Authors: Seyedamirhossein Mohseni Armaki | Yaqi Guo | Roan Streefland | Patrick Baeuerlein | J.M.C. Mol | Majid Ahmadi | Santosh Kumar | Peyman Taheri
Source: ECS Meeting Abstracts (article, 2025-07-11)
Field: Chemistry — Electrochemistry

Detection of Heavy Metal Ions Based on Frequency-Dependent Physicochemical Processes at the Electrode/Electrolyte Interface Real-time, in situ monitoring of aqueous environments is crucial for addressing pressing challenges in environmental protection, public health, and industrial processes. Detecting contaminants in water, analyzing biomarkers in biological fluids, and ensuring the safety of consumables require analytical techniques that are accurate, sensitive, rapid, cost-effective, and non-invasive. Traditional laboratory-based methods, while reliable, are predominantly ex situ—they involve expensive equipment, are time-consuming, and often risk altering sensitive samples during analysis. These limitations underscore the urgent need for innovative sensing technologies capable of providing immediate and reliable data without compromising sample integrity. Electrochemical sensors have emerged as promising candidates due to their affordability, simplicity, and potential for miniaturization. However, conventional DC-based electrochemical sensors largely rely on redox reactions, which involve electron transfer processes that can degrade the electrode surface over time. This degradation limits the sensors' reusability and longevity, making them less suitable for continuous monitoring applications. When a solid electrode contacts an electrolyte, an interface known as the electric double layer (EDL) forms. The structure of the EDL depends on the properties of the both the electrodes (e.g., roughness and work function), and the electrolyte (e.g., composition and concentration). This interfacial structure holds significant potential for sensing applications. Historically, double-layer capacitance has been the primary focus of EDL studies; however, it represents only one aspect of the interface. Electrochemical impedance spectroscopy (EIS) at steady-state conditions offers a compelling alternative to redox-based sensing. Operating under open-circuit potential (OCP) conditions, EIS minimizes electrode degradation and sample alteration by avoiding electrochemical reactions. By measuring impedance over a range of frequencies, EIS provides detailed, multidimensional insights into interfacial processes. Despite its potential, the adoption of EIS has been hindered by a lack of theoretical clarity. Traditional approaches rely heavily on empirical fitting models, such as equivalent electrical circuits, which fail to capture the physical and chemical phenomena occurring at the interface. This reliance on empirical models limits the predictive power of EIS and raises concerns about the reliability of its data, as observed responses often appear random or incidental without a solid theoretical basis. To address this gap, a comprehensive theoretical model of EIS must justify both the DC properties of the interface, such as EDL capacitance, and the non-ideal behavior of impedance, including phenomena like the constant phase element (CPE). The origin of the CPE has remained elusive, often incorporated empirically rather than derived from first principles. This theoretical shortfall has contributed to skepticism about the reliability and interpretability of EIS data, especially for applications requiring precise and predictable sensor responses. In this work, we present a robust theoretical model for the electrode/electrolyte interface, grounded in continuum mechanics and incorporating fundamental ion properties such as size, mobility, and spatial distribution near the electrode surface. This model provides a comprehensive framework that explains general impedance behavior while also accounting for non-idealities such as the CPE phenomena. Additionally, we investigate how ion properties influence impedance behavior, demonstrating their significant impact on the EIS response. Building on this theoretical foundation, we conducted extensive experimental studies using over 500 aqueous solutions containing zinc, lead, and cadmium salts paired with various anions such as sulfate, chloride, and nitrate. Our experimental results align closely with model predictions, confirming that ions with different characteristics significantly influence the impedance response. Recognizing the complexity of these relationships, we utilized machine learning algorithms to analyze the experimental data. This approach enabled accurate prediction of ion concentrations based on their impedance signatures, showcasing the practical utility and the reliability of EIS as a sensitive and robust electrochemical sensing method. Electrolyte ; Electrode ; Interface (matter) ; Ion ; Metal ions in aqueous solution ; Materials science ; Metal ; Inorganic chemistry ; Chemistry ; Analytical Chemistry (journal) ; Environmental chemistry ; Metallurgy ; Physical chemistry ; Composite material ; Organic chemistry Electrochemical Analysis and Applications ; Advanced Chemical Sensor Technologies ; Analytical Chemistry and Sensors