SIMULATION OF THE DEVELOPMENT OF PH IN THE PORE SOLUTION OF SLAG CEMENT PASTE AT EARLY AGE

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1 SIMULATION OF THE DEVELOPMENT OF PH IN THE PORE SOLUTION OF SLAG CEMENT PASTE AT EARLY AGE Peng Gao (1, 2), Guang Ye (2), Jiangxiong Wei (1), Qijun Yu (1) (1) School of Materials Science and Engineering, South China University of Technology, Guangzhou, People's Republic of China (2) Microlab, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft, The Netherlands Abstract The prediction and control of the development of ph in the pore solutions of cement-based materials, particularly at early age, is important for both engineering practise and academic interests. This study aims to simulate the development of ph in the pore solutions of slag cement pastes at early age based on the 3D numerical cement hydration model HYMOSTRUC3D [1]. HYMOSTRUC3D was used to simulate the hydration of slag cements. Taylor s method [2] was used to predict the [Na + ] and the [K + ]. The thermodynamic equilibriums of the CH and the gypsum in the slag cement pastes were used to predict the [Ca 2+ ], the [SO ] and the [OH - ]. The development of ph in the pore solutions of the slag cement pastes was simulated based on the [OH - ]. The results of simulation indicate that the [Na + ] and the [K + ] in the pore solutions of slag cement pastes predicted by this study are in good agreement with the experimental results. However the accuracy of the simulation of [Ca 2+ ] and [SO ] is relatively low. The simulated ph in the pore solutions of slag cement pastes is in good agreement with that of experiment before 10 hours and after 72 hours. 1. INTRODUCTION Blended cements, i.e., the Portland cement blended with the supplementary cementitious materials (SCMs), like silica fume, blast furnace slag, and fly ash, etc. are widely used in civil engineering constructions. The ph in the pore solutions of blended cement pastes is an important parameter which controls the reactivity of SCMs and the durability of concrete structures made of blended cement [3]. The prediction and control of the development of ph in the pore solutions of blended cement pastes becomes an important task for both engineering practise and academic interests. 273

2 Increasing work has focused on simulating the development of ph in the pore solutions of cement-based materials. Taylor proposed a method to predict the [Na + ] and the [K + ] in the pore solution of Portland cement paste [2]. van Eijk and Brouwers used the CEMHYD3D to simulate the degree of hydration of Portland cement []. They predicted the [Na + ] and the [K + ] in the pore solution of Portland cement paste based on Taylor s method. Then, they established the relationship between the [Ca 2+ ] and the [OH - ] by introducing the thermodynamic equilibrium of the CH (Portlandite) in the cement paste. At last, they predicted the [OH - ] and related ph based on the charge balance of ions (Na +, K +, Ca 2+ and OH - ) in the pore solution. The simulation accurately predicted the ph at the long term, but showed low accuracy at early age due to insufficient consideration of SO. After that, [5-7] updated the binding factors of C-S-H and C-A-S-H for Na + and K + in order to improve the accuracy of simulation. However, the accuracy of simulation at early age is still low. Recently, National Institute of Standards and Technology (NIST, United States) has updated the CEMHYD3D to version 3.0 which has the function of predicting the development of ph in the pore solutions of Portland cement pastes by considering SO [8]. However, the development of ph in the pore solutions of slag cement pastes was not considered. Table 1: Chemical compositions of Portland cement and blast furnace slag Raw materials Chemical composition (%) CaO SiO 2 Al 2 O 3 Fe 2 O 3 MgO K 2 O Na 2 O SO 3 PC BFS Table 2: Mixture proportions of simulated blended cement pastes Sample No. PC (%) BFS (%) W/B P100B P70B P50B P30B This study aims to simulate the development of ph in the pore solution of Portland cement blended with blast furnace slag at early age based on the 3D numerical cement hydration model HYMOSTRUC3D [1]. Na +, K +, Ca 2+, SO and OH - are considered to simulate the development of ph in the pore solutions of the blended cement pastes (In this study, blended cement denotes Portland cements blended with blast furnace slag). In the simulation, the hydration of the blended cements is simulated by HYMOSTRUC3D. The [Na + ] and the [K + ] 27

