Determining interchromophore effects for energy transport in molecular networks using machine-learning algorithms.
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| Title: | Determining interchromophore effects for energy transport in molecular networks using machine-learning algorithms. |
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| Authors: | Rolczynski BS; Electronics Science and Technology Division, Code 6800, U.S. Naval Research Laboratory, Washington, DC 20375, USA. brian.rolczynski@nrl.navy.mil., Díaz SA; Center for Bio/Molecular Science and Engineering, Code 6900, U.S. Naval Research Laboratory, Washington, DC 20375, USA., Kim YC; Materials Science and Technology Division, Code 6300, U.S. Naval Research Laboratory, Washington, DC 20375, USA., Mathur D; Department of Chemistry, Case Western Reserve University, Cleveland, OH 44106, USA., Klein WP; Center for Bio/Molecular Science and Engineering, Code 6900, U.S. Naval Research Laboratory, Washington, DC 20375, USA., Medintz IL; Center for Bio/Molecular Science and Engineering, Code 6900, U.S. Naval Research Laboratory, Washington, DC 20375, USA., Melinger JS; Electronics Science and Technology Division, Code 6800, U.S. Naval Research Laboratory, Washington, DC 20375, USA. brian.rolczynski@nrl.navy.mil. |
| Source: | Physical chemistry chemical physics : PCCP [Phys Chem Chem Phys] 2023 Feb 01; Vol. 25 (5), pp. 3651-3665. Date of Electronic Publication: 2023 Feb 01. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Royal Society of Chemistry Country of Publication: England NLM ID: 100888160 Publication Model: Electronic Cited Medium: Internet ISSN: 1463-9084 (Electronic) Linking ISSN: 14639076 NLM ISO Abbreviation: Phys Chem Chem Phys Subsets: MEDLINE; PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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