A method for predicting the reaction degree of alkali-activated slag-based paste based on parameterized reaction kinetics equation

Abstract

This invention belongs to the field of civil engineering materials technology, and specifically discloses a method for predicting the reaction degree of alkali-activated slag-based slurry based on a parameterized reaction kinetic equation. This method, based on existing literature research on alkali-activated slag slurry and alkali-activated fly ash slurry, establishes a parameterized reaction kinetic model by setting quantitative relationships between reaction kinetic parameters, key material parameters, and temperature. This model enables direct and continuous prediction of the reaction degree of alkali-activated slag-based slurry using mix proportion information, and can predict the reaction degree from the start of the reaction to any specified age. Furthermore, this prediction method covers both single alkali-activated slag slurry and composite slurries with alkali-activated fly ash, ensuring universality. Compared to existing methods that can only calculate the reaction degree for slurries with measured cumulative heat release curves, this method eliminates the need for extensive practical experimental research.

Description

Technical Field

[0001] This invention belongs to the field of civil engineering materials technology, specifically, it relates to a method for predicting the degree of reaction of alkali-activated slag-based slurry based on parameterized reaction kinetic equations. Background Technology

[0002] Alkali-activated slag-fly ash systems possess advantages such as excellent mechanical properties and low carbon emissions. Their microstructure and macroscopic properties are closely related to the reaction process. However, the reaction process is influenced by multiple factors, including activators and precursors, resulting in complex kinetic behavior that is difficult to describe and predict accurately. Therefore, achieving accurate prediction of the reaction extent of this system is crucial for revealing the evolution of its microstructure and regulating its macroscopic properties.

[0003] Currently, the determination of the reaction extent of alkali-activated materials mainly relies on experimental testing (such as backscattered image analysis and acid dissolution methods) and kinetic calculations. However, these methods all have significant drawbacks. The former struggles to obtain continuous and predictable data on the entire reaction extent; while the latter can calculate the reaction extent at any age, its kinetic parameters (such as...) are limited. k i , T i The lack of a clear quantitative relationship between the material parameters such as activators and precursors makes it impossible to directly predict the full-stage reaction degree of samples with different mix proportions.

[0004] While some studies have evaluated the reactivity of alkali-activated cementitious materials, such as Chinese patent CN108101390A, this evaluation method requires individual testing of each sample at various ages to obtain the reactivity level. It cannot directly calculate the continuous reactivity level of specimens with known mix proportions at any age. In other words, this evaluation method remains entirely dependent on actual experimental test results and cannot provide predictive assessments detached from experimental conditions.

[0005] In summary, further research is needed on methods for predicting the degree of reaction of alkali-activated cementitious materials. Summary of the Invention

[0006] To address the problems existing in the evaluation methods for the reaction degree of various alkali-activated cementitious materials in the prior art, this invention proposes a new method for predicting the reaction degree of alkali-activated slag-based slurry based on parameterized reaction kinetic equations. This method can directly predict the reaction degree of the corresponding alkali-activated slag-based slurry at all stages based on known mix proportion information. Moreover, it can predict the reaction degree not only for simple alkali-activated slag slurry, but also for composite alkali-activated slag-fly ash slurry.

[0007] The present invention specifically adopts the following technical solution: In a first aspect, the present invention provides a method for predicting the degree of reaction in alkali-activated slag slurry based on parameterized reaction kinetic equations, comprising the following steps: S1. Collect material parameters and isothermal calorimetric curve data of alkali-activated slag slurry, and calculate kinetic parameters based on the isothermal calorimetric curves. k i and T i A dataset of dynamic parameters and material parameters was established.

[0008] Specifically, this collection operation was carried out based on the research results of existing literature [1]~[6] on alkali-activated slag slurry.

[0009] The existing references [1] to [6] are as follows: [1] Mahmood A H. Babaee M. Continuous monitoring of the early-ageproperties of activated GGBFS with alkaline solutions of different concentrations[J]. Journal of Materials in Civil Engineering, 2021, 33(12):04021374. [2] Gebregziabiher BS, Thomas RJ, Peethamparan S. Temperature andactivator effect on early-age reaction kinetics of alkali-activated slagbinders[J]. Construction and Building Materials, 2016, 113: 783-793. [3] Zuo Y. Experimental Study and Numerical Simulation of theReaction Process and Microstructure Formation of Alkali-Activated Materials[D]. Delft: Delft University of Technology. 2019. [4] Almakhadmeh WA, Soliman A. Effect of activator nature onproperty development of alkali-activated slag binders[J]. Journal ofSustainable Cement-Based Materials, 2020, 10(4): 240-256. [5] Ouyang X, Ma Y, Liu Z, Liang J, Ye G. Effect of the sodiumsilicate modulus and slag content on fresh and hardened properties of alkali-activated fly ash / slag[J]. Minerals, 2019, 10(1): 15. [6] Ravikumar D, Neithalath N. Reaction kinetics in sodium silicatepowder and liquid activated slag binders evaluated using isothermalcalorimetry[J]. Thermochimica acta, 2012, 546: 32-43. Among them, the material parameters of alkali-activated slag slurry include the Na2O content in the activator. N and SiO2 content S and the composition of slag X .

[0010] Furthermore, N The calculation method is shown in Equation 1 below: Formula 1 S The calculation method is shown in Equation 2 below: Formula 2 Specifically, the activator in Formula 1 and Formula 2 refers to the activator in the alkali-activated slag slurry, and the total precursor refers to the slag in the alkali-activated slag slurry.

[0011] X The calculation method is shown in Equation 3 below: Formula 3 In Equation 3, This represents the amount of CaO in the slag. This represents the amount of MgO in the slag. This represents the amount of Al2O3 in the slag.

[0012] Furthermore, N The value range is 2.5% to 8%. S The value range is 1.94% to 11.63%, and the corresponding modulus of the activator (referring to the molar ratio of silicon dioxide to sodium oxide in the activator) ranges from 0.5 to 2.0. X The value range is 1.1380~1.9432.

[0013] The activator is a composite activator obtained by mixing sodium hydroxide and sodium silicate solutions. The sodium hydroxide is solid, the modulus of the sodium silicate solution ranges from 2.0 to 3.4, and the water content of the sodium silicate solution ranges from 55 wt% to 65 wt%. By adding sodium hydroxide to the sodium silicate solution to adjust the modulus, the modulus range of the adjusted composite activator is controlled within the range of 0.5 to 2.0.

[0014] Among them, isothermal calorimetric curve data includes heat flux curve data (i.e. t ~d Q / d t ) and cumulative heat release curve data (i.e. t ~ Q );in, t Represents time, in hours (h). Q This represents the amount of heat released, expressed in J / g.

[0015] Furthermore, the steps for establishing a dataset of kinetic parameters for alkali-activated slag slurry include: S11. Based on the cumulative heat release curve of the alkali-activated slag slurry, the degree of reaction at different times within the time range of the isothermal calorimetric curve is calculated using the following formula 4. α(t) : Formula 4 In Equation 4, α(t) for t The degree of reaction at any given moment; Q(t) for t The cumulative heat released at any given time, expressed in J / g; Q max The maximum heat release of the slag is taken as 460 J / g.

[0016] S12. Based on the bimodal morphology of the heat flow curve of alkali-activated slag slurry, the hydration reaction process of alkali-activated slag slurry is divided into six reaction stages, including: (1) ttr, 0 ~ t tr, 1 Nucleation stage I; (2) t tr, 1 ~ t tr, 2 Phase I: Interface Stage; (3) t tr, 2 ~ t tr, 3 Induction period; (4) t tr, 3 ~ t tr, 4 Nucleation stage II; (5) t tr, 4 ~ t tr, 5 Phase II: Interface Stage; And (6) t tr, 5 ~ t tr, 6 : Diffusion phase; in, t tr, 0 =0 indicates that the reaction has started; t tr, 1 The peak time of the initial peak represents the boundary between nucleation growth stage I and phase interface stage I. t tr, 2 and t tr, 3 Let |d| represent the start and end times of the induction period, respectively. 2 Q d t 2 |≤0.2 is the range for the induction period; t tr, 4 The peak time of the acceleration peak represents the boundary between nucleation growth stage II and phase interface stage II. t tr, 5 and t tr, 6 These represent the start and end times of the diffusion phase, respectively, with the start time of the diffusion phase denoted by d. 2 Q d t 2 Using -0.1 as the criterion, the theoretical end time of the diffusion period is infinity.

[0017] The duration of the stage is calculated using the following formula (5). T i : Formula 5 In Equation 5, i Integers from 1 to 6, corresponding to the obtained T 1. T 2. T 3. T 4. T 5. T 6 represents the duration of each of the following stages: nucleation growth phase I, phase interface phase I, induction phase, nucleation growth phase II, phase interface phase II, and diffusion phase.

