Detection and classification of gaseous sulfur compounds by solid electrolyte cyclic voltammetry of cermet sensor...

Area of Science:

• Electrochemistry
• Chemical Sensing
• Materials Science

Background:

• Toxic industrial chemicals (TICs) pose significant health risks.
• Accurate detection of specific hazardous gases is crucial for occupational safety.
• Existing sensor technologies may lack selectivity or robustness for complex gas mixtures.

Purpose of the Study:

• To develop and validate an electrochemical sensor array for detecting multiple sulfur-containing gases.
• To assess the sensor array's performance in identifying SO(2), H(2)S, and CS(2) among 11 TIC compounds.
• To evaluate a signal processing and classification approach for reliable gas identification.

Main Methods:

• Utilized a sensor array of four ceramic-metallic (cermet) solid electrolyte sensors.
• Employed cyclic voltammetry to generate current-voltage profiles for analytes.
• Processed raw voltammograms via background subtraction, signal concatenation, wavelet transformation, and probabilistic neural network classification.
• Trained models on one sensor array and validated on a second, independent array.

Main Results:

• Successfully identified and classified SO(2), H(2)S, and CS(2) with high true positive rates (up to 96.7%).
• Achieved low false positive rates for sulfur compounds (≤2.2%), interferents (≤0.9%), and clean air (≤5.8%).
• Demonstrated effective detection of sulfur compounds at concentrations from 10% to 200% of their Threshold-Limited Value (TLV).

Conclusions:

• Cermet-based electrochemical sensor arrays offer a rugged, low-cost, and reusable platform for multi-compound gas detection.
• The integrated signal processing and classification method enables reliable identification of specific sulfur gases in complex mixtures.
• This technology shows significant promise for real-time monitoring of hazardous sulfur compounds at parts-per-million (ppm) levels.