Mechanical properties evaluation of waste gangue-based cemented backfill materials based on an improved response surface model.

Traditional mining methods damage the cultivated land and produce gangue waste that often contaminates the environment. Yet, these problems can be mitigated by transforming the waste into gangue-based cemented backfill material (GCBM), whose mechanical properties are crucial for surface protection. Therefore, in this study, an intelligent model based on laboratory tests was developed to evaluate the GCBM's mechanical properties. The strength tests and polynomial response surface model (PRSM) were used to analyze the non-linear correlation between the influencing factors and the uniaxial compressive strength (UCS). Meanwhile, the importance of multidimensional factors was analyzed by the mean impact value, revealing that concentration and gangue proportion are the most sensitive factors. In addition, an intelligent response surface model (IRSM) based on support vector regression model was constructed by enhancing an optimization algorithm with chaotic mapping and adaptive methods. The performance of the traditional PRSM and the novel IRSM was compared, and the IRSM was validated. The IRSM can predict UCS more efficiently and effectively than the traditional PRSM under high-dimensional factors, with R2 of 0.96 and MBE of 0.05. This indicated that the IRSM has the potential to promote coal mine waste reduction and environmental protection.

Insight into the Micro Evolution of Backfill Paste Prepared with Modified Gangue as Supplementary Cementitious Material: Dissolution and Hydration Mechanisms.

Gangue-based backfill cementitious materials (BCM) are widely applied due to their low CO2 footprint, while the application is restricted by gangue's low reactivity. In this study, dry chemical modification was developed to modify the gangue, and multiple characterized approaches were used to characterize the dissolution property, mineral composition, and particle size distribution of modified gangue (MCG), as well as the compressive strength and microstructure of BCM. The findings show that the residue weight of MCG stabilized at 2 wt.% of formic acid, and the modification reduces the kaolinite and calcite, resulting in smaller particles. Additionally, the three days compressive strength of the BCM made with MCG was improved from 0.3 MPa to 0.6 MPa. Attributed to the increased reactivity of MCG, it was found that the dissolution weight increased by 2.13%. This study offers a novel method for activating gangue and a new kind of MCG-prepared BCM, which makes a significant contribution towards achieving the UN Sustainable Development Goals.

Preventing water inrush hazards in coal mines by coal gangue backfilling in gobs: influences of the particle size and stress on seepage characteristics.

The backfilling mining method that fills gobs with coal gangue can prevent water inrush hazards, protect groundwater resources, and protect the ecological environment of the mining area. However, initial conditions including the particle size distribution of gangue and the stress environment may affect the seepage characteristics of gangue backfill and inrush prevention ability. Taking the particle size and stress as main controlling factors, the seepage tests were designed for gangue to evaluate influences of the particle size and stress on the void ratio, permeability, and non-Darcian flow factor of gangue. In the meantime, the four stages in dynamic changes of seepage channels were studied and the impervious envelope lines of gangue backfill materials were provided. The results show that the larger the particle sizes, the stronger the crushing resistance of particles; under high stress (> 6.67 MPa), seepage channels in small gangue particles (< 5 mm) change in a more complex manner, and the non-Darcian flow phenomena become more significant. The particle size and stress exert significant influences on the seepage characteristics. Therefore, when reducing water inrush hazards by gangue backfilling in gobs, the particle size distribution should be optimized by combining the stress and water pressure conditions. Seepage channels in gangue backfill materials vary with changes in the particle size and stress. Their variation can be divided into four stages: shrinkage of seepage channels, reconstruction of seepage channels, dynamic equilibrium between slight expansion and shrinkage, and persistence of the impervious effect. After the first and second stages have been fully developed, the preliminary impervious conditions are met; after full development of the fourth stage, the gangue backfill materials reach an impervious state.

Control of surface deformation and overburden movement in coal mine area by an innovative roadway cemented paste backfilling method using mining waste.

