Impedance spectroscopy is a widely used electrochemical technique with a wide variety of applications. Many of these applications benefit from the additional accessibility provided by low-cost impedance devices. With this in mind, a low-cost impedance device was designed for a high performance-to-cost ratio. The performance of this analyzer was validated against a high-performance DropSens µStat-i 400s potentiostat by performing an application-based experiment. Nitrate detection provides a relevant experiment because of the importance of maintaining precise nitrate concentrations to mitigate the impact of nitrate fluctuations on the environment. Dissolved nitrate samples of different concentrations, in the range 3–1000 $\mathrm{m}\mathrm{g}/\mathrm{L}$, were confirmed colorimetrically and measured with both instruments. A calibration curve of the real impedance matched a sigmoidal transfer, with a linear region for concentrations below 10 mg/L. The device under investigation exhibited an average magnitude error of 1.28% and an average phase error of $0.96$${}^{\circ }$ relative to the high-performance standard, which validates the performance of the low-cost device. A cost analysis is presented that highlights some of the complexities of cost comparisons.

The development of low-cost impedance spectroscopy devices is limited by the capabilities of low-cost hardware. Impedance spectroscopy requires high accuracy over a large bandwidth and dynamic range for most applications. In this paper, back-end signal processing solutions are examined and implemented to improve both the bandwidth and dynamic range of a typical low-cost impedance analyser without modifying the hardware. The bandwidth is improved by undersampling the input waveforms and reconstructing the signals based on the known frequency information. The bandwidth can be increased by multiple orders of magnitude and the limiting factor of the system becomes amplifier bandwidth and the Analog-to-Digital Converter (ADC) sample-and-hold circuit. Despite allowing signals to become orders of magnitude larger than the ADC range, the original signal can be reconstructed based on the measured saturated signal. This saturation technique more than doubles the dynamic range for any given accuracy requirement.

The adverse health effects of the presence of lead in wastewater streams are well documented, with conventional methods of lead recovery and removal suffering from disadvantages such as high energy costs, the production of toxic sludge, and low lead selectivity. Klebsiella pneumoniae and Paraclostridium bifermentans have been identified as potential lead-precipitating species for use in a lead recovery bioreactor. Electrical impedance spectroscopy (EIS) on a low-cost device is used to determine the potential for the probe-free and label-free monitoring of cell growth in a bioreactor containing these bacteria. A complex polynomial is fit for several reactive equivalent circuit components. A direct correlation is found between the extracted supercapacitance and the plated colony-forming unit count during the exponential growth phase, and a qualitative correlation is found between all elements of the measured reactance outside the exponential growth phase. Strong evidence is found that Pb(II) ions act as an anaerobic respiration co-substrate for both cells observed, with changes in plated count qualitatively mirrored in the Pb(II) concentration. Guidance is given on the implementation of EIS devices for continuous impedance monitoring.

This study investigates the use of impedance spectroscopy for fingerprinting aqueous salt solutions. By analysing solutions containing Sodium Nitrate (${\mathrm{NaNO}}_3$), Sodium Sulphate (${\mathrm{Na}}_2{\mathrm{SO}}_4$), and their mixtures, we explore how impedance data can potentially be used to distinguish between different salt compositions and concentrations. Our findings demonstrate the potential of this method for precise solution characterisation as well as highlighting the benefits of access to low-cost impedance analysers such as the one used for this investigation. More research and data is required to fully realise the potential of this approach.

This work introduces a digital post-processing algorithm—level-crossing downsampling (LC-DS)—for estimating sine-wave parameters from sequences of quantized values acquired by standard ADCs. LC-DS emulates level-crossing sampling by retaining only transition points, reducing correlated quantization error and accelerating least-squares regression. Its performance is benchmarked against uniform least-squares regression and calibrated sinefit to highlight accuracy and computational trade-offs. Across a wide dynamic range, LC-DS consistently outperforms uniform sampling and approaches the accuracy of calibrated sinefit for low-level signals, while remaining up to two orders of magnitude faster for large datasets. Unlike conventional methods, LC-DS scales efficiently with data size, enabling real-time estimation without hardware modifications. Practical and simulated experiments, including electrochemical impedance spectroscopy, confirm robustness under conditions such as signal saturation. These results position LC-DS as a compelling alternative for applications requiring both high precision and computational efficiency.