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A Simple, Low-cost, and Robust System to Measure the Volume of Hydrogen Evolved by Chemical Reactions with Aqueous Solutions
Published on: August 17, 2016
Engineering Synergistic Pd-Ni Co-Modified System for Highly Efficient Hydrogen Sensing
Beixi An1, Yeong Jae Kim2, Jiaqi Yan1
1School of Physical Science and Technology, Lanzhou University, 222 South Tianshui Road, Lanzhou 730000, China.
ACS Sensors
|June 10, 2026
Summary
This study introduces a new palladium-nickel oxide (Pd-NiO) modified tungsten oxide (WO3) sensor for enhanced hydrogen detection. The novel sensor offers high sensitivity and selectivity at low temperatures, improving safety in hydrogen applications.
Area of Science:
- Materials Science
- Chemical Engineering
- Sensor Technology
Background:
- Hydrogen sensors are crucial for safety in hydrogen production, storage, and transport.
- Palladium-based sensors offer good hydrogen selectivity but suffer from Pd oxidation and agglomeration, degrading performance.
- Developing sensors with low operating temperatures, high sensitivity, and selectivity remains a key challenge.
Purpose of the Study:
- To develop a novel bimetallic sensor using palladium-nickel oxide (Pd-NiO) co-modified WO3 nanospheres.
- To enhance hydrogen sensing performance, particularly at low operating temperatures.
- To investigate the synergistic effects of NiO doping on Pd-WO3 sensor characteristics.
Main Methods:
- Synthesis of Pd-NiO/WO3 nanospheres via a bimetallic modulation strategy.
- Characterization of sensor performance including response, selectivity, and stability at 160 °C.
- Mechanistic studies involving oxygen adsorption and Pd oxidation suppression.
- Machine learning-assisted gas discrimination for enhanced selectivity.
Main Results:
- The Pd-NiO/WO3 sensor demonstrated a high response (25) to 50 ppm H2 at 160 °C, significantly outperforming Pd-WO3.
- Achieved fast response-recovery times, excellent hydrogen selectivity, and good long-term stability.
- NiO doping effectively suppressed Pd oxidation and enhanced catalytic activity.
- Machine learning achieved 95.8% classification accuracy for gas discrimination.
Conclusions:
- The bimetallic Pd-NiO/WO3 nanosphere strategy offers synergistic effects for superior hydrogen sensing performance.
- The developed sensor shows practical applicability, reliably detecting hydrogen from water-splitting devices.
- This approach provides an effective route for engineering advanced synergistic co-modified systems for high-performance hydrogen sensing.
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