Caving mining method could lead to massive waste rocks hauled to surface while leaving a large void in underground. This would eventually result in the surface subsidence and damage to the environment and surface infrastructures. In this study, we proposed three different backfilling methodologies to minimise the surface subsidence being 1) 100 % mining and 100 % backfilling (method 1); 2) leaving one slice of coal between two backfilled slices (method 2) and 3) leaving one slice of coal between one backfilled slice (method 3). The backfilling materials are made of waste rock, fly ash and cement and the optimal ratio has been found through the test program designed based on the orthogonal experiment design method. The strength of the backfilling paste is 3.22 MPa at the axial strain 0.033. The mine scale numerical simulation has also been conducted and it was concluded that the method 1 would lead to 0.098 m roof deformation in underground roadway whereas the method 2 and method 3 only induced a roof deformation around 32.7 % and 17.3 % of that induced by the method 1, respectively. All three methodologies have been approved to minimise the roof deformation and disturbance to the rock by mining operations. At last, the surface subsidence has been scientifically evaluated based on the probability integration method of surface movement. It indicated that the surface subsidence, horizontal movement, inclined movement and curvature of rock surrounding the panel void were all below the minimum value required by regulation. This confirmed that the selected backfilling mining is able to ensure the integrity of the surface infrastructures. This technology provides a new way to control the surface subsidence caused by coal mining.

Turn "Waste" Into Wealth: MoO2 @coal Gangue Electrocatalyst with Amorphous/Crystalline Heterostructure for Efficient Li-O2 Batteries.

Unreasonable accumulation of coal gangue in mining area has become the major source of global pollution. Probing the high-valued utilization of coal gangue has become a key approach to address the problem. Herein, a promising catalyst of MoO2 @coal gangue with amorphous/crystalline heterostructure derived from mine solid waste, which acts as an efficient cathode for Li-O2 batteries is first reported. Impressively, the as-prepared catalyst exhibits a favorable initial discharge capacity of 9748 mAh g-1 and promising long-term cyclic stability over 2200 h. Experimental results coupled with density functional theory (DFT) analysis reveal that the synergistic interaction between high-activity MoO2 and stable SiO2 , unique amorphous/crystalline heterostructure and the modified interfacial adsorption of LiO2 intermediate are critical factors in promoting the electrochemical performance. This work provides a new insight to design marked electrocatalysts by mine solid waste for Li-O2 batteries.

Evaluation of rheological and mechanical performance of gangue-based cemented backfill material: a novel hybrid machine learning approach.

Waste discharge and surface damage are the unavoidable consequences of coal mining. However, filling waste into goaf can help reuse waste materials and protect the surface environment. In this paper, it is proposed to fill coal mine goaf with gangue-based cemented backfill material (GCBM), while the rheological and mechanical performances of GCBM influence the filling effect. A method that combines laboratory experiments and machine learning is proposed to predict the GCBM performance. The correlation and significance of eleven factors that affect GCBM are analyzed using random forest method, and the nonlinear effects of the main factors on the slump and uniaxial compressive strength (UCS) are analyzed. The optimization algorithm is improved, and the improved algorithm is combined with a support vector machine to build a hybrid model. The hybrid model is systematically verified and analyzed using predictions and convergence performances. The results demonstrate that the R2 of the predicted and measured values is 0.93 and the root mean square error is 0.1912, indicating that the improved hybrid model can effectively predict the slump and UCS and can promote sustainable waste use.

Experimental Study on Performance Optimization of Grouting Backfill Material Based on Mechanically Ground Coal Gangue Utilizing Urea and Quicklime.

Previously conducted studies have established that grouting backfill in mining-induced overburden bed separation and mined-out areas with broken rocks provides an efficient strategy to control strata movement and surface subsidence caused by underground mining. Grouting backfill materials (GBMs) based on coal gangue (CG) are highly desirable in coal mining for accessibility to abundant CG and urgent demand for CG disposal. However, CG is generally employed as coarse aggregate due to rather rigid and inert properties, limiting its application in GBMs. Herein, to reduce reliance on fine aggregates, such as fly ash and clay, cemented GBM formulations using ground CG powder as a dominant component were proposed. Urea and quicklime were utilized as additives to optimize slurry transportability and compressive strength. Besides typical grinding without additives, CG powder was also prepared via grinding with urea, intending to enhance the hydrogen bonding (HB) interaction between urea and minerals contained in CG. The effect of grinding time and urea on CG particle size and phase composition was investigated. Then, the dependence of slurry transportability and compressive strength on grinding time, solid concentration, urea, and quicklime dosage were revealed. It has been experimentally proved that grinding for 30~90 min significantly decreased CG particle size and even induced crystal deformation of dolomite and kaolinite. For GBMs, urea improved slurry flowability, possibly caused by decreased water absorption on the CG surface and the release of water encapsulated in hydrated cement particles. Moreover, quicklime strengthened GBM bodies, which could be explained by an accelerated pozzolanic reaction between CG powder and additional CH supplied by quicklime hydration. G60U3-based GBM-B2 with 5% quicklime provided a stable and smooth slurry with a bleeding rate of 1.25%, a slump flow of 205 mm, and a hardened body with a seven-day UCS of 1.51 MPa.

