eprintid: 10204490
rev_number: 9
eprint_status: archive
userid: 699
dir: disk0/10/20/44/90
datestamp: 2025-02-11 13:17:33
lastmod: 2025-02-11 13:17:33
status_changed: 2025-02-11 13:17:33
type: article
metadata_visibility: show
sword_depositor: 699
creators_name: Li, Zhendong
creators_name: Hernández, Federico J
creators_name: Salguero, Christian
creators_name: Lopez, Steven A
creators_name: Crespo-Otero, Rachel
creators_name: Li, Jingbai
title: Machine learning photodynamics decode multiple singlet fission channels in pentacene crystal
ispublished: pub
divisions: UCL
divisions: B04
divisions: C06
divisions: F56
note: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
abstract: Crystalline pentacene is a model solid-state light-harvesting material because its quantum efficiencies exceed 100% via ultrafast singlet fission. The singlet fission mechanism in pentacene crystals is disputed due to insufficient electronic information in time-resolved experiments and intractable quantum mechanical calculations for simulating realistic crystal dynamics. Here we combine a multiscale multiconfigurational approach and machine learning photodynamics to understand competing singlet fission mechanisms in crystalline pentacene. Our simulations reveal coexisting charge-transfer-mediated and coherent mechanisms via the competing channels in the herringbone and parallel dimers. The predicted singlet fission time constants (61 and 33 fs) are in excellent agreement with experiments (78 and 35 fs). The trajectories highlight the essential role of intermolecular stretching between monomers in generating the multi-exciton state and explain the anisotropic phenomenon. The machine-learning-photodynamics resolved the elusive interplay between electronic structure and vibrational relations, enabling fully atomistic excited-state dynamics with multiconfigurational quantum mechanical quality for crystalline pentacene.
date: 2025-01-30
date_type: published
publisher: Springer Science and Business Media LLC
official_url: https://doi.org/10.1038/s41467-025-56480-y
oa_status: green
full_text_type: pub
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 2357500
doi: 10.1038/s41467-025-56480-y
medium: Electronic
pii: 10.1038/s41467-025-56480-y
lyricists_name: Crespo Otero, Rachel
lyricists_id: RCRES48
actors_name: Crespo Otero, Rachel
actors_id: RCRES48
actors_role: owner
funding_acknowledgements: 22303053 [National Natural Science Foundation of China (National Science Foundation of China)]; NSF-CHE-2144556 [National Science Foundation (NSF)]; G00006360 [Massachusetts Life Sciences Center (MLSC)]; RPG-2019-122 [Leverhulme Trust]; EP/R029385/1 [RCUK | Engineering and Physical Sciences Research Council (EPSRC)]; IES\R2\222057 [Royal Society]
full_text_status: public
publication: Nature Communications
volume: 16
article_number: 1194
event_location: England
issn: 2041-1723
citation:        Li, Zhendong;    Hernández, Federico J;    Salguero, Christian;    Lopez, Steven A;    Crespo-Otero, Rachel;    Li, Jingbai;      (2025)    Machine learning photodynamics decode multiple singlet fission channels in pentacene crystal.                   Nature Communications , 16     , Article 1194.  10.1038/s41467-025-56480-y <https://doi.org/10.1038/s41467-025-56480-y>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10204490/1/Crespo%20Otero_s41467-025-56480-y.pdf