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Mapping Correlated Environmental Landscapes in the Fluorescence Response of a Pyrenylated Charge-Transfer Probe via Data-Driven Nonlinear Regression
1 Introduction Fluorescence measurements are often treated as straightforward readouts of molecular behavior, yet in practice, the intensity response is rarely simple. Even for well-characterized chromophores, fluorescence intensity can change nonlinearly with the surrounding environment as radiative and nonradiative pathways compete on comparable energy scales. These changes are typically probed at discrete experimental points, and usually by varying one parameter at a time.
Dual‐Mode Ratiometric ESIPT Probes for Vapor‐Phase Detection of a Pulmonary Agent: Leveraging Machine Learning for High‐Precision Quantitative Analysis
Conflict of Interests The authors declare no conflict of interest. Supporting Information Filename Description asia202401676-sup-0001-SuppMat.docx148.9 KB Supporting Information References 1, , , Anal. Chem. 2019, 91, 5690–5697. 2, , , , , , , Coord. Chem. Rev. 2022, 463, 214527. 3, , , ACS Sens. 2017, 2, 178–182. 4a) , , , , , , , , Chem. Sci. 2022, 13, 4523–4532; b) , , , , , , Spectrochim. Acta A Mol. Biomol. Spectrosc. 2021, 253, 119589. 5, , , , Sens. Actuators B: Chem. 2021, 326, 128837. 6a) , , Environ.
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