Optimized preparation of gangue waste-based geopolymer adsorbent based on improved response surface methodology for Cd(II) removal from wastewater.

Resource utilization of gangue solid waste has become an essential research direction for green development. This study prepared a novel gangue based geopolymer adsorbent (GPA) for the removal of Cd(II) from wastewater using pretreatment gangue (PG) as the main raw material. The ANOVA indicated that the obtained quadratic model of fitness function (R2 > 0.99, P-value <0.0001) was significant and adequate, and the contribution of the three preparation conditions to the removal of Cd(II) was: calcination temperature > Na2CO3:PG ratio > water-glass solid content. The hybrid response surface method and gray wolf optimization (RSM-GWO) algorithm were adopted to acquire the optimum conditions: Na2CO3:PG ratio = 1.05, calcination temperature of 701 °C, solid content of water glass of 22.42%, and the removal efficiency of Cd(II) by GPA obtained under the optimized conditions (GPAC) was 97.84%. Adsorption kinetics, adsorption isotherms and characterization by XRD, FTIR, Zeta potential, FSEM-EDS and BET were utilized to investigate the adsorption mechanism of GPAC on Cd(II). The results showed that the adsorption of Cd(II) from GPAC was consistent with the pseudo-second-order model (R2 = 0.9936) and the Langmuir model (R2 = 0.9988), the adsorption was a monolayer adsorption process and the computed maximum Cd(II) adsorption (50.76 mg g-1) was approximate to experimental results (51.47 mg g-1). Moreover, the surface morphology of GPAC was rough and porous with a specific surface area (SSA) of 18.54 m2 g-1, which provided abundant active sites, and the internal kaolinite was destroyed to produce a zeolite-like structure where surface complexation and ion exchange with Cd(II) through hydroxyl (-OH) and oxygen-containing groups (-SiOH and -AlOH) were the main adsorption mechanisms. Thus, GPAC is a lucrative adsorbent material for effective Cd(II) wastewater treatment, complying with the "high value-added" usage of solid wastes and "waste to cure poison" green sustainable development direction.

Control effect of coal mining solid-waste backfill for ground surface movement in slice mining: a case study of the Nantun Coal Mine.

Management of solid waste and protecting the ecological balance of the region are key challenges that the coal mining industry has to face. This study evaluated the effect of solid waste backfilling mining on the overlying strata movement and surface deformation variation pattern in slice mining. The mechanical characteristics of different cemented paste backfills (CPB) were compared. The CPB specimens were made of coal gangue and cement with or without the addition of fly ash. The experiments showed that the mechanical strength of the CPBs made of coal gangue and cement increased dramatically. A numerical simulation was then performed to analyze the variation patterns of the overlying strata displacement and surrounding rock stress distribution before and after filling the 3lower and 3upper coal seams with CPB. The CPBs reduced the movement of the surface by 95.1% and 95% during the mining of the 3lower and 3upper coal seams, respectively. Finally, we used a mining-induced subsidence prediction and analysis system to predict the influence of the 3lower and 3upper coal seams on the ground surface subsidence. It was found that the ground surface subsidence induced by CPB mining was 1/20 that of the cumulative ground surface subsidence caused by caving mining. CPB mining could effectively control the ground surface subsidence caused by multi-slice mining of the thick coal seam, offering protection for buildings above the ground. Our research provides theoretical and technical support for coal mining under buildings subjected to similar conditions.

Effects of lateral cyclic loading on compression behaviours of granular waste rocks for backfilling to reduce environmental pollution.