[0018] S13. Using the reaction kinetic integral equations represented sequentially by Equations 6 to 11 for the nucleation growth phase I, phase interface stage I, induction phase, nucleation growth phase II, phase interface stage II, and diffusion phase, calculate the reaction rate parameters for each of the following phases: nucleation growth phase I, phase interface stage I, induction phase, nucleation growth phase II, phase interface stage II, and diffusion phase. k 1. k 2. k 3. k 4. k 5 and k 6: Formula 6 Formula 7 Formula 8 Formula 9 Formula 10 Formula 11 In equations 6 to 11, α The degree of reaction is represented by a value of [value missing]. t The degree of reaction corresponding to the time, and the t The difference in the degree of reaction at the beginning of the current stage (i.e., one of the six reaction stages mentioned above); where, t The degree of reaction at any given moment α(t) The degree of reaction at the beginning of each stage is calculated based on Equation 4 above.

[0019] S14. Kinetic parameters for constructing alkali-activated slag slurry k i , T i With material parameters N , S , X The dataset.

[0020] S2. Through regression analysis, establish the quantitative relationship between the kinetic parameters and material parameters of alkali-activated slag slurry, and construct a parameterized reaction kinetic model of alkali-activated slag slurry.

[0021] Specifically, the steps include: performing regression fitting based on the dataset from step S14 to obtain dynamic parameters. k i , T i With material parameters N , S , X The correlation relationship includes three cases: having a correlation relationship, being considered a constant, and having an insignificant correlation relationship.

[0022] Furthermore, based on the correlation, a multivariate nonlinear regression is performed using Equation 12 to establish the dynamic parameters. k i , T i With material parameters N , S , X Relationship: Formula 12 In Equation 12, y Represents reaction rate parameter k i and stage duration T i Any one of them; x 1. x 2. x 3 represents the parameters that affect the material, where x 1 is the main parameter affecting the material. x 2 and x 3 are secondary influencing material parameters; priority should be given to... N As the main influencing material parameters x 1; If the dynamic parameters are the same as N When the correlation is not significant, then... S As x 1; If the dynamic parameters are the same as N , S When the correlations are not significant, then... X As x 1; f(x 1 ) , f(x 2 ) and f(x 3 ) These are the correlation expressions for the corresponding individual material parameters; l 1. l 2 andl 3 are respectively f(x 1 ) , f(x 2 ) and f(x 3 ) The corresponding correction coefficients are obtained according to this rule. k i and stage duration T i The results of the multiple nonlinear regression.

[0023] Therefore, the relationship between the kinetic parameters and material parameters of alkali-activated slag slurry is shown in Equations 13-24, which is the parameterized reaction kinetic model of alkali-activated slag slurry: k 1 = 9.35258 Equation 13 k 2 = 0.25081 Equation 14 Formula 15 Formula 16 Formula 17 Formula 18 T 1 = 0.16677 Equation 19 Formula 20 Formula 21 Formula 22 Formula 23 Formula 24 S3. Based on the kinetic parameters of the alkali-activated slag slurry provided in step S1 and the parameterized reaction kinetic model of the alkali-activated slag slurry provided in step S2, predict the degree of reaction of the alkali-activated slag slurry with a known mix ratio at different ages.

[0024] Specifically, it includes the following steps: S31. For alkali-activated slag slurry with a known mix ratio, calculate the material parameters according to Equations 1 to 3. N , S , X ; S32. Substitute the material parameters obtained in step S31 into equations 13 to 24 to obtain the prediction. k i and prediction T i ; S33, The prediction obtained in step S32k i and prediction T i Substituting into equations 5 through 11, we can determine... t Calculate the degree of reaction at each reaction stage at any given time. α i ; S34. Calculate the alkali-activated slag slurry using the following formula 25. t Total Response Level at Time α SL(t) That is, to obtain alkali-activated slag slurry with a known mix ratio at different ages (i.e., different ages). t The degree of response at any given moment: Formula 25 In Equation 25, α i Indicates the first i The degree of response at each stage i for t The reaction stage at any given moment.

[0025] Among them, the alkali-activated slag slurry is cured at room temperature.

[0026] A second aspect of the present invention provides a method for predicting the degree of reaction in alkali-activated slag-fly ash slurry based on parameterized reaction kinetic equations, comprising the following steps: Q11. Modify the reaction kinetic model parameters of alkali-activated slag slurry in the above-mentioned prediction method for the degree of reaction of alkali-activated slag slurry.

[0027] Specifically, the method for correcting the reaction kinetics model parameters of alkali-activated slag slurry includes: deleting the induction period from the heat flow curve of the alkali-activated slag slurry, that is, letting... t tr, 2 = t tr, 3 , T 3=0、 α Set 3 to 0 to correct the model parameters.

[0028] Q12. Based on the corrected model parameters, predict the degree of reaction of alkali-activated slag in alkali-activated slag-fly ash slurry with a known mix ratio at different ages.

[0029] Specifically, it includes the following steps: Q121. For an alkali-activated slag-fly ash slurry with a known mix ratio, calculate the material parameters according to Equations 26, 27, and 3. N’ , S’ , X ; N’The calculation method is shown in Equation 26 below: Formula 26 S’ The calculation method is shown in Equation 27 below: Formula 27 The activator in Formulas 26 and 27 refers to the activator in the alkali-activated slag-fly ash slurry, and the total precursor refers to the total amount of slag and fly ash in the alkali-activated slag-fly ash slurry.

[0030] Specifically, N’ The value range is 2.5% to 8%. S’ The value range is 1.94% to 11.63%, and the corresponding modulus of the activator ranges from 0.5 to 2.0.

[0031] Specifically, the activator is a composite activator obtained by mixing sodium hydroxide and sodium silicate solutions; wherein, sodium hydroxide is solid, the modulus of the sodium silicate solution ranges from 2.0 to 3.4, and the water content of the sodium silicate solution ranges from 55 wt% to 65 wt%. By adding sodium hydroxide to the sodium silicate solution to adjust the modulus, the modulus range of the adjusted composite activator is controlled within the range of 0.5 to 2.0.

[0032] Q122. Substitute the material parameters obtained in step Q121 into the corrected model parameters obtained in step Q11 to obtain the prediction. k i and prediction T i ; Q123, The prediction obtained in step Q122 k i and prediction T i Substituting into equations 5 through 11, we can determine... t Calculate the degree of reaction at each reaction stage at any given time. α i ; Q124. Calculate the alkali-activated slag slurry in alkali-activated slag-fly ash slurry using Equation 25. t Total Response Level at Time α SL(t) That is, to obtain the alkali-activated slag slurry at different ages (i.e., different proportions) in an alkali-activated slag-fly ash slurry with a known mix ratio. t The degree of response at any given moment.

[0033] Q21. Based on existing literature on alkali-activated fly ash slurry, collect isothermal calorimetric curve data of alkali-activated fly ash slurry, and calculate kinetic parameters based on the isothermal calorimetric curves. k’ iand T’ i A dataset of kinetic parameters and temperature for alkali-activated fly ash slurry was established.

[0034] This collection operation was carried out based on the research results of the existing literature [3] on alkali-activated fly ash slurry.

[0035] Among them, isothermal calorimetric curve data includes heat flux curve data (i.e. t ~d Q / d t ) and cumulative heat release curve data (i.e. t ~ Q );in, t Represents time, in hours (h). Q This represents the amount of heat released, expressed in J / g.

[0036] The specific steps for establishing a dataset of kinetic parameters and temperature for alkali-activated fly ash slurry include: Q211. Based on the cumulative heat release curve of alkali-activated fly ash slurry, the degree of reaction at different times within the time range of the isothermal calorimetric curve is calculated using the following formula 28. α(t) ': Formula 28 In Equation 28, α’(t) for t The degree of reaction at any given moment; Q'(t) for t The cumulative heat released at any given time, expressed in J / g; Q’ max The maximum heat release of fly ash is taken as 250 J / g.

[0037] Q212. Based on the morphological characteristics of the heat flow curve of alkali-activated fly ash slurry, the hydration reaction process of alkali-activated fly ash slurry is divided into three stages, including: (1) t’ tr, 0 ~ t ' tr, 1 Nucleation stage; (2) t ' tr, 1 ~ t’ tr, 2 Phase interface stage; And (3) t’ tr, 2 ~ t’ tr, 3 : Diffusion phase; in, t’ tr, 0 =0 indicates that the reaction has started; t’ tr, 1The peak time point represents the boundary between the nucleation growth period and the phase interface stage. t’ tr, 2 and t’ tr, 3 These represent the start and end times of the diffusion phase, respectively, with the start time of the diffusion phase denoted by d. 2 Q d t 2 Using -0.1 as the criterion, the theoretical end time of the diffusion period is infinity.

