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Research data supporting "Purely electrical detection of electrolyte concentration through microfluidic impedance spectroscopy"


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Description

The data comprises of impedance spectra measured using a Sciospec ISX3v2 impedance analyser, of a novel device consisting of aerosol-jet printed silver interdigitated electrodes integrated into a microfluidic channel. Each impedance spectrum (.spec file) consists of some metadata, followed by the measured real (Re / Ohms) and imaginary (Img / Ohms) components measured at each measurement frequency (Freq / Hz). The subfolders contain experimental details. For example, the concentration of the chemical species (in millimolar, mM), and the species. The final subfolder contains information regarding the measurement channel (e.g. '2-4'). Each channel is connected to one pair of electrodes, which lie under 1 channel csv files are also provided, which have been exported from the code, and contain the impedance spectra and important features (such as the turning point frequency of the capacitance-frequency curves). This enables plotting of the data without running the complete analysis code, if required. The code consists of various Jupyter Notebooks (ipynb) (Python 3.7), which have been used to analyse the data. Each dataset has a separate associated Jupyter Notebook. The 'source' of the code should be input, and must match the directory of the data on the user's computer. Each function contains a short description, and all functions are called by the 'analysis_all()' function at the end of the script. Comments are present to explain specifics of the code where relevant. Together, the data and code have been used to determine the concentration of 'unknown' solutions, and to investigate various properties of the device.

Version

Software / Usage instructions

Code was run using Jupyter Notebooks (Python 3.7)

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Rights and licensing

Except where otherwised noted, this item's license is described as Attribution 4.0 International (CC BY 4.0)
Sponsorship
EPSRC (2438201)
T.W. acknowledges support from an EPSRC Doctoral Training Partnership studentship (EP/T517847/1). L.I. acknowledges support from an EPSRC Doctoral Training Partnership studentship (EP/R513180/1). S.K.-N. acknowledges support from UK Research and Innovation (UKRI) under the UK government’s Horizon Europe funding guarantee (EP/Y032535/1). This research was supported by the joint collaboration project between GSK Consumer Healthcare and the University of Cambridge through the Centre for Advanced Photonics and Electronics consortium.