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February 11, 2026The Journal of Physical Chemistry Letters0 citations

Efficient Monte Carlo Simulation of Faceted Nanoparticles Using Analytical Interaction Potentials

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ŞÇŞafak ÇallıoğluQYQuanpeng YangYSYuanchuan Shao

Key Points

  • This research aims to model the self-assembly of faceted nanoparticles using efficient Monte Carlo simulations.
  • Developed a simulation framework incorporating analytical potentials for interactions.
  • Implemented virtual cluster moves to enhance sampling and account for diffusion.
  • Conducted phase behavior calculations under varying interparticle attractions.
  • Simulations using analytical potentials are significantly faster than traditional models.
  • Attraction between nanoparticles improves ordering at lower volume fractions.
  • Transitions from isotropic to semiordered phases are influenced by attractive forces.

Abstract

Understanding how energetic interactions between faceted nanoparticles (NPs) drive their self-assembly into higher-order architectures is critical for controlling various properties of NP assemblies. Here, we integrate analytical potentials that capture orientation-dependent van der Waals interactions into a Monte Carlo simulation framework for fast and accurate modeling of NP self-assembly. By implementing virtual cluster moves in the framework, we overcome sampling limitations and account for size-dependent diffusion of clusters. Simulations using the analytical potentials are orders of magnitude faster than atomistic and coarse-grained models while producing correct assembly morphologies. Phase behavior calculations of faceted NPs with weak and strong interparticle attractions show that attraction enhances ordering and shifts isotropic-to-semiordered transitions to lower volume fractions, while semiordered-to-crystalline transitions remain largely entropy driven. Overall, this work highlights the importance of enthalpic interactions and the advantages of using analytical potentials for efficient simulations of faceted NPs.

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Cite This Study

Çallıoğlu et al. (2026) studied this question.

synapsesocial.com/papers/698c1c22267fb587c655e579https://doi.org/10.1021/acs.jpclett.5c04083
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