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April 26, 2026ACS Applied Materials & Interfaces0 citations

Density–Energy Balanced Selection of Chiral Honeycomb Superstructures from Deprotonated Carboxylate Molecules on Ag(111)

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SCShenwei ChenHWHaiwei WangXZXi Zhang

Key Points

  • The research aims to explore the self-assembly process of specific molecular compounds on a surface and the resulting periodic structures formed.
  • Utilized scanning tunneling microscopy to observe molecular self-assembly on Ag(111) surface.
  • Evaluated the effects of annealing and molecular coverage on the formation of periodic honeycomb structures.
  • Developed an analytical model assessing molecular density and intermolecular binding energy contributions.
  • Identified the thermodynamically favored states HC4 and HC5 at near-equilibrium conditions.
  • Demonstrated that the ground state under fixed density conditions results in the coexistence of two adjacent honeycomb phases HC(N) and HC(N+1).
  • Provided a thermodynamic framework for controlling surface-confined supramolecular networks.

Abstract

Here, we investigate the self-assembly of 4,4',4″-(1,3,3a1,4,6,7,9-heptaazaphenalene-2,5,8-triyl) tribenzoic acid on Ag(111) by scanning tunneling microscopy. Upon annealing, complete deprotonation drives the formation of a family of periodic honeycomb superstructures, denoted as HCN (N = 1-8), which are composed of triangular molecular sublattices and exhibit pronounced organizational chirality. By controlling the molecular coverage and annealing conditions, we identify the coexistence of HC4 and HC5 as the thermodynamically favored state near equilibrium. An analytical model incorporating the coupled contributions of molecular density and average intermolecular binding energy, supported by a rigorous convexity-based analysis, demonstrates that the ground state under a fixed density constraint corresponds to the coexistence of two adjacent HCN and HCN+1 phases. These results provide a unified thermodynamic framework for understanding and controlling surface-confined supramolecular networks.

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Cite This Study

Chen et al. (2026) studied this question.

synapsesocial.com/papers/69edabb84a46254e215b3a42https://doi.org/10.1021/acsami.5c25893
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