[0038] The duration of the stage is calculated using the following formula 29. T’ i : Formula 29 In Equation 29, i The integers from 1 to 3 correspond to the obtained T’ 1. T’ 2. T’ 3 represents the duration of the nucleation growth period, the phase interface stage, and the diffusion period, in that order.

[0039] Q213. Using the reaction kinetic integral equations representing the nucleation growth period, phase interface stage, and diffusion period respectively, as shown in Equations 30 to 32, calculate the reaction rate parameters for the nucleation growth period, phase interface stage, and diffusion period respectively. k’ 1. k’ 2 and k’ 3: Formula 30 Formula 31 Formula 32 In equations 30 to 32 α’ The degree of reaction is represented by a value of [value missing]. t The degree of reaction corresponding to the time is t The difference in the degree of reaction at the beginning of the stage at which the time is located; among which, t The degree of reaction at any given moment α’(t) Both the degree of reaction at the beginning of the stage and the degree of reaction at the beginning of the stage are calculated according to Equation 29 above.

[0040] Q214. Calculate the above kinetic parameters at 50℃ and 60℃ respectively. k’ i , T’ i And construct dynamic parameters k’ i , T’ i Datasets with temperature (including 50°C and 60°C).

[0041] Q22. Based on the kinetic parameters of alkali-activated fly ash at different temperatures, predict the degree of reaction of alkali-activated fly ash in alkali-activated slag-fly ash slurry with a known mix ratio at different ages.

[0042] The specific prediction steps are as follows: Q221. Based on the slag content in the alkali-activated slag-fly ash slurry, select the kinetic parameters at the corresponding temperature from the data set in step Q214. k’ i , T’ i Substitute into equations 29 to 32, and determine... t Calculate the degree of reaction at each reaction stage at any given time. α’ i .

[0043] Specifically, when the mass of slag in the alkali-activated slag-fly ash slurry is ≤50% of the total precursor mass (the sum of the masses of slag and fly ash), the kinetic parameters corresponding to 50℃ in the data set of step Q214 are used. k’ i and T’ i When the slag mass in the alkali-activated slag-fly ash slurry is greater than 50% of the total precursor mass, the kinetic parameters corresponding to 60℃ in the data set of step Q214 are used. k’ i and T’ i .

[0044] Q222. For alkali-activated fly ash slurry, the total degree of reaction at 50℃ or 60℃ is equal to the sum of the degree of reaction at each stage.

[0045] The following formula (33) is used to calculate the alkali-activated fly ash slurry. t Total Response Level at Time α FA(t) : Formula 33 In Equation 33, α’ i Indicates the first i The degree of response at each stage i For Phase 1 to Phase 3 t The reaction stage at any given moment.

[0046] Q3. Calculate the degree of reaction of the alkali-activated slag-fly ash composite system according to the following formula 34: Formula 34 In Equation 34, PSL This is the ratio of slag mass to total precursor mass. P FA It is the ratio of the mass of fly ash to the total mass of precursors, where the total mass of precursors is equal to the sum of the masses of slag and fly ash. α SL ( t ) is the age period t The degree of alkali activation of the reaction in slag slurry, α FA ( t ) is the age period t The degree of reaction of fly ash slurry activated by alkali.

[0047] The fly ash mentioned above is Class F fly ash (also known as low-calcium fly ash); that is, the total mass fraction of SiO2, Al2O3 and Fe2O3 is ≥70%.

[0048] Among them, the alkali-activated slag-fly ash slurry is cured at room temperature.

[0049] The beneficial effects of this invention are: The method for predicting the reaction degree of alkali-activated slag-based slurry provided by this invention is based on existing literature research on alkali-activated slag slurry and alkali-activated fly ash slurry. By establishing quantitative relationships between reaction kinetic parameters, key material parameters, and temperature, a parameterized reaction kinetic model is constructed. This model enables direct and continuous prediction of the reaction degree of the alkali-activated slag-based system using mix proportion information, and can predict the reaction degree from the start of the reaction to any specified age. Furthermore, the system covered by this prediction method fully encompasses both single alkali-activated slag slurry and its composite slurry with alkali-activated fly ash, ensuring universality. Attached Figure Description

[0050] Figure 1 This is a flowchart of the steps in the method for predicting the degree of reaction of alkali-activated slag slurry according to the present invention; Figure 2 This is a schematic diagram of the heat flow curve stage division of alkali-activated slag slurry in the method for predicting the degree of reaction of alkali-activated slag slurry according to the present invention. Figure 3 This is an example diagram illustrating the correlation between kinetic parameters and individual material parameters in the method for predicting the degree of reaction in alkali-activated slag slurry according to the present invention. Figure 4 In the method for predicting the degree of reaction in alkali-activated slag slurry according to the present invention, the relationship between kinetic parameters and individual material parameters is considered as a constant. N Example diagram (≥6) Among them, [1], [2], [3], and [4] correspond to the existing literature [1] to [4] in Table 3, respectively; Figure 5 This is an example diagram showing that the correlation between kinetic parameters and individual material parameters is not significant in the method for predicting the degree of reaction of alkali-activated slag slurry according to the present invention. Among them, [1], [4], [5], and [6] correspond to the existing literature [1] and [4] to [6] in Table 4, respectively; Figure 6 This is a flowchart of the steps in the method for predicting the degree of reaction of alkali-activated slag-fly ash slurry according to the present invention; Figure 7 This is a schematic diagram of the heat flow curve of the alkali-activated slag-fly ash composite system in the method for predicting the degree of reaction of alkali-activated slag-fly ash slurry according to the present invention. Figure 8 This is a schematic diagram of the heat flow curve stage division of alkali-activated fly ash slurry in the method for predicting the degree of reaction of alkali-activated slag-fly ash slurry according to the present invention. Figure 9 This is a comparison between the predicted results of the full-stage reaction degree of alkali-activated slag slurry in Example 1 of the present invention and the calculated results of the reaction degree of alkali-activated slag slurry in the prior art; Figure 10 This is a prediction of the full-stage reaction degree of the alkali-activated slag slurry after modification according to Example 2 of the present invention; Figure 11 This is a prediction of the full-stage reaction degree of alkali-activated fly ash slurry at 50°C according to Example 2 of the present invention; Figure 12 This is a prediction of the full-stage reaction degree of the alkali-activated slag-fly ash composite system (50% slag + 50% fly ash) in Example 2 of the present invention, and a comparison of the reaction degree calculation results in Comparative Example 2. Figure 13 This is a prediction of the full-stage reaction degree of alkali-activated fly ash slurry at 60°C according to Example 3 of the present invention; Figure 14 This is a prediction of the full-stage reaction degree of the alkali-activated slag-fly ash composite system (70% slag + 30% fly ash) in Example 3 of the present invention. Detailed Implementation

[0051] Based on existing literature on alkali-activated slag slurry and alkali-activated fly ash slurry, this invention proposes two methods for predicting the reaction degree of alkali-activated slag slurry and alkali-activated slag-fly ash slurry, respectively, based on parameterized reaction kinetic equations.

[0052] Specifically, the existing literature [1]~[6] upon which the prediction method for the reaction degree of alkali-activated slag slurry is based is as follows: [1] Mahmood A H. Babaee M. Continuous monitoring of the early-ageproperties of activated GGBFS with alkaline solutions of differentconcentrations[J]. Journal of Materials in Civil Engineering, 2021, 33(12):04021374. [2] Gebregziabiher B S, Thomas R J, Peethamparan S. Temperature andactivator effect on early-age reaction kinetics of alkali-activated slagbinders[J]. Construction and Building Materials, 2016, 113: 783-793. [3] Zuo Y. Experimental Study and Numerical Simulation of theReaction Process and Microstructure Formation of Alkali-Activated Materials[D]. Delft: Delft University of Technology. 2019. [4] Almakhadmeh W A, Soliman A. Effect of activator nature onproperty development of alkali-activated slag binders[J]. Journal ofSustainable Cement-Based Materials, 2020, 10(4): 240-256. [5] Ouyang X, Ma Y, Liu Z, Liang J, Ye G. Effect of the sodiumsilicate modulus and slag content on fresh and hardened properties of alkali-activated fly ash / slag[J]. Minerals, 2019, 10(1): 15. [6] Ravikumar D, Neithalath N. Reaction kinetics in sodium silicatepowder and liquid activated slag binders evaluated using isothermalcalorimetry[J]. Thermochimica acta, 2012, 546: 32-43. The existing literature on which the method for predicting the reaction degree of alkali-activated fly ash slurry is based is the aforementioned existing literature [3].

