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We demonstrate that the corrosion of AISI 1045 medium carbon steel and pure aluminum can be quantified by the turn-off fluorescent sensor Phen Green-SK (PGSK) in ethanol-based solutions. We first evaluate the dependence of the chelation enhanced quenching of PGSK on iron and aluminum ion concentrations. Subsequently, we apply PGSK to examine the anodic dissolution of metal corrosion. The observed time-dependent PGSK-quenching quantifies the corrosion rates of two metals over 24 h of immersion in ethanol-based solutions. The PGSK-based quantification of corrosion is compared to scanning electron microscopy and electrochemical techniques, including open circuit potential and Tafel extrapolation. The corrosion rates calculated from PGSK-quenching and Tafel extrapolation are in agreement, and both indicate a decrease in corrosion rates over 24 h. Our work shows PGSK can efficiently sense and quantify anodic corrosion reactions at metal interfaces, especially in organic solvents or other non-aqueous environments where the application of electrochemical techniques can be limited by the poor conductivity of the surrounding medium. 

Abstract Laser color marking produces nearly permanent, environmentally friendly, vibrant colors on surfaces. However, previous work has used high‐power‐density pulsed lasers to induce the physicochemical reactions for marking. Here, laser color marking on stainless steel 304 (SS304) is performed with a less expensive continuous wave (CW) laser and a power density five orders of magnitude below that previously reported by combining an electrochemical cell with a fluorescence microscope. Using a combination of optical microscopy, x‐ray photoelectron spectroscopy, and bulk electrochemistry, it is demonstrated that the laser‐induced luminescence and colors are due to enrichment (32 ± 9% increase) of Cr₂O₃in the SS304 passive film. It is shown that the enrichment proceeds by a different chemical mechanism than the oxygen pyrolysis that occurs in typical laser color marking. The technique provides a new pathway for laser color marking of metals in industrial settings with applications as diverse as solar absorbers or corrosion prevention. 

Interfacial oxidation–reduction reactions have important applications in corrosion and catalysis, but traditional electrochemical cell methods cannot be used to study these reactions in non-conducting environments such as non-aqueous solvents. We demonstrate that the molecule resazurin that can be reduced to highly-fluorescent resorufin is compatible for sensing in non-aqueous solvents. We characterize the spectral properties of the dyes in ethanol, dimethylformamide (DMF), acetone, and dimethyl sulfoxide (DMSO), showing a ∼10× increase in intensity for “turned-on” resorufin compared to resazurin in all four solvents. We then apply resazurin to sense corrosive reduction reactions at iron surfaces. Increases in fluorescence intensity due to resazurin reduction to resorufin are observed in ethanol, acetone, and DMSO, while DMF had no turn-on. Our work shows that fluorescent dyes have considerable potential to be used to understand redox reactions in non-aqueous solvents, but care must be taken to understand the interplay between the dye, the solvent, and the reactions occurring. 

Abstract Single-molecule FRET (smFRET) is a versatile technique to study the dynamics and function of biomolecules since it makes nanoscale movements detectable as fluorescence signals. The powerful ability to infer quantitative kinetic information from smFRET data is, however, complicated by experimental limitations. Diverse analysis tools have been developed to overcome these hurdles but a systematic comparison is lacking. Here, we report the results of a blind benchmark study assessing eleven analysis tools used to infer kinetic rate constants from smFRET trajectories. We test them against simulated and experimental data containing the most prominent difficulties encountered in analyzing smFRET experiments: different noise levels, varied model complexity, non-equilibrium dynamics, and kinetic heterogeneity. Our results highlight the current strengths and limitations in inferring kinetic information from smFRET trajectories. In addition, we formulate concrete recommendations and identify key targets for future developments, aimed to advance our understanding of biomolecular dynamics through quantitative experiment-derived models.