Carbon Thin-Film Electrodes as High-Performing Substrates for Correlative Single Entity Electrochemistry.

Correlative methods to characterize single entities by electrochemistry and microscopy/spectroscopy are increasingly needed to elucidate structure-function relationships of nanomaterials. However, the technical constraints often differ depending on the characterization techniques to be applied in combination. One of the cornerstones of correlative single-entity electrochemistry (SEE) is the substrate, which needs to achieve a high conductivity, low roughness, and electrochemical inertness. This work shows that graphitized sputtered carbon thin films constitute excellent electrodes for SEE while enabling characterization with scanning probe, optical, electron, and X-ray microscopies. Three different correlative SEE experiments using nanoparticles, nanocubes, and 2D Ti3C2Tx MXene materials are reported to illustrate the potential of using carbon thin film substrates for SEE characterization. The advantages and unique capabilities of SEE correlative strategies are further demonstrated by showing that electrochemically oxidized Ti3C2Tx MXene display changes in chemical bonding and electrolyte ion distribution.

Correlating Thickness and Phase of Single Co(OH)2 Micro-Platelets to the Intrinsic Activity of Oxygen Evolution Electrocatalysis.

Morphology, crystal phase, and its transformation are important structures that frequently determine electrocatalytic activity, but the correlations of intrinsic activity with them are not completely understood. Herein, using Co(OH)2 micro-platelets with well-defined structures (phase, thickness, area, and volume) as model electrocatalysts of oxygen evolution reaction, multiple in situ microscopy is combined to correlate the electrocatalytic activity with morphology, phase, and its transformation. Single-entity morphology and electrochemistry characterized by atomic force microscopy and scanning electrochemical cell microscopy reveal a thickness-dependent turnover frequency (TOF) of α-Co(OH)2. The TOF (≈9.5 s-1) of α-Co(OH)2 with ≈14 nm thickness is ≈95-fold higher than that (≈0.1 s-1) with ≈80 nm. Moreover, this thickness-dependent activity has a critical thickness of ≈30 nm, above which no thickness-dependence is observed. Contrarily, ß-Co(OH)2 reveals a lower TOF (≈0.1 s-1) having no significant correlation with thickness. Combining single-entity electrochemistry with in situ Raman microspectroscopy, this thickness-dependent activity is explained by more reversible Co3+/Co2+ kinetics and larger ratio of active Co sites of thinner α-Co(OH)2, accompanied with faster phase transformation and more extensive surface restructuration. The findings highlight the interactions among thickness, ratio of active sites, kinetics of active sites, and phase transformation, and offer new insights into structure-activity relationships at single-entity level.

Electrochemical Imaging of Precisely-Defined Redox and Reactive Interfaces.

Understanding the diverse electrochemical reactions occurring at electrode-electrolyte interfaces (EEIs) is a critical challenge to developing more efficient energy conversion and storage technologies. Establishing a predictive molecular-level understanding of solid electrolyte interphases (SEIs) is challenging due to the presence of multiple intertwined chemical and electrochemical processes occurring at battery electrodes. Similarly, chemical conversions in reactive electrochemical systems are often influenced by the heterogeneous distribution of active sites, surface defects, and catalyst particle sizes. In this mini review, we highlight an emerging field of interfacial science that isolates the impact of specific chemical species by preparing precisely-defined EEIs and visualizing the reactivity of their individual components using single-entity characterization techniques. We highlight the broad applicability and versatility of these methods, along with current state-of-the-art instrumentation and future opportunities for these approaches to address key scientific challenges related to batteries, chemical separations, and fuel cells. We establish that controlled preparation of well-defined electrodes combined with single entity characterization will be crucial to filling key knowledge gaps and advancing the theories used to describe and predict chemical and physical processes occurring at EEIs and accelerating new materials discovery for energy applications.

Recent Trends and Perspectives in Single-Entity Electrochemistry: A Review with Focus on a Water Splitting Reaction.

Electrochemical measurements involving single nanoparticles have attracted considerable research attention. In recent years, various studies have been conducted on single-entity electrochemistry (SEE) for the in-depth analyses of catalytic reactions. Although, several electrocatalysts have been developed for H2 energy production, designing innovative electrocatalysts for this purpose remains a challenging task. Stochastic collision electrochemistry is gaining increased attention because it has led to new findings in the SEE field. Importantly, it facilitates establishing structure activity relationships for electrocatalysts by monitoring transient signals. This article reviews the recent achievements related to hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) using different electrocatalysts at the nanoscale level. In particular, it discusses the electrocatalytic activities of noble metal nanoparticles, including Ag, Au, Pt, and Pd nanoparticles, at the single-particle level. Because heterogeneity is a key factor affecting the catalytic activity of nanostructures, our work focuses on the influence of heterogeneities in catalytic materials on the OER and HER activities. These results may help to achieve a better understanding of the fundamental processes involved in the water splitting reaction.