[0053] Reference Figure 1 As shown, the method for predicting the degree of reaction in alkali-activated slag slurry specifically includes the following steps: S1. Based on existing literature on alkali-activated slag slurry, material parameters and isothermal calorimetric curve data of alkali-activated slag slurry were collected, and kinetic parameters were calculated based on the isothermal calorimetric curves. k i and T i A dataset of dynamic parameters and material parameters was established.

[0054] Among the material parameters are the Na2O content in the activator. N and SiO2 content S and the composition of slag X .

[0055] N The calculation method is shown in Equation 1 below: Formula 1 S The calculation method is shown in Equation 2 below: Formula 2 The activator in Formula 1 and Formula 2 refers to the activator in the alkali-activated slag slurry, and the total precursor refers to the slag in the alkali-activated slag slurry.

[0056] XThe calculation method is shown in Equation 3 below: Formula 3 In Equation 3, This represents the amount of CaO in the slag. This represents the amount of MgO in the slag. This represents the amount of Al2O3 in the slag.

[0057] Specifically, N The value range is 2.5% to 8%. S The value range is 1.94% to 11.63%, corresponding to a modulus range of 0.5 to 2.0 for the activator; X The value range is 1.1380~1.9432.

[0058] Specifically, the activator is a composite activator formed by combining sodium hydroxide and sodium silicate solutions; wherein, sodium hydroxide is a solid, the modulus of the sodium silicate solution ranges from 2.0 to 3.4, and the water content of the sodium silicate solution ranges from 55% to 65%. By adding sodium hydroxide to the sodium silicate solution to adjust the modulus, the modulus range of the above-mentioned composite activator after adjustment is controlled within the range of 0.5 to 2.0.

[0059] Among them, isothermal calorimetric curve data includes heat flux curve data (i.e. t ~d Q / d t ) and cumulative heat release curve data (i.e. t ~ Q );in, t Represents time, in hours (h). Q This represents the amount of heat released, expressed in J / g.

[0060] The specific steps for establishing a dataset of dynamic parameters include: S11. Based on the cumulative heat release curve of the alkali-activated slag slurry, the degree of reaction at different times within the time range of the isothermal calorimetric curve is calculated using the following formula 4. α(t) : Formula 4 In Equation 4, α(t) for t The degree of reaction at any given moment; Q(t) for t The cumulative heat released at any given time, expressed in J / g; Q max The maximum heat release of the slag is taken as 460 J / g.

[0061] S12, the heat flow curve of alkali-activated slag slurry exhibits a bimodal characteristic (e.g. Figure 2As shown, according to the direction indicated by the horizontal axis of the heat flow curve (where the first peak is the initial peak and the second peak is the acceleration peak), based on the morphological characteristics of the heat flow curve of alkali-activated slag slurry, its hydration reaction process is divided into six stages, as follows: ① t tr, 0 ~ t tr, 1 Nucleation growth stages I and ② t tr, 1 ~ t tr, 2 Phase interface stages I and ③ t tr, 2 ~ t tr, 3 : Induction period, ④ t tr, 3 ~ t tr, 4 Nucleation growth stage II, ⑤ t tr, 4 ~ t tr, 5 Phase II and ⑥ of the phase interface t tr, 5 ~ t tr, 6 : Diffusion period.

[0062] The key time points for each feature are as follows: t tr, 0 =0 indicates that the reaction has started; t tr, 1 The peak time of the initial peak represents the boundary between nucleation growth stage I and phase interface stage I. t tr, 2 and t tr, 3 These represent the start and end times of the induction period, respectively, and |d| is selected. 2 Q d t 2 |≤0.2 is the range for the induction period; t tr, 4 The peak time of the acceleration peak represents the boundary between nucleation growth stage II and phase interface stage II. t tr, 5 and t tr, 6 These represent the start and end times of the diffusion period, respectively, with the start time denoted by d. 2 Q d t 2=-0.1 is used as the criterion, and the end time of the diffusion period is theoretically infinite.

[0063] The duration of the stage is calculated using the following formula (5). T i : Formula 5 In Equation 5, i Integers from 1 to 6 T 1. T 2. T 3. T 4. T 5. T 6 represents the duration of each of the following stages: ① nucleation growth stage I, ② phase interface stage I, ③ induction stage, ④ nucleation growth stage II, ⑤ phase interface stage II, and ⑥ diffusion stage, in hours.

[0064] S13. Using the reaction kinetic integral equations represented sequentially by Equations 6 to 11 for the nucleation growth phase I, phase interface stage I, induction phase, nucleation growth phase II, phase interface stage II, and diffusion phase, calculate the reaction rate parameters for each of the following phases: nucleation growth phase I, phase interface stage I, induction phase, nucleation growth phase II, phase interface stage II, and diffusion phase. k 1. k 2. k 3. k 4. k 5. k 6.

[0065] Formula 6 Formula 7 Formula 8 Formula 9 Formula 10 Formula 11 In equations 6 to 11, α The degree of reaction is represented by a value of [value missing]. t The degree of reaction corresponding to the time, and the t The difference in the degree of reaction at the beginning of the current stage (i.e., one of the six reaction stages mentioned above); where, t The degree of reaction at any given moment α(t) The degree of reaction at the beginning of each stage is calculated based on Equation 4 above.

[0066] S14, Constructing dynamic parameters k i , T i With material parametersN , S , X The dataset.

[0067] S2. Through regression analysis, establish the quantitative relationship between kinetic parameters and material parameters, and construct a parameterized reaction kinetic model.

[0068] Specifically, the steps include: performing regression fitting based on the dataset from step S14 to obtain dynamic parameters. k i , T i With material parameters N , S , X The correlation relationships are shown in Table 1 below: Table 1 Correlation between kinetic parameters and material parameters In Table 1 above, the general rule for judging the correlation (i.e., the existence of corresponding equations) is as follows: based on the research results of existing literature on alkali-activated slag slurry, the material parameters are... N , S , X With dynamic parameters k i , T i The corresponding data are fitted, and if a graph can be formed with dynamic parameters as the ordinate and material parameters as the abscissa, and the goodness of fit R... 2 If the value is greater than or equal to 0.32, then the two are considered to have a correlation.

[0069] Composition of slag X With the corresponding base-activated reaction rate parameters k Let's take the correlation relationship of 4 as an example to illustrate.

[0070] According to existing literature, the composition of slag X and the corresponding base-activated reaction rate parameters k The data for 4 are shown in Table 2 below.

[0071] Table 2 Composition of Slag X and the corresponding base-activated reaction rate parameters k 4 data Therefore, based on the composition of slag X The x-axis represents the base-activated reaction rate parameter. k Using 4 as the ordinate, and through linear fitting, the correlation equation between the two can be formed, such as... Figure 3 As shown.

[0072] The general rule for determining "considered a constant value" is as follows: based on the research results of alkali-activated slag slurry in existing literature, if the kinetic parameters no longer show significant changes with the material parameters within a certain range, and their coefficient of variation is less than 0.6, then it is considered a constant value.

[0073] Based on the Na2O content in the activator N The duration of the corresponding nucleation phase II T Let's take the correlation relationship of 3 as an example to illustrate.

[0074] According to existing literature, the Na2O content in the activator... N and the duration of the corresponding nucleation phase II. T The data for 3 are shown in Table 3 below.

[0075] Table 3 Na2O content in activator N and the duration of the corresponding nucleation phase II. T 3 data It can be seen that when N When ≥6, T 3 no longer with N It does not change significantly with the increase, but gradually tends to stabilize; and, when N When ≥6, within its interval T The coefficient of variation for 3 is 0.54, which is less than 0.6, therefore it will be considered a constant. Figure 4 As shown.

[0076] The general rule for judging "insignificant correlation" is as follows: Based on the research results of existing literature on alkali-activated slag slurry, if the data distribution is relatively scattered, no regularity is observed, and the regression fit R is not significant... 2 If the value is less than 0.32, the correlation is considered to be insignificant.

[0077] Based on the SiO2 content in the activator S and the corresponding base-activated reaction rate parameters k The insignificant correlation in 4 is illustrated by the example.

[0078] According to existing literature, the SiO2 content in the activator... S and the corresponding base-activated reaction rate parameters k The data for 4 are shown in Table 4 below.

[0079] Table 4. SiO2 content in activator S and the corresponding base-activated reaction rate parameters k 4 data It can be seen that their distribution is relatively scattered and shows no regularity, such as Figure 5 As shown, the regression fit Rfit is... 2 The value is only 0.0414. Therefore, by determining the goodness of fit R... 2 A value less than 0.3 indicates that the correlation is not significant.

