Reproducible Laser-Induced Graphene Electrodes for Electrochemical Conductivity Sensing Enabled by Full Factorial Design of Experiments
Year: 2026
Type: article
Abstract: Laser-induced graphene (LIG) enables scalable fabrication of conductive carbon electrodes directly on polymer substrates, but variations in laser-processing conditions can affect electrode properties and sensing reliability. In this work, a full factorial design of experiments was used to investigate how laser power, scan speed, focus offset, and scan cycle number influence LIG fabrication and quantitative aqueous conductivity sensing. Sheet resistance was used to identify under-exposed, optimized, and over-exposed processing regimes. Representative conditions were further characterized using surface and quasi-cross-sectional scanning electron microscopy, Raman spectroscopy, dynamic water contact-angle measurements, and cyclic voltammetry. Optimized conditions produced continuous porous LIG layers approximately 25–27 µm thick, with lower sheet resistance, more uniform graphitic structure, larger apparent electroactive surface area, and more defined ferri/ferrocyanide redox responses. Dynamic contact-angle measurements also revealed processing-dependent wetting behavior. Optimized and non-optimized electrodes were then compared as functionalization-free conductivity sensors using broadband electrochemical impedance spectroscopy and equivalent-circuit fitting to isolate bulk solution resistance. Over 13.33–3740 µS cm⁻¹, the optimized electrode produced a log–log resistance–conductivity slope of −0.944, approaching the theoretical inverse relationship, with measurement-to-measurement and sensor-to-sensor relative standard deviations of 1.79% and 3.00%, respectively. These results establish a fabrication–structure–impedance–conductivity relationship for reproducible LIG-based conductivity sensing in aqueous environmental monitoring applications.
Source: ECS Sensors Plus
Authors: NIHAL AHMED, Michael Neubauer, Stephan Warnat
Institution: Montana State University
Language: English
Subfield: Analytical Chemistry
Field: Chemistry
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,500
OpenAlex ID: W7225807659
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