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Photochemistry with Cyanines in the Near Infrared: A Step to Chemistry 4.0 Technologies
Cyanines covering the absorption in the near infrared (NIR) are attractive for distinct applications. They can interact either with lasers exhibiting line‐shaped focus emitting at both 808 and 980 nm or bright high intensity NIR‐LEDs with 805 nm emission, respectively. This is drawing attention to I...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6851862/ https://www.ncbi.nlm.nih.gov/pubmed/31270883 http://dx.doi.org/10.1002/chem.201901746 |
Sumario: | Cyanines covering the absorption in the near infrared (NIR) are attractive for distinct applications. They can interact either with lasers exhibiting line‐shaped focus emitting at both 808 and 980 nm or bright high intensity NIR‐LEDs with 805 nm emission, respectively. This is drawing attention to Industry 4.0 applications. The major deactivation occurs through a non‐radiative process resulting in the release of heat into the surrounding, although a small fraction of radiative deactivation also takes place. Most of these NIR‐sensitive systems possess an internal activation barrier to react in a photonic process with initiators resulting in the generation of reactive radicals and acidic cations. Thus, the heat released by the NIR absorber helps to bring the system, consisting of an NIR sensitizer and initiator, above such internal barriers. Molecular design strategies making these systems more compatible with distinct applications in a certain oleophilic surrounding are considered as a big challenge. This includes variations of the molecular pattern and counter ions derived from super acids exhibiting low coordinating properties. Further discussion focusses on the use of such systems in Chemistry 4.0 related applications. Intelligent software tools help to improve and optimize these systems combining chemistry, engineering based on high‐throughput formulation screening (HTFS) technologies, and machine learning algorithms to open up novel solutions in material sciences. |
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