journal article·2025-09-05

Surface Air Plasma Treatment of Laser-Induced Graphene-Based Electrodes for Enhanced Electrochemical Sensing Performance

Saumik Dey Shovan, Shapour Jafargholinejad, Mohamad Kannan Idris, Carlos Rodríguez Perales, Aamir Minhas-Khan, Pouya Rezai, Gerd Grau

ACS Applied Nano Materials· Volume 8· Issue 35
Publisher page

Abstract

Laser-induced graphene (LIG) is a cost-effective and sustainable single-step electrode fabrication technique for electrochemical applications that eliminates the need for additional materials or complex processing. Plasma treatment has been applied to enhance the electrochemical performance of LIG electrodes. However, the effect of varying treatment durations on LIG performance remains unexplored, leaving a gap in understanding whether electrochemical properties improve gradually with increased exposure time. We investigate the effect of air plasma treatment time (0–120 s) on the electrochemical and material properties of LIG electrodes. Treatment intervals are set at 10 s from 0–60 s for detailed trend analysis, with an extended 120 s point. Cyclic voltammetry (CV) and material characterization techniques determine the optimal treatment time of the 50 s that enhances sensor performance by balancing increased surface reactivity with overexposure. Compared to untreated electrodes, the optimized electrodes exhibited a 243% increase in CV current, a 25-fold reduction in charge transfer resistance ( R ct ) measured via electrochemical impedance spectroscopy (EIS), a 10-fold lower limit of detection (LOD) for potassium ferrocyanide/ferricyanide. Additionally, the treated sensors maintained stable performance over 14 days, demonstrating their long-term reliability. These findings highlight the importance of plasma treatment optimization in enhancing the performance of LIG-based electrochemical sensors.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Gas Sensing Nanomaterials and Sensors · Analytical Chemistry and Sensors · Electrochemical sensors and biosensors

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Electrical Engineering and Computer Science, Lassonde School of Engineering

York University

Department of Mechanical Engineering, Lassonde School of Engineering

Academic Unit of Electrical Engineering

Autonomous University of Zacatecas

Funding

York University · Natural Sciences and Engineering Research Council of Canada

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