Determining interchromophore effects for energy transport in molecular networks using machine-learning algorithms

Nature uses chromophore networks, with highly optimized structural and energetic characteristics, to perform important chemical functions. Due to its modularity, predictable aggregation characteristics, and established synthetic protocols, structural DNA nanotechnology is a promising medium for arra...

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Veröffentlicht in:	Physical chemistry chemical physics : PCCP 2023-02, Vol.25 (5), p.3651-3665
Hauptverfasser:	Rolczynski, Brian S, Díaz, Sebastián A, Kim, Young C, Mathur, Divita, Klein, William P, Medintz, Igor L, Melinger, Joseph S
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Chromophores Energy transfer Machine learning Modularity Molecular dynamics Networks Optoelectronics Relay
Online-Zugang:	Volltext
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