2022
DOI: 10.26434/chemrxiv-2022-0w70n
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Reflective microscopy for mechanistic insights in corrosion research

Abstract: Reflective microscopy (RM) is a robust, label free optical imaging technique that allows fast operando measurements of structural changes on metal interfaces at nanoscale in a wide field. Based on the analysis of the reflected light, RM can be simply understood as “video camera” to produce optical photographs of studied interfaces and thus, it has been used for many years as a complementary tool for the visual inspection. However, recent developments in the optical models and refining the experimental design p… Show more

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Cited by 1 publication
(2 citation statements)
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“…RM is a label-free optical imaging technique that utilizes the local changes in the refractive index of the imaged interface to reveal various (electro-)chemical phase conversions. [13][14][15][16][17][18][19][20][21] This technique is particularly useful for detecting bubble formation, changes in surface film thickness and roughness, and ion intercalations. [15,17,[22][23][24][25][26] RM is widely employed in the field of surface science, both as a standalone method and in combination with other local techniques such as nanopipet approaches.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…RM is a label-free optical imaging technique that utilizes the local changes in the refractive index of the imaged interface to reveal various (electro-)chemical phase conversions. [13][14][15][16][17][18][19][20][21] This technique is particularly useful for detecting bubble formation, changes in surface film thickness and roughness, and ion intercalations. [15,17,[22][23][24][25][26] RM is widely employed in the field of surface science, both as a standalone method and in combination with other local techniques such as nanopipet approaches.…”
Section: Introductionmentioning
confidence: 99%
“…[27][28][29] RM has high temporal and spatial resolution, allowing for measurements with a resolution of approximately 200 nm and acquisition rates up to kHz in a wide field (mm) range. [13,24] However, the generation of large optical datasets also poses significant challenges in processing feature-rich optical images. One common approach is the use of machine vision procedures that employ computer algorithms.…”
Section: Introductionmentioning
confidence: 99%