Granular waste rocks filled in goaf can replace coal seams to support roofs, thus reducing the extent of overlying strata movement, and thus reducing the environment damage caused by coal mining. To better to control the compression-induced deformation (CID) of waste rocks for backfill (WRBs), a loose material, it is feasible to apply lateral cyclic loads on granular waste rocks in advance. In order to study the effect of lateral cyclic loading on granular waste rocks, by utilising pre-lateral cyclic loading and axial loading, the deformation of granular waste rocks under load was tested on a compression simulation experimental platform for solid backfill materials. Furthermore, the changes in displacement, stress and mass of granular waste rocks during lateral cyclic loading were attained. The test results showed that (1) the loading stress progressively increased with the growth of the loading displacement, in which the rising process was divided into three stages according to the rate of loading. (2) With the increase in number of loading cycles, the rate of increase of stress in stage I increased and the stress reached increasingly higher levels; at the same time, stage II was gradually shortened. Eventually, only a single stage prevailed as the stress rapidly reached its preset maximum value, and the final displacement of the samples gradually declined. (3) The axial stress-strain curves of the samples exhibited a quasi-exponential relationship. Through lateral cyclic loading, the relative density of WRBs was significantly improved, and their deformation resistance was strengthened. (4) During backfill mining, lateral cyclic loads were applied to granular waste rocks, which improved the bearing capacity thereof and reduced strata movement and surface subsidence. This is beneficial to the protection of the surface environment and surrounding buildings.

Identification of agricultural quarantine materials in passenger's luggage using ion mobility spectroscopy combined with a convolutional neural network.

As economic globalization intensifies, the recent increase in agricultural products and travelers from abroad has led to an increase in the probability of invasive alien species. A major pathway for invasive alien species is agricultural quarantine materials (AQMs) in travelers' baggage. Thus, it is meaningful to develop efficient methods for early detection and prompt action against AQMs. In this study, a method based on the combination of odor detection of AQMs using ion mobility spectroscopy (IMS) and convolutional neural network (CNN) analysis for the identification of AQM species in luggage was developed. Two different ways were investigated to feed the IMS data of AQMs into the CNN, either as one-dimensional data (1D) (as a spectrum) or as two-dimensional data (2D) (as an IMS topographic map). The performances of CNN models were also compared to those of the commonly used classification algorithms: partial least squares discriminant analysis (PLS-DA) and soft independent modeling of class analogy (SIMCA). By doing gradient-weighted class activation mapping (Grad-CAM), the essential IMS feature regions from the CNN models to predict different AQM species were also identified. The results of this research demonstrated that the application of the CNN to the IMS data of AQMs yielded superior classification performance compared to PLS-DA and SIMCA. Especially, the CNN-2D model which utilized the IMS topographic map as input achieved the best classification accuracy both on the calibration and validation sets. In addition, the Grad-CAM method had an ability to detect critical discriminating spectral regions for different types of AQM samples, and could provide explanation for the CNNs' decision-making. Despite the inherent limitations of the present analytical protocol, the results showed that the method of IMS in combination with a CNN has great potential to be a complement for sniffer dogs and X-ray imaging techniques to detect AQMs.

Thermal enhancement of gangue-cemented paste backfill with graphite and silica sand: an experimental investigation.

Thermal conductivity of mine backfill is vital for understanding the geothermal energy extraction potential in deep underground mines. Geothermal energy extraction efficiency could be improved with higher thermal conductivity of backfill. Thermal conductivities of gangue-cemented paste backfill enhanced with graphite and silica sand were investigated through laboratory tests in this article. The thermal conductivity measurement was conducted using the Hot Disk Thermal Constants Analyzer. Effects of graphite and silica sand on the thermal conductivity, slump, and compressive strength of gangue-cemented paste backfill were analyzed. The results highlighted the favorable influence of graphite on the thermal performance of backfilling materials, with adverse effect on the mechanical behavior and negative impact on the flowability. Thermal conductivity of gangue-cemented paste backfill markedly increased with graphite ratio, while more water is consumed for the workable slurry with the increased graphite ratio, which also leads to the degradation of compressive strength. The reasonable graphite content should be determined with the expected thermal enhancement and acceptable compressive strength. The addition of silica sand can effectively enhance the thermal conductivity of GCPB without degrading the compressive performance and flow performance. This study would provide a new insight into the design of backfill considering the thermal conductivity and lay a foundation for the efficient geothermal energy in deep mines.

Experimental study of microorganism-induced calcium carbonate precipitation to solidify coal gangue as backfill materials: mechanical properties and microstructure.

