at a controlled rate to enhance the aerobic biomineralization processes by providing more oxygen. Eqs. 2–3 show the chemical reactions of peroxides towards the production of hydrogen peroxide and subsequently oxygen liberation, where M represents the divalent metal (Cassidy and 7
Irvine, 1999; Kao et al., 2003). As shown in the Eq. 2, hydrogen peroxide is produced by the reaction between peroxide (ORC) and water. This process is subsequently followed by decomposition of hydrogen peroxide into oxygen (Eq. 3). (2) (3) It has been reported that oxygen is required to initiate and maintain the bacterial activity for the biomineralization of CaCO3 which is induced through urea hydrolysis or oxidation of organic carbon pathways (Tziviloglou et al., 2016). Considering the poor solubility of oxygen in the water, the bio self-healing approach for concrete crack treatment is only limited to the surface areas where a sufficient amount of oxygen is available. To address this issue, we proposed the addition of ORCs. However, the addition of various ORCs results in the production of different CaCO3 concentrations. It was found that UP and MP are significant ORCs on enhancing CaCO3 precipitation, while CP and ZP have a negative effect on CaCO3 biomineralization. Zhang et al. (2016) reported that CP can increase the bacterially induced CaCO3 precipitation in the presence of Bacillus species. However, our data show that UP and MP have more significant influence on producing CaCO3. This might be due to the rapid oxygen-releasing rate of CP at the early stage of the fermentation (Lee et al., 2014), which leads to exceeding its critical level, and consequently, CaCO3 precipitation is inhibited. As depicted in Fig. 1, among the investigated ORCs, the presence of ZP in fermentation media results in the drastic decline in bacterial CaCO3 precipitation. As compared to the control experiment, a considerable reduction in CaCO3 precipitation was observed due to the presence of the lowest concentration of ZP (3.33 g/L). This shows that the availability of ZP has the most detrimental effect on the biomineralization process. Previously, Rothenstein et al. (2012) reported that the presence of zinc in culture media can affect the growth rate of Halomonas halophila. It is hypothesised that the zinc is extracellularly bound to the cells and consequently affects the CaCO3 precipitation. On the other hand, a low concentration of UP and MP resulted in a slight increase in CaCO3 precipitation. Due to a low solubility and slow reaction rate of MP with water, it has the slowest oxygen-releasing capability (Camci-Unal et al., 2013) which provides a sustained release of oxygen during the fermentation. Dissolution of UP in water not only releases oxygen, but also provides a higher supply of urea which is essential to inducing carbonate during biosynthesis. However, a greater amount of urea than it can be consumed by bacteria to initiate the biomineralization process, remains unused. Overall, the screening results suggest that UP and MP are the most promising sources for the support of bacterial production of CaCO 3, and therefore an optimization study was performed for further enhancement of CaCO3 biosynthesis.
4.2
Optimization of significant ORCs for CaCO3 precipitation
Adequate oxygen supply to the cells is often critical in aerobic fermentation; however, the excessive release of oxygen by ORCs might adversely affect the bioprocesses (Spain et al., 1989). Furthermore, it has been noted that the irreversible cell damage can occur as a result of temporary oxygen depletion (Lee, 1992). Therefore the optimization was carried out to propose an optimum concentrations for the selected ORCs which can provide a continuous supply of oxygen, and facilitates the bacteria to induce CaCO3 under oxygen-limiting conditions. The CCF design matrix used in the present investigation enabled us to study and explore the effect of various 8
concentrations of potent ORCs on CaCO3 precipitation. The regression analysis of the experimental design listed in Table 2 reflects that all single factor and quadratic model terms, excluding X12, are significant (pvalue<0.05) on bacterial precipitation of CaCO3. A p-value of less than 0.05 also shows that the interactive term of X1X2 significantly affects the biosynthesis of CaCO3. As compared to the control sample, the results for optimization study demonstrate that the biosynthesis of CaCO3 enhanced and the presence of the optimum concentrations of MP and UP resulted in an increase in CaCO3 concentration from 22.99 g/L to 34.39 g/L. This confirms that the optimization was successfully achieved. The comparisons between observed and predicted CaCO3 concentration showed a good correlation between the experimental results and the fitted model. The error associated with repetitions was determined based on the replicates of the central points. The analysis of variance results indicate an R2 value of 0.985 which ensures a satisfactory adjustment of the model to the experimental data. As given in Table 3, the significant regression and the non-significant lack of fit also suggest that the model has been well fitted to the experimental data. As depicted in Fig. 7, a 3D response surface plot was constructed to illustrate the synergistic effects of the influential ORCs and to provide a visual interpretation for the location of the optimal concentrations. The shape of the corresponding plot shows the mutual interaction between variables is significant, and CaCO3 precipitation is considerably affected by the concentration of UP and MP. The data indicate that the low and high concentrations of both UP and MP adversely affect the biomineralization of CaCO 3. The oxygen released by the low concentrations of ORCs could not meet the cell requirement, and the high levels of ORCs showed toxicity by releasing an excessive amount of oxygen than required by bacteria. The precipitation of CaCO 3 was enhanced with increases in the concentrations of UP and MP to approximately 3300 and 12 mg/L, respectively. However, further increases in the concentration of UP and MP led to a decrease in CaCO3 concentration. The high concentrations of UP and MP cause the oxygen releasing process to take place too quickly, and the resulted supersaturation state inhibits the bacterial activity. Another possible explanation for the inhibitory effect of high concentrations of UP and MP is due to oxygen toxicity which causes inhibition of metabolism and respiration in microorganisms (Haugaard, 1968).
