Evaluating the Use of Edge Detection in Extracting Feature Size from Scanning Electrochemical Microscopy Images

General Method for Fitting Kinetics from the SECM Images of Reactive Sites on Flat Surfaces

Scanning electrochemical microscopy (SECM) is a technique for imaging electrochemical reactions at a surface. The interaction between electrochemical reactions occurring at the sample and scanning electrode tip is quite complicated and requires computer modeling to obtain quantitative information from SECM images. Often, existing computer models must be modified, or a new model must be created from scratch to fit kinetic parameters for different reactive features. This work presents a method that can simulate the SECM image of a reactive feature of any shape on a flat surface which is coupled to a computer program which effectuates the automated fitting of kinetic information from these images. This fitting program is evaluated along with several methods for estimating the shapes of reactive features from their SECM images. Estimates of the reactive feature shape from SECM images were not sufficiently accurate and produced median relative errors for the surface rate constant that were >50%. Fortunately, more precise techniques for imaging the reactive features such as optical microscopy can supply sufficiently accurate shapes for the fitting procedure to produce accurate results. Fits of simulated SECM images using the actual shape from the simulation produced median relative errors for the surface rate constant that were <10% for the smallest reactive features tested. This method was applied to the SECM images of aluminum alloy AA7075 which revealed diffusion-limited kinetics for ferrocene methanol reduction over inclusions in the surface of the alloy.

Quantitative Feedback Referencing for Improved Kinetic Fitting of Scanning Electrochemical Microscopy Measurements

Scanning electrochemical microscopy (SECM) has matured as a technique for studying local electrochemical processes. The feedback mode is most commonly used for extracting quantitative kinetic information. However, approaching individual regions of interest, as is commonly done, does not take full advantage of the spatial resolution that SECM has to offer. Moreover, fitting of experimental approach curves remains highly subjective due to the manner of estimating the tip-to-substrate distance. We address these issues using negative or positive feedback currents as a reference to calculate the tip-to-substrate distance directly for quantitative kinetic fitting of approach curves and line profiles. The method was first evaluated by fitting simulated data and then tested experimentally by resolving negative feedback and intermediate kinetics behavior in a spatially controlled fashion using (i) a flat, binary substrate composed of Au and SiO₂ segments and (ii) a dual-mediator system for live-cell measurements. The methodology developed herein, named quantitative feedback referencing (QFR), improves fitting accuracy, removes fitting subjectivity, and avoids substrate-microelectrode contact.

Bridging the Gap between Single Nanoparticle Imaging and Global Electrochemical Response by Correlative Microscopy Assisted By Machine Vision

The nanostructuration of an electrochemical interface dictates its micro- and macroscopic behavior. It is generally highly complex and often evolves under operating conditions. Electrochemistry at these nanostructurations can be imaged both operando and/or ex situ at the single nanoobject or nanoparticle (NP) level by diverse optical, electron, and local probe microscopy techniques. However, they only probe a tiny random fraction of interfaces that are by essence highly heterogeneous. Given the above background, correlative multimicroscopy strategy coupled to electrochemistry in a droplet cell provides a unique solution to gain mechanistic insights in electrocatalysis. To do so, a general machine-vision methodology is depicted enabling the automated local identification of various physical and chemical descriptors of NPs (size, composition, activity) obtained from multiple complementary operando and ex situ microscopy imaging of the electrode. These multifarious microscopically probed descriptors for each and all individual NPs are used to reconstruct the global electrochemical response. Herein the methodology unveils the competing processes involved in the electrocatalysis of hydrogen evolution reaction at nickel based NPs, showing that Ni metal activity is comparable to that of platinum.

Theoretical and experimental verification of imaging resolution factors in scanning electrochemical microscopy

The imaging resolution of scanning electrochemical microscopy (SECM) depends strongly on the tip electrode size and the tip-substrate distance. Herein, etched glass encapsulation was applied to fabricate a gold disk electrode, and the size of the tip electrode was accurately determined from the steady-state limiting current. Referring to the theoretical research carried out by our predecessors, the formula for the imaging resolution was derived, followed by the imaging of gold spots and cells with the prepared microelectrodes of different sizes and with different tip-substrate distances. A depth scan was performed to generate 2D current maps of the gold spot relative to the position of the microelectrode in the x-z plane. Probe approach curves and horizontal sweeps were obtained from one depth scan image by simply extracting vertical and horizontal cross-sectional lines, and further characterized by comparison with simulated curves through modeling of the experimental system. The experimental results were basically consistent with the theory, revealing that the highest imaging resolution can be obtained with the smallest tip electrode when d/a = 1, and when the size of the tip electrode is fixed the smallest tip-substrate distance can give the highest imaging resolution.

Super-resolution Scanning Electrochemical Microscopy

To achieve super-resolution scanning electrochemical microscopy (SECM), we must overcome the theoretical limitation associated with noncontact electrochemical imaging of surface-generated species. This is the requirement for mass transfer to the electrode, which gives rise to the diffusional broadening of surface features. In this work, a procedure is developed for overcoming this limitation and thus generating "super-resolved" images using point spread function (PSF)-based deconvolution, where the point conductor plays the same role as the point emitter in optical imaging. In contrast to previous efforts in SECM towards this goal, our method uses a finite element model to generate a pair of corresponding blurred and sharp images for PSF estimation, avoiding the need to perform parameter optimization for effective deconvolution. It can therefore be used for retroactive data treatment and an enhanced understanding of the structure-property relationships that SECM provides.