Toward Prediction of Nonradiative Decay Pathways in Organic Compounds I: The Case of Naphthalene Quantum Yields
Many 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 syst...
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| Format: | Article |
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American Chemical Society (ACS)
2020
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| Online Access: | https://hdl.handle.net/1721.1/128158 |
| _version_ | 1826213424545136640 |
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| author | Kohn, Alexander Wolfe Lin, Zhou Van Voorhis, Troy |
| author2 | Massachusetts Institute of Technology. Department of Chemistry |
| author_facet | Massachusetts Institute of Technology. Department of Chemistry Kohn, Alexander Wolfe Lin, Zhou Van Voorhis, Troy |
| author_sort | Kohn, Alexander Wolfe |
| collection | MIT |
| description | Many 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. |
| first_indexed | 2024-09-23T15:48:52Z |
| format | Article |
| id | mit-1721.1/128158 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T15:48:52Z |
| publishDate | 2020 |
| publisher | American Chemical Society (ACS) |
| record_format | dspace |
| spelling | mit-1721.1/1281582022-10-02T04:17:50Z Toward Prediction of Nonradiative Decay Pathways in Organic Compounds I: The Case of Naphthalene Quantum Yields Kohn, Alexander Wolfe Lin, Zhou Van Voorhis, Troy Massachusetts Institute of Technology. Department of Chemistry Many 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. US Department of Energy, Office of Basic Energy Sciences (Grant DE-FG02-07ER46474) 2020-10-23T15:26:47Z 2020-10-23T15:26:47Z 2019-06 2019-05 Article http://purl.org/eprint/type/JournalArticle 1932-7447 1932-7455 https://hdl.handle.net/1721.1/128158 Kohn, 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 Society http://dx.doi.org/10.1021/acs.jpcc.9b01243 Journal of Physical Chemistry C Article 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. application/pdf American Chemical Society (ACS) Prof. Van Voorhis |
| spellingShingle | Kohn, Alexander Wolfe Lin, Zhou Van Voorhis, Troy Toward Prediction of Nonradiative Decay Pathways in Organic Compounds I: The Case of Naphthalene Quantum Yields |
| title | Toward Prediction of Nonradiative Decay Pathways in Organic Compounds I: The Case of Naphthalene Quantum Yields |
| title_full | Toward Prediction of Nonradiative Decay Pathways in Organic Compounds I: The Case of Naphthalene Quantum Yields |
| title_fullStr | Toward Prediction of Nonradiative Decay Pathways in Organic Compounds I: The Case of Naphthalene Quantum Yields |
| title_full_unstemmed | Toward Prediction of Nonradiative Decay Pathways in Organic Compounds I: The Case of Naphthalene Quantum Yields |
| title_short | Toward Prediction of Nonradiative Decay Pathways in Organic Compounds I: The Case of Naphthalene Quantum Yields |
| title_sort | toward prediction of nonradiative decay pathways in organic compounds i the case of naphthalene quantum yields |
| url | https://hdl.handle.net/1721.1/128158 |
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