[0080] Furthermore, based on the correlation relationships shown in Table 1, a multivariate nonlinear regression was performed using Equation 12 to establish the dynamic parameters. k i , T i With material parameters N , S , X Relationship: Formula 12 In Equation 12, y Represents reaction rate parameter k i and stage duration T i Any one of them; x 1. x 2. x 3 represents the parameters that affect the material, where x 1 is the main influencing material parameter. x 2 and x 3 are secondary influencing material parameters; priority should be given to... N As the main influencing material parameters x 1; If the dynamic parameters are the same as N When the correlation is not significant (see Table 1), then... S As x 1; If the dynamic parameters are the same as N , S When the correlations are not significant, then... X As x 1; f(x 1 ) , f(x 2 ) and f(x 3 ) These are the correlation expressions for the corresponding individual material parameters (see Table 1); l 1. l 2 and l 3 are respectively f(x 1 ) , f(x 2 ) and f(x 3 ) The corresponding correction coefficients are obtained according to this rule.k i and stage duration T i The results of the multiple nonlinear regression are shown in Table 5 below.

[0081] Table 5 Reaction rate parameters k i and stage duration T i Multiple nonlinear regression results Therefore, the relationship between the kinetic parameters and the material parameters is shown in Equations 13 to 24, which is also the parameterized reaction kinetic model of alkali-activated slag slurry: k 1 = 9.35258 Equation 13 k 2 = 0.25081 Equation 14 Formula 15 Formula 16 Formula 17 Formula 18 T 1 = 0.16677 Equation 19 Formula 20 Formula 21 Formula 22 Formula 23 Formula 24 S3. Based on the kinetic parameters of the alkali-activated slag slurry provided in step S1 and the parameterized reaction kinetic model of the alkali-activated slag slurry provided in step S2, predict the degree of reaction of the alkali-activated slag slurry with a known mix ratio at different ages.

[0082] Specifically, it includes the following steps: S31. For alkali-activated slag slurry with a known mix ratio, calculate the material parameters according to Equations 1 to 3. N , S , X ; S32. Substitute the material parameters obtained in step S31 into equations 13 to 24 to obtain the prediction. k i and prediction T i ; S33, The prediction obtained in step S32 ki and prediction T i Substituting into equations 5 through 11, we can determine... t Calculate the degree of reaction at each reaction stage at any given time. α i ; S34. Calculate the alkali-activated slag slurry using the following formula 25. t Total Response Level at Time α SL(t) That is, to obtain alkali-activated slag slurry with a known mix ratio at different ages (i.e., different ages). t The degree of reaction at any given moment: Formula 25 In Equation 25, α i Indicates the first i The degree of response at each stage i for t The reaction stage at any given moment.

[0083] It should be noted that the above prediction method applies to alkali-activated slag slurry cured at room temperature, excluding cases cured by heating or low temperature. This is because heating promotes the reaction in alkali-activated slag slurry, thereby increasing the degree of reaction; while low temperature curing reduces the degree of reaction.

[0084] Based on the above-obtained prediction results of the reaction degree of alkali-activated slag slurry, and after model correction, combined with the research results of existing literature on alkali-activated fly ash slurry, a prediction method for the reaction degree of alkali-activated slag-fly ash slurry can be obtained.

[0085] Reference Figure 6 The method for predicting the degree of reaction in alkali-activated slag-fly ash slurry specifically includes the following steps: Q11. Modify the reaction kinetic model parameters of alkali-activated slag slurry in the above-mentioned prediction method for the degree of reaction of alkali-activated slag slurry.

[0086] Reference Figure 7 As shown, for the alkali-activated slag-fly ash composite system, its heat flow curve can be decomposed into the heat flow curves of the alkali-activated slag slurry and the alkali-activated fly ash slurry. Therefore, it is reasonable to calculate the degree of reaction of the composite system based on the degree of reaction of the alkali-activated slag slurry and the alkali-activated fly ash slurry. Furthermore, through... Figure 7 It is known that the composite system has no induction period after the initial peak. Therefore, when calculating the degree of reaction of the composite system, the induction period of the alkali-activated slag slurry needs to be removed to correct the model parameters.

[0087] Specifically, the method for correcting the reaction kinetics model parameters of alkali-activated slag slurry includes: deleting the induction period of the heat flow curve of alkali-activated slag slurry, that is, letting... t tr, 2 = t tr, 3 , T 3=0、 α Set 3 to 0 to correct the model parameters.

[0088] Q12. Based on the corrected model parameters, predict the degree of reaction of alkali-activated slag in alkali-activated slag-fly ash slurry with a known mix ratio at different ages.

[0089] Specifically, it includes the following steps: Q121. For an alkali-activated slag-fly ash slurry with a known mix ratio, calculate the material parameters according to Equations 26, 27, and 3. N’ , S’ , X ; N’ The calculation method is shown in Equation 26 below: Formula 26 S’ The calculation method is shown in Equation 27 below: Formula 27 The activator in Formulas 26 and 27 refers to the activator in the alkali-activated slag-fly ash slurry, and the total precursor refers to the total amount of slag and fly ash in the alkali-activated slag-fly ash slurry.

[0090] Specifically, N’ The value range is 2.5% to 8%. S’ The value range is 1.94% to 11.63%, and the corresponding modulus of the activator ranges from 0.5 to 2.0.

[0091] Specifically, the activator is a composite activator formed by combining sodium hydroxide and sodium silicate solutions; wherein, sodium hydroxide is a solid, the modulus of the sodium silicate solution ranges from 2.0 to 3.4, and the water content of the sodium silicate solution ranges from 55% to 65%. By adding sodium hydroxide to the sodium silicate solution to adjust the modulus, the modulus range of the adjusted composite activator is controlled within the range of 0.5 to 2.0.

[0092] Q122. Substitute the material parameters obtained in step Q121 into the corrected model parameters obtained in step Q11 to obtain the prediction. k i and prediction T i ; Q123, The prediction obtained in step Q122 ki and prediction T i Substituting into equations 5 through 11, we can determine... t Calculate the degree of reaction at each reaction stage at any given time. α i ; Q124. Calculate the alkali-activated slag slurry in alkali-activated slag-fly ash slurry using Equation 25. t Total Response Level at Time α SL(t) That is, to obtain the alkali-activated slag slurry at different ages (i.e., different proportions) in an alkali-activated slag-fly ash slurry with a known mix ratio. t The degree of response at any given moment.

[0093] Q21. Based on existing literature on alkali-activated fly ash slurry, collect isothermal calorimetric curve data of alkali-activated fly ash slurry, and calculate kinetic parameters based on the isothermal calorimetric curves. k’ i and T’ i A dataset of dynamic parameters and temperature was established.

[0094] Among them, isothermal calorimetric curve data includes heat flux curve data (i.e. t ~d Q / d t ) and cumulative heat release curve data (i.e. t ~ Q );in, t Represents time, in hours (h). Q This represents the amount of heat released, expressed in J / g.

[0095] The specific steps for establishing a dataset of dynamic parameters include: Q211. Based on the cumulative heat release curve of alkali-activated fly ash slurry, the degree of reaction at different times within the time range of the isothermal calorimetric curve is calculated using the following formula 28. α’(t) : Formula 28 In Equation 28, α’(t) for t The degree of reaction at any given moment; Q'(t) for t The cumulative heat released at any given time, expressed in J / g; Q’ max The maximum heat release of fly ash is taken as 250 J / g.

[0096] Q212. Based on the morphological characteristics of the heat flow curve of alkali-activated fly ash slurry, the hydration reaction process of alkali-activated fly ash slurry is divided into three stages, as follows: ① t’tr, 0 ~ t’ tr, 1 : Nucleation growth stage, ② t’ tr, 1 ~ t’ tr, 2 : Phase interface stage, and ③ t’ tr, 2 ~ t’ tr, 3 : Diffusion period.

[0097] The time points for each characteristic are as follows: t’ tr, 0 =0 indicates that the reaction has started; t’ tr, 1 The peak time point represents the boundary between the nucleation growth period and the phase interface stage. t’ tr, 2 and t’ tr, 3 These represent the start and end times of the diffusion phase, respectively, with the start time of the diffusion phase denoted by d. 2 Q d t 2 Using -0.1 as the criterion, the theoretical end time of the diffusion period is infinity.

[0098] The duration of the stage is calculated using the following formula 29. T’ i : Formula 29 In Equation 29, i The integers from 1 to 3 correspond to the obtained T’ 1. T’ 2. T’ 3 represents the duration of the nucleation growth period, the phase interface stage, and the diffusion period, in that order.

