0
Article ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 2 ? Original research — experimental, observational, or case-control study. Direct primary evidence. Marine & Wildlife Sign in to save

Design Optimization Study of a Capacitive Sensor for Detecting Microplastics in Water

2025 Score: 38 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Anh Dung Nguyen, Thanh H. Nguyen, My-An Tran Le, Tran Van Tung, Dinh Duc Nguyen

Summary

Researchers optimized the design of a capacitive sensor for detecting microplastics in water, incorporating both sensing and reference capacitors to minimize parasitic components and common-mode noise. The study found that the optimized sensor architecture improved detection performance for microplastic particles in aqueous environments.

This study investigates the design optimization of a capacitive sensor for the detection of microplastics in water. To enhance sensor performance and minimize parasitic components as well as common-mode noise, the sensor architecture incorporates both a reference capacitor and a sensing capacitor. The sensor electrode, fabricated from copper, is positioned externally on the water pipe wall. Simulations were conducted with microplastic particles exhibiting a dielectric constant of 1.5 and radii ranging from 50 µm to 350 µm to analyze the sensor’s operational principles. The simulation results indicate a linear relationship between the sensor’s output capacitance and varying microplastic particle sizes. These findings suggest that the proposed sensor architecture holds significant potential for precise microplastic size measurement in aquatic environments

Sign in to start a discussion.

More Papers Like This

Article Tier 2

RF MEMS Resonance Sensor for Measuring Microplastics Concentration

Researchers designed an RF MEMS resonance sensor capable of detecting microplastics in water at low cost, offering a practical alternative to expensive conventional particle analyzers for environmental monitoring.

Article Tier 2

Microfluidic Microwave Sensor for Rapid Detection of Microplastics in Water: Optimization, Modeling, and Performance Evaluation

Researchers developed a microfluidic sensor that uses microwave technology to rapidly detect microplastics in water samples without physical contact. The sensor was optimized to distinguish between different concentrations and sizes of plastic particles with high sensitivity. The technology could enable faster and more practical on-site monitoring of microplastic contamination in water supplies.

Article Tier 2

Detection of microplastics by microfluidic microwave sensing: An exploratory study

Researchers developed a compact microwave sensor on a microfluidic chip to detect microplastics in water samples. The system works by measuring how the presence of plastic particles changes the electrical properties of water. While the technology shows promise as a rapid and portable detection method, its current sensitivity needs improvement before it can detect the low microplastic concentrations typically found in natural freshwater.

Article Tier 2

Size and concentration characterization of microplastic particles in aqueous samples using sensitivity-enhanced coupled planar microwave resonators

Researchers developed a novel microwave sensing platform for real-time detection and characterization of microplastic particles in water samples. The sensor uses an enhanced coupled planar microwave resonator design with a low-cost disposable sample holder, enabling rapid, non-destructive measurement of microplastic particle size and concentration without cross-contamination between tests.

Article Tier 2

Toward Continuous Nano-Plastic Monitoring in Water by High Frequency Impedance Measurement With Nano-Electrode Arrays

Researchers explored high-frequency impedance measurements using CMOS nano-electrode arrays as a potential tool for real-time, label-free monitoring of nanoplastic particles in water, demonstrating nano-scale detection capability with potential for continuous environmental monitoring.

Share this paper