3 are predicted based on Taylor s method [2]. The [Ca 2+ ], the [SO ] and the [OH - ] are simulated based on thermodynamic mechanism in cement science [9]. 2. MODELING APPORACH 2.1 Hydration of Portland cement blended with blast furnace slag In this study, HYMOSTRUC3D is used to simulate the hydration of blended cements. The chemical compositions of Portland cement (PC) and blast furnace slag (BFS) are given in Table 1. The mixture proportions of simulated blended cement pastes come from the mixture design in [10]. The mixture proportions are given in Table 2. The water/binder ratio (W/B) is fixed at Prediction of concentrations of alkali ions (Na + and K + ) The concentrations of alkali ions (Na + and K + ) in the pore solutions of blended cement pastes are predicted based on Taylor s method [2]. During the reaction of PC and BFS in the blended cement pastes, the alkali ions are released from the particles of PC and BFS. Some amount of alkali ions are chemically bound by the products of PC and BFS, and other amount of alkali ions are free in the pore solutions. The amount of chemically bound alkali ions was assumed to be proportional to the concentrations of alkali ions in the pore solution of blended cement pastes [2]. Based on this kind of relationship, the concentrations of alkali ions in the pore solutions of blended cement pastes can be calculated. In Portland cement, alkali can exist in both sulphate (gypsum) and the clinker of cement. Taylor indicated that 35 % of the total Na 2 O and 70 % of the total K 2 O occurred as sulphates [2]. Therefore, the amount of alkali ions (mole) from PC is introduced as: n f α f (1 k ) f f PC PC X2O,PC X PC X2O,PC X X,PC (1) M X2O Where n X,PC denotes the mole content of Na + or K + from PC; f PC denotes the mass percentage of PC in the blended cements; α PC denotes the degree of hydration of PC in the blended cement pastes; f X2O,PC denotes the mass percentage of Na 2 O or K 2 O in PC; M X2O denotes the molecular mass of Na 2 O or K 2 O; k X denotes the mass fraction of Na 2 O or K 2 O occurred as sulphates (0.35 for Na 2 O, 0.70 for K 2 O). In this study, the alkali in BFS is assumed to homogenously distribute in the particles of BFS. The amount of alkali ions (mole) from BFS is introduced as: n f α f BFS BFS X2O,BFS X (2),BFS M X2O Where n X,BFS denotes the mole content of Na + or K + from BFS; f BFS denotes the mass percentage of BFS in the blended cements; α BFS denotes the degree of hydration of BFS in the blended cement pastes; f X2O,BFS denotes the mass percentage of Na 2 O or K 2 O in BFS. k 275