The treatment of coal gangue solid waste and microbially induced calcium carbonate precipitation (MICP) consolidate technology is a focus of research at home and abroad. MICP technology was used to solidify and cement coal gangue particles and endows them with a certain strength. The process does not use the traditional cementitious material (Portland cement) and is eco-friendly and pollution-free. The mechanical properties including unconfined compressive strength, CaCO3 content, scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and infrared spectroscopy (FTIR) were used for macroscopic and microscopic analyses. The results show that the average strength of CG-based bio-mineralized backfill materials reaches 1.55 MPa and the maximum strength is 2.17 MPa, suggesting the potential for its use as an underground fill. Compared with unmineralized gangue, the CaCO3 crystal content in CG-based mineralized material is increased by 8.75% on average, and the maximum content is 13.34%. In the process of bacterial liquid perfusion, there is uneven distribution of bacteria in the material, which results in fewer CaCO3 crystals being locally generated in the mineralized material and affects the overall compressive strength of gangue columns. Moreover, the greater the amount of calcium carbonate, the larger the strength of the mineralized material. SEM analysis results indicate that the gaps between gangue particles are filled with CaCO3 crystals, and the calcium carbonate crystals are mostly polyhedral, showing stacked growth and contain a small number of spherical crystals that exist alone. The results of FTIR and EDS analysis show that the CaCO3 crystals in the mineralized material are mainly in the form of calcite, followed by a small amount of vaterite. Comprehensive analysis demonstrates that the preparation of CG-based bio-mineralized backfilling materials is successful, and this experiment provides new ideas and methods for the treatment of solid waste such as coal gangue and building material waste.

Feature selection of infrared spectra analysis with convolutional neural network.

Data-driven deep learning analysis, especially for convolution neural network (CNN), has been developed and successfully applied in many domains. CNN is regarded as a black box, and the main drawback is the lack of interpretation. In this study, an interpretable CNN model was presented for infrared data analysis. An ascending stepwise linear regression (ASLR)-based approach was leveraged to extract the informative neurons in the flatten layer from the trained model. The characteristic of CNN network was employed to visualize the active variables according to the extracted neurons. Partial least squares (PLS) model was presented for comparison on the performance of extracted features and model interpretation. The CNN models yielded accuracies with extracted features of 93.27%, 97.50% and 96.65% for Tablet, meat, and juice datasets on the test set, while the PLS-DA models obtained accuracies with latent variables (LVs) of 95.19%, 95.50% and 98.17%. Both the CNN and PLS models demonstrated the stable patterns on active variables. The repeatability of CNN model and proposed strategies were verified by conducting the Monte-Carlo cross-validation.

Integrated green mining technology of "coal mining-gangue washing-backfilling-strata control-system monitoring"-taking Tangshan Mine as a case study.

In Tangshan Mine, there are four engineering problems, including the layout of multiple seam mining system, serious environmental damages caused by gangue accumulation and surface collapse, nearly 100 million tons of three under coal (coal trapped under buildings, water bodies, and railways) to be released, and the control accuracy of stratum formations to be improved. The work developed the integrated green mining technology of coal mining, gangue washing-backfilling, strata control, and system monitoring. First, a production system was designed for surface-underground transportation of backfilling materials, underground gangue separation, multiple-seam combined backfilling, and mining. Second, key backfilling equipment was developed at mining heights of 2.2 and 3.5 m by backfilling system layout and precise stratum control methods in Tangshan Mine. After real-time monitoring of stope pressure, backfilling effect, and surface deformation, we evaluated the implementation effect of mining, washing, and backfilling technology. The integrated coal mining in seams 5, 8, and 9 of Tangshan Mine showed that the four backfilling surfaces of T3281, T3292, F5001, and F5002 recovered 946,000 t of raw coal and 1.18 million tons of filled gangue, with a net profit of 363.20 million yuan. The maximum land subsidence values (18, 119, 64, and 47mm) were far lower than the deformation extremes based on the requirements of surface building protection.

Mining footprint of the underground longwall caving extraction method: A case study of a typical industrial coal area in China.

