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This work was funded by the Ministry of Science and Innovation (Ref. No. PID2021-122516OB-I00). This publication was created as part of NCCR Catalysis (grant number 180544), a National Centre of Competence in Research funded by the Swiss National Science Foundation. We also acknowledge Generalitat de Catalunya and the European Union under Grant 2020_FI_B 00266, 2023-FI-3-00027, and TotalEnergies (contract reference CT00001052). We thank the Barcelona Supercomputing Center (BSC-RES) for providing generous computational resources.

Analysis of institutional authors

Minotaki, Maria GAuthorGeiger, JulianAuthorRuiz-Ferrando, AndreaAuthorSabadell-Rendon, AlbertCorresponding AuthorLopez, NuriaCorresponding Author

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April 28, 2024
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A generalized model for estimating adsorption energies of single atoms on doped carbon materials

Publicated to:Journal Of Materials Chemistry a. 12 (-): 11049-11061 - 2024-03-20 12(-), DOI: 10.1039/d3ta05898k

Authors: Minotaki, Maria G; Geiger, Julian; Ruiz-Ferrando, Andrea; Sabadell-Rendon, Albert; Lopez, Nuria

Affiliations

Inst Chem Res Catalonia ICIQ CERCA, Barcelona Inst Sci & Technol BIST, Av Paisos Catalans 16, Tarragona 43007, Spain - Author
Univ Rovira & Virgili, Tarragona 43007, Spain - Author

Abstract

Single metal atoms on doped carbons constitute a new class of extremely appealing materials, as they present the best metal utilization for catalysis. However, their stability can be compromised by metal aggregation and the formation of nanoparticles, which often results in reduced activity or even catalyst deactivation. In many cases, the carbon hosts are generated via thermal processes, leading to poorly controlled materials. This causes a structural and compositional diversity that is modeled via indirect procedures and by comparison to a collection of structural models with different compositions. Our aim in this work is to develop a general framework based on machine learning techniques to determine the stability of the different structures against aggregation as nanoparticles. Here, we built machine learning models for the cavities and identified the robust features characterizing the metal-support interaction, considering different heteroatoms in the decorative cavity and single metal atoms. The descriptors presented here are accessible and cost-effective, such as the cavity size, electronegativity of the metal and heteroatoms, different covalent radii, and the metal electronic density. These can then be employed in the search for a mathematical equation that describes the adsorption energy via the Bayesian machine scientist. The algorithm is able to separate coordination, and covalent and ionic contributions expressed by the descriptors. This approach paves the way towards general modeling of single atoms in modified carbons particularly addressing one of the crucial features, stability. Single metal atoms on doped carbons constitute a new class of extremely appealing materials, as they present the best metal utilization for catalysis.

Keywords

CatalystsEfficiencyGrapheneIdentificationMetalOxygen reduction

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Journal Of Materials Chemistry a due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2024 there are still no calculated indicators, but in 2023, it was in position 24/178, thus managing to position itself as a Q1 (Primer Cuartil), in the category Chemistry, Physical.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2025-08-28:

  • WoS: 1

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-08-28:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 4.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 4 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 1.25.
  • The number of mentions on the social network X (formerly Twitter): 3 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (Minotaki, Maria) and Last Author (López Alonso, Núria).

the authors responsible for correspondence tasks have been Sabadell Rendón, Albert and López Alonso, Núria.