4 Only C-S-H (from OPC), C-A-S-H (from BFS) and HT (hydrotalcite-like phase, from BFS) are assumed to bind alkali in the blended cement pastes. Based on Taylor s method [2], the concentrations of alkali ions are introduced as: [X ] V X,PC X,BFS (3) solution Rd X,C-S-H,PC m C-S-H,PC n Rd n X,C-A-S-H,BFS m C-A-S-H,BFS Rd X,HT,BFS where, [X + ] denotes the [Na + ] or the [K + ] in the pore solutions of blended cement pastes, Rd X,C-S-H,PC denotes the binding factor of C-S-H for Na + or K + []. Rd X,C-A-S-H,BFS denotes the binding factor of C-A-S-H for Na + or K +. Rd X,HT,BFS denotes the binding factor of HT for Na + or K +. The binding factors of C-S-H, C-A-S-H and HT for alkali are important for the simulation. In this study, the binding factors are based on [5-7]: the binding factors of C-S-H for Na + and K + are 0.39 ml/g and 0.30 ml/g, respectively. Both the binding factors of C-A-S-H for Na + and K + are 0.30 ml/g. Both the binding factors of HT for Na + and K + are 0.30 ml/g. 2.3 Prediction of concentrations of Ca 2+ and SO The equilibriums of CH and gypsum are considered in the simulation of the [Ca 2+ ] and the [SO ]. According to the thermodynamic equilibrium [9], if CH is saturated, [Ca 2+ ] and [OH - ] can be calculated as: m HT,BFS 0 {CH } {Ca } {OH } 2 [Ca ] γ Ca 1 2 [OH ] (γ OH ) 2 k 0,CH () where {i}=γ i [i] denotes the activity of ions; γ i denotes the activity coefficient of ions; k 0,CH denotes the solubility constant of CH. It equals to based on [11]; The activity coefficients of ions are calculated based on the Davies equation [12]. If gypsum is saturated, [Ca 2+ ] and [SO ] can be calculated as: {Ca } {SO {CSH } {CaSO 0 2 } 1 k 0 2 0,CSH 2 } {H2O} [Ca ] γ [SO ] γ 11 Ca SO Where k 0,C SH2 denotes the solubility constant of gypsum. It equals to based on [11]. Based on the charge balance of positive ions and negative ions in the pore solutions of blended cement pastes: [Na ] [K ] 2[Ca ] 2[SO ] [OH ] (6) (5) I m The I m (ions strength) is calculated as: 0.5 ([Na ] [K ] [Ca ] [SO ] [OH ]) (7) Based on thermodynamic mechanism, [Ca 2+ ], [SO ] and [OH - ] can be calculated based on four equations (Eq. to Eq. 7) at any given hydration stage. 276

5 2. Prediction of development of ph Based on Eq. 6, [OH - ] can be calculated as: - [OH ] [Na ] [K ] 2[Ca ]- 2[SO ] (8) The ph in the pore solutions of blended cement pastes is calculated as: - ph 1 log[oh ] (9) 3. RESULTS AND DISCUSSION 3.1 Concentrations of ions and ph The concentration of ions and the development of ph in the pore solutions of the blended cement pastes are simulated and compared with the experimental data [10]. The results are presented Figure 1 to Figure. Both the [Na + ] and the [K + ] in the pore solutions of blended cement pastes decrease with the increase of amount of BFS in the blended cements, and increase with the hydration time (Fig. 1). The simulation results are in good agreement with the experimental results for all mixtures. The [Ca 2+ ] in the pore solutions of blended cement pastes increase with the increase of amount of BFS in the blended cements, and decrease with the hydration time (Figure 2). The [Ca 2+ ] of simulation are lower than that of experiment; however both the simulation results and experimental results show the same trends. The [SO ] in the pore solution of blend cement pastes decrease with the increase of amount of BFS in the blended cements, and decrease with the hydration (Fig. 3). The [SO ] of simulation are lightly higher than that of experiment. The [SO ] of simulation exhibit a sharp decline around 10 hours and level off at zero, which is caused by the exhaust of gypsum. Moreover, the disagreement may come from insufficient consideration of the equilibrium of other products such as AFt and AFm. (a) [Na + ] from simulation (b) [Na + ] from experiment 277

6 (c) [K + ] from simulation (d) [K + ] from experiment Figure 1: [Na + ] and [K + ] in pore solutions of blended cement pastes (a) [Ca 2+ ] from simulation (b) [Ca 2+ ] from experiment Figure 2: [Ca 2+ ] in pore solutions of blended cement pastes (a) [SO ] from simulation (b) [SO ] from experiment Figure 3: [SO ] in pore solutions of blended cement pastes The ph in the pore solution of blended cement pastes decrease with the increase of amount of BFS in blended cements, and increase with the hydration time (Fig. ). The ph of simulation shows a sharp increase around 10 hours, which is different from that of experiment. Except 278

