Dehydroxylation of Kaolinite: Evaluation of Activation Energy by Thermogravimetric Analysis and Density Functional Theory Insights

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The paper aims to feature the combination of TG and DFT calculations to obtain some distinctive conclusions. However, the content of DFT calculations is too scanty and lacks depth, resulting in no novel conclusions being drawn.

1. There is a lack of basis for establishing the four dehydration models from A to D, which needs to be further elaborated. For instance, there are two types of hydroxyl groups and two types of oxygen atoms, thus giving rise to the possibility of four combinations.
2. The comparison between the activation energy and the reaction energy is inappropriate. Generally speaking, the activation energy is more suitably compared with the reaction energy barrier. This requires transition state calculations, which have not been carried out in this paper.
3. In fact, White et al. have already conducted excellent DFT work (J. Phys. Chem. A 2010, 114, 4988–4996), dividing the dehydroxylation steps into 13 steps. Shani Sperinck et al. (J. Mater. Chem., 2011, 21, 2118–2125) have also carried out outstanding molecular dynamics simulation work. Therefore, the DFT research in this paper does not surpass that of previous researchers.

Author Response

Summary. The paper aims to feature the combination of TG and DFT calculations to obtain some distinctive conclusions. However, the content of DFT calculations is too scanty and lacks depth, resulting in no novel conclusions being drawn.

 

Response. Thank you very much for taking the time to review our manuscript. Indeed, this work combines experimental results with DFT calculations to derive (i) ‘experimental’ conclusions, from the comparison between the two kaolin samples; (ii) ‘computational’ conclusions, from the comparison among four mono-dehydrated structural models; and (iii) ‘integrated’ conclusions, emerging from the comparison between experimental and computational findings. This combined experimental-theoretical approach, which is common in the literature, may appear relatively limited in depth to readers accustomed to purely experimental or purely computational studies, since narrower methodological scopes typically allow for deeper treatment within the same article length. However, the hybrid methodology adopted here was designed to meet the specific objectives of our study. In parallel, we are conducting additional DFT studies to explore the dehydroxylation process in greater detail, which we intend to present in a future publication (as commented in our manuscript, see lines 335-336).

Regarding the rest of your report, please find the detailed responses below.

 

Comments 1. There is a lack of basis for establishing the four dehydration models from A to D, which needs to be further elaborated. For instance, there are two types of hydroxyl groups and two types of oxygen atoms, thus giving rise to the possibility of four combinations.

 

Response 1.

We have re-elaborated the description of the dehydrated models from A to D, as suggested. Now we have included the following text:

‘Different mono-dehydrated variants were modelled to simulate the removal of a single water molecule. Considering that the kaolinite structure has two types of hydroxyl groups (at the outer and inner surface, see Figure 1) and two types of oxygen atoms (bonded to Al or Si atoms), four combinations were proposed for the removal of the H2O molecule from the structure. These were labelled as System A, B, C, and D, and are illustrated in Figure 3.’ (see lines 136-141).

 

Comments 2. The comparison between the activation energy and the reaction energy is inappropriate. Generally speaking, the activation energy is more suitably compared with the reaction energy barrier. This requires transition state calculations, which have not been carried out in this paper.

 

Response 2.

In this work we calculate by DFT the reaction energy Q as a first approach to provide reference energy ‘values against which the experimental results could be compared’ (line 161). We also explain in our manuscript that ‘the calculated Q values offer a lower bound for the thermal activation energy Ea, as the reverse process (rehydration) is non-spontaneous under ambient conditions’ (lines 317-318). We know that transition state calculations provide a more close description of the activation process, but (and because of this) they require considering additional variables such as reaction paths and, as a consequence, are computationally more demanding. We are currently performing such kinds of calculations, which will provide additional DFT-insights of the dehydroxylation process. We think that such analyses are beyond the objectives of the current article, and probably will be of interest for an audience more specific than that of the Minerals journal. Because of this we are planning a future more in-depth publication based on this kind of DFT calculations. That is the reason why we comment in the manuscript that ‘further work is needed to assess the kinetic feasibility of the associated atomic diffusion steps, where barriers related to atomic diffusion through the Al sheet to the interlayer may be expected. These studies are currently underway and will be presented in a future publication’ (lines 335-336).

