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• W3214301144 abstract "An arrayed combination of water-soluble deep cavitands and cationic dyes has been shown to optically sense insect pheromones at micromolar concentration in water. Machine learning approaches were used to optimize the most effective array components, which allows differentiation between small structural differences in targets, including between different diastereomers, even though the pheromones have no innate chromophore. When combined with chiral additives, enantiodiscrimination is possible, dependent on the size and shape of the pheromone." @default.
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• W3214301144 date "2021-01-01" @default.
• W3214301144 modified "2023-09-24" @default.
• W3214301144 title "Enantioselective sensing of insect pheromones in water" @default.
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• W3214301144 doi "https://doi.org/10.1039/d1cc05540b" @default.
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