Titanium oxynitride carbon composite nanofibers (TiON/C-CNFs) were synthesised with electrospinning and subsequent heat treatment in ammonia gas. In situ four-probe electrical conductivity measurements of individual TiON/C-CNFs were performed. Additionally, the TiON/C-CNFs were thoroughly analysed with various techniques, such as X-ray and electron diffractions, electron microscopies and spectroscopies, thermogravimetric analysis and chemical analysis to determine the crystal structure, morphology, chemical composition, and N/O at. ratio. It was found that nanofibers were composed of 2–5 nm sized titanium oxynitride (TiON) nanoparticles embedded in an amorphous carbon matrix with a small degree of porosity. The average electrical conductivity of a single TiON/C-CNF was 1.2 kS/m and the bulk electrical conductivity of the TiON/C-CNF fabric was 0.053 kS/m. From the available data, the mesh density of the TiON/C-CNF fabric was estimated to have a characteristic length of 1.0 µm and electrical conductivity of a single TiON/C-CNF was estimated to be from 0.45 kS/m to 19 kS/m. The electrical conductivity of the measured TiON/C-CNFs is better than that of amorphous carbon nanofibers and has ohmic behaviour, which indicates that it can effectively serve as a new type of support material for electrocatalysts, batteries, sensors or supercapacitors.

A novel self-supported architecture, based on carbon nanofibers homogeneously coated by an ultrathin TiON layer and functionalized by a fine dispersion of Ir nanoparticles with ultralow loading (60 microgr*cm-2 with particle size ≈1.5 nm), is presented as a potential anode for proton exchange membrane electrolysis cells. This structure serves as an ideal anode for rapid electrochemical oxygen evolution reaction in acidic conditions. It combines the high conductivity of the carbon-TiON core-shell structure, the chemical stability of the TiON thin layer to protect C against corrosion, and the enhanced mass activity of Ir nanoparticles. Additionally, it offers excellent mechanical stability and a straightforward, scalable fabrication process. The electrochemical activity (80 mA cm-2 / 1.2 mA*g-1Ir @ 1.6 V) outperforms C-Ir and Ir-black references. Preliminary long-term test are carried out and strategies for a potential improvement of the long-term stability are critically discussed.

Understanding and controlling material transformations at the nano- and microscale is vital for advancing technologies that depend on materials with complex, multiscale architectures, such as those used in electrocatalysis, energy storage, and other functional nanomaterials. While conventional scanning electron microscopy (SEM) offers valuable structural information, it typically images random locations before and after treatment, making it difficult to discern true transformations from natural sample heterogeneity. Identical location SEM (IL-SEM) overcomes this limitation by enabling precise re-imaging of the same nanoscale region, thereby providing definitive evidence of structural evolution. When applied through a well-defined protocol, it offers unmatched access to morphology, microstructure, and local composition changes. Despite its simplicity and unique potential for visualizing dynamic material behavior, IL-SEM remains underutilized. Therefore, this article presents a comprehensive guide for the practical implementation of IL-SEM, outlining step-by-step procedures and key considerations to ensure reliable application. We highlight its methodological advantages, identify common challenges, and offer practical solutions. To illustrate IL-SEM’s potential, we showcase representative case studies focused on the dynamic restructuring of various electrocatalysts, including supported nanoparticles and bulk alloys. By providing an optimized workflow and actionable tips, this work positions IL-SEM as a powerful tool for uncovering transformation mechanisms and accelerating progress across materials research disciplines beyond electrocatalysis.

Electrochemical systems are inherently dynamic, often leading to unreliable performance assessments and even degradation. To address this challenge, we developed a self-correcting operando electrochemical impedance spectroscopy (EIS) method, regulated by a custom Python script, enabling non-destructive, real-time, and adaptive control over electrochemical processes. The methods' applicability was demonstrated on copper-catalyzed electrochemical CO2 reduction (ECO2R), a system known for its instability. By dynamically adjusting electrochemical parameters based on live EIS feedback, we effectively neutralized bubble-induced artifacts and achieved reliable tracking of activity and selectivity evolution. Additionally, the approach enabled direct observation of catalyst surface changes under true reaction conditions, yielding accurate operando insights into how interfacial alterations drive ECO2R performance shifts. Altogether, the results presented in this letter establish our method as a versatile operando framework to uncover, correct, and ultimately eliminate artifacts arising from the dynamic behavior of electrochemical systems.