Crystal Prediction via Genetic Algorithms in a Model Chiral System

Nikolai D. Petsev, Arash Nikoubashman, Folarin Latinwo, Frank H. Stillinger, Pablo G. Debenedetti

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Chiral crystals and their constituent molecules play a prominent role in theories about the origin of biological homochirality and in drug discovery, design, and stability. Although the prediction and identification of stable chiral crystal structures is crucial for numerous technologies, including separation processes and polymorph selection and control, predictive ability is often complicated by a combination of many-body interactions and molecular complexity and handedness. In this work, we address these challenges by applying genetic algorithms to predict the ground-state crystal lattices formed by a chiral tetramer molecular model, which we have previously shown to exhibit complex fluid-phase behavior. Using this approach, we explore the relative stability and structures of the model's conglomerate and racemic crystals, and present a structural phase diagram for the stable Bravais crystal types in the zero-temperature limit.

Original languageEnglish (US)
Pages (from-to)7771-7780
Number of pages10
JournalJournal of Physical Chemistry B
Issue number39
StatePublished - Oct 6 2022

All Science Journal Classification (ASJC) codes

  • Materials Chemistry
  • Surfaces, Coatings and Films
  • Physical and Theoretical Chemistry


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