Longwall caving mining (LCM) can lead to many environmental problems that have drawn worldwide attention. A previous survey found that most scholars tend to analyze the two issues separately, that is, coal mining-induced subsidence and heavy metal pollution sources in the soil of the mining regions. Based on field monitoring as well as the collection and analysis of soil samples, a previous study estimated ground settlement and analyzed the surface subsidence law and spatial distribution characteristics of heavy metals in soils. Moreover, a geographic information system was combined with multivariate statistical analysis methods to analyze the heavy metal pollution sources in soils. At the same time, the mechanism of heavy metal accumulation in the subsidence area was analyzed. The study found that the most active subsidence of settlement was 137.5 m behind the workface and moved forward with the workface. LCM has already caused significant disturbance to the soils in the Hengyuan Mine. Moreover, the distribution pattern of eight heavy metals was consistent with the surface subsidence law. The sources of heavy metal pollution in the soils were also identified; namely, coal mining-induced subsidence (64.1%) and mixed transportation and wind-mediated spread (35.9%), offering a reinterpretation of the LCM's footprint.

Risk Assessment of Heavy Metals in Overlapped Areas of Farmland and Coal Resources in Xuzhou, China.

Heavy metals (As, Cu, Cd, Cr, Pb, Zn, Hg) in soil of a typical overlapped area of farmland and coal resources (OAFCR) in Xuzhou were investigated, meanwhile the pollution levels and risks of there were discussed. The results are: Pollution Load Index (PLI) showed no heavy metals (HMs) pollution; 3.74% of soil samples were above moderately accumulated with Hg; the ecological risk (Er) values followed the order: Hg > Cd > Cu > As > Pb > Cr > Zn, and there has a moderate degree of potential ecological risk (PER) with the mean PER of 184.26; the non-carcinogenic risk of all seven HMs to human beings is acceptable, and the carcinogenic risk caused by As, Cd and Cr can be tolerated; the exposure ways both of carcinogenic and non-carcinogenic is: oral > dermal > inhalation, while children are suffering higher health risks than adults.

Long term leaching behavior of arsenic from cemented paste backfill made of construction and demolition waste: Experimental and numerical simulation studies.

The arsenic long-term leaching behavior of the cemented paste backfill obtained from the construction and demolition waste (CPB-CDW) is captured, which can be utilized in the potential engineering application. Laboratory studies were conducted on samples obtained from a mining site and the test results were imported into a numerical simulation model. It was found that the Elovich equation can describe well the As leaching behavior. Initially, the As concentrations decreased in the roadway in the mine and then increased along the roadway and attained a maximum concentration (8.149 × 10-3 mg/L) at the lower segment. When the groundwater was in the static mode, the As concentration increased dramatically followed by a gradual increase. Eventually, the concentration decreased gradually. For the dynamic condition, the As tended to move in a cluster form and the associated leaching and mass transfer process of As in the CPB-CDW were similar to those observed when the groundwater was in a static condition. However, the difference in the distribution of the amount of As in the leachate fluctuated continuously and the overall trend was to approach a steady state. As such, the time frame of such a mass transfer in the mobilized water is reduced significantly.

A preliminary study of solid-waste coal gangue based biomineralization as eco-friendly underground backfill material: Material preparation and macro-micro analyses.

Solid-waste coal gangue (CG) mixed with cement as underground backfilling material is widely applied in coal mines throughout China. However, this material can pollute the environment during its production, preparation, and transportation, which is mainly caused by cement. As a cement-free eco-friendly technology, microbially induced carbonate precipitation (MICP) technology can produce biomineralization products to consolidate loose grains, and the microbial growth environment is adapted to underground temperature with no pollution. To this end, this study gets the Bacillus pasteurii with special resistance by strain domestication, proposes a CG-based bio-mineralized underground backfilling material without using cement, and analyses the characteristics of it from macro- to microscopic perspectives by dissolution test, scanning electron microscopy (SEM), Energy-dispersive spectroscopy (EDS) and X-ray diffraction (XRD). The results indicate that strain domestication leads to B. pasteurii, which can withstand CG leaching solution and 1 M urea simultaneously. This satisfies the basic requirements of CG based mineralized material. Through the circulation perfusion method, the intact CG based biomineralized specimens are obtained. Macroscopically, the bacteria bind gangue grains into a whole with high biomineral content (11.66%). The utilization rate of mineralizing solution is up to 66.82% which makes good use of raw materials. Microscopically, a new crystal formation is observed, and CG particles are consolidated well where the crystals precipitate to fill the pores and bind the particles together. Hence this method has a significant influence on the deposition of biominerals. Meanwhile the biomineralization improves the microstructure considerably and bonds the CG particles as a whole. A comprehensive analysis of the test results shows that, from an environment viewpoint, the preliminary study of new CG based bio-mineralized material is successful.