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Smartphone Enabled Machine Learning Approach Assisted Copper Quantification and Opto-Electrochemical Explosive Recognition by Aldazine-Functionalized Chemobiosensor

https://doi.org/10.2139/ssrn.4776755
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An asymmetric naked-eye chemo-sensor for Cu2+ in aqueous solution
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A colorimetric chemosensor for Cu(II) ion in aqueous medium
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Specific detection of Cu2+ by a pH-independent colorimetric rhodamine based chemosensor
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Static and dynamic model fluorescence quenching of laser dye by carbon tetrachloride in binary mixtures
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Simple and sensitive colorimetric sensors for the selective detection of Cu2+ in aqueous buffer
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Hg(II) sensing platforms with improved photostability: The combination of rhodamine derived chemosensors and up-conversion nanocrystals
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Simple and Accurate Quantification of Quantum Yield at the Single-Molecule/Particle Level
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Reconsideration of the Detection and Fluorescence Mechanism of a Pyrene-Based Chemosensor for TNT
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Diethylenetriaminepentaacetic Acid-Functionalized Gold Nanoparticles for the Detection of Toxic Chromium Assisted by a Machine-Learning Approach
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Discerning Detection of Mutagenic Biopollutant TNP from Water and Soil Samples with Transition Metal-Containing Luminescence Metal–Organic Frameworks
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Advancing Biosensors with Machine Learning
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New insights into the sensing mechanism of a phosphonate pyrene chemosensor for TNT
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