| Title: | Frequency-domain analysis of voltammetric signals : a framework to augment electrochemical sensing explored through benzenediol detection |
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| Authors: | ID Krishnamurthy, Abhilash, Institut "Jožef Stefan" (Author)
ID Žagar, Kristina, Institut "Jožef Stefan" (Author) |
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| Files: |  URL - Source URL, visit https://www.sciencedirect.com/science/article/pii/S0263224125030659?via%3Dihub
 PDF - Presentation file, download (6,14 MB)
MD5: EA1C29CA9456410A7F5A24B312BE91F7
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| Language: | English |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: |  IJS - Jožef Stefan Institute
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| Abstract: | Electrochemical signals are traditionally interpreted in the time domain, where overlapping faradaic and non-faradaic currents, noise, and drift obscure frequency-dependent behaviour. This study introduces a frequency-domain framework that complements time-domain analysis by decomposing voltammetric signals into their harmonic components through Fourier methods. AC voltammetry provides experimental evidence of how increasing excitation frequency progressively suppresses faradaic clarity, while a modified Randles equivalent circuit model explains this response through the interplay of charge-transfer, diffusion, and double-layer charging processes. Fourier series analysis of canonical voltammetric techniques, including linear sweep, cyclic, differential pulse, and square wave voltammetry, shows that waveform geometry uniquely defines harmonic structure. Fast Fourier transform analysis of practical data reveals artefacts introduced by finite sampling, binning, and spectral leakage. These effects highlight the need for conceptual awareness when interpreting experimental spectra. Quantitative spectral descriptors such as the centroid, bandwidth, flatness, and low-frequency power fraction link waveform design directly to faradaic visibility and measurement clarity. Frequency-domain analysis therefore establishes that electrochemical measurement is inherently frequency-structured. By combining experimental data, equivalent circuit modelling and spectral metrics within a single framework, this approach provides a general route to optimise waveform parameters, reduce capacitive interference, and improve interpretability across electrochemical techniques. Viewed more broadly, this perspective reframes the process of the measurement itself, showing that time-domain signals are projections of an underlying spectral reality. |
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| Keywords: | frequency domain, spectral decomposition, electrochemical sensors, benzenediols |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 17.06.2025 |
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| Article acceptance date: | 10.11.2025 |
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| Publication date: | 12.11.2025 |
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| Publisher: | Elsevier |
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| Year of publishing: | 2026 |
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| Number of pages: | str. 1-12 |
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| Numbering: | Vol. 259, pt. B, [article no.] 119706 |
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| Source: | Nizozemska |
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| PID: | 20.500.12556/DiRROS-24836  |
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| UDC: | 544.5/.6 |
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| ISSN on article: | 1873-412X |
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| DOI: | 10.1016/j.measurement.2025.119706 |
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| COBISS.SI-ID: | 262276611 |
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| Copyright: | © 2025 The Author(s). |
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| Note: | Nasl. z nasl. zaslona;
Opis vira z dne 19. 12. 2025;
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| Publication date in DiRROS: | 22.12.2025 |
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| Views: | 9 |
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| Downloads: | 8 |
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