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Exploring New Azobenzene Type Photoswitches by Machine Learning with Lowest Possible Fluorescence Excitons with Ease of Synthesis.

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Title: Exploring New Azobenzene Type Photoswitches by Machine Learning with Lowest Possible Fluorescence Excitons with Ease of Synthesis.
Authors: Waheeb, Azal S.1,2 (AUTHOR), Hasan, Duha M.1 (AUTHOR), Mallah, Shaimaa H.1 (AUTHOR), Sumrra, Sajjad H.3 (AUTHOR) sajjadchemist@uog.edu.pk, Noreen, Sadaf3 (AUTHOR) sadafnoreen234@gmail.com, Elnaggar, Ashraf Y.4 (AUTHOR), Hassan, Abrar U.5 (AUTHOR), El Azab, Islam H.4 (AUTHOR), Kyhoiesh, Hussein A. K.6 (AUTHOR), Mahmoud, Mohamed H. H.7 (AUTHOR)
Source: Journal of Fluorescence. Nov2025, Vol. 35 Issue 11, p10701-10712. 12p.
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  Data: Exploring New Azobenzene Type Photoswitches by Machine Learning with Lowest Possible Fluorescence Excitons with Ease of Synthesis.
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        Value: 10.1007/s10895-025-04336-5
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      – TitleFull: Exploring New Azobenzene Type Photoswitches by Machine Learning with Lowest Possible Fluorescence Excitons with Ease of Synthesis.
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              M: 11
              Text: Nov2025
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