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Ion pair receptors typically contain two separate binding sites, for the metal and the anion respectively. Here we report a less synthetically demanding approach, whereby we prepared a family of ion pair sensors based on a rhodamine fluorescent scaffold containing a tunable cation binding motif. When exposed to ion pairs, a competition for the metal ion is established between these ligands and anions. Structural and spectroscopic evidence showed that anions bind through weaker secondary interactions in the metal's outer coordination sphere and their presence influences the optical spectroscopic properties of the coordination complex in distinctive ways. The relationship between the binding site's metal affinity and its tunable properties, and the sensors' discriminatory power for anions was explained as a function of the metal ion's binding preferences. These effects were also exploited to discriminate cations and anions concurrently through multivariate data analysis methods.

A family of coumarin-enamine chemodosimeters is evaluated for their potential use as fluorescent molecular probes for multiple analytes [cadmium(II), cobalt(II), copper(II), iron(II), nickel(II), lead(II), and zinc(II)], as their chloride and acetate salts. These fluorophores displayed excellent optical spectroscopic modulation when exposed to ion pairs with different Lewis acidic and basic properties in dimethyl sulfoxide (DMSO). The chemodosimeters were designed to undergo excited-state intramolecular proton transfer (ESIPT), which leads to significant Stokes shifts (ca. 225 nm) and lower-energy fluorescence emission (ca. 575 nm). A more basic anion, e.g., acetate, inhibited the ESIPT mechanism by deprotonation of the enol, producing a binding pocket (N^O- chelate) that can coordinate to an appropriate metal ion. Coordination of the metal ions enhances the fluorescent intensity via the chelation-enhanced fluorescence emission mechanism. Subjecting the spectroscopic data to linear discriminant analysis provided insights into the source of these systems' markedly different behavior toward ion pairs, despite the subtle structural differences in the organic framework. These compounds are examples of versatile, low-molecular-weight, dual-channel fluorescent sensors for ion-pair recognition. This study paves the way for using these probes as practical components of a sensing array for different metal ions and their respective anions.

The transformative potential of pattern-based sensing techniques is often hampered by their difficulty in dealing with mixtures of analytes, a drawback that severely limits the applications of this sensing approach (the "problem of mixtures"). We show here that this is not an intrinsic limitation of the pattern sensing method. Indeed, we developed general guidelines for the design of the sensing, signal detection, and data interpretation methods to avoid this constraint, which resulted in chemical fingerprinting systems capable of recognizing unknown mixtures of analytes in a single experiment, without separation or pre-treatment before data acquisition. In support of these design principles, we report their successful application to an important analytical problem, metal ion discrimination and quantitation, by constructing a sensor array that provided a linear colorimetric response over a wide range of analyte concentrations. The resulting data set was interpreted using common multivariate data processing algorithms to achieve quantitative identification and concentration determination for pure and mixture samples, with excellent predictive ability on unknowns. Separation and detection methods for analyte mixtures, normally envisioned as independent processes, were successfully integrated in a single system.

Azo dyes are ubiquitous pollutants that contaminate water supplies and threaten human, biota, and ecosystem health. Their detection and discrimination are a considerable challenge owing to the numerous structural, chemical, and optical similarities between dyes, complexity of the wastewater in which they are found, and low environmental concentrations. Here, we demonstrate that the inner filter effect (IFE), in combination with conjugated polymer array-based sensing, offers a rapid approach for the quantitative profiling of these pollutants. The array was constructed using three anionic conjugated polyelectrolytes whose varying spectroscopic properties led to distinct IFE patterns in the presence of various dyes. These unique fluorescence response patterns were identified and processed using linear discriminant analysis (LDA), enabling the individual identification of 12 closely related azo dyes. To demonstrate the potential for utility in the environment, the array was used to differentiate between these dyes at nanomolar concentrations in water.

The inner filter effect and multivariate array sensing using conjugated polymers are combined for the detection and challenging discrimination of closely related polycyclic aromatic hydrocarbons., Natural and anthropogenic activities result in the production of polycyclic aromatic hydrocarbons (PAHs), persistent pollutants that negatively impact the environment and human health. Rapid and reliable methods for the detection and discrimination of these compounds remains a technological challenge owing to their relatively featureless properties, structural similarities, and existence as complex mixtures. Here, we demonstrate that the inner filter effect (IFE), in combination with conjugated polymer (CP) array-based sensing, offers a straightforward approach for the quantitative and qualitative profiling of PAHs. The sensor array was constructed from six fluorescent fluorene-based copolymers, which incorporate side chains with peripheral 2-phenylbenzimidazole substituents that provide spectral overlap with PAHs and give rise to a pronounced IFE. Subtle structural differences in copolymer structure result in distinct spectral signatures, which provide a unique “chemical fingerprint” for each PAH. The discriminatory power of the array was evaluated using linear discriminant analysis (LDA) and principal component analysis (PCA) in order to discriminate between 16 PAH compounds identified as priority pollutants by the US Environmental Protection Agency (EPA). This array is the first multivariate system reliant on the modulation of the spectral signatures of CPs through the IFE for the detection and discrimination of closely related polynuclear aromatic species.