 

Comments 3. In fact, White et al. have already conducted excellent DFT work (J. Phys. Chem. A 2010, 114, 4988–4996), dividing the dehydroxylation steps into 13 steps. Shani Sperinck et al. (J. Mater. Chem., 2011, 21, 2118–2125) have also carried out outstanding molecular dynamics simulation work. Therefore, the DFT research in this paper does not surpass that of previous researchers.

 

Response 3.

We are aware of the mentioned papers, and that of White et al. was already cited in our manuscript (ref. 38). Indeed, both are extensive and valuable works that deal with computational simulations on kaolinite dehydroxylation. However, such studies have not assessed the reaction and/or activation energies of the process. So, we think that our DFT results provide original and important results. We also consider that our DFT calculations combined with our experimental results enhance the analysis of the dehydroxylation process. Considering these comments, we have re-written the Introduction section to detail these aspects, including the additional reference of Sperinck et al., as follows:

‘Although these methods have proven to be powerful tools for analysing materials, careful comparison with experimental data is necessary to ensure consistency of the proposed DFT-models and their predicted properties. To date, few studies have applied computational methods such as DFT and molecular dynamics to the case of dehydroxylated kaolinite [38–41], and to the authors’ knowledge, none have focused specifically on the energy aspects of the dehydroxylation process’ (lines 59-64).

Reviewer 2 Report

Comments and Suggestions for Authors

This manuscript presents a well-structured and comprehensive study combining experimental thermogravimetric analysis (TG) and Density Functional Theory (DFT) calculations to investigate the dehydroxylation of kaolinite. The dual methodology provides valuable insights into both macroscopic and atomistic aspects of the process. The work is scientifically sound, with clear objectives and logical progression. However, some areas require clarification and expansion to strengthen the manuscript for possible publication in “Minerals (ISSN 2075-163X)”.

1. The industrial sample (SRB) contains significant quartz and other impurities, yet their specific influence on dehydroxylation kinetics is not thoroughly discussed. How do these impurities affect the reaction mechanism? Are there any secondary reactions (e.g., quartz phase transitions) that could interfere with the TG analysis? Authors are advised to read and cite; https://www.sciencedirect.com/science/article/pii/S0008622325000156
2. The XRD data (Table 1) shows a notable difference in kaolinite content (96% vs. 76.6%). A more detailed discussion on how this compositional variation impacts the observed activation energies would be beneficial.
3. The study does not address the reproducibility of TG measurements. Were replicate runs performed to assess variability? Given the sensitivity of kinetic analysis to experimental conditions, some discussion on error margins and consistency would strengthen the conclusions. Authors are advised to read and cite; https://www.sciencedirect.com/science/article/pii/S1383586624049359
4. The DFT models focus on idealized mono-dehydroxylation scenarios (Systems A-D). While useful, real-world dehydroxylation involves multiple water molecules and structural defects. Acknowledging these simplifications and discussing their potential impact on the results would improve the theoretical framework. Authors are advised to read and cite; https://www.sciencedirect.com/science/article/pii/S0927775725002080
5. How do the DFT-derived reaction energies compare with previous computational studies on kaolinite dehydroxylation? A brief literature comparison would contextualize the findings. Authors are advised to read and cite; https://www.sciencedirect.com/science/article/pii/S2352710225008289
6. The study provides fundamental insights but could better link findings to practical applications. For example:
   1. How do the lower activation energies in SRB affect industrial thermal processing (e.g., energy efficiency, reaction times)?
   2. Are there implications for metakaolin production or ceramic/cement applications?

Author Response

Summary

This manuscript presents a well-structured and comprehensive study combining experimental thermogravimetric analysis (TG) and Density Functional Theory (DFT) calculations to investigate the dehydroxylation of kaolinite. The dual methodology provides valuable insights into both macroscopic and atomistic aspects of the process. The work is scientifically sound, with clear objectives and logical progression. However, some areas require clarification and expansion to strengthen the manuscript for possible publication in “Minerals (ISSN 2075-163X)”.

 

Response

Thank you very much for taking the time to review this manuscript and for your positive feedback. Please find the detailed responses to your comments below.

 

Comments 1. The industrial sample (SRB) contains significant quartz and other impurities, yet their specific influence on dehydroxylation kinetics is not thoroughly discussed. How do these impurities affect the reaction mechanism? Are there any secondary reactions (e.g., quartz phase transitions) that could interfere with the TG analysis? Authors are advised to read and cite; https://www.sciencedirect.com/science/article/pii/S0008622325000156

 

Response 1.

