Accurate methods that can continuously detect low concentrations of hydrogen peroxide (H₂O₂) have a huge application potential in biological, pharmaceutical, clinical and environmental analysis. Luminescent probes and nanomaterials are used for fabrication of sensors for H₂O₂ that can be applied for these purposes. In contrast to previous reviews focusing on the chemical design of molecular probes for H₂O₂, this mini-review highlights the latest luminescent nanoparticular materials and new luminescent optical sensors for H₂O₂ in terms of the nanomaterial composition and luminescent receptor used in the sensors. The nanomaterial section is subdivided into schemes based on gold nanoparticles, polymeric nanoparticles with embedded enzymes, probes showing aggregation-induced emission enhancement, quantum dots, lanthanide-based nanoparticles and carbon based nanomaterials, respectively. Moreover, the sensors are ordered according to the type of luminescent receptor used within the sensor membranes. Among them are lanthanide complexes, metal-ligand complexes, oxidic nanoparticles and organic dyes. Further, the optical sensors are confined to those that are capable to monitor the concentration of H₂O₂ in a sample over time or are reusable. Optical sensors responding to gaseous H₂O₂ are not covered. All nanomaterials and sensors are characterized with respect to the analytical reaction towards H₂O₂, limit of detection (LOD), analytical range, electrolyte, pH and response time/incubation time. Applications to real samples are given. Finally, we assess the suitability of the nanomaterials to be used in membrane-based sensors and discuss future trends and perspectives of these sensors in biomedical research.

A simple method was developed for determining aloin in A. vera samples by UV–visible spectroscopy with the study of the results of measurements by principal component analysis (PCA), which showed the separation of samples in the PC space depending on their manufacturer. The spectra of model binary (aloin–malic acid) and ternary (aloin–malic acid–citric acid) systems and the spectra of A. vera samples were decomposed using the mutual information least dependent component analysis (MILCA) algorithm based on the minimization of numerical values of mutual information. A good correlation is observed for model mixtures between the predicted and actual concentrations of aloin in the samples under study (n = 3, r = 0.986). The spectra of the model systems, that is, A. vera samples with a known concentration of aloin, and the spectra of A. vera samples artificially contaminated relative to the initial samples were used as calibration systems for the decomposition of the spectra of A. vera samples by independent component analysis. It was demonstrated that UV spectroscopy in combination with corresponding chemometric data processing enables the quantitative determination of aloin in plant samples of A. vera.