Developing a potentiometric sensor with required target properties is a challenging task. This work explores the potential of quantitative structure-property relationship (QSPR) modeling in the prediction of potentiometric selectivity for plasticized polymeric membrane sensors based on newly synthesized ligands. As a case study, we have addressed sensors with selectivity towards carbonate—an important topic for environmental and biomedical studies. Using the logKsel(HCO3−/Cl−) selectivity data on 40 ionophores available in literature and their substructural molecular fragments as descriptors, we have constructed a QSPR model, which has demonstrated reasonable precision in predicting selectivities for newly synthesized ligands sharing similar molecular fragments with those employed for modeling.
While potentiometric, plasticized membrane sensors are known as convenient, portable and inexpensive analytical instruments, their development is time- and resource-consuming, with a poorly predictable outcome. In this study, we investigated the applicability of the QSPR (quantitative structure–property relationship) method for predicting the potentiometric sensitivity of plasticized polymeric membrane sensors, using the ionophore chemical structure as model input. The QSPR model was based on the literature data on sensitivity, from previously studied, structurally similar ionophores, and it has shown reasonably good metrics in relating ionophore structures to their sensitivities towards Cu2+, Cd2+ and Pb2+. The model predictions for four newly synthesized diphenylphosphoryl acetamide ionophores were compared with real potentiometric experimental data for these ionophores, and satisfactory agreement was observed, implying the validity of the proposed approach.
In this work, a chemical reaction between gaseous ozone
and aqueous
solution of Mn(CH3COO)2 in drops has been researched.
It has been shown that the formation of HxMnO2·nH2O nanocrystals with a morphology
of nanosheets and a birnessite-like crystal structure with a thickness
of 5–8 nm is observed on the surface of drops. These nanocrystals
are oriented spontaneously to the solution–gas interface and
constitute peculiar ribbons with a width of 1–2 μm, some
of which form ordered honeycomb structures (OHS) with a 5–20
μm cell size. To explain the observed effect, the scheme of
chemical reactions that take place at the interface between the surface
of a drop and ozone has been modeled, and it can be described using
a diffusion pattern model taking into account the action of “force
fields” on the surface of a drop, which arise due to its curvature.
After the drop is dried, these structures practically retain their
morphology and form a fractal structure with a geometric area equal
to the area of the drop base on the surface of the substrate. The
study of the electrocatalytic properties of these structures revealed
that they are active electrocatalysts in the oxygen evolution reaction
(OER) during water electrolysis in alkaline medium. The most efficient
of the obtained electrocatalysts are characterized by an overpotential
value of 284 mV at a current of 10 mA/cm2 and the Tafel
coefficient of 37.7 mV/dec and are currently one of the best among
pure manganese oxides. Finally, it has also been assumed that this
effect is explained by the morphological features of the structures
obtained, which contribute to the removal of oxygen bubbles from the
electrode surface during electrolysis.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.