Impurities such as quartz may affect the dehydroxylation mechanism indirectly, through a modification on heat and mass transfer. This is because they are not directly linked to a sample mass loss during thermal treatment in the analyzed temperature range (and TG senses mass loss), but they may affect the mass loss rate in kaolinite. In particular, at about 600 ºC quartz has a polymorphic transition of triclinic low-quartz to the hexagonal modification of high-quartz, which produces an expansion that can be studied by thermodilatometric measurements and may modify heat transfer in the sample. In the revised version of our manuscript we have a more thoughtful discussion on this issue, including the suggested reference, by the following text:

‘In addition, Figure 6a reveals that Ea in SRB is more sensitive to β, showing a stronger dependence than in KGa-1. This may indicate the influence of secondary processes occurring at higher heating rates, likely related to the presence of quartz and other impurities. For instance, at about 600 ºC occurs the α-β-phase quartz transition [19,56], which produces a dilatometric expansion that can modify thermal diffusivity in the sample [57]. This may lead to heat and mass transfer effects in the kaolin sample that distort the primary kinetic mechanism at elevated reaction rates’ (lines 225-232).

On the other hand, we do not think that the article you advised to read and cite is so closely linked to the analysis carried out here.

 

Comments 2. The XRD data (Table 1) shows a notable difference in kaolinite content (96% vs. 76.6%). A more detailed discussion on how this compositional variation impacts the observed activation energies would be beneficial.

 

Response 2.

We performed a more detailed discussion as suggested. As a continuation of the previous point, we also included the following text in our revised manuscript:

‘Since industrial kaolins often contain accessory minerals or are mixed with other raw materials, these results highlight the value of assessing Ea in detail and point to the possibility of tuning the thermal response through material formulation. In particular, the two studied kaolins of this work present notable differences in kaolinite content (see Table 1) which lead to differences on Ea, as observed in Figure 6a.’ (lines 233-238)

 

Comments 3. The study does not address the reproducibility of TG measurements. Were replicate runs performed to assess variability? Given the sensitivity of kinetic analysis to experimental conditions, some discussion on error margins and consistency would strengthen the conclusions. Authors are advised to read and cite; https://www.sciencedirect.com/science/article/pii/S1383586624049359

 

Response 3. Yes, runs were replicated and the variations on the obtained values are within the ranges presented in the manuscript. As suggested, in the revised version we have included a comment on the consistency of our results in the conclusions section. In this respect, we have included the following text:

‘The activation energy (Ea) ranges from 35 to 60 kcal/mol depending on the heating rate β, with the values for SRB being lower than those for KGa-1. This finding is attributed to the lower structural order in SRB, which likely results in higher reactivity. The range of obtained Ea values is consistent with that reported in the literature for kaolins under similar experimental conditions’ (lines 346-351)

On the other hand, we do not think that the article you advised to read and cite would fit in our analysis.

 

Comments 4. The DFT models focus on idealized mono-dehydroxylation scenarios (Systems A-D). While useful, real-world dehydroxylation involves multiple water molecules and structural defects. Acknowledging these simplifications and discussing their potential impact on the results would improve the theoretical framework. Authors are advised to read and cite; https://www.sciencedirect.com/science/article/pii/S0927775725002080

 

Response 4.

We now include some comments on these simplifications, as suggested: ‘These selected idealized mono-dehydrated scenarios are intentionally diverse to assess theoretically the differences on a first step of the dehydroxylation process. Conversely, real dehydroxylation experiments involve the removal of multiple water molecules in a material with impurities and defects’ (lines 145-149). Also, we have re-written the final part of the DFT calculations subsection: ‘The selected mono-dehydrated kaolinite variants cover a wide range of plausible dehydration scenarios, and will provide reference Q values against which the experimental results can be compared’ (lines 161-163).

Comments 5. How do the DFT-derived reaction energies compare with previous computational studies on kaolinite dehydroxylation? A brief literature comparison would contextualize the findings. Authors are advised to read and cite; https://www.sciencedirect.com/science/article/pii/S2352710225008289

 

Response 5.