4.3
Experimental verification
In order to validate the optimization results, verification experiments were performed at the predicted values derived from the model. The review of the optimization as a contour curve plot given in Fig. 7 shows the relative effects of UP and MP on CaCO3 precipitation. To evaluate the performance of optimized ORCs on the biomineralization process, the critical parameters such as DO and pH were monitored. The validation experiments showed that there is an increase in bacterial precipitation of CaCO3 as compared to the control run, and it has only a negligible difference with the value predicted by the model. More importantly, the optimized sample could accelerate the biomineralization of CaCO3. The presence of ORCs resulted in a 22.5% increase in CaCO3 precipitation at 72 h of fermentation. Taking into account that the majority of the concrete cracks are generated at the early age, an ideal bio self-healing compound requires to activate immediately upon crack formation and fill the entire crack in a short period of time. Moreover, it has been noted that the ORCs are able to last from four months to over a year (Koenigsberg and Sandefur, 1999). Therefore the addition of proposed
9
optimum ORCs as a supplementary bio self-healing agent can enhance the concrete performance by efficiently filling the concrete cracks upon their formation. The bacterial metabolic activity has an important role in the biomineralization process, and it can be affected by the level of DO. As shown in Fig. 2a, the samples containing the optimum concentrations of UP and MP have a higher level of DO throughout the fermentation as compared to the control samples. The higher DO level during fermentation not only boosts the cell populations, but also contributes to bacterial growth in oxygenlimiting conditions. These higher nucleation sites provide a favourable condition to further increase CaCO3 precipitation due to the controlled and continuous supply of oxygen which meets the requirement for bacteria to initiate the biomineralization process. The bacterial cell has an important role in the biosynthesis of CaCO3 precipitation. Stocks-Fischer et al. (1999) reported that the bacterial cells serve as nucleation sites in the biomineralization process. Eqs. 4–9 represent the bacterially induced CaCO3 precipitation process through urea hydrolysis pathway (Burne and Chen, 2000; Seifan et al., 2016b). →
(4) (5) (6) (7) (8) (9)
In general, a higher concentration of bacterial cells increases the urease concentration which catalyses the hydrolysis of urea into carbonate (Okwadha and Li, 2010). Therefore urea hydrolysis has a direct relationship with bacterial cell concentration, and this has a direct effect on CaCO3 precipitation. On the other hand, one of the most common issues associated with the presence of ORCs is the sudden release of oxygen, which may affect the bacterial metabolism and CaCO3 precipitation capacity. Since MP content in the optimized sample has a low solubility in water, it guarantees a gradual and continuous release of oxygen (Barbara Walawska et al., 2007). pH is another significant parameter on biomineralization of CaCO3 by affecting the bacterial urease activity (Gorospe et al., 2013). Our results also confirm the effect of pH on biomineralization of CaCO3. It was noticed that the control experiment had a higher pH, and more CaCO3 was precipitated over the first 35 h of fermentation. However, the optimized sample had higher pH and more CaCO3 precipitation as compared to the control for the rest of fermentation period. This is due to the fact that carbonate tends to dissolve rather than precipitate at a low pH level (Loewenthal. R.E and Marais. G.V.R, 1978). The increase of H+ in solution caused a decline in pH for both optimized and control experiments due to CO 2 dissolution. On the other hand, after 72 h of fermentation, the produced OH- neutralized H+ in fermentation medium through the dissolution of NH3(g) and, consequently, pH increased (Becker et al., 2003; Li et al., 2013). Overall, a greater pH fluctuation was observed in the control solution during the dropping of pH, while in both fermentation runs, the pH increased more steadily. Over the oxygen liberating period, the reaction between ORCs and water results in increase in pH, and this leads to stabilizing the pH variation.