[0099] Q213. Using the reaction kinetic integral equations representing the nucleation growth period, phase interface stage, and diffusion period respectively, as shown in Equations 30 to 32, calculate the reaction rate parameters for the nucleation growth period, phase interface stage, and diffusion period respectively. k’ 1. k’ 2 and k’ 3: Formula 30 Formula 31 Formula 32 In equations 30 to 32 α’ The degree of reaction is represented by a value of [value missing].t The degree of reaction corresponding to the time is t The difference in the degree of reaction at the beginning of the stage at which the time is located; among which, t The degree of reaction at any given moment α’(t) Both the degree of reaction at the beginning of the stage and the degree of reaction at the beginning of the stage are calculated according to Equation 29 above.

[0100] Q214. Calculate the above kinetic parameters at 50℃ and 60℃ respectively. k’ i , T’ i And construct dynamic parameters k’ i , T’ i The dataset with temperature (including 50℃ and 60℃) is shown in Table 6 below: Table 6. Data set of kinetic parameters of alkali-activated fly ash slurry at different temperatures. Q22. Based on the kinetic parameters of alkali-activated fly ash at different temperatures, predict the degree of reaction of alkali-activated fly ash in alkali-activated slag-fly ash slurry with a known mix ratio at different ages.

[0101] The specific prediction steps are as follows: Q221. Calculate the kinetic parameters at the corresponding temperatures in Table 6. k’ i , T’ i Substitute equations 30 to 32, and determine... t Calculate the degree of reaction at each reaction stage at any given time. α’ i .

[0102] Specifically, the selection of kinetic parameters for fly ash at different temperatures is related to the slag mass ratio: when the slag mass in the alkali-activated slag-fly ash slurry is ≤50% of the total precursor mass (the sum of the masses of slag and fly ash), the kinetic parameters corresponding to 50℃ in Table 6 are adopted. k’ i and T’ i When the slag mass in the alkali-activated slag-fly ash slurry is greater than 50% of the total precursor mass, the kinetic parameters corresponding to 60℃ in Table 6 shall be used. k’ i and T’ i .

[0103] This is because the hydration reaction of slag releases heat, which accelerates the reaction of fly ash. Therefore, when the slag content is high (>50%), the hydration reaction releases more heat, promoting the reaction of fly ash. In this case, a kinetic parameter of 60℃ is selected for fly ash. Conversely, when the slag content is low (≤50%), the hydration reaction releases relatively less heat, and a kinetic parameter of 50℃ is selected for fly ash.

[0104] Q222. For alkali-activated fly ash slurry, the total degree of reaction at 50℃ or 60℃ is equal to the sum of the degree of reaction at each stage.

[0105] The following formula (33) is used to calculate the alkali-activated fly ash slurry. t Total Response Level at Time α FA(t) : Formula 33 In Equation 33, α’ i Indicates the first i The degree of response at each stage i For Phase 1 to Phase 3 t The reaction stage at any given moment.

[0106] Q3. Calculate the degree of reaction of the alkali-activated slag-fly ash composite system according to the following formula 34: Formula 34 In Equation 34, P SL This is the ratio of slag mass to total precursor mass. P FA It is the ratio of the mass of fly ash to the total mass of precursors, where the total mass of precursors is equal to the sum of the masses of slag and fly ash. α SL ( t ) is the age period t The degree of reaction of alkali-activated slag slurry (corrected). α FA ( t ) is the age period t The degree of reaction of fly ash slurry activated by alkali.

[0107] It should be noted that the above prediction method applies to alkali-activated slag-fly ash slurry cured at room temperature, excluding cases of heating or low-temperature curing. This is because heating promotes the reaction in alkali-activated slag-fly ash slurry, thereby increasing the degree of reaction; while low-temperature curing reduces the degree of reaction.

[0108] The technical solution of the present invention will now be described in conjunction with the accompanying drawings and embodiments. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other implementation methods obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0109] Example 1 This embodiment aims to provide a process for predicting the degree of reaction of alkali-activated slag slurry with a known ratio.

[0110] First, the material parameters of alkali-activated slag slurry are calculated.

[0111] The chemical composition of the slag is shown in Table 7 below.

[0112] Table 7 Chemical composition of slag (wt%) Therefore, the result is obtained according to Equation 3 above. X It is 1.36.

[0113] Meanwhile, the activator used is a composite activator made of sodium hydroxide and sodium silicate solution; wherein, the sodium silicate solution has a modulus of 2 and its chemical composition is 14.70wt% Na2O, 29.40wt% SiO2, and 55.90wt% H2O; the modulus is adjusted to 1 by adding solid sodium hydroxide to the sodium silicate solution.

[0114] Based on Equations 1 and 2 above, the Na2O content in the activator can be calculated. N The SiO2 content is 6% with a modulus of 1. S It is 5.81%.

[0115] Then, the calculated material parameters N , S , X Substituting the parameterized reaction kinetic equations 13 to 24, the corresponding predictions are obtained. k i and T i Specifically, they are: k 1 = 9.35258 Equation 13-1 k 2 = 0.25081 Equation 14-1 Formula 15-1 Equation 16-1 Formula 17-1 Formula 18-1 T 1 = 0.16677 Equation 19-1 Formula 20-1 Equation 21-1 Equation 22-1 Equation 23-1 Equation 24-1 The third step is to calculate the results from equations 13-1 to 24-1 above. k i and T i Substituting the formulas for calculating the stage duration and the stage reaction kinetic equations (Equations 5-11), we first determine... t The reaction stage at any given moment is determined, and the degree of reaction at each stage is then calculated. α i .

[0116] Formula 6-1 Equation 7-1 Formula 8-1 Formula 9-1 Equation 10-1 Formula 11-1 Step 4: Alkali activation of slag slurry t Total Response Level at Time α SL ( t The sum of the degree of each stage reaction is equal to the sum of the degree of each stage reaction, as shown in Equation 25.

[0117] Formula 25 In the formula α i Indicates the first i The degree of response at each stage i For stages 1 through 6 t The reaction stage at any given moment.

[0118] Finally, the formulas in steps three and four are solved mathematically to obtain the alkali-activated slag slurry at any given time point. t The prediction results of the continuous full-stage reaction extent, such as Figure 9 As shown.

[0119] To verify the reliability of the prediction results of the method for predicting the degree of reaction of alkali-activated slag slurry based on parametric reaction kinetic equation disclosed in Example 1 above, the alkali-activated slag slurry with a known mix ratio was calculated using conventional calculation methods in the prior art.

[0120] It should be noted that the calculation method for the degree of reaction in the prior art must be carried out based on the cumulative exothermic curve of a determined mix ratio that has been tested and obtained; therefore, the comparison process here can only be carried out for mix ratios and ages for which the cumulative exothermic curve has been studied and tested in existing literature.

[0121] Specifically, the proportions are the same as in Example 1, and its cumulative heat release curve is obtained; wherein Q max The value is 460 J / g.

[0122] Based on Equation 4 above and Equations 35 and 36 below, the degree of reaction at 1 day, 3 days and 28 days is calculated.

[0123] Formula 35 Formula 36 In Equations 35 and 36 τ and β These are the time parameter and the shape parameter, respectively.

[0124] More specifically, Equations 4, 35, and 36 are commonly used methods and formulas for calculating the degree of reaction in the prior art. References can be found in the aforementioned existing literature [3], as well as in existing literature [7] (Chithiraputhiran S, Neithalath N. Isothermal reaction kinetics and temperature dependence of alkali activation of slag, fly ash and their blends[J]. Construction and Building Materials, 2013, 45: 233-242.) and existing literature [8] (Caron R, Patel RA, Dehn F. Activationkinetic model and mechanisms for alkali-activated slag cements[J]. Construction and Building Materials, 2022, 323: 126577.). Substituting Equation 4 into Equation 35 yields Equation 36. First, based on the cumulative exothermic curve data, Equation 4 can be used to obtain the isothermal calorimetric test time range. α ( t )and t The corresponding data are obtained, and the response levels at 1 day, 3 days, and 28 days are obtained by mathematical methods based on Equation 36.

[0125] The degree of reaction calculated using the conventional methods in the prior art, and the comparison with the predicted results of Example 1, are shown in Table 8 and... Figure 9 As shown.

[0126] Table 8. Prediction results of the reaction degree of alkali-activated slag slurry and calculation results of existing technical methods. From Table 8 and Figure 9 As can be seen from this embodiment, the method for predicting the degree of reaction of alkali-activated slag slurry based on parameterized reaction kinetic equations is close to the result of the degree of reaction obtained by calculation in the prior art, indicating that the result is reliable. Moreover, the prediction method can also achieve prediction of the degree of reaction in the continuous whole stage.

[0127] Example 2 This embodiment aims to provide a process for predicting the degree of reaction in alkali-activated slag-fly ash slurry.

[0128] First, the material parameters of alkali-activated slag-fly ash slurry are calculated.