As mentioned in the text, although there are different computational studies on kaolinite dehydroxylation (including DFT and molecular dynamics simulations), to our knowledge ‘none have focused specifically on the energy aspects of the dehydroxylation process’ (line 63). Nevertheless, in order to comply with your request, we have included a brief comparison with DFT-derived reaction energies in pyrophyllite, which is a 2:1 phyllosilicate: ‘As commented above, to the authors’ knowledge there are no predictions of Q or Ea for kaolinite in the literature. Nevertheless, quantum mechanical methods have been applied to the study of the dehydroxylation of pyrophyllite, which is a 2:1 phyllosilicate. There, using cluster models it has been predicted activation energies in the range 22-55 kcal/mol [61,62], in close agreement to the Q values obtained in this work for mono-dehydrated kaolinite’ (lines 319-323).

 

Comments 6. The study provides fundamental insights but could better link findings to practical applications. For example:

How do the lower activation energies in SRB affect industrial thermal processing (e.g., energy efficiency, reaction times)? Are there implications for metakaolin production or ceramic/cement applications?

 

Response 6.

We have rearranged and rewritten a paragraph in the Conclusions section considering your comments: ‘The insights into the relationship between structural order and reactivity are particularly valuable for tailoring kaolin-based materials to specific industrial applications. In such contexts, controlling phase transformation kinetics and reducing activation energies can be crucial to improving thermal performance, including aspects such as energy efficiency and reaction times. A deeper understanding of the associated energies and mechanisms enables the optimization of industrial practices, ranging from scaling and heating protocols to operating strategies and device design, ultimately contributing to lower installation and operating costs’ (lines 354-361).

 

Reviewer 3 Report

Comments and Suggestions for Authors

Dehydroxylation of kaolinite: evaluation of activation energy by thermogravimetric analysis and density functional theory insights

The subject matter of the article is highly relevant and engaging; however, certain refinements are necessary to enhance its overall clarity and scientific rigor.

 

Abstract

Include quantitative validation of DFT results against experimental Ea values with error bars or confidence intervals.

Clarify the choice of kinetic models with references to model discrimination criteria

 

Keywords: Add Density functional theory and metakaolin

 

Introduction

Reduce verbosity by consolidating overlapping discussions on process complexity and kinetic variability.

Clarify Novelty: Explicitly state how the proposed methodology advances beyond existing experimental and DFT studies.

 

Materials and Methods

To enhance the practical relevance of this study, a value-oriented narrative is integrated, emphasizing how the comparative analysis of kaolin samples informs strategic decision-making for industrial upgrading pathways and model-based dehydroxylation process design. This work hypothesizes that the elevated quartz content and reduced hydroxyl index (HI) observed in the SRB sample will result in distinctive kinetic profiles during thermal activation. These differences are expected to influence its reactivity and suitability for high-performance applications such as advanced ceramics or pozzolanic binders.

A SWOT-style comparison elucidates the strengths, weaknesses, opportunities, and threats associated with each sample. For instance, while SRB’s higher quartz content may reduce reactivity (a potential weakness), it could offer processing advantages in composite formulations requiring structural rigidity (an opportunity). Conversely, the RB sample’s higher HI and lower quartz content suggest enhanced reactivity but may necessitate more stringent control during calcination to prevent over-dehydroxylation.

These insights are positioned within a broader industrial and technological roadmap. Specifically, the findings contribute to the rational design of performance-graded metakaolins and support the development of AI-augmented thermochemical process optimization frameworks. By aligning academic analysis with industrial deployment potential, this approach fosters a more predictive and application-oriented perspective on kaolin thermal transformation.

 

Results

 

This study exemplifies methodological excellence through systematic kinetic modeling, rigorous thermogravimetric (TG) analysis, and cross-validation with independent mineralogical datasets. It significantly advances the current understanding of kaolinite thermal reactivity by:

Differentiating kaolins of varying structural order through distinct thermal decomposition signatures,

Identifying a predominant kinetic regime (F3 model) consistently applicable across compositional variants,

Correlating microstructural parameters—such as crystallinity and impurity load—with observed kinetic behavior,

Highlighting analytical constraints and proposing refined thermal analysis protocols for enhanced resolution and reproducibility.

These insights establish a robust technical basis for the customized thermal processing of naturally occurring kaolins, with direct implications for the development of next-generation materials ranging from catalytic supports to geopolymers and pozzolanic binders. In such applications, the extent of dehydroxylation and the trajectory of structural evolution are pivotal determinants of end-use performance. This work thus paves the way for more predictive, composition-specific thermal activation strategies within high-value industrial domains.

