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Article
Peer-Review Record

Quantum-Chemical Modeling of the Catalytic Activity of Graphene Doped with Metal Phthalocyanines in ORR

Catalysts 2022, 12(7), 786; https://doi.org/10.3390/catal12070786
by Kirill Y. Vinogradov 1, Anzhela V. Bulanova 1,*, Roman V. Shafigulin 1, Elena O. Tokranova 1 and Hong Zhu 2
Reviewer 1: Anonymous
Reviewer 2:
Catalysts 2022, 12(7), 786; https://doi.org/10.3390/catal12070786
Submission received: 29 June 2022 / Revised: 14 July 2022 / Accepted: 15 July 2022 / Published: 18 July 2022
(This article belongs to the Special Issue Advances in Graphene/Nanocomposites for Catalytic Applications)

Round 1

Reviewer 1 Report

 

The authors reported their theoretical investigations using a nanosheet of graphene with H-determinations at the edge as a templet for doping with some transition metals. The geometric configurations of the metal-doped system with/without the adsorbate are exhibited. The free energy profiles of the related doping systems for ORR are plotted and discussed. The authors must consider the following comments before this work could be accepted: 

1.     Keywords are not suitable which cannot be used for efficient retrieval. For instance, doping with transition metals should be mentioned;

2.     There are many typos and mistakes in grammar, e.g., “ The fuel cells is one solutions to this problem.”, “They are silent, have high efficiency and environmentally friendly,……”, “One of the most expensive fuel cell components are……” at very beginning of this manuscript. The English writing should be carefully checked and intensively modified;

3.     The authors used a 0D carbon nanosheet with hydrogen determinations as the model for graphene. However, they didn’t talk about the size effect of the graphene nanosheet. I’m very curious about the choice of this size used in their investigation. If the size of this graphene nanosheet becomes larger, will it affect the conclusion?

4.     The authors used the basis sets 6-31G* for all involved species. However, the validities of these basis sets, especially for the transition metals with d-electrons, must be carefully proved, before any discussion about the physical properties of the related system.

5.     As a conclusion, the authors claimed that the Co-doped graphene is the best one for ORR. However, as they introduced in their text and Fig. 5, the Cr-doped one may be better than the Co-doped system. I’m little confused here. Please make this point clear!

6.     Why does the Co- or Cr-doped system possess the best properties for the ORR? I saw the profiles. But, what are the specific physical reasons for this phenomenon? There should be more discussions with deep physic insights.

 

Author Response

Dear reviewer, thank you very much for the review! We are sending responses to your comments.

 

1. Keywords are not suitable which cannot be used for efficient retrieval. For instance, doping with transition metals should be mentioned;

The list of keywords has been corrected, new keywords have been added.

2. There are many typos and mistakes in grammar, e.g., “ The fuel cells is one solutions to this problem.”, “They are silent, have high efficiency and environmentally friendly,……”, “One of the most expensive fuel cell components are……” at very beginning of this manuscript. The English writing should be carefully checked and intensively modified;

Thank you for the comment. The text has been checked and corrected.

3. The authors used a 0D carbon nanosheet with hydrogen determinations as the model for graphene. However, they didn’t talk about the size effect of the graphene nanosheet. I’m very curious about the choice of this size used in their investigation. If the size of this graphene nanosheet becomes larger, will it affect the conclusion?

The active center of the ORR on the considered structures is a metal atom surrounded by 4 nitrogen atoms. To increase the accuracy of the calculations, the nearest carbon surroundings were added to the model. Further expansion of the nanosheet with other active centers was impractical due to a significant increase in the time required for the calculations. The calculation was performed for the elementary actin.

4. The authors used the basis sets 6-31G* for all involved species. However, the validities of these basis sets, especially for the transition metals with d-electrons, must be carefully proved, before any discussion about the physical properties of the related system.

Before the calculations, several bases were used: 6-31G*, 6-311G** and also pseudopotentials for metals were used. All calculations showed similar energy profiles, but the basis 6-31G* showed the minimum calculation time.

5. As a conclusion, the authors claimed that the Co-doped graphene is the best one for ORR. However, as they introduced in their text and Fig. 5, the Cr-doped one may be better than the Co-doped system. I’m little confused here. Please make this point clear!

Yes, the catalyst containing chromium does exhibit high catalytic activity, comparable to that of cobalt. However, the overpotential on chromium is 0.56 V, while that on cobalt is 0.52 V. From this point of view, the cobalt-containing catalyst is more effective.

6. Why does the Co- or Cr-doped system possess the best properties for the ORR? I saw the profiles. But, what are the specific physical reasons for this phenomenon? There should be more discussions with deep physic insights

The efficiency of the catalyst depends significantly on the overpotential of the reaction: the lower the overpotential, the higher the catalytic activity. The value of the overpotential is determined by the minimum amount of energy released at each stage of the ORR (equation 5). Thus, the best catalyst will be characterized by a uniform energy release, ⅟4 of the total energy release during the reaction. Cobalt- and chromium-containing catalysts meet these conditions most completely.

Reviewer 2 Report

There need to be some basic things fixed before publication.

1) Abdtarct does not provide enough information about the paper.

2) Introduction part is very weak. Identify the research gap and objectives of your research clearly in the last paragraph of the introduction.

3) Ref 12 to 17. Write at least something about the papers.

4) Table 1, only figures, no data reported. Hence it could not be called a table.

5) Fig 4. How the overpotentials are calculated? Its reference?

6) How dispersion corrections are accounted for in the study during simulations?

Author Response

Dear reviewer, thank you very much for the review! We are sending responses to your comments.

 

1) Abdtarct does not provide enough information about the paper.

Thanks for the comment. The abstract has been updated to include more information about the article now.

2) Introduction part is very weak. Identify the research gap and objectives of your research clearly in the last paragraph of the introduction.

The introduction has been expanded.

3) Ref 12 to 17. Write at least something about the papers.

Articles 12-17 were discussed in more detail.

4) Table 1, only figures, no data reported. Hence it could not be called a table.

Table 1 is represented as Figure 1 with the corresponding renumbering of the remaining elements.

5) Fig 4. How the overpotentials are calculated? Its reference?

The overpotential (ηORR) was calculated as follows [22]:

ηORR = 1.20 - min{ΔG1 , ΔG2 , ΔG3 , ΔG4}, (5)

where 1.20 is ¼ of the total free energy change, ΔGi is the free energy change for each stage.

A reference to the calculation formula for overvoltage (Equation 5) has been added to the text.

6) How dispersion corrections are accounted for in the study during simulations?

Thanks for the valuable observation. The keywords calculating dispersion corrections (like "EmpiricalDispersion") were not used. But in future work this correction will be taken into account.

Round 2

Reviewer 1 Report

The authors have revised their manuscript by fully considering my comments. Therefore, I recommend publishing this article in its current form.

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