Dataset associated with: Operando optical imaging reveals beyond-meniscus nanoelectrochemistry mediated by a nanometric wetting film

Supplementary Movie 1: 20211126_LG_PtNPs_20211108_10mM_KCl_CV1.avi Description: raw optical movie discussed in Figure 2 Corresponding electrochemical data: Louis_2021-11-26_001_CV1.asc Python script for standard image analysis as described in Materials and methods: image_treatment_CV1.py Corresponding SEM images: Pt_KCl_1_00-07.tif Supplementary Movie 2: 20211126_LG_PtNPs_20211108_10mM_KCl_CV2.avi Description: raw optical movie discussed in Figure 1, 2 and 3 Corresponding electrochemical data: Louis_2021-11-26_001_CV2.asc Python script for standard image analysis as described in Materials and methods: image_treatment_CV2.py Python script to analyze the Pt NPs inside the droplet as reported in Figure S1: image_treatment_CV2_inside_droplet.py Python script to extract the optical transients of all Pt NPs located outside the droplet: image_treatment_CV2_variance1.py; generates a well-defined last frame CV2_last_frame_b.png, the array CV2_outside_pos.txt containing the positions of all Pt NPs, and the array CV2_outside_trans.txt containing their optical transients Python script to analyze the variance of the optical transients as reported in Figure 3: image_treatment_CV2_variance2.py Python script to evaluate the voltage drop as reported in Figure 3: ohmic_drop.py; uses simulated data from ref 29 contained in simulations_rectification_model.csv Corresponding SEM images: Pt_KCl_2_00-23.tif Supplementary Movie 3: 20211201_LG_ITO_10mM_KCl_A_CV1.avi Description: raw optical movie discussed in Figure 5 Corresponding electrochemical data: Louis_2021-12-01_001_CV1.asc Python script for image analysis based on the Farnebäck algorithm can be provided upon reasonable request Corresponding SEM images: A_last-2_00-01.tif correlations.py: Python script that, as shown in Figure 2, plots the correlations between maximum current, size, and distance using data from several Pt NPs analyzed in SM2 and compiled in correlations_data.csv