10
4.4
Morphological observation and crystal characterization
The EDS spectrum taken for the bioprecipitates clearly showed that the main compositions are Ca, O, and C. A high degree of similarity between the pure CaCO3 and precipitated crystals is another indication that the presence of ORCs can successfully facilitate the CaCO3 biosynthesis process. Bioprecipitation of CaCO3 may result in the production of different polymorphs, including calcite, vaterite, aragonite, and two hydrated crystalline phases, monohydro calcite and ikaite (Kaur et al., 2013). It has been noted that the production of the polymorphs depends on bacterial strains, growing environments, and their chemical nature (González-Muñoz et al., 2010; Wei et al., 2015). Taking into account that CaCO3 polymorphs have different mechanical and physical properties (i.e., density, hardness and solubility), and they may be used in various applications, it requires determining whether the presence of ORCs will change the CaCO3 polymorphs. For the bio-concrete application, the precipitation of vaterite is preferred rather than calcite. Vaterite has a lower density than calcite, and this contributes to occupy more space and the efficiency of the bio-concrete will be increased. Bacterial cell wall characteristics and growth medium composition are the main factors influencing the bacterially induced CaCO3 morphology. Furthermore, a number of previous studies have demonstrated the role of bacterial extracellular polymeric substance (EPS) in the bacterial production of CaCO3 polymorphs (Braissant et al., 2003; Kawaguchi and Decho, 2002). Specifically, Bosak and Newman (2005) noted that the presence of EPS encourages the precipitation of vaterite particles rather than calcite. In our investigation the results obtained by XRD and SEM disclosed that the presence of ZP has an effect on the CaCO3 morphology and vaterite formation is suppressed. This might be due to the changes in nucleation energy caused by extracellular attachment of zinc onto the bacterial cell wall. This result corresponds with the finding of Rothenstein et al. (2012) who observed that the availability of zinc in a fermentation solution had an effect on the morphology of induced CaCO3 precipitation.
5
Conclusion
In this investigation, we proposed a simple, active and long-term protocol to not only enhance but also accelerate the bacterially induced CaCO3 precipitation up to 34.39 g/L. The experimental results clearly show that the CaCO3 precipitation and cell growth are significantly enhanced by the addition of optimum concentrations of UP (1800 mg/L) and MP (8.3 mg/L). It is believed that the optimum concentrations of ORCs are promising to enhance the bio self-healing concrete performance. The addition of proposed compounds can activate and support the biomineralization process in oxygen-limiting areas such as deep cracks and interior parts of the concrete matrix.
Acknowledgments This investigation was financially supported by The University of Waikato, New Zealand.
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Competing interests The authors declare that they have no conflict of interest.
Ethical approval This study does not contain any studies with human participants or animals performed by any of the authors.
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Seifan M., Samani A.K., Burgess J.J., Berenjian A., 2016a. The Effectiveness of Microbial Crack Treatment in Self Healing Concrete In: Berenjian A., Jafarizadeh-Malmiri H., Song Y. (Eds.), High Value Processing Technologies. Nova Science, pp. 97-123. Seifan M., Samani A.K., Berenjian A., 2016b. Bioconcrete: next generation of self-healing concrete. Appl. Microbiol. Biotechnol. 100, 2591-2602. Seifan M., Samani A.K., Berenjian A., 2016c. Induced calcium carbonate precipitation using Bacillus species. Appl. Microbiol. Biotechnol. 100, 9895-9906. Seifan M., Samani A.K., Berenjian A., 2017. New insights into the role of pH and aeration in the bacterial production of calcium carbonate (CaCO3). Appl. Microbiol. Biotechnol. 101, 3131– 3142. Sondi I., Matijević E., 2001. Homogeneous precipitation of calcium carbonates by enzyme catalyzed reaction. J. Colloid. Interf. Sci. 238, 208-214. Spain J.C., Milligan J.D., Downey D.C., Slaughter J.K., 1989. Excessive Bacterial Decomposition of H2O2 During Enhanced Biodegradation. Ground Water. 27, 163-167. Stocks-Fischer S., Galinat J.K., Bang S.S., 1999. Microbiological precipitation of CaCO3. Soil. Biol. Biochem. 31, 1563-1571. Tsai T.T., Kao C.M., Surampalli R.Y., Chien H.Y., 2009. Enhanced bioremediation of fuel-oil contaminated soils: Laboratory feasibility study. J. Environ. Eng. 135, 845-853. Tziviloglou E., Van Tittelboom K., Palin D., Wang J., Sierra-Beltrán M.G., Erşan Y.Ç., Mors R., Wiktor V., Jonkers H.M., Schlangen E., De Belie N., 2016. Bio-based self-healing concrete: from research to field application. In: Hager M., Van der Zwaag S., Schubert U.S. (Eds), Selfhealing Materials. Springer, New York LLC, pp 345-386. Vogt C., Alfreider A., Lorbeer H., Hoffmann D., Wuensche L., Babel W., 2004. Bioremediation of chlorobenzene-contaminated ground water in an in situ reactor mediated by hydrogen peroxide. J. Contam. Hydrol. 68, 121-141. Walawska B., Gluzińska J., Miksch K., Turek-Szytow J., 2007. Solid inorganic peroxy compounds in environmental protection. Pol. J. Chem. Technol. 68-72. Wang J., Dewanckele J., Cnudde V., Van Vlierberghe S., Verstraete W., De Belie N., 2014. X-ray computed tomography proof of bacterial-based self-healing in concrete. Cem. Concr. Compos. 53, 289-304. Wei S., Cui H., Jiang Z., Liu H., He H., Fang N., 2015. Biomineralization processes of calcite induced by bacteria isolated from marine sediments. Braz. J. Microbiol. 46, 455-464. Zhang J.L., Wang C.G., Wang Q.L., Feng J.L., Pan W., Zheng X.C., Liu B., Han N.X., Xing F., Deng X., 2016. A binary concrete crack self-healing system containing oxygen-releasing tablet and bacteria and its Ca2+-precipitation performance. Appl. Microbiol. Biotechnol. 1-12.