Enhancing low-concentration cell detection in single entity electrochemical systems through forced convection.

This study advances the detection of bacteria at low concentrations in single-entity electrochemistry (SEE) systems by integrating forced convection. Our results show that forced convection significantly improves the mass transfer rate of electrolyte, with the mass transfer coefficient demonstrating a proportional relationship to the flow rate to the power of 1.37. Notably, while the collision frequency of E. coli initially increases with the flow rate, a subsequent decrease is observed at higher rates. This pattern is attributed to the mechanics of cell collision under forced convection. Specifically, while forced convection propels cells towards the ultra-microelectrode (UME), it does not aid in their penetration through the boundary layer, leading to cells being driven away from the UME at higher flow rates. This hypothesis is supported by the statistical analysis of collision data, including signal heights and rise times. By optimizing the flow rate to 2 mL/min, we achieved enhanced detection of E. coli in concentrations ranging from 0.9 × 107 to 5.0 × 107 cells/mL. This approach significantly increased collision frequency by elevating the mass transfer of cells, with the mass transfer coefficient rising from 0.1 × 10-5 m/s to 0.9 × 10-5 m/s. It provides a viable solution to the challenges of detecting bacteria at low concentrations in SEE systems.

Benchmarking the Intrinsic Activity of Transition Metal Oxides for the Oxygen Evolution Reaction with Advanced Nanoelectrodes.

The intrinsic activity assessment of transition metal oxides (TMOs) as key electrocatalysts for the oxygen evolution reaction (OER) has not been standardized due to uncertainties regarding their structure and composition, difficulties in accurately measuring their electrochemically active surface area (ECSA), and deficiencies in mass-transfer (MT) rates in conventional measurements. To address these issues, we utilized an electrodeposition-thermal annealing method to precisely synthesize single-particle TMOs with well-defined structure and composition. Concurrently, we engineered low roughness, spherical surfaces for individual particles, enabling precise measurement of their ECSA. Furthermore, by constructing a conductor-core semiconductor-shell structure, we evaluated the inherent OER activity of perovskite-type semiconductor materials, broadening the scope beyond just conductive TMOs. Finally, using single-particle nanoelectrode technique, we systematically measured individual TMO particles of various sizes for OER, overcoming MT limitations seen in conventional approaches. These improvements have led us to propose a precise and reliable approach to evaluating the intrinsic activity of TMOs, not only validating the accuracy of theoretical calculations but also revealing a strong correlation of OER activity on the melting point of TMOs. This discovery holds significant importance for future high-throughput material research and applications, offering valuable insights in electrocatalysis.

Monitoring the electroactive cargo of extracellular vesicles can differentiate various cancer cell lines.

Extracellular vesicles (EVs) are pivotal in cell-to-cell communication due to the array of cargo contained within these vesicles. EVs are considered important biomarkers for identification of disease, however most measurement approaches have focused on monitoring specific surface macromolecular targets. Our study focuses on exploring the electroactive component present within cargo from EVs obtained from various cancer and non-cancer cell lines using a disk carbon fiber microelectrode. Variations in the presence of oxidizable components were observed when the total cargo from EVs were measured, with the highest current detected in EVs from MCF7 cells. There were differences observed in the types of oxidizable species present within EVs from MCF7 and A549 cells. Single entity measurements showed clear spikes due to the detection of oxidizable cargo within EVs from MCF7 and A549 cells. These studies highlight the promise of monitoring EVs through the presence of varying electroactive components within the cargo and can drive a wave of new strategies towards specific detection of EVs for diagnosis and prognosis of various diseases.

Electrochemical Characterization of Neurotransmitters in a Single Submicron Droplet.

Single-entity electrochemistry, which employs electrolysis during the collision of single particles on ultramicroelectrodes, has witnessed significant advancements in recent years, enabling the observation and characterization of individual particles. Information on a single aqueous droplet (e.g., size) can also be studied based on the redox species contained therein. Dopamine, a redox-active neurotransmitter, is usually present in intracellular vesicles. Similarly, in the current study, the electrochemical properties of neurotransmitters in submicron droplets were investigated. Because dopamine oxidation is accompanied by proton transfer, unique electrochemical properties of dopamine were observed in the droplet. We also investigated the electrochemical properties of the adsorbed droplets containing DA and the detection of oxidized dopamine by the recollision phenomenon.

