Recent Publications Feed (ADMIN)

Square wave voltammetry (SWV) is most commonly used to enhance electroanalytical current signals of a redox analyte of interest. The SWV is typically recorded in a potential region where both non-faradaic and faradaic currents are collected, however only data in the faradaic region is analysed. In this paper we show how by collecting the full current-time (i-t) data, arising from the SWV potential pulse sequence, and analysing in the region of the potential scan where non-faradaic currents arise, further analytical information can be collected, over short time periods (typically seconds). Importantly, we show how information on solution resistance, R (and solution conductivity) and double layer capacitance, C, can be extracted from this data, without the need to conduct further electrochemical experiments, such as electrochemical impedance spectroscopy or independent solution conductivity measurements. Knowledge of the latter is important for measurement in real world samples, where the electrolyte concentration is unknown. We show how SWV measurements of electrode capacitance with repeat SWV scans, can also be used to determine whether a changing faradaic SWV signal is due to electrode fouling or changing analyte concentration. Finally, knowledge of both parameters (RC) is essential for optimisation of the SWV parameters such that the faradaic SWV signal is truly free from non-faradaic contributions.

The surface charge and topography of human hair are visualized synchronously at the nanoscale using scanning ion conductance microscopy (SICM), a scanning nanopipette probe technique that uses local ion conductance currents to image the physicochemical properties of interfaces. By combining SICM data with finite element method (FEM) simulations that solve for ion transport at the nanopipette under bias, one is able to quantitatively correlate colocated surface charge and topography. The hair samples studied herein, from a 25-year-old Caucasian male with light hair (as an exemplar), reveal that untreated hair, in areas ca. 1 cm from the root, has a fairly uniform negative charge density of ca. −15 mC/cm–2 (in pH 6.8 aqueous solution), with some higher magnitude negative values localized near the boundaries between hair cuticles. Common chemical treatments result in varying degrees of charge heterogeneity. A bleach treatment produces some highly negatively charged localized regions (−80 to −100 mC/cm–2 at pH 6.8), due to hair damage, while a chemical conditioner treatment causes an overall increase in the homogeneity of the surface charge, together with a shift in the surface charge to positive values. Bleached surfaces are temporarily repaired to some extent through the use of a conditioner, as judged by the surface charge values. Finally, SICM is able to detect differences in the surface charge density of hair at different distances from the root (equivalent to hair age). Presently, the assessment of hair surface charge mainly relies on zeta-potential measurements which lack spatial resolution, among other drawbacks. In contrast, SICM enables quantitative surface charge mapping that should be beneficial in deepening understanding of the physicochemical properties of hair and lead to the rational development of new treatments and the assessment of their efficacy at the nanoscale. Given the widespread interest in the surface charge properties of interfaces, this work further demonstrates that SICM should generally become an important characterization tool for surface analytical chemists.

The redox activity (Li‐ion intercalation/deintercalation) of a series of individual LiMn2O4particles of known geometry and (nano)structure, within an array, is determined using a correlative electrochemical microscopy strategy. Cyclic voltammetry (current–voltage curve, I–E) and galvanostatic charge/discharge (voltage–time curve, E–t) are applied at the single particle level, using scanning electrochemical cell microscopy (SECCM), together with co‐location scanning electron microscopy that enables the corresponding particle size, morphology, crystallinity, and other factors to be visualized. This study identifies a wide spectrum of activity of nominally similar particles and highlights how subtle changes in particle form can greatly impact electrochemical properties. SECCM is well‐suited for assessing single particles and constitutes a combinatorial method that will enable the rational design and optimization of battery electrode materials.