7 that, the ph of simulation is in good agreement with that of experiment. (a) ph from simulation (b) ph from experiment Figure : ph in pore solutions of blended cement pastes 3.2 Discussion The simulated ph values in the pore solution of Portland cement by van Eijk s method and by the method presented in this study are shown in Fig. 5. Both simulations show high accuracy after 72 hours. This study improves the accuracy of simulation before 10 hours. However, the simulation results do not math with experiment from 10 to 72 hours. Figure 5: Improvement of the simulation of ph in the pore solution of Portland cement paste The discrepancy between simulation and experiment from 10 to 72 hours is caused by the sharp decline of simulated [SO ]. Because the SO is assumed to only come from the gypsum, the [SO ] is sharply decreased to zero when gypsum is exhausted. However, The [SO ], in reality, is higher than zero due to the thermodynamic equilibrium of other products in cement pastes such as AFt and AFm. Based on Eq. 8, the [OH - ] of simulation is higher than that of experiment because the simulation of [SO ] is lower than that of experiment. Based on Eq. 9, the ph of simulation is therefore higher than that of experiment. If the thermodynamic equilibrium of AFt and AFm is taken into account, the accuracy of simulating will be increased []. However, in the meantime, the variables will be expanded 279

8 and the functions of equilibrium of ions will be more complicated.. CONCLUSIONS (1) The simulated concentrations of alkali ions (Na + and K + ) in the pore solution of slag cement pastes are in good agreement with the experimental results. However the accuracy of the simulation of [Ca 2+ ] and [SO ] is relatively low. (2) The simulated ph in the pore solutions of slag cement pastes are in good agreement with that of experiment before 10 hours and after 72 hours. (3) Compared with van Eijk s method, this study improves the accuracy on the prediction of ph in the pore solution of Portland cement paste. The prediction of the development of ph in the pore solution is extended to the blast furnace slag cement. ACKNOWLEDGEMENTS This work was funded by the China Scholarship Council (CSC), and the Research Centre of TU Delft in Urban System and Environment (No. C36103). REFERENCES [1] Van Breugel, K., 'Simulation of hydration and formation of structure in hardening cement-based materials', PhD Thesis, Delft University of Technology, The Netherlands, [2] Taylor, H.F.W., 'A method for predicting alkali ion concentrations in cement pore solutions', Adv. Cem. Res. 1 (1) (1987) [3] Lothenbach, B., Scrivener, K., and Hooton, R.D., 'Supplementary cementitious materials', Cem. Concr. Res. 1 (12) (2011) [] van Eijk,R.J., Brouwers, H.JH., 'Prediction of hydroxyl concentrations in cement pore water using a numerical cement hydration model', Cem. Concr. Res. 30 (11) (2000) [5] Brouwers, H.J.H., and VanEijk, R.J., 'Alkali concentrations of pore solution in hydrating OPC', Cem. Concr. Res. 33 (2) (2003) [6] Chen, W., and Brouwers, H.J.H., 'Alkali binding in hydrated Portland cement paste', Cem. Concr. Res. 0 (5) (2010) [7] Chen, W., and Brouwers, H.J.H., 'A method for predicting the alkali concentrations in pore solution of hydrated slag cement paste', J. Mater. Sci. 6 (10) (2011) [8] Bentz, D.P., 'CEMHYD3D: a three-dimensional cement hydration and microstructure development modeling package. Version 3.0', NISTIR US Department of Commerce. (2005). [9] Damidot, D., Lothenbach, B., Herfort, D., and Glasser, F.P., 'Thermodynamics and cement science', Cem. Concr. Res. 1 (7), (2011) [10] Ye, G., 'Numerical simulation of connectivity of individual phases in hardening cement-based systems made of blended cement with and without admixtures', VENI report, Delft, Delft University of Technology, the Netherlands, (2007). [11] Blanc, P., Bourbon, X., Lassin, A., and Gaucher, E.C., 'Chemical model for cement-based materials: Thermodynamic data assessment for phases other than C S H', Cem. Concr. Res. 0 (9), (2010) [12] Hummel, W., Berner, U., Curti, E., Pearson, F.J., and Thoenen, T., 'Nagra/PSI chemical thermodynamic data base 01/01', Radiochim. Acta. 90 (9/11) (2002)