Emerging Data Processing Methods for Single-Entity Electrochemistry.

Single-entity electrochemistry is a powerful tool that enables the study of electrochemical processes at interfaces and provides insights into the intrinsic chemical and structural heterogeneities of individual entities. Signal processing is a critical aspect of single-entity electrochemical measurements and can be used for data recognition, classification, and interpretation. In this review, we summarize the recent five-year advances in signal processing techniques for single-entity electrochemistry and highlight their importance in obtaining high-quality data and extracting effective features from electrochemical signals, which are generally applicable in single-entity electrochemistry. Moreover, we shed light on electrochemical noise analysis to obtain single-molecule frequency fingerprint spectra that can provide rich information about the ion networks at the interface. By incorporating advanced data analysis tools and artificial intelligence algorithms, single-entity electrochemical measurements would revolutionize the field of single-entity analysis, leading to new fundamental discoveries.

Multiscale Analysis of Electrocatalytic Particle Activities: Linking Nanoscale Measurements and Ensemble Behavior.

Nanostructured electrocatalysts exhibit variations in electrochemical properties across different length scales, and the intrinsic catalytic characteristics measured at the nanoscale often differ from those at the macro-level due to complexity in electrode structure and/or composition. This aspect of electrocatalysis is addressed herein, where the oxygen evolution reaction (OER) activity of ß-Co(OH)2 platelet particles of well-defined structure is investigated in alkaline media using multiscale scanning electrochemical cell microscopy (SECCM). Microscale SECCM probes of ∼50 µm diameter provide voltammograms from small particle ensembles (ca. 40-250 particles) and reveal increasing dispersion in the OER rates for samples of the same size as the particle population within the sample decreases. This suggests the underlying significance of heterogeneous activity at the single-particle level that is confirmed through single-particle measurements with SECCM probes of ∼5 µm diameter. These measurements of multiple individual particles directly reveal significant variability in the OER activity at the single-particle level that do not simply correlate with the particle size, basal plane roughness, or exposed edge plane area. In combination, these measurements demarcate a transition from an "individual particle" to an "ensemble average" response at a population size of ca. 130 particles, above which the OER current density closely reflects that measured in bulk at conventional macroscopic particle-modified electrodes. Nanoscale SECCM probes (ca. 120 and 440 nm in diameter) enable measurements at the subparticle level, revealing that there is selective OER activity at the edges of particles and highlighting the importance of the three-phase boundary where the catalyst, electrolyte, and supporting carbon electrode meet, for efficient electrocatalysis. Furthermore, subparticle measurements unveil heterogeneity in the OER activity among particles that appear superficially similar, attributable to differences in defect density within the individual particles, as well as to variations in electrical and physical contact with the support material. Overall this study provides a roadmap for the multiscale analysis of nanostructured electrocatalysts, directly demonstrating the importance of multilength scale factors, including particle structure, particle-support interaction, presence of defects, etc., in governing the electrochemical activities of ß-Co(OH)2 platelet particles and ultimately guiding the rational design and optimization of these materials for alkaline water electrolysis.

Stability Investigations on a Pt@HGS Catalyst as a Model Material for Fuel Cell Applications: The Role of the Local pH.

Increasing the resistance of catalysts against electrochemical degradation is one of the key requirements for the wider use of Proton Exchange Membrane Fuel Cells (PEMFCs). Here, we study the degradation of one entity of a highly stable catalyst, Pt@HGS, on a nanoelectrode under accelerated mass transport conditions. We find that the catalyst degrades more rapidly than expected based on previous ensemble measurements. Corroborated by identical location transmission electron microscopy and catalyst layer experiments, we deduce that locally different pH values are likely the reason for this difference in stability. Ultimately, this work provides insights into the actual conditions present in a PEMFC and raises questions about the applicability of accelerated stress tests usually performed to evaluate catalyst stability, particularly when they are performed in half-cell setups under inert gas.

Probing conformational kinetics of catalase with and without magnetic field by single-entity collision electrochemistry.

The conformational motions of enzymes are crucial for their catalytic activities, but these fluctuations are usually spontaneous and unsynchronized and thus difficult to obtain from ensemble-averaged measurements. Here, we employ label-free single-entity electrochemical measurements to monitor in real time the fluctuating enzymatic behavior of single catalase molecules toward the degradation of hydrogen peroxide. By probing the electrochemical signals of single catalase molecules at a carbon nanoelectrode, we were able to observe three distinct current traces that could be attributed to conformational changes on the sub-millisecond timescale. Whereas, nearly uniform single long peaks were observed for single catalase molecules under a moderate magnetic field due to the restricted conformational changes of catalase. By combining high-resolution current signals with a multiphysics simulation model, we studied the catalytic kinetics of catalase with and without a magnetic field, and further estimated the maximum catalytic rate and conformational transition rate. This work introduces a new complementary approach to existing single-molecule enzymology, giving further insight into the enzymatic reaction mechanism.

