From crystal structure prediction to polymorphic behaviour: Monte Carlo threshold mapping of crystal energy landscapes
From crystal structure prediction to polymorphic behaviour: Monte Carlo threshold mapping of crystal energy landscapes
Crystal structure prediction has developed into a valuable tool for anticipating the likely crystalline arrangement that a molecule will adopt, with applications in materials discovery and polymorph screening. Although powerful, crystal structure prediction is usually limited to locating the local minima of the crystal energy surface. We demonstrate how, by mapping the energy barriers between structures, applying the Monte Carlo threshold algorithm provides a richer description of the crystal energy landscape which allows us to rationalize the differences in experimental conditions under which different crystal polymorphs are observed. As a demonstration, we apply the method to three polymorphic polycyclic aromatic hydrocarbons, phenanthrene, pyrene, and perylene.
crystal structure prediction, polymorphism, computational chemistry, energy landscapes
Juan Royo, Pedro
394ccb72-0cde-47e5-a9ee-7f32bfc56602
Day, Graeme M.
e3be79ba-ad12-4461-b735-74d5c4355636
Juan Royo, Pedro
394ccb72-0cde-47e5-a9ee-7f32bfc56602
Day, Graeme M.
e3be79ba-ad12-4461-b735-74d5c4355636
Juan Royo, Pedro and Day, Graeme M.
(2026)
From crystal structure prediction to polymorphic behaviour: Monte Carlo threshold mapping of crystal energy landscapes.
Chemical Science.
(doi:10.1039/D5SC08644B).
Abstract
Crystal structure prediction has developed into a valuable tool for anticipating the likely crystalline arrangement that a molecule will adopt, with applications in materials discovery and polymorph screening. Although powerful, crystal structure prediction is usually limited to locating the local minima of the crystal energy surface. We demonstrate how, by mapping the energy barriers between structures, applying the Monte Carlo threshold algorithm provides a richer description of the crystal energy landscape which allows us to rationalize the differences in experimental conditions under which different crystal polymorphs are observed. As a demonstration, we apply the method to three polymorphic polycyclic aromatic hydrocarbons, phenanthrene, pyrene, and perylene.
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d5sc08644b
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Accepted/In Press date: 8 January 2026
e-pub ahead of print date: 12 January 2026
Keywords:
crystal structure prediction, polymorphism, computational chemistry, energy landscapes
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Local EPrints ID: 509094
URI: http://eprints.soton.ac.uk/id/eprint/509094
ISSN: 1478-6524
PURE UUID: 19a56a60-b8ba-4bac-8077-547ebc80b2d9
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Date deposited: 11 Feb 2026 17:36
Last modified: 12 Feb 2026 03:26
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Author:
Pedro Juan Royo
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