[0129] The alkali-activated slag-fly ash slurry uses Class F fly ash and is prepared with 50 wt% slag and 50 wt% fly ash.

[0130] The chemical composition of slag and fly ash is shown in Table 9 below.

[0131] Table 9 Chemical composition of slag and fly ash (wt%) Therefore, the result is obtained according to Equation 3 above. X It is 1.58.

[0132] Meanwhile, the activator used is a composite activator made of sodium hydroxide and sodium silicate solution; wherein, the sodium silicate solution has a modulus of 3.4 and its chemical composition is 8.25wt% Na2O, 27.5wt% SiO2, and 64.25wt% H2O; the modulus is adjusted to 0.93 by adding sodium hydroxide to the sodium silicate solution.

[0133] The Na₂O content in the activator can be calculated based on Equations 26 and 27 above. N’ The content is 6%, the modulus is 0.93, and the corresponding SiO2 content is... S’ It is 5.4%.

[0134] Then, the degree of reaction of alkali-activated slag slurry in alkali-activated slag-fly ash slurry was predicted.

[0135] Specifically, (1) the calculated N’ , S’ , X Substituting the parameterized reaction kinetic equations 13-24 into the corrected equations (where equation 21 is replaced by...), T 3=0), predicting the corresponding k i and T i See below: k 1 = 9.35258 Equation 13-2 k 2 = 0.25081 Equation 14-2 Formula 15-2 Formula 16-2 Formula 17-2 Formula 18-2 T 1 = 0.16677 Equation 19-2 Formula 20-2 Equation 21-2 Equation 22-2 Equation 23-2 Equation 24-2 (2) The results obtained from Equations 13-2 to 24-2 above k i and T i Substituting the formulas for calculating the stage duration and the stage reaction kinetic equations (Equations 5-11), we first determine... t The reaction stage at any given moment is determined, and the degree of reaction at each stage is then calculated. α i .

[0136] Formula 6-2 Equation 7-2 Formula 8-2 Formula 9-2 Equation 10-2 Formula 11-2 (3) Alkali-activated slag slurry t Total Response Level at Time α’ SL ( t The sum of the degree of each stage reaction is equal to the sum of the degree of each stage reaction, as shown in Equation 25.

[0137] Formula 25 In the formula α i Indicates the first i The degree of response at each stage i For stages 1 through 6 t The reaction stage at any given moment.

[0138] (4) Solve the formulas in (2) and (3) mathematically to obtain the corrected time point of the alkali-activated slag slurry in the alkali-activated slag-fly ash slurry. t The prediction results of the continuous full-stage reaction extent, such as Figure 10 As shown.

[0139] The third step is to predict the degree of reaction of alkali-activated fly ash slurry in alkali-activated slag-fly ash slurry.

[0140] Specifically, (1) based on the mass ratio of fly ash in the alkali-activated slag-fly ash composite system (that is, equal to 50% of the total precursor mass (the sum of the masses of slag and fly ash)), the kinetic parameters corresponding to 50℃ of the alkali-activated fly ash slurry in Table 6 above are adopted, i.e. k’ 1. k’ 2. k’ 3 are 5.35217, 0.02812, and 0.00001 respectively. T’ 1. T’ 2. T’ 3 are 0.07709, 37.28902, and +∞ respectively.

[0141] (2) The dynamic parameters in (1) k’ i and T’ i Substituting the formulas for calculating the duration of each stage and the stage-specific reaction kinetics equations (equations 29-32), we first determine... t The reaction stage at any given moment is determined, and the degree of reaction at each stage is then calculated. α’ i .

[0142] Formula 30-1 Formula 31-1 Equation 32-1 (3) Alkali-activated fly ash slurry t Total Response Level at Time α FA ( t The sum of the degree of reaction in each stage is equal to the sum of the degree of reaction in each stage, as shown in Equation 33.

[0143] Formula 33 In the formula α i Indicates the first i The degree of response at each stage i For Phase 1 to Phase 3 t The reaction stage at any given moment.

[0144] (4) Solve the formulas in (2) and (3) mathematically to obtain the alkaline activated fly ash slurry at 50℃ at any time point. t The prediction results of the continuous full-stage reaction extent, such as Figure 11 As shown.

[0145] Finally, the degree of reaction of the alkali-activated slag-fly ash composite system was calculated according to Equation 34, and the predicted results are as follows: Figure 12 As shown.

[0146] Formula 34 In the formula P SL This is the ratio of slag mass to total precursor mass. P FA The ratio of fly ash mass to total precursor mass is given, where the total precursor mass equals the sum of the masses of slag and fly ash. In this embodiment... P SL and P FA All values ​​are 0.5. α SL ( t The age obtained in the second step is... t The degree of reaction of alkali-activated slag slurry after correction ( Figure 10 (as shown) α FA ( t The age obtained in the third step is... t The degree of alkali activation of fly ash slurry reaction (e.g.) Figure 11 (As shown).

[0147] To verify the reliability of the prediction results of the method for predicting the degree of reaction of alkali-activated slag-fly ash slurry based on parametric reaction kinetic equation disclosed in Example 2 above, the alkali-activated slag-fly ash slurry with a known mix ratio was calculated using conventional calculation methods in the prior art.

[0148] It should be noted that, since the calculation method for the degree of reaction in the prior art must be based on the cumulative exothermic curve that has been tested, the comparison process here can only be carried out on the ratios and ages for which the cumulative exothermic curves have been studied and tested in the existing literature.

[0149] Specifically, the mix proportions are consistent with those of Example 1, that is, the chemical composition of slag and fly ash is consistent with Table 9 in Example 2, and their cumulative exothermic curves are obtained.

[0150] The degree of reaction at 7 days was determined by SEM image analysis. The cumulative heat release at 7 days was obtained from the cumulative heat release curve. The maximum heat release was calculated based on Equation 4 above. Q max Then, the cumulative heat release data obtained from the test... Q(t) and the calculated Q max Substitute into Equation 4 to obtain the degree of response at different ages. For specific calculation steps, please refer to the existing literature mentioned above [3].

[0151] A comparison of the reaction degree calculated using conventional methods in the prior art with the predicted results of Example 2. Figure 12 As shown.

[0152] from Figure 12 As can be seen from this embodiment, the method for predicting the degree of reaction of alkali-activated slag-fly ash slurry based on parameterized reaction kinetic equations is close to the results of the degree of reaction obtained by calculation in the prior art, indicating that its results are reliable.

[0153] Example 3 This embodiment uses the same slag and fly ash components as Embodiment 2. The difference is that, firstly, the alkali-activated slag-fly ash slurry in this embodiment is prepared with 70wt% slag and 30wt% fly ash.

[0154] Furthermore, the Na2O content in the activator... N and SiO2 content S This is consistent with Example 2.

[0155] Secondly, the prediction results for the degree of reaction of alkali-activated slag slurry in alkali-activated slag-fly ash slurry are the same as those in Example 2, and will not be repeated here.

[0156] The third step, predicting the degree of reaction of the alkali-activated slag slurry in the alkali-activated slag-fly ash slurry, specifically includes: (1) Based on the mass ratio of fly ash in the alkali-activated slag-fly ash composite system (that is, equal to 30% of the total precursor mass (the sum of the masses of slag and fly ash)), the kinetic parameters corresponding to 60℃ of the alkali-activated fly ash slurry in Table 6 above are adopted, i.e. k’ 1. k’ 2. k’ The values ​​for 3 are 5.41113, 0.03797, and 0.00001, respectively. T’ 1. T’ 2. T’ 3 are 0.07625, 32.51827, and +∞ respectively.

[0157] (2) The dynamic parameters in (1) k’ i and T’ i Substituting the formulas for calculating the duration of each stage and the stage-specific reaction kinetics equations (equations 29-32), we first determine... t The reaction stage at any given moment is determined, and the degree of reaction at each stage is then calculated. α’ i .

[0158] Formula 30-2 Formula 31-2 Equation 32-2 (3) Alkali-activated fly ash slurry t Total Response Level at Time α FA ( t The sum of the degree of reaction in each stage is equal to the sum of the degree of reaction in each stage, as shown in Equation 33.

[0159] Formula 33 In the formula α i Indicates the first i The degree of response at each stage i For Phase 1 to Phase 3 t The reaction stage at any given moment.

[0160] (4) Solve the formulas in (2) and (3) mathematically to obtain the alkaline activated fly ash slurry at 60℃ at any time point. t The prediction results of the continuous full-stage reaction extent, such as Figure 13 As shown.

[0161] Finally, the degree of reaction of the alkali-activated slag-fly ash composite system was calculated according to Equation 34, and the predicted results are as follows: Figure 14 As shown.