 

Conclusion

The conclusion presents a methodologically sound and strategically articulated synthesis, effectively showcasing the power of integrating analytical techniques with atomistic simulations to unravel complex solid-state transformation phenomena. Nonetheless, the extrapolation of these findings to industrial-grade, impurity-rich kaolins remains limited by the idealized nature of the theoretical models. To enhance translational relevance, future investigations should prioritize the development of more representative computational frameworks and complementary experimental validations that bridge the gap between pristine theoretical constructs and the heterogeneity inherent in real-world process environments.

 

References

Revise and standardize the references in accordance with current guidelines.

 

Figures

I recommend enhancing the graphical quality and resolution of the figures particularly Figure 5 to ensure clearer visualization and improved interpretability of the data presented.

 

 

Author Response

Summary

Dehydroxylation of kaolinite: evaluation of activation energy by thermogravimetric analysis and density functional theory insights

The subject matter of the article is highly relevant and engaging; however, certain refinements are necessary to enhance its overall clarity and scientific rigor.

 

Response

Thank you very much for taking the time to review this manuscript and for your positive feedback. Please find the detailed responses to your comments below.

 

Comments 1. Abstract

Include quantitative validation of DFT results against experimental Ea values with error bars or confidence intervals. Clarify the choice of kinetic models with references to model discrimination criteria

 

Response 1.

We have improved the Abstract considering your comments. In particular, now the last part clarifies the validation of DFT against the experimental Ea values: ‘The mechanism and kinetic parameters were evaluated from a series of thermogravimetric measurements. Non-isothermal kinetic analysis reveals that dehydroxylation follows a third-order (F3) reaction mechanism, with activation energies (Ea) ranging from 35 to 60 kcal/mol. Additionally, theoretical calculations based on Density Functional Theory were performed on four systems in which a water molecule is removed by combining OH group and H atom vacancies in the kaolinite unit cell. These models represent the onset of dehydroxylation and provide values for the reaction energy Q from first-principles, which serve as reference values for Ea. The results confirm that water molecule formation involving both OH at the kaolinite outer surface and inner surface are energetically competitive and highlight the crucial role of structural relaxations following water removal to determine Q values in the range 30-50 kcal/mol, in very good agreement with the experiments’ (lines 5-16).

 

Comments 2. Keywords: Add Density functional theory and metakaolin

Response 2. We have included the suggested keywords.

 

Comments 3. Introduction

Reduce verbosity by consolidating overlapping discussions on process complexity and kinetic variability.

 

Response 3.

We have revised the Introduction section as suggested, and we have performed some reductions. In the previous version we said ‘Therefore, different approaches to the study of the dehydroxylation kinetics have been reported. A common experimental approach to study dehydroxylation is through thermogravimetric analysis..’ . Now, the last part was replaced by ‘A common one is through thermogravimetric analysis ...’ (see lines 45-47).

 

Comments 4. Clarify Novelty: Explicitly state how the proposed methodology advances beyond existing experimental and DFT studies.

 

Response 4.

We have rewritten the last paragraph of the Introduction section to clarify novelty and advances:

‘… the aim of this work is to analyse the transformation of kaolinite into metakaolin using a methodology that combines experiments and theoretical calculations based on DFT. Experimentally, thermogravimetric techniques are used in order to assess the activation energy for two kaolinite samples: a well-crystallized reference and a locally sourced industrial kaolin. This selection aims to underscore the contrast between a well-characterized standard kaolinite and an industrial-grade material, whose composition, including secondary minerals, realistically reflects the heterogeneous nature of kaolins encountered in practical applications. Due to the complexity of the dehydroxylation process, special attention is paid to its early stages, as these are crucial for accurately describing the phenomenon. On the other hand, DFT is used to assess the reaction energy involved when a water molecule is extracted from the kaolinite structure. Four distinct cases were considered for the formation of a single water molecule by combining species within the kaolinite lattice. The resulting energies provide first-principles benchmarks for idealized structures, advancing beyond previous studies by enabling a direct comparison with experimental activation energies. The DFT predictions deepens the mechanistic understanding of kaolinite dehydroxylation and complement the experimental kinetic analyses’ (lines 65-81).

 

Comments 5. Materials and Methods

To enhance the practical relevance of this study, a value-oriented narrative is integrated, emphasizing how the comparative analysis of kaolin samples informs strategic decision-making for industrial upgrading pathways and model-based dehydroxylation process design. This work hypothesizes that the elevated quartz content and reduced hydroxyl index (HI) observed in the SRB sample will result in distinctive kinetic profiles during thermal activation. These differences are expected to influence its reactivity and suitability for high-performance applications such as advanced ceramics or pozzolanic binders.

