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dc.contributor.authorKohn, Alexander Wolfe
dc.contributor.authorLin, Zhou
dc.contributor.authorVan Voorhis, Troy
dc.date.accessioned2020-10-23T15:26:47Z
dc.date.available2020-10-23T15:26:47Z
dc.date.issued2019-06
dc.date.submitted2019-05
dc.identifier.issn1932-7447
dc.identifier.issn1932-7455
dc.identifier.urihttps://hdl.handle.net/1721.1/128158
dc.description.abstractMany emerging technologies depend on our ability to control and manipulate the excited-state properties of molecular systems. These technologies include fluorescent labeling in biomedical imaging, light harvesting in photovoltaics, and electroluminescence in light-emitting devices. All of these systems suffer from nonradiative loss pathways that dissipate electronic energy as heat, which causes the overall system efficiency to be directly linked to the quantum yield (Φ) of the molecular excited state. Unfortunately, Φ is very difficult to predict from the first principles because the description of a slow nonradiative decay mechanism requires an accurate description of long-timescale excited-state quantum dynamics. In the present study, we introduce an efficient semi-empirical method of calculating the fluorescence quantum yield (Φfl) for molecular chromophores, which converts simple electronic energies computed using time-dependent density functional theory into an estimate of Φfl. As with all machine learning strategies, the algorithm needs to be trained on fluorescent dyes for which Φfl’s are known, so as to provide a black-box method which can later predict Φ’s for chemically similar chromophores that have not been studied experimentally. As a first illustration of how our proposed algorithm can be trained, we examine a family of 25 naphthalene derivatives. The simplest application of the energy gap law is found to be inadequate to explain the rates of internal conversion (IC) or intersystem crossing (ISC)—the electronic properties of at least one higher lying electronic state (Sn or Tn) or one far-from-equilibrium geometry are typically needed to obtain accurate results. Indeed, the key descriptors turn out to be the transition state between the Franck–Condon minimum and a distorted local minimum near an S1/S0 conical intersection (which governs IC) and the magnitude of the spin–orbit coupling (which governs ISC). The resulting Φfl’s are predicted with reasonable accuracy (±0.22), making our approach a promising ingredient for high-throughput screening and rational design of the molecular excited states with desired Φ’s. We thus conclude that our model, while semi-empirical in nature, does in fact extract sound physical insight into the challenge of describing nonradiative relaxations.en_US
dc.description.sponsorshipUS Department of Energy, Office of Basic Energy Sciences (Grant DE-FG02-07ER46474)en_US
dc.publisherAmerican Chemical Society (ACS)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1021/acs.jpcc.9b01243en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceProf. Van Voorhisen_US
dc.titleToward Prediction of Nonradiative Decay Pathways in Organic Compounds I: The Case of Naphthalene Quantum Yieldsen_US
dc.typeArticleen_US
dc.identifier.citationKohn, Alexander W. et al. "Toward Prediction of Nonradiative Decay Pathways in Organic Compounds I: The Case of Naphthalene Quantum Yields." Journal of Physical Chemistry C 123, 25 (June 2019): 15394–15402 © 2019 American Chemical Societyen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Chemistryen_US
dc.relation.journalJournal of Physical Chemistry Cen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.date.submission2020-10-08T21:37:15Z
mit.journal.volume123en_US
mit.journal.issue25en_US
mit.licensePUBLISHER_POLICY
mit.metadata.statusComplete


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