[0162] Formula 34 In the formula P SL This is the ratio of slag mass to total precursor mass. P FA The ratio of fly ash mass to total precursor mass is given, where the total precursor mass equals the sum of the masses of slag and fly ash. In this embodiment... P SL and P FA The values ​​are 0.7 and 0.3 respectively. α SL ( t The age obtained in the second step is... t The degree of reaction of the modified alkali-activated slag slurry (e.g.) Figure 10 (as shown) α FA ( t The age obtained in the third step is... t The degree of alkali activation of fly ash slurry reaction (e.g.) Figure 13 (As shown).

[0163] Existing methods for calculating the degree of reaction typically rely on measured cumulative exothermic curves with a defined mix proportion or reaction degree data obtained through other characterization methods, followed by calculation using formulas. This means that such methods are only applicable to slurries with mix proportions for which cumulative exothermic curves have been tested, and cannot predict the reaction degree of slurries with known mix proportions for which no such tests have been performed. In contrast, this invention, based on the aforementioned measured thermodynamic curves obtained in the prior art, establishes the relationship between kinetic parameters and material parameters, constructing a parameterized reaction kinetic equation. This enables the prediction of the reaction degree of slurries with known mix proportions for which no such tests have been performed.

[0164] The embodiments described above are for illustrative purposes only and do not constitute a specific limitation on the present invention. Any modifications made without departing from the basic concept of the present invention, as well as any obvious modifications derived therefrom, are within the scope of protection of the present invention.

Claims

1. A method for predicting the degree of reaction in alkali-activated slag slurry based on parameterized reaction kinetic equations, characterized in that, Including the following steps: S1. Collect material parameters and isothermal calorimetric curve data of alkali-activated slag slurry, and calculate kinetic parameters based on the isothermal calorimetric curves. k i and T i Then, a dataset of the kinetic parameters and the material parameters is established; wherein, the material parameters include the Na2O content in the activator. N and SiO2 content S and the composition of slag X ; S2. Through regression analysis, establish the quantitative relationship between the kinetic parameters and material parameters of the alkali-activated slag slurry, and construct a parameterized reaction kinetic model of the alkali-activated slag slurry; S3. Based on the kinetic parameters of the alkali-activated slag slurry provided in step S1 and the parameterized reaction kinetic model of the alkali-activated slag slurry provided in step S2, predict the degree of reaction of the alkali-activated slag slurry with a known mix ratio at different ages.

2. The prediction method according to claim 1, characterized in that, Step S2 specifically includes: based on the dataset obtained in step S1, performing regression fitting, and adjusting the dynamic parameters... k i , T i With the material parameters N , S , X The correlation relationships can be summarized into three categories: those with a correlation relationship, those considered constant, and those with an insignificant correlation relationship. Based on the correlation, multiple nonlinear regression is performed using equation (1) to establish the dynamic parameters. k i , T i With the material parameters N , S , X The relationship, namely the parameterized reaction kinetic model of alkali-activated slag slurry: Equation (1) In equation (1), y Represents reaction rate parameter k i and stage duration T i Any one of them; x 1. x 2. x 3 represents the parameters that affect the material, where x 1 is the main parameter affecting the material. x 2 and x 3 are secondary influencing material parameters; priority should be given to... N As the main influencing material parameters x 1; If the dynamic parameters are the same as N When the correlation is not significant, then... S As x 1; If the dynamic parameters are the same as N , S When the correlations are not significant, then... X As x 1; f(x 1 ) , f(x 2 ) and f(x 3 ) These are the correlation expressions for the corresponding individual material parameters; l 1. l 2 and l 3 are respectively f(x 1 ) , f(x 2 ) and f(x 3 ) The corresponding correction factor.

3. The prediction method according to claim 2, characterized in that, Step S3 specifically includes: S31. For alkali-activated slag slurry with a known mix ratio, calculate the material parameters. N , S , X ; S32. Substitute the material parameters obtained in step S31 into the formula of the parameterized reaction kinetics model of the alkali-activated slag slurry to obtain the predicted... k i and prediction T i ; S33, The prediction obtained in step S32 k i and prediction T i Substitute the dynamic parameters k i and T i In the calculation formula, by determining t Calculate the degree of reaction at each reaction stage at any given time. α i ; S34. Calculate the alkaline-activated slag slurry using formula (2). t Total Response Level at Time α SL(t) That is, to obtain the degree of reaction of alkali-activated slag slurry with a known mix ratio at different ages: Equation (2) In equation (2), α i Indicates the first i The degree of response at each stage i for t The reaction stage at any given moment.

4. The prediction method according to any one of claims 1 to 3, characterized in that, The alkali-activated slag slurry is cured at room temperature.

5. A method for predicting the degree of reaction in alkali-activated slag-fly ash slurry based on parameterized reaction kinetic equations, characterized in that, Including the following steps: Q11. Modify the reaction kinetic model parameters of alkali-activated slag slurry in the prediction method of the reaction degree of alkali-activated slag slurry according to any one of claims 1 to 4, and delete the induction period in the heat flow curve of the alkali-activated slag slurry; Q12. Based on the model parameters corrected in step Q11, predict the degree of reaction of alkali-activated slag in alkali-activated slag-fly ash slurry with known mix ratio at different ages. Q21. Based on existing literature on alkali-activated fly ash slurry, collect isothermal calorimetric curve data of alkali-activated fly ash slurry, and calculate kinetic parameters based on the isothermal calorimetric curves. k’ i and T’ i A dataset of kinetic parameters and temperature for alkali-activated fly ash slurry was established. Q22. Based on the kinetic parameters of alkali-activated fly ash at different temperatures, predict the degree of reaction of alkali-activated fly ash in alkali-activated slag-fly ash slurry with a known mix ratio at different ages. Q3. Calculate the degree of reaction of the alkali-activated slag-fly ash composite system according to formula (3): Equation (3) In equation (3), P SL This is the ratio of slag mass to total precursor mass. P FA It is the ratio of the mass of fly ash to the total mass of precursors, where the total mass of precursors is equal to the sum of the masses of slag and fly ash; α SL ( t The age obtained in step Q12 is t The degree of alkali activation of the reaction in slag slurry, α FA ( t The age obtained in step Q22 is t The degree of reaction of fly ash slurry activated by alkali.

6. The prediction method according to claim 5, characterized in that, Step Q12 specifically includes: Q121. For an alkali-activated slag-fly ash slurry with a known mix ratio, calculate the material parameters. N’ , S’ , X ; Q122. Substitute the material parameters obtained in step Q121 into the formula for the corrected model parameters in step Q11 to obtain the prediction. k i and prediction T i ; Q123, The prediction obtained in step Q122 k i and prediction T i Substitute the dynamic parameters k i and T i In the calculation formula, by determining t Calculate the degree of reaction at each reaction stage at any given time. α i ; Q124. Calculate the alkali-activated slag slurry in alkali-activated slag-fly ash slurry using formula (4). t Total Response Level at Time α SL(t) That is, to obtain the degree of reaction of alkali-activated slag slurry at different ages in alkali-activated slag-fly ash slurry with a known mix ratio: Equation (4) In equation (4), α i Indicates the first i The degree of response at each stage i for t The reaction stage at any given moment.

7. The prediction method according to claim 5, characterized in that, Step Q22 specifically includes: Q221. Based on the slag content in the alkali-activated slag-fly ash slurry, select the kinetic parameters at the corresponding temperature from the data set of kinetic parameters and temperature of the alkali-activated fly ash slurry in step Q21. k’ i , T’ i Substitute the dynamic parameters k i and T i In the calculation formula, by determining t Calculate the degree of reaction at each reaction stage at any given time. α’ i ; Q222. Calculate the alkaline activated fly ash slurry in alkaline activated slag-fly ash slurry using formula (5). t Total Response Level at Time α FA(t) : Equation (5).

8. The prediction method according to claim 7, characterized in that, The kinetic parameters at the corresponding temperature are selected from the data set of kinetic parameters and temperature of the alkali-activated fly ash slurry in step Q21. k’ i , T’ i The rules are: When the slag mass in the alkali-activated slag-fly ash slurry is ≤50% of the total precursor mass, the kinetic parameters corresponding to 50℃ in the data set of step Q21 are used. k’ i and T’ i ; When the slag mass in the alkali-activated slag-fly ash slurry is greater than 50% of the total precursor mass, the kinetic parameters corresponding to 60℃ in the data set of step Q21 are used. k’ i and T’ i .

9. The prediction method according to any one of claims 5 to 8, characterized in that, The alkali-activated slag-fly ash slurry is cured at room temperature.

10. The prediction method according to any one of claims 5 to 8, characterized in that, The fly ash is Class F fly ash.

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