Carbonation and self-healing in concrete: Kinetic Monte Carlo simulations of mineralization - data

<p>Carbonation in concrete can be exploited to reduce the environmental footprint of the construction industry, through applications such as self-healing and carbon capture and storage. These applications however are still empirical, due to a lack of models linking the chemistry of carbonation at the molecular scale to microstructure development and macroscopic properties. This limitation is particularly important for new, greener concretes, for which there is scarcity of long-term experimental data. This work proposes a coarse-grained Kinetic Monte Carlo (KMC) approach to simulate microstructural evolution of a model cement paste during carbonation, along with evolution of pore solution chemistry and saturation indexes of solid species involved. The simulations predict the effective rate constants for Ca(OH)2 dissolution and CaCO3 precipitation, which depend on the microstructure and are directly fed to a macroscale reactive transport model to predict experimental data on carbonate penetration. This proposed multiscale approach can help understand and manage the carbonation of both traditional and new concretes, supporting applications in residual lifetime assessment, carbon capture, and self-healing.     <br></p><p>Data description: File name: Figures_data_final.xlsx</p><p>Column names in the excel sheet are referred to in the description in <strong>[square brackets]</strong></p><p>Sheet name: Figure 2 </p><p>The table provides experimental results on carbonation degree and depth of penetration at 14 and 28 days. </p><p>[B] Carbonation degree (%) as a function of [A] distance from exposed face of the sample (mm) on the 14^th day. </p><p>[E] Carbonation degree (%) as a function of [D] distance from exposed face of the sample (mm) on the 28^th day. These values were obtained from Lawrence et. al. (2006).</p><p><em>R.M.H. Lawrence, T.J. Mays, P. Walker, D. D’Ayala, Determination of carbonation profiles in non-hydraulic lime mortars using thermogravimetric analysis, Thermochim Acta. 444 (2006) 179–189. https://doi.org/10.1016/j.tca.2006.03.002.</em></p><p>Sheet name: Figure 4</p><p>The table provides inputs to calculate the CH-CH harmonic pair potential. Using the input values in [A] and [B] Interaction energy, U (in MPa nm³) [G] is determined with respect to Interparticle distance (r, nm) [F].  </p><p>Sheet name: Figure 6</p><p>The table provides zero-rate dissolution-precipitation parametrization for C-S-H. The table shows the solution state with respect to time for saturation index, beta = 0, 0.5, 0.9, 1.1, 2, and 10. The column for each set of beta provides [F] Step, [G] Time (ns), ionic concentration in mol/L of [H] Ca²⁺, [I] H₄SiO₄, [J] H₂O, [K] OH^-, [O] Number of C-S-H particles [P] rate of dissolution (particles/time), [Q] ionic strength, activity of [R] Ca²⁺, [S] H₄SiO₄, [T] OH^-, [V] beta of C-S-H, [W] grain volume (nm³), [X] grain diameter (nm), [Y] grain surface area (nm²), [Z] rate of dissolution (nm²/s). </p><p>Sheet name: Figure 10</p><p>The table provides number of particles during small-box preliminary simulations, comparing the kinetics emerging from the use of (a) straight rates and (b) net rates. The data provides: </p><p>Number of particles of [B] C-S-H, [C] CH and [D] CaCO₃ with respect to [A] time (s) using straight rates. </p><p>Number of particles of [G] C-S-H, [H] CH and [I] CaCO₃ with respect to [F] time (s) using net rates.  </p><p>Sheet name: Figure 12</p><p>The table provides CaCO₃ precipitation with respect to time and the evolution of the concentration of  Ca ions in solution during the simulation. [B] Number of CaCO₃ with respect to [A] time (s), [E] concentration of Ca²⁺ (mmol/L) with respect to [D] time (s).</p><p>Sheet name: Figure 13</p><p>The table provides solution properties in the growth regime. Saturation index, beta [B] CH, [C] CaCO₃ with respect to [A] time (s).</p><p>Sheet name: Figure 14</p><p>The table provides comparison between (a) MASKE-simulated vs analytical concentration of Ca²⁺ and number of particles of (b) CH and (c) CaCO₃.     </p><p>Concentration of Ca²⁺ (mmol/L) [B] analytical [C] simulated with respect to [A] time (s).</p><p>Number of particles of CH [F] analytical [G] simulated with respect to [E] time (s).</p><p>Number of particles of CaCO₃ [J] analytical [K] simulated with respect to [I] time (s).</p><p>Sheet name: Figure 15</p><p>The table provides comparison of simulated carbonation profiles and the experimental data of Lawrence et al. (2006) in Figure 2.</p><p>Simulated profiles for 14 days [B] carbonation degree (%) with respect to [A] distance from exposed face of the sample (mm). </p><p>Simulated profiles for 28 days [E] carbonation degree (%) with respect to [D] distance from exposed face of the sample (mm). </p><p>Sheet name: Figure 16</p><p>The table provides simulated profiles of concentration of ,  and estimated . </p><p>Simulated profiles for 14 days [B] concentration of Ca(OH)₂, [C] concentration of CaCO₃ (mol/L) , [D] pH, with respect to [A] distance from exposed face of the sample (mm).  </p><p>Simulated profiles for 28 days [G] concentration of Ca(OH)₂, [H] concentration of CaCO₃ (mol/L) , [I] pH, with respect to [F] distance from exposed face of the sample (mm).  </p><p>Sheet name: Figure 17</p><p>The table provides predicted carbonation profiles with altered rate constants and the results of Lawrence et al. (2006)</p><p>Simulated profiles for 14 days, higher rates [B] carbonation degree (%) with respect to [A] distance from exposed face of the sample (mm). </p><p>Simulated profiles for 14 days, lower rates [E] carbonation degree (%) with respect to [D] distance from exposed face of the sample (mm). </p><p>Simulated profiles for 28 days, higher rates [H] carbonation degree (%) with respect to [G] distance from exposed face of the sample (mm). </p><p>Simulated profiles for 28 days, lower rates [K] carbonation degree (%) with respect to [J] distance from exposed face of the sample (mm). </p><p>Sheet name: Figure 18</p><p>The table provides reaction rates predicted by various models.</p><p>Columns [B], [C], [E], [F] provides the various parameters used in the comparison. [H] Model name and [I] rate (mol/L/s) .</p><p>Sheet name: Figure 20</p><p>Table provides data for stress-strain plots of intact vs fully precipitated with interfacial energy,  = 0.5 and  = 0.05.</p><p>Stress in MPa of [B] intact, [C] fully precipitated,  = 0.5, [D] fully precipitated,  = 0.05 with respect to [A] strain [nm/nm]. </p>