In the last decades, electrochemical sensing techniques have been used to investigate a plethora of chemical, physical, biological and environmental processes. For instance amperometry, where the electrode voltage is kept constant, and voltammetry, where the electrode voltage is perturbed according to a predefined waveform, are the methods of choice for a wide range of measurements in neuroscience [1-3]. From the current response of the electrode information about the characteristics, and therefore identity, of the analyte can be drawn. While amperometric methods offer good temporal resolution they cannot discriminate between different molecules undergoing an electrochemical reaction step at the electrode surface [4]. On the other hand, in a large number of applications dynamic multicomponent systems are involved and thus, a technique that is capable of monitoring different analytes simultaneously is required in order to study them. Voltammetric techniques have been shown to offer improved selectivity as well as improved discrimination against non-faradaic contributions to the signal. Ultramicroelectrodes (voltammetric electrodes of typically less than 10μm) enable the accurate measurement of time-dependent currents and have proven to be a very useful tool for in vivo experimentation offering unparalleled spatial and temporal resolution combined with good selectivity [5, 6].

The major difficulty of voltammetric methods lies in their interpretation. Electrochemical signals are intrinsically nonlinear and nonstationary. For a long time voltammetric measurements were confined in small-amplitude perturbations to avoid nonlinear effects of electron transfer. Lately, ac voltammetry, which uses a 'slow' ramp superimposed on a 'faster' large-amplitude/high-frequency harmonic as voltage excitation, has drawn considerable attention due to its enhanced voltammetric detail as well as its ability to investigate phenomena on different timescales. Such large-amplitude/high-frequency voltage waveforms though cause capacitance interference to the current output to become substantial [4]. Hitherto there have been few alternatives to the FFT technique for frequency analysis, although fundamental assumptions of the theory, such as periodicity, continuity and linearity, are not satisfied [7]. As a result, ac voltammetric data-sets could not be fully interpreted [8, 9].

In this work we use a technique - the Hilbert transform - which is valid for nonstationary signal processing and has been often used to analyse nonlinear phenomena [10]. It results in the instantaneous attributes of the current response, the instantaneous amplitude and the instantaneous phase.

We will show that the proposed method adequately minimises the significant capacitance contributions related to rapid voltammetric techniques and, moreover, it enables the accurate determination of a set of species- and process-specific parameters allowing monitoring of the dynamical behaviour of the system under investigation as well as the sensor/environment interface [11]. We conducted a large number of numerical simulations modelling the nonlinear electron-transfer- and mass-transport-dynamics and derived the behaviour of the current response signal with respect to order-of-magnitude variations of the physical parameters. The characteristic patterns that emerge from this sensitivity analysis allows for the determination of parameters such as the formal oxidation potential E₀, the kinetic reaction constant k₀, the charge-transfer coefficient α and the diffusion coefficient D [4]. We will illustrate that the proposed methodology proves very robust towards enhanced capacitance interference, mainly, and noise levels which normally preclude quantitative analysis with conventional tools. The fact that separate predictions from two signal components of the the same data are utilised enhances the confidence of this method. Microscopic experiments using electrodes 7 - 30 μm with two model electrochemical species (rutheniumhexamine and ferrocyanide) on two electrode materials (carbon and platinum) acquired in less than 1 second show excellent agreement with published values obtained using much lengthier and experimentally tedious methods suggesting possible applications in biological, chemical and environmental sensing. Moreover, the enhanced voltammetric detail provided by the herein introduced method can be used to separate between chemicals with very similar electrochemical signature with obvious applications in sub-second monitoring of multicomponent systems [12].

References

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[9] Sher AA, Bond AM, Gavaghan DJ, Harriman K, Feldberg SW, Duffy NW, Guo SX, Zhang J. Resistance capacitance and electrode kinetic effects in Fourier-transformed large-amplituded large-amplitude sinusoidal voltammetry: Emergence of powerful and intuitively obvious tools for recognition of patterns of behaviour. Anal. Chem. 2004; 76: 6214-6228.

[10] Anastassiou CA, Parker KH, O'Hare D, Determination of kinetic and thermodynamic parameters of surface confined species through ac voltammetry and a nonstationary signal processing technique: the Hilbert transform. Anal. Chem. 2005; 77: 3357-3364.

[11] Anastassiou CA, Ducros N, Parker KH, O'Hare D, Characterisation of ac voltammetric reaction-diffusion dynamics: From patterns to physical patterns Anal. Chem. (in press) DOI: 10.1021/ac060122v.

[12] Anastassiou CA, Patel BA, Arundell M, Yeoman MS, Parker KH, O'Hare D, Novel subsecond voltammetric separation between dopamine and serotonin in the presence of ascorbate. Anal. Chem. (submitted).