Food safety in health: a model of extraction for food contaminants.

Contaminants are the critical targets of food safety supervision and risk assessment. In existing research, food safety knowledge graphs are used to improve the efficiency of supervision since they supply the relationship between contaminants and foods. Entity relationship extraction is one of the crucial technologies of knowledge graph construction. However, this technology still faces the issue of single entity overlap. This means that a head entity in a text description may have multiple corresponding tail entities with different relationships. To address this issue, this work proposes a pipeline model with neural networks for multiple relations enhanced entity pairs extraction. The proposed model can predict the correct entity pairs in terms of specific relations by introducing the semantic interaction between relation identification and entity extraction. We conducted various experiments on our own dataset FC and on the open public available data set DuIE2.0. The results of experiments show our model reaches the state-of-the-art, and the case study indicates our model can correctly extract entity-relationship triplets to release the problem of single entity overlap.

Imaging the Footprint of Nanoscale Electrochemical Reactions for Assessing Synergistic Hydrogen Evolution.

This work proposes a novel method for measuring the intrinsic activity of single metal-based nanoparticles towards water reduction in neutral media at industrially relevant current densities. Instead of using gas nanobubbles as proxy, the method uses optical microscopy to track the local footprint of the reaction through the precipitation of metal hydroxide, which is associated to the local pH increase during electrocatalysis. The results show the electrocatalytic activities of different types of metal nanoparticles and bifunctionnal core-shell nanostructures made of Ni and Pt, and demonstrate the importance of metal hydroxide nano-shells in enhancing electrocatalysis. This method should be generalizable to any electrocatalytic reaction involving pH changes such as nitrate or CO2 reduction.

Time-Resolved Electrochemical Impedance Spectroscopy of Stochastic Nanoparticle Collision: Short Time Fourier Transform versus Continuous Wavelet Transform.

This work demonstrates the utilization of short-time Fourier transform (STFT), and continuous wavelet transform (CWT) electrochemical impedance spectroscopy (EIS) for time-resolved analysis of stochastic collision events of platinum nanoparticles (NPs) onto gold ultramicroelectrode (UME). The enhanced electrocatalytic activity is observed in both chronoamperometry (CA) and EIS. CA provides the impact moment and rough estimation of the size of NPs. The quantitative information such as charge transfer resistance (Rct ) relevant to the exchange current density of a single Pt NP is estimated from EIS. The CWT analysis of the phase angle parameter is better for NP collision detection in terms of time resolution compared to the STFT method.

Crystalline silica particle functionalized by PEG for its collision-enhanced detection at ultramicroelectrode.

Detecting individual particulate matter is highly significant in many areas, such as mine safety, environment, and human health. The analytical method based on single entity electrochemistry (SEE) has shown great potential in detecting, counting, and measuring individual particles, especially conductive metals or carbon particles, based on their unique charge transfer reactions at an ultramicroelectrode (UME). In this study, we report an innovative SEE method for improving the sensitivity of the detection of electrochemical inert crystalline silica particles by functionalizing silica particles with polyethylene glycol (PEG) molecules. The PEG surface functionalization of the silica was characterized by Fourier-transform infrared (FTIR) spectroscopy and X-ray photoelectron spectroscopy (XPS) techniques. The morphology of silica particles was characterized by a scanning electron microscope (SEM), and a transmission electron microscope (TEM) was employed to calibrate size distribution and determine the elemental composition of silica particles. The surface charges of silica particles were measured by dynamic light scattering techniques. The collision behaviors of crystalline silica particles with UME were investigated by cyclic voltammetric experiments, which are rarely reported in the literature. The crystalline silica particles were detected based on electrochemically blocking the flux of the redox mediator at the surface of UME, which showed significant signal amplification in the proposed method. Our method was demonstrated for detecting crystalline silica functionalized with or without PEG, acquiring the limit of quantification (LOQ) values of 0.391 µM (23.45 µg/L) and 0.824 µM (49.45 µg/L), respectively, which confirmed that a more than two times improvement in LOQ could be achieved over the PEG functionalized silica particles. We further presented a theoretical model using finite element simulations with COMSOL Multiphysics. We deduced a quantitative relation between the distribution of the current step size and the size distribution of silica particles. Therefore, the reported method here provides a paradigm for SEE-based detection of electrochemically inert crystalline silica particles, which extends the previous report substantially concerning particle detection.