 

Response 5.

We have taken into account this comment, and we also tried to avoid unnecessary repetitions. So, in the revised manuscript we have rewritten the following text in the starting part of Materials and methods section: ‘‘Table 1 summarizes the chemical and mineralogical composition of both samples. KGa-1 contains more than 90 wt.% kaolinite, while SRB shows a significant amount of quartz (22 wt.%), which results in a higher SiO2 content compared to KGa-1. This compositional contrast between the selected materials serves as a basis for comparative analysis and may contribute to strategic decisions in industrial upgrading pathways’’ (see lines 87-91).

We think that there are also other parts in the article that deal with this issue. For example this previously mentioned: ‘This selection aims to underscore the contrast between a well-characterized standard kaolinite and an industrial-grade material, whose composition, including secondary minerals, realistically reflects the heterogeneous nature of kaolins encountered in practical applications’ (lines 69-72). Also, in the results: ‘Since industrial kaolins often contain accessory minerals or are mixed with other raw materials, these results highlight the value of assessing Ea in detail and point to the possibility of tuning the thermal response through material formulation’ (lines 233-236). This line of analysis is also addressed in the conclusions, see lines 346-361.

 

Comments 6. A SWOT-style comparison elucidates the strengths, weaknesses, opportunities, and threats associated with each sample. For instance, while SRB’s higher quartz content may reduce reactivity (a potential weakness), it could offer processing advantages in composite formulations requiring structural rigidity (an opportunity). Conversely, the RB sample’s higher HI and lower quartz content suggest enhanced reactivity but may necessitate more stringent control during calcination to prevent over-dehydroxylation. These insights are positioned within a broader industrial and technological roadmap. Specifically, the findings contribute to the rational design of performance-graded metakaolins and support the development of AI-augmented thermochemical process optimization frameworks. By aligning academic analysis with industrial deployment potential, this approach fosters a more predictive and application-oriented perspective on kaolin thermal transformation.

 

Response 6.

Considering this comment, we have included the following brief paragraph at the end of the experimental part of the results: ‘Finally, the experimental Ea values reveal a nuanced balance between compositional complexity and the structural order of the kaolinite phase: despite SRB presents higher quartz content, its lower crystallinity leads to enhanced reactivity (a potential strength). However, the presence of accessory minerals may still pose challenges for achieving consistent product properties during thermal processing (a potential weakness)’ (lines 280-284).

 

Comments 7. Results

This study exemplifies methodological excellence through systematic kinetic modeling, rigorous thermogravimetric (TG) analysis, and cross-validation with independent mineralogical datasets. It significantly advances the current understanding of kaolinite thermal reactivity by:

Differentiating kaolins of varying structural order through distinct thermal decomposition signatures, Identifying a predominant kinetic regime (F3 model) consistently applicable across compositional variants, Correlating microstructural parameters—such as crystallinity and impurity load—with observed kinetic behavior, Highlighting analytical constraints and proposing refined thermal analysis protocols for enhanced resolution and reproducibility.

These insights establish a robust technical basis for the customized thermal processing of naturally occurring kaolins, with direct implications for the development of next-generation materials ranging from catalytic supports to geopolymers and pozzolanic binders. In such applications, the extent of dehydroxylation and the trajectory of structural evolution are pivotal determinants of end-use performance. This work thus paves the way for more predictive, composition-specific thermal activation strategies within high-value industrial domains.

 

Response 7.

Thank you very much for all this positive feedback.

 

Comments 8. Conclusion

The conclusion presents a methodologically sound and strategically articulated synthesis, effectively showcasing the power of integrating analytical techniques with atomistic simulations to unravel complex solid-state transformation phenomena. Nonetheless, the extrapolation of these findings to industrial-grade, impurity-rich kaolins remains limited by the idealized nature of the theoretical models. To enhance translational relevance, future investigations should prioritize the development of more representative computational frameworks and complementary experimental validations that bridge the gap between pristine theoretical constructs and the heterogeneity inherent in real-world process environments.

 

Response 8.