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Fig.1 The effect of oxygen releasing compounds on bacterially induced CaCO3 precipitation.
Fig. 2 The variations of DO and pH for the amended fermentation medium containing the optimum concentrations of selected ORCs.
15
Fig. 3 SEM micrograph of CaCO3 crystals at the screening stage for the medium supplemented with a) MP, b) UP, c) CP and d) ZP.
Fig. 4 SEM micrograph of CaCO3 precipitation when the media was supplemented with the optimum concentrations of ORCs.
16
Fig. 5 EDS spectra for the pure CaCO3 crystal and the particle precipitated in the media supplemented with optimum concentrations of ORCs.
Fig. 6 XRD spectra of bacterially induced CaCO3 precipitation in the a) screening study, b) optimization study, and c) media supplemented with optimum concentrations of ORCs.
17
Fig. 7 Response surface plot shows the synergistic effects of influential ORCs (UP and MP) on bacterial induced CaCO 3 precipitation; a review of the optimization. Table 1 Experimental conditions of the central composite face-centered (CCF) design and responses indicating both original and scaled factors. Factors a X1 (mg/L)
X2 (mg/L)
Observed CaCO3 (g/L)
Predicted CaCO3 (g/L)
1
333.33 (-1)
6.67 (-1)
34.19
34.71
2
4333.33 (+1)
6.67 (-1)
34.39
33.32
3
333.33 (-1)
33.33 (+1)
4.08
5.92
4
4333.33 (+1)
33.33 (+1)
15.17
15.42
5
333.33 (-1)
20.00 (0)
33.49
31.12
6
4333.33 (+1)
20.00 (0)
34.26
35.18
7
2333.33 (0)
6.67 (-1)
34.36
34.91
8
2333.33 (0)
33.33 (+1)
13.66
11.57
9
2333.33 (0)
20.00 (0)
32.34
34.05
10
2333.33 (0)
20.00 (0)
34.19
34.05
11
2333.33 (0)
20.00 (0)
34.07
34.05
Run
a
Values are expressed as real and scaled levels, X1 = Urea-hydrogen peroxide (UP) and X2= Magnesium peroxide (MP)
Table 2 Statistical analysis from the central composite face-centered (CCF) design experiments. Term
Coefficient
Standard Error
p-value
Constant
34.05
0.99
3.95e-07
18
X1
2.03
0.79
0.050
X2
-11.67
0.79
2.56e-05
X12
-0.89
1.22
0.494
-10.81
1.22
0.000
0.97
0.037
2
X2
X1 X2
2.72 2
2
2
X1: UP, X2: MP, R =0.985, R (Adj.)=0.969 and Q =0.865
Table 3 Analysis of variance of the quadratic model for the central composite face-centered (CCF) design. Source
DF
SS
MS
SD
F value
p-value
Regression
5
1206.40
241.28
15.53
64.52
0.000
Residual
5
18.69
3.74
1.93
-
-
Lack of Fit
3
16.58
5.53
2.35
5.22
0.165
Pure error
2
2.12
1.06
1.03
-
-
Total corrected
10
11.07
-
-
1225.10
122.51
DF degree of freedom, SS sum of squares, MS mean sum of squares, SD standard deviation
Highlights
Higher DO levels provided for the bacterial cells in the oxygen-limiting conditions.
Optimization of ORCs accelerated bacterially induced CaCO3 precipitation.
Crystal morphologies changed in the presence of ORCs.
19