Current Opinion in Electrochemistry最新文献

Fundamental insights into electrode–electrolyte interfaces are crucial for our understanding of electrochemical processes. Standard electrochemical methods, such as cyclic voltammetry, can reveal important information about the systems of interest. Nevertheless, information about structure and morphology of the electrode–electrolyte interface is not that easily accessible. In situ scanning tunnelling microscopy can resolve the electrode as well as the direct interface to the electrolyte in real time during electrochemical measurements. This includes changes of the electrode in the nanometre to micrometre range, for example, during metal deposition or corrosion, as well as the observation of ordered molecular adlayers on the electrode. In this work, we want to highlight the capabilities of such studies to better understand the fundamental processes of electrocatalysis and metal deposition and dissolution, which are essential to electrochemical energy storage systems.

Anode catalysis reduces the cost and remarkably improves the fuel cell performance; however, it is often neglected owing to its fast kinetics. Currently, the majority of hydrogen is obtained by reforming and purifying the hydrocarbons containing impurities such as CO, CO₂, and H₂S. CO adsorbs more strongly than hydrogen onto the anode catalysts, inhibiting hydrogen oxidation and resulting in performance degradation. Although activity enhancement is essential, impurity tolerance should be preferred over activity for fuel-cell anode catalysts. Various studies have reported improved CO tolerance via lowering the intrinsic CO adsorption energy of the catalyst by tuning the electronic structure or modulating the OH adsorption energy by placing oxophilic materials near the catalysts. Herein, we categorize recent noteworthy studies according to their strategies and present innovative design principles for CO-resistant anode catalysts.

The ferro-/ferricyanide couple has been extensively investigated as a redox species in various redox flow batteries (RFBs) due to its advantageous electrochemical properties, user-friendliness, and affordable cost. However, the high concentration and stability of ferro-/ferricyanide are important for developing high-energy density and long-cycle life RFBs. Different methods have been explored to increase its concentration through diverse ion effects and cation modification while also exploring the effects of pH, light, and air sensitivity on its stability. This review will provide an overview of recent research on the concentration enhancement of ferro-/ferricyanide and its stability for RFBs.

The recent integration of machine learning into materials design has revolutionized the understanding of structure–property relationships and optimization of material properties beyond the trial-and-error paradigm. On one hand, machine learning has significantly accelerated the development of atomically dispersed metal-nitrogen-carbon (M-N-C) electrocatalysts, which traditionally heavily relied on heuristic approaches. On the other hand, the primary challenge of leveraging machine learning to expedite M-N-C materials discovery lies in the cost associated with data collection. We review recent machine learning integration strategies for M-N-C catalyst development, including discussions on the typical algorithms such as symbolic regression and convolutional neural networks employed for the theoretical design, synthesis optimization via active learning, and advanced microscopy characterization. Subsequently, we provide our perspective on potential near-future directions for furthering machine learning-assisted development of new M-N-C catalysts and elucidating the complex physicochemical mechanisms governing the selectivity, activity, and durability in this class of materials.

Materials degradation is a major factor that limits the wider adoption of renewable and clean energy technologies. This is particularly true for the Pt group metal-free (PGM-free) atomically dispersed metal-nitrogen-carbon (M-N-C) catalysts. While many experimental studies have investigated and reported the phenomenological aspects of M-N-C degradation, only a few modeling studies have considered degradation mechanisms at the atomic level. Understanding the mechanisms responsible for activity loss occurring in atomically dispersed M-N-C’s is crucial towards rationally designing active, durable, and less expensive Earth-abundant catalysts. Towards this end, we have surveyed recent literature concerning the modeling of corrosion mechanisms that impact M-N-C catalysts (Fe–N–C, in particular) and offer our own perspectives on the future direction of this field.

Coulombic efficiency (CE) is a crucial metric in battery research, particularly for aqueous Zinc (Zn)-metal batteries. Nonetheless, the accurate determination of Zn CE is complicated due to a lack of awareness about charge loss triggered by the hydrogen evolution reaction (HER) and non-standardized testing conditions. This study reveals the governing factors affecting the Zn CE measurement under different testing conditions, such as applied current density, Zn-plating capacity, and half-cell platforms. Through literature and experimental studies, it is evident that the Zn CE inherently increases with higher current densities and capacities. When decoupling the actual potentials of HER and Zn deposition, HER-triggered parasitic reactions can be self-suppressed owing to greater overpotential for HER than for Zn-plating at higher current densities. A consistent trend was observed when using different Zn salts and current collectors. This awareness can help standardize CE measuring protocols for validating novel concepts and materials.

The advancement of photocatalytic technologies requires complete system efficiency, and to this end, electrochemical sensors have the potential to complement and enhance the development of semiconductor catalyst and reactor design. A particular advantage of electroanalysis is that the sensors may be incorporated directly into photocatalytic reactors to allow real-time in situ analysis. This can then facilitate more accurate process control in the photocatalytic reactor. This report highlights the use of electroanalysis to monitor photocatalytic processes, considering applications where it has been used to date. Relevant properties of the sensors, with particular interest on sensitivity and response times are detailed alongside comparison to the more commonly used analytical techniques. It also explores the most recent progressions beyond monitoring photocatalytic remediation processes including photocatalytic valorization and reactive oxygen species monitoring.