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Updated: Nov 21, 2025

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Published on: February 1, 2022
Graphene Nanoparticle-Based, Nitrate Ion Sensor Characteristics
Mohammad Taghi Ahmadi1, Morteza Bodaghzadeh1, Seyed Saeid Rahimian Koloor2,3
1Nanotechnology Research Center, Nano-Physic Group, Physics Department, Urmia University, Urmia 5756151818, Iran.
This study developed a novel carbon nanoparticle sensor for detecting nitrate ions in wastewater. The sensor, made from high-density polyethylene, effectively identified various nitrate compounds, offering a promising solution for environmental monitoring.
Area of Science:
- Environmental Science
- Materials Science
- Nanotechnology
Background:
- Nitrate ion contamination from industry and agriculture is a significant environmental issue.
- Carbon-based nanomaterials offer unique properties ideal for sensing applications.
Purpose of the Study:
- To develop and evaluate a novel sensor for detecting nitrate ions in environmental samples.
- To utilize high-density polyethylene (HDPE) as a carbon source for sensor fabrication.
Main Methods:
- Fabrication of a metal-nanoparticle-metal (MNM) sensor using pulsed arc discharge with HDPE as the carbon source.
- Testing the sensor's response to various nitrate compounds (NaNO3, Pb(NO3)2, Zn(NO3)2, NH4NO3) at different concentrations.
- Investigating the sensor's current-voltage (I-V) characteristics and comparing experimental results with simulations and analytical models.
Main Results:
- The fabricated graphene nano-strand sensor successfully recognized and detected multiple nitrate compounds.
- The sensor demonstrated distinct I-V characteristics for different nitrate ions and concentrations.
- Simulations and analytical investigations showed good agreement with the measured sensor performance.
Conclusions:
- The proposed HDPE-derived carbon nanoparticle sensor is effective for identifying nitrate ions in wastewater.
- This technology presents a viable approach for environmental monitoring of nitrate pollution.
- The study validates the sensor's performance through experimental, analytical, and simulation methods.
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