Search

This review overviews and revalues the role that the electrochemical techniques and the continuously evolving electrode designs play in the tremendous progress experienced by electrochemical biosensing. These aspects are scarcely covered in the recent literature on electrochemical biosensors and are discussed in this article through selected representative examples together with other approaches involving the use of signal amplification strategies, electrocatalytic materials, ratiometric designs or antifouling chemistries. Regarding electrodes, the continuous advances made in screen-printed, micro-, paper-based and flexible and wearable materials are critically overviewed. Concerning electrochemical techniques, the use of selected widely known techniques (electrochemical impedance spectroscopy, stripping voltammetry, and potentiometry) to successfully address different applications in response to current biosensing challenges is highlighted through their smart coupling with new experimental designs, bioreceptors and materials. [ABSTRACT FROM AUTHOR]

• Effects of thermodynamic and kinetic dispersion in surface confined voltammetry. • Distinguishing dispersed from non-dispersed cases by looking at voltammetry data. • Thermodynamic dispersion is usually resolvable for all experiments. • Kinetic dispersion is only resolvable for certain systems under defined conditions. Dispersion, or the distribution of kinetic and thermodynamic parameter values describing a redox reaction, has long been acknowledged as a complicating factor in the analysis of both solution and surface-confined voltammetry experiments. In this tutorial paper, we show how varying levels of dispersion can affect the appearance of the experimental current, mainly illustrating the concept with reference to surface-confined reversible one electron transfer. We focus on three voltammetric techniques, ramped Fourier Transform AC Voltammetry, Purely Sinusoidal Voltammetry and Direct Current Voltammetry, showing the effect the dispersion parameters have on the appearance of the resulting current. We have also implemented an interactive web-based simulation package for comparison of the effects of the various parameters, available here. As modelling dispersion significantly increases the computational burden of simulating voltammetry experiments, making well-informed choices about when to include this effect is essential. To facilitate this, we discuss the intuition for when to include dispersion when fitting experimental voltammetry data, again with reference to the three techniques described above. [ABSTRACT FROM AUTHOR]