Thank you very much for the positive feedback. We are now performing a more in-depth computational analysis on kaolinite dehydroxylation considering transition state calculations as a way to reduce this gap you mention. Nevertheless, such analysis involves additional methodologies, are computationally more expensive, and likely will result in a more extensive and practically entirely theoretical publication. This is commented in our manuscript to some extent: ‘further work is needed to assess the kinetic feasibility of the associated atomic diffusion steps, where barriers related to atomic diffusion through the Al sheet to the interlayer may be expected. These studies are currently underway and will be presented in a future publication’ (lines 333-336).

 

Comments 9. References

Revise and standardize the references in accordance with current guidelines.

 

Response 9.

We have revised following the journal guidelines and corrected some formatting errors.

Comments 10. Figures

I recommend enhancing the graphical quality and resolution of the figures particularly Figure 5 to ensure clearer visualization and improved interpretability of the data presented.

 

Response 10.

We have improved figures by including more major and minor ticks. In the case of Figure 5, we have also performed changes for a clearer visualization of the data (we changed scale limits and now use smaller points for the different sets of data).

Reviewer 4 Report

Comments and Suggestions for Authors

Report

In the article, entitled “Dehydroxylation of kaolinite: evaluation of activation energy by thermogravimetric analysis and density functional theory insights,” the authors have examined the dehydroxylation process in two kaolinite samples employing thermogravimetric techniques and theoretical calculations. The authors' findings suggest that dehydroxylation follows a third-order reaction mechanism, and the activation energy depends on the structure of kaolinite as well as heating rate.

The manuscript is well written, and the observed results support the conclusion. I have a few comments that authors may consider addressing.

Comments:

• Did the authors use the samples as they are, or were they dried to remove adsorbed water molecules before performing the TG experiments? If any preprocessing or cleaning methods were performed before the measurements, the authors should consider mentioning that in section 2 of the manuscript.
• Can authors provide the mass spectrum of gases evolved during TG analysis? A mass spectrum would be helpful to characterize and quantify the gases released during TG measurements.
• In Figure 4, the temperature axis shows only two major ticks. I suggest that authors include a decent number of major and minor ticks in the temperature scale for a better data representation.
• The dehydroxylation reaction rate curves for KGa-1 (Figure 4c) show small shoulder peaks between 600 and 700 °C; on the other hand, this peak is absent for SRB. Authors should consider explaining the origin of this shoulder peak in Figure 4c.
• Authors should consider including the error bars in Figures 6a-b.
• It is interesting to see that activation energy increases with the increase in the heating rate. Furthermore, the change in the dehydroxylation activation energy for the SRB sample is more significant with the change in the heating rate compared to KGa-1. The authors provided some explanation to justify this phenomenon. However, a more thorough investigation using spectroscopic tools is required to fully understand this thermal response. Can authors perform in situ FTIR or Raman spectroscopy? Can water adsorbed on the surface or present in the interlayers facilitate proton transfer at a lower heating rate?
• I suggest that authors provide the geometrical coordinates of the calculated structures in the supporting information.

Comments for author File: Comments.pdf

Author Response

Summary

In the article, entitled “Dehydroxylation of kaolinite: evaluation of activation energy by thermogravimetric analysis and density functional theory insights,” the authors have examined the dehydroxylation process in two kaolinite samples employing thermogravimetric techniques and theoretical calculations. The authors' findings suggest that dehydroxylation follows a third-order reaction mechanism, and the activation energy depends on the structure of kaolinite as well as heating rate.

The manuscript is well written, and the observed results support the conclusion. I have a few comments that authors may consider addressing.

 

Response

Thank you very much for taking the time to review this manuscript and for your positive feedback. Please find the detailed responses to your comments below.

 

Comments 1. Did the authors use the samples as they are, or were they dried to remove adsorbed water molecules before performing the TG experiments? If any preprocessing or cleaning methods were performed before the measurements, the authors should consider mentioning that in section 2 of the manuscript.

 

Response 1.

Samples were analyzed without preprocessing. Figure 4 shows that they dry during the TG experiments, which is also commented in the text: ‘Up to 150 °C, a drying process takes place in which the water adsorbed on the sample is released, with a mass loss of about 1-2 wt.%.’ (lines 167-169).

 

Comments 2. Can authors provide the mass spectrum of gases evolved during TG analysis? A mass spectrum would be helpful to characterize and quantify the gases released during TG measurements.

 

Response 2.

