Electrochemical sensor for rapid acrylamide detection in drinking water

Overview

This solution offers a rapid, low-cost electrochemical screening tool for detecting acrylamide in drinking water. Acrylamide is a potentially harmful contaminant that can form during high-temperature cooking processes and enter water supplies, posing health concerns that require reliable monitoring. The sensor leverages waste coffee grounds (WCG) as a sustainable electrode material combined with metallo-porphyrin chemistry to achieve direct electrochemical detection of acrylamide at potentials where dissolved oxygen does not interfere. This approach provides water utilities, food manufacturers, and environmental testing laboratories with an accessible alert system for acrylamide presence in water samples.

Technical specifications

Key features:

• Sensor platform: An array of up to ten working electrodes printed on a single sensor chip using patented flexographic carbon printing technology
• Electrode modification: Each working electrode is modified with different metallo-porphyrins (such as iron-based porphyrins) that interact directly with acrylamide molecules
• Sustainable materials: Waste coffee grounds serve as the carbon source for graphitic electrode material, reducing production costs and environmental impact
• Stable attachment: Porphyrin molecules remain firmly attached to the graphitic electrode surface through noncovalent π–π interactions
• Detection method: Differential pulse voltammetry generates response curves across multiple electrode types
• Data processing: Artificial neural network (ANN) modelling combines responses from individual electrodes to recognize acrylamide concentration patterns
• Experimental design: Fractional factorial design enables efficient measurement across multiple acrylamide concentration levels

Technology readiness level

The technology is currently at an early-to-mid stage of development. Preliminary laboratory results have demonstrated that amides can interact directly with metallo-porphyrins under specific potentials, establishing the scientific basis for the approach. The research team is now seeking funding for a research assistant to advance the project over a six-month period. The next phase involves printing the multi-electrode sensor chip, completing the matrix of voltammetric measurements, and developing the ANN-based pattern recognition algorithm for concentration determination. Upon successful completion of this validation phase, the technology will be positioned for further development toward field deployment and commercialization.