Electrochemical Analysis of Attoliter Water Droplets in Organic Solutions through Partitioning Equilibrium.

Herein, we report the electrochemical monitoring of attoliters of water droplets in an organic medium by the electrolysis of an extracted redox species from the continuous phase upon collisional events on an ultramicroelectrode. To obtain information about a redox-free water droplet in an organic solvent, redox species with certain concentrations need to be contained inside it. The redox species inside the droplet were delivered by a partitioning equilibrium between the organic phase and the water droplets. The mass transfer of the redox species from the surrounding organic phase to the droplet is very fast because of the radial diffusion, which resultantly establishes the equilibrium. Upon the collisional contact between the droplet and the electrode, the extracted redox species in the water droplets were selectively electrolyzed, even though the redox species in the organic continuous phase remained unreacted because of the different solvent environments. The electrolysis of the redox species in the droplets, where the concentration is determined by the equilibrium constant of the redox species in water/oil, can be used to estimate the size of single water droplets in an organic solution.

Crystal Plane-Related Oxygen-Evolution Activity of Single Hexagonal Co3 O4 Spinel Particles.

The electrocatalytic activity for the oxygen evolution reaction in alkaline electrolyte of hexagonal spinel Co3 O4 nanoparticles derived using scanning electrochemical cell microscopy (SECCM) is correlated with scanning electron microscopy and atomic force microscopy images of the droplet landing sites. A unique way to deconvolute the intrinsic catalytic activity of individual crystal facets of the hexagonal Co3 O4 spinel particle is demonstrated in terms of the turnover frequency (TOF) of surface Co atoms. The top surface exposing 111 crystal planes displayed a thickness-dependent TOF with a TOF of about 100 s-1 at a potential of 1.8 V vs. RHE and a particle thickness of 100 nm. The edge of the particle exposing (110) planes, however, showed an average TOF of 270±68 s-1 at 1.8 V vs. RHE and no correlation with particle thickness. The higher atomic density of Co atoms on the edge surface (2.5 times of the top) renders the overall catalytic activity of the edge planes significantly higher than that of the top planes. The use of a free-diffusing Os complex in the alkaline electrolyte revealed the low electrical conductivity through individual particles, which explains the thickness-dependent TOF of the top planes and could be a reason for the low activity of the top (111) planes.

Single-entity Electrochemistry Unveils Dynamic Transformation during Tandem Catalysis of Cu2 O and Co3 O4 for Converting NO3 - to NH3.

Electrochemically converting nitrate to ammonia is an essential and sustainable approach to restoring the globally perturbed nitrogen cycle. The rational design of catalysts for the nitrate reduction reaction (NO3 RR) based on a detailed understanding of the reaction mechanism is of high significance. We report a Cu2 O+Co3 O4 tandem catalyst which enhances the NH3 production rate by ≈2.7-fold compared to Co3 O4 and ≈7.5-fold compared with Cu2 O, respectively, however, most importantly, we precisely place single Cu2 O and Co3 O4 cube-shaped nanoparticles individually and together on carbon nanoelectrodes provide insight into the mechanism of the tandem catalysis. The structural and phase evolution of the individual Cu2 O+Co3 O4 nanocubes during NO3 RR is unveiled using identical location transmission electron microscopy. Combining single-entity electrochemistry with precise nano-placement sheds light on the dynamic transformation of single catalyst particles during tandem catalysis in a direct way.

Advances in optical counting and imaging of micro/nano single-entity reactors for biomolecular analysis.

Ultrasensitive detection of biomarkers is of paramount importance in various fields. Superior to the conventional ensemble measurement-based assays, single-entity assays, especially single-entity detection-based digital assays, not only can reach ultrahigh sensitivity, but also possess the potential to examine the heterogeneities among the individual target molecules within a population. In this review, we summarized the current biomolecular analysis methods that based on optical counting and imaging of the micro/nano-sized single entities that act as the individual reactors (e.g., micro-/nanoparticles, microemulsions, and microwells). We categorize the corresponding techniques as analog and digital single-entity assays and provide detailed information such as the design principles, the analytical performance, and their implementation in biomarker analysis in this work. We have also set critical comments on each technique from these aspects. At last, we reflect on the advantages and limitations of the optical single-entity counting and imaging methods for biomolecular assay and highlight future opportunities in this field.