Sorry but we do not have such equipment. However, we think that including such mass spectra may deviate the work from the proposed objectives. In the literature we found that Heide and Földvari (2006) have performed mass spectrometric gas-release studies in KGa-1 ( dx.doi.org/10.1016/j.tca.2006.05.011). They tracked the release of water and other secondary species (H2, CO2 and hydrocarbon fragments) during kaolinite dehydroxylation. The main mass loss is due to the release of water, but they also detected hydrogen and also an indication of CO2 fixation in the structure.

Comments 3. In Figure 4, the temperature axis shows only two major ticks. I suggest that authors include a decent number of major and minor ticks in the temperature scale for a better data representation.

 

Response 3.

We apologize for this flaw. In the revised manuscript we have improved all figures to include a more decent number of major and minor ticks, as indicated.

 

Comments 4. The dehydroxylation reaction rate curves for KGa-1 (Figure 4c) show small shoulder peaks between 600 and 700 °C; on the other hand, this peak is absent for SRB. Authors should consider explaining the origin of this shoulder peak in Figure 4c.

 

Response 4.

Such shoulder peaks correspond to KGa-1 and high heating rates, and are not present in SRB. So, we think that they should be related to the purity and crystallinity of KGa-1 compared to SRB. In KGa-1 high heating rates promote the kaolinite delamination (see the reference of Ptáček et al (2014)), which occurs simultaneously with its dehydroxylation, modifying the rate of the last. On the contrary, SRB is composed of a less crystalline kaolinite (as observed through the Hinckley index), accompanied by a significant amount of quartz, so the delamination is less evident for this kaolin using the same heating rates.

In the revised version of our manuscript we included and explanation in this line, using the following text: ‘Finally, for high heating rates, the reaction rate curve for KGa-1 (Figure 4c) shows a small shoulder peak between 600 and 700 °C, which is absent in SRB (Figure 4f). This feature is likely related to the higher crystallinity and purity of KGa-1, where delamination processes promoted at elevated heating rates may locally overlap with dehydroxylation [19], slightly modifying the reaction profile. Given their subtle nature, these shoulders are considered a secondary feature in the overall kinetic analysis, but they suggest the use of low heating rates to more accurately track kaolinite dehydroxylation’ (lines 190-197).

 

Comments 5. Authors should consider including the error bars in Figures 6a-b.

Response 5.

Error bars are included but are small and practically indistinguishable in the scale of the graph. We now clarify this in the figure caption by including the following text: ‘Error bars are inside the dots.’

 

Comments 6. It is interesting to see that activation energy increases with the increase in the heating rate. Furthermore, the change in the dehydroxylation activation energy for the SRB sample is more significant with the change in the heating rate compared to KGa-1. The authors provided some explanation to justify this phenomenon. However, a more thorough investigation using spectroscopic tools is required to fully understand this thermal response. Can authors perform in situ FTIR or Raman spectroscopy? Can water adsorbed on the surface or present in the interlayers facilitate proton transfer at a lower heating rate?

 

Response 6

Sorry but we do not have the equipment to apply such spectroscopies in situ. Considering your comment, we included the following text: ‘A more thorough investigation using other experimental techniques may provide additional insights to fully understand the thermal response at these higher heating rates’ (see lines 277-279).

On the other hand, regarding the question if adsorbed water facilitates proton transfer at low heating rates, there is evidence that points in this direction. Temuujin et al. (1998) have studied the effect of water vapour on the thermal transformation of kaolinite using different experimental techniques, including FTIR, and found that water vapour atmospheres enhance the dehydroxylation of kaolinite to form metakaolinite. Nahdi et al. (2002) have also studied kaolinite dehydroxylation as a function of water vapour pressure, and found that activation energy decreases as the water vapour pressure increases. Nevertheless, the mechanisms to understand this observed effect are still not thoroughly established, especially their dependence with the heating rate. Both investigations are now cited in our manuscript in the introduction section.

 

Comments 7. I suggest that authors provide the geometrical coordinates of the calculated structures in the supporting information.

 

Response 7.

We have created a supplementary materials file with all the structural data of the calculated systems. We have also included in the main document the following text: ‘The obtained internal atomic coordinates are provided as supplementary material’ (lines 288-289).

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The authors' response does not answer the key questions raised by the reviewer. Therefore, the major issues highlighted in the previous review report remain unresolved.

 

 

Reviewer 2 Report

Comments and Suggestions for Authors

Authors did not cite the reviewer's suggested references.

Reviewer 3 Report

Comments and Suggestions for Authors

Accept in present form