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Pei et al. J Mater Inf 2023;3:26 https://dx.doi.org/10.20517/jmi.2023.35 Page 11 of 14

CONCLUSIONS
In summary, this study provides a systematic investigation into the potential of C N -loaded TACs in
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electrocatalytic NRR using DFT calculations. Employing a stringent “five-step” filtering strategy, we have
identified TM @C N (TM = Pt, Ru, Re) as highly promising candidates with the attributes of low energy
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cost, high selectivity, remarkable stability (both thermodynamic and kinetic), and remarkably low limiting
potentials (-0.35~-0.11 V). Our analysis of electronic properties highlights that the exceptional NRR activity
can be ascribed to the electron acceptance and donation mechanism involving d-π* interactions. This
mechanism, combined with charge density differences and PDOS, underscores the qualifications of
TM @C N as electrocatalysts. Furthermore, we have explored the linkage between chemical activity and the
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electronic structure of TM @C N surfaces, revealing a pivotal physical parameter that allows precise control
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over the catalytic performance of TM trimer clusters. In conclusion, this work significantly improves our
overall comprehension regarding the stability, activity, and selectivity of TM @C N electrocatalysts.
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Moreover, it provides a valuable methodology for efficiently screening and designing innovative TACs
specifically tailored for NRR. We anticipate that these findings will ignite further exploration and
experimentation, both in theory and practice, aiming to unlock the vast potential of TACs in NRR and its
associated electrochemical reactions.
DECLARATIONS
Authors’ contributions
Made substantial contributions to the conception and design of this article, writing, and editing: Pei W,
Zhang W, Yu X
Made substantial contributions to the collation of literature and writing: Liu Y, Zhou S, Tu Y, Zhao J
Performed data analysis and discussion: Hou L, Xia W, Wang Z

Availability of data and materials
Supplementary materials are available from the Journal of Materials Informatics or from the authors.

Financial support and sponsorship
This work was supported by the National Natural Science Foundation of China (Nos. 12304300, 11974068,
91961204, and 12075201), the Natural Science Foundation of Jiangsu Province (Nos. BK20230555 and
BK20230563), the Natural Science Foundation of Jiangsu Higher Education Institutions of China (No.
23KJB140019), the Fundamental Research Funds for the Central Universities of China (Nos.
DUT20LAB110 and DUT22ZD103), Outstanding Doctor Program of Yangzhou City “Lv Yang Jin Feng”
(No. YZLYJFJH2022YXBSO84), and Open Research Fund of CNMGE Platform & NSCC-TJ
(CNMGE2023007). The authors acknowledge the computer resources provided by the Shanghai
Supercomputer Center.

Conflicts of interest
All authors declared that there are no conflicts of interest.

Ethical approval and consent to participate
Not applicable.