Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/152203
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dc.contributor.authorBowal, Kimberlyen_US
dc.contributor.authorGrančič, Peteren_US
dc.contributor.authorMartin, Jacob W.en_US
dc.contributor.authorKraft, Markusen_US
dc.date.accessioned2021-07-22T01:57:38Z-
dc.date.available2021-07-22T01:57:38Z-
dc.date.issued2019-
dc.identifier.citationBowal, K., Grančič, P., Martin, J. W. & Kraft, M. (2019). Sphere encapsulated Monte Carlo : obtaining minimum energy configurations of large aromatic systems. The Journal of Physical Chemistry A, 123(33), 7303-7313. https://dx.doi.org/10.1021/acs.jpca.9b04821en_US
dc.identifier.issn1089-5639en_US
dc.identifier.urihttps://hdl.handle.net/10356/152203-
dc.description.abstractWe introduce a simple global optimization approach that is able to find minimum energy configurations of clusters containing aromatic molecules. The translational and rotational perturbations required in Monte Carlo-based methods often lead to unrealistic configurations within which two or more molecular rings intersect, causing many of the computational steps to be rejected and the optimization process to be inefficient. Here we develop a modification of the basin-hopping global optimization procedure tailored to tackle problems with intersecting molecular rings. Termed the Sphere Encapsulated Monte Carlo (SEMC) method, this method introduces sphere-based rearrangement and minimization steps at each iteration, and its performance is shown through the exploration of potential energy landscapes of polycyclic aromatic hydrocarbon (PAH) clusters, systems of interest in combustion and astrophysics research. The SEMC method provides clusters that are accurate to 5% mean difference of the minimum energy at a 10-fold speed up compared to previous work using advanced molecular dynamics simulations. Importantly, the SEMC method captures key structural characteristics and molecular size partitioning trends as measured by the molecular radial distances and coordination numbers. The advantages of the SEMC method are further highlighted in its application to previously unstudied heterogeneous PAH clusters.en_US
dc.description.sponsorshipNational Research Foundation (NRF)en_US
dc.language.isoenen_US
dc.relation.ispartofThe Journal of Physical Chemistry Aen_US
dc.rightsThis document is the Accepted Manuscript version of a Published Work that appeared in final form in The Journal of Physical Chemistry A, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/acs.jpca.9b04821.en_US
dc.subjectEngineering::Chemical engineeringen_US
dc.titleSphere encapsulated Monte Carlo : obtaining minimum energy configurations of large aromatic systemsen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Chemical and Biomedical Engineeringen_US
dc.contributor.organizationCambridge Centre for Advanced Research and Education in Singapore (CARES)en_US
dc.identifier.doi10.1021/acs.jpca.9b04821-
dc.description.versionAccepted versionen_US
dc.identifier.pmid31339720-
dc.identifier.scopus2-s2.0-85070919418-
dc.identifier.issue33en_US
dc.identifier.volume123en_US
dc.identifier.spage7303en_US
dc.identifier.epage7313en_US
dc.subject.keywordsOptimizationen_US
dc.subject.keywordsEnergyen_US
dc.description.acknowledgementThis project was supported by the National Research Foundation (NRF), Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) program. K.B. is grateful to the Cambridge Trust and the Stanley Studentship at King’s College, Cambridge for their financial support. M.K. gratefully acknowledges the support of the Alexander von Humboldt foundation.en_US
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