Hello, I am trying to perform a Mott-Schottky analysis for anodized TiO2 nanotube arrays. The ac voltage is 10 mV and the frequency is 1 kHz. I am performing a DC scan from -0.6V to 0.4V vs. Ag/AgCl at a rate of 10 mV/s. However, upon performing the analysis, the results are very noisy. I do not get noisy data when performing EIS (Nyquist plot). Is it possibly due to the nature of my sample? I tried at different scan rates (1, 10 and 20 mV/s) and frequencies (1 kHz vs. 10 kHz) but to no avail. If there are any papers that can aid with counteracting Mott-Schottky pitfalls, I would be grateful.
An Insight into the Role of Oxygen Vacancy in Hydrogenated TiO 2
Nanocrystals in the Performance of Dye-Sensitized Solar Cells
DOI: 10.1021/am5085447
Noisy data in Mott-Schottky analysis can arise due to several reasons:
Instrumentation Noise: Noise present in the measurement instrument or data acquisition system, such as fluctuations in the voltage or current readings, can introduce noise into the data.
Electrical Interference: Electrical interference from nearby devices, power lines, or other sources can corrupt the measurements and lead to noisy data.
Environmental Factors: Temperature variations, humidity, and other environmental factors can affect the measurement setup, leading to fluctuations in the data.
Imperfections in the Sample: The presence of impurities, defects, or variations in the composition of the sample being analyzed can introduce noise into the measured data.
Electrode Interface: The interface between the electrode and the sample can introduce noise due to factors like surface roughness, adsorption/desorption processes, or differences in the contact resistance.
Sample Preparation: Improper sample preparation techniques or handling procedures can introduce artifacts or imperfections, leading to noisy data.
To ensure accurate results, it is important to minimize noise in Mott-Schottky analysis by employing proper experimental techniques, using high-quality measurement instruments, shielding against electrical interference, maintaining stable environmental conditions, and carefully preparing and handling the samples. Additionally, appropriate data processing techniques, such as signal filtering or averaging, can be employed to reduce the impact of noise on the final analysis.
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