Boronic acids can be used as receptors in chemical sensors for sugars, but their binding affinity and solubility are usually very poor in water. We improved these parameters by covalently connecting boronic acid moieties to the surface of third-generation poly(amido)amine (PAMAM) dendrimers to form a family of PAMAM–boronic acid receptors that display multivalent behavior. We confirmed the increased interaction strength of these modified boronic acid receptors using diol-containing dyes such as 4-methylesculetin and alizarin red S as probes in optical spectroscopy experiments. We then translated these results to sugar sensing using the self-assembled [PAMAM-ba·(dye)n] complexes as sensors in an indicator displacement assay. Our approach successfully detected simple sugars (e.g. fructose, glucose, galactose and ribose) in water, traditionally a very challenging medium for carbohydrate detection. Finally, we demonstrated the use of these polymer-based sensors in a multivariate array sensing platform for the discrimination of simple sugars in water as a proof of principle towards their broader applicability under physiologically and environmentally relevant conditions.

A simple sensing ensemble was designed to discriminate structurally similar divalent metal chlorides utilizing multivariate data analysis. The system features the binding of four synthesized coumarin-enamine probes to a series of ten metal chlorides. Linear discriminant analysis (LDA) achieves what univariate data analysis alone cannot i.e., full analyte discrimination and differentiation.

The organophosphate class of compounds includes common herbicides as well as highly toxic nerve gases whose detection is important from an environmental and a public safety perspective. We describe here a fluorescence turn-on sensor array for the rapid detection and quantitation of relevant organophosphates in neutral water. The array elements self-assemble from commercially available dyes and PAMAM dendrimers, and sensing is based on an indicator displacement assay. Data interpretation through pattern recognition methods (PCA, LDA) showed excellent cluster separation and sample classification. In addition, we were also able to use this system for simultaneous differentiation and quantitative analysis of methylphosphonate (a nerve gas byproduct), glyphosate (a ubiquitous herbicide), and inorganic phosphate over a wide range of concentrations (10 μM to 2 mM).

An off-the-shelf supramolecular sensing system was designed to discriminate biologically relevant phosphates in neutral water using multivariate data analysis. The system is based on an indicator displacement assay comprising only two unmodified commercially available components: a dendritic poly-electrolyte and a common fluorescent dye. Effective discrimination of nucleotide diphosphates and inorganic diphosphate was achieved through principal component analysis (PCA).

The nature and relative strength of the intermolecular interactions responsible for the behavior of PAMAM dendrimers as encapsulating agents were investigated in neutral aqueous solution through optical spectroscopy methods. In order of relative importance, we found electrostatics, hydrogen bonding, and interactions mediated by aromatic moieties in the guest molecules to be the main drivers to complex formation in these systems. Insights were gained by studying the binding of small targeted organic anions to these dendrimers (G3–G6) by an indicator displacement method, monitoring spectral signals (absorbance, fluorescence emission, and anisotropy). This study contributes to a more complete understanding of the fundamental interactions involved when these hyperbranched polyelectrolytes function as supramolecular hosts, a role they commonly assume in many of their applications e.g. as drug delivery vectors.

A simple sensing ensemble was designed to discriminate structurally similar divalent metal chlorides utilizing multivariate data analysis. The system features the binding of four synthesized coumarin-enamine probes to a series of ten metal chlorides. Linear discriminant analysis (LDA) achieves what univariate data analysis alone cannot i.e., full analyte discrimination and differentiation.

An off-the-shelf supramolecular sensing system was designed to discriminate biologically relevant phosphates in neutral water using multivariate data analysis. The system is based on an indicator displacement assay comprising only two unmodified commercially available components: a dendritic poly-electrolyte and a common fluorescent dye. Effective discrimination of nucleotide diphosphates and inorganic diphosphate was achieved through principal component analysis (PCA).

Boronic acids can be used as receptors in chemical sensors for sugars, but their binding affinity and solubility are usually very poor in water. We improved these parameters by covalently connecting boronic acid moieties to the surface of third-generation poly(amido)amine (PAMAM) dendrimers to form a family of PAMAM–boronic acid receptors that display multivalent behavior. We confirmed the increased interaction strength of these modified boronic acid receptors using diol-containing dyes such as 4-methylesculetin and alizarin red S as probes in optical spectroscopy experiments. We then translated these results to sugar sensing using the self-assembled [PAMAM-ba·(dye)n] complexes as sensors in an indicator displacement assay. Our approach successfully detected simple sugars (e.g. fructose, glucose, galactose and ribose) in water, traditionally a very challenging medium for carbohydrate detection. Finally, we demonstrated the use of these polymer-based sensors in a multivariate array sensing platform for the discrimination of simple sugars in water as a proof of principle towards their broader applicability under physiologically and environmentally relevant conditions.