Nanoscale Intelligent Imaging Based on Real-Time Analysis of Approach Curve by Scanning Electrochemical Microscopy

Nanoscale Quantitative Imaging of Single Nuclear Pore Complexes by Scanning Electrochemical Microscopy

The nuclear pore complex (NPC) is a proteinaceous nanopore that solely and selectively regulates the molecular transport between the cytoplasm and nucleus of a eukaryotic cell. The ∼50 nm-diameter pore of the NPC perforates the double-membrane nuclear envelope to mediate both passive and facilitated molecular transport, thereby playing paramount biological and biomedical roles. Herein, we visualize single NPCs by scanning electrochemical microscopy (SECM). The high spatial resolution is accomplished by employing ∼25 nm-diameter ion-selective nanopipets to monitor the passive transport of tetrabutylammonium at individual NPCs. SECM images are quantitatively analyzed by employing the finite element method to confirm that this work represents the highest-resolution nanoscale SECM imaging of biological samples. Significantly, we apply the powerful imaging technique to address the long-debated origin of the central plug of the NPC. Nanoscale SECM imaging demonstrates that unplugged NPCs are more permeable to the small probe ion than are plugged NPCs. This result supports the hypothesis that the central plug is not an intrinsic transporter, but is an impermeable macromolecule, e.g., a ribonucleoprotein, trapped in the nanopore. Moreover, this result also supports the transport mechanism where the NPC is divided into the central pathway for RNA export and the peripheral pathway for protein import to efficiently mediate the bidirectional traffic.

Nanoelectrochemistry at liquid/liquid interfaces for analytical, biological, and material applications

Herein, we feature our recent efforts toward the development and application of nanoelectrochemistry at liquid/liquid interfaces, which are also known as interfaces between two immiscible electrolyte solutions (ITIES). Nanopipets, nanopores, and nanoemulsions are developed to create the nanoscale ITIES for the quantitative electrochemical measurement of ion transfer, electron transfer, and molecular transport across the interface. The nanoscale ITIES serves as an electrochemical nanosensor to enable the selective detection of various ions and molecules as well as high-resolution chemical imaging based on scanning electrochemical microscopy. The powerful nanoelectroanalytical methods will be useful for biological and material applications as illustrated by in situ studies of solid-state nanopores, nuclear pore complexes, living bacteria, and advanced nanoemulsions. These studies provide unprecedented insights into the chemical reactivity of important biological and material systems even at the single nanostructure level.

Electrochemical Imaging of Interfaces in Energy Storage via Scanning Probe Methods: Techniques, Applications, and Prospects

Developing a deeper understanding of dynamic chemical, electronic, and morphological changes at interfaces is key to solving practical issues in electrochemical energy storage systems (EESSs). To unravel this complexity, an assortment of tools with distinct capabilities and spatiotemporal resolutions have been used to creatively visualize interfacial processes as they occur. This review highlights how electrochemical scanning probe techniques (ESPTs) such as electrochemical atomic force microscopy, scanning electrochemical microscopy, scanning ion conductance microscopy, and scanning electrochemical cell microscopy are uniquely positioned to address these challenges in EESSs. We describe the operating principles of ESPTs, focusing on the inspection of interfacial structure and chemical processes involved in Li-ion batteries and beyond. We discuss current examples, performance limitations, and complementary ESPTs. Finally, we discuss prospects for imaging improvements and deep learning for automation. We foresee that ESPTs will play an enabling role in advancing EESSs as we transition to renewable energies.

Deconvoluting Kinetic Rate Constants of Catalytic Substrates from Scanning Electrochemical Approach Curves with Artificial Neural Networks

Extracting information from experimental measurements in the chemical sciences typically requires curve fitting, deconvolution, and/or solving the governing partial differential equations via numerical (e.g., finite element analysis) or analytical methods. However, using numerical or analytical methods for high-throughput data analysis typically requires significant postprocessing efforts. Here, we show that deep learning artificial neural networks can be a very effective tool for extracting information from experimental data. As an example, reactivity and topography information from scanning electrochemical microscopy (SECM) approach curves are highly convoluted. This study utilized multilayer perceptrons and convolutional neural networks trained on simulated SECM data to extract kinetic rate constants of catalytic substrates. Our key findings were that multilayer perceptron models performed very well when the experimental data were close to the ideal conditions with which the model was trained. However, convolutional neural networks, which analyze images as opposed to direct data, were able to accurately predict the kinetic rate constant of Fe-doped nickel (oxy)hydroxide catalyst at different applied potentials even though the experimental approach curves were not ideal. Due to the speed at which machine learning models can analyze data, we believe this study shows that artificial neural networks could become powerful tools in high-throughput data analysis.

A nanoelectrode-based study of water splitting electrocatalysts

The development of low-cost and efficient catalytic materials for key reactions like water splitting, CO₂ reduction and N₂ reduction is crucial for fulfilling the growing energy consumption demands and the pursuit of renewable and sustainable energy. Conventional electrochemical measurements at the macroscale lack the potential to characterize single catalytic entities and nanoscale surface features on the surface of a catalytic material. Recently, promising results have been obtained using nanoelectrodes as ultra-small platforms for the study of the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) on innovative catalytic materials at the nanoscale. In this minireview, we summarize the recent progress in the nanoelectrode-based studies on the HER and OER on various nanostructured catalytic materials. These electrocatalysts can be generally categorized into two groups: 0-dimensional (0D) single atom/molecule/cluster/nanoparticles and 2-dimensional (2D) nanomaterials. Controlled growth as well as the electrochemical characterization of single isolated atoms, molecules, clusters and nanoparticles has been achieved on nanoelectrodes. Moreover, nanoelectrodes greatly enhanced the spatial resolution of scanning probe techniques, which enable studies at the surface features of 2D nanomaterials, including surface defects, edges and nanofacets at the boundary of a phase. Nanoelectrode-based studies on the catalytic materials can provide new insights into the reaction mechanisms and catalytic properties, which will facilitate the pursuit of sustainable energy and help to solve CO₂ release issues.

Simultaneous Intelligent Imaging of Nanoscale Reactivity and Topography by Scanning Electrochemical Microscopy

Scanning electrochemical microscopy (SECM) enables reactivity and topography imaging of single nanostructures in the electrolyte solution. The in situ reactivity and topography, however, are convoluted in the real-time image, thus requiring another imaging method for subsequent deconvolution. Herein, we develop an intelligent mode of nanoscale SECM to simultaneously obtain separate reactivity and topography images of non-flat substrates with reactive and inert regions. Specifically, an ∼0.5 μm-diameter Pt tip approaches a substrate with an ∼0.15 μm-height active Au band adjacent to an ∼0.4 μm-wide slope of the inactive glass surface followed by a flat inactive glass region. The amperometric tip current versus tip-substrate distance is measured to observe feedback effects including redox-mediated electron tunneling from the substrate. The intelligent SECM software automatically terminates the tip approach depending on the local reactivity and topography of the substrate under the tip. The resultant short tip-substrate distances allow for non-contact and high-resolution imaging in contrast to other imaging modes based on approach curves. The numerical post-analysis of each approach curve locates the substrate under the tip for quantitative topography imaging and determines the tip current at a constant distance for topography-independent reactivity imaging. The nanoscale grooves are revealed by intelligent topography SECM imaging as compared to scanning electron microscopy and atomic force microscopy without reactivity information and as unnoticed by constant-height SECM imaging owing to the convolution of topography with reactivity. Additionally, intelligent reactivity imaging traces abrupt changes in the constant-distance tip current across the Au/glass boundary, which prevents constant-current SECM imaging.