Exploring the structural stability, thermal and mechanical properties of nanoporous carbon nitride nanosheets using a transferrable machine learning interatomic potential

HIGHLIGHTS

• What: The authors employed the twostep passive training approach , which provides a robust method for evaluating mechanical and thermal properties with the MTP model (for technical details, refer to the supporting information of Ref ). The last two lattices, hexaazatrinaphthylene-graphdiyne (HATN-GDY) and vinylidene-linked framework (V-COF) have been very recently synthesized, and the predicted lattice constant of the geometry optimized lattices by the developed MTP in this study shows less than 1% difference with those obtained by DFT method. The study demonstrates how the transferable MLIP facilitates the analysis of stability, thermal, and mechanical properties . . .
  

   

  

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