Most commercial ammonia sensors rely on solid materials that absorb gas molecules and undergo chemical reactions – a process that limits their response speed.
Triboelectric nanogenerator probes (TENG-P), which generate electrical signals through liquid-solid contact electrification, can operate on millisecond timescales but have traditionally lacked gas-sensing capability.
The research team addressed this limitation by drawing inspiration from the alveoli of the human respiratory system. Like alveoli, which use air-filled cavities to enable efficient gas exchange, the new sensor employs air-cavity droplets, or A-droplets, as mobile gas carriers.
These droplets capture ammonia from the surrounding air and deliver it directly to the sensing interface.
The Triboelectric Mechanism
Each A-droplet consists of a water shell surrounding a small air cavity and is produced using a coaxial injection system that precisely controls droplet size and stability. When an A-droplet strikes the sensor surface, it briefly forms a closed electrical circuit, producing a signal through liquid-solid contact electrification.
Ammonia diffuses into the droplet and dissolves in the water, where it ionizes into ammonium (NH4+) and hydroxide (OH-) ions. These ions alter the charge-transfer process at the interface between the droplet and the sensor’s fluorinated ethylene propylene (FEP) triboelectric layer.
As ammonia concentration increases, competitive ion adsorption suppresses electron transfer, producing a measurable reduction in electrical output.
While the interfacial charge-transfer event itself occurs within milliseconds, the overall sensing response – defined as the time required for the signal to stabilize – is governed by the droplet release cycle.
In this system, the response time is 1.4 seconds, faster than most reported ammonia sensors.
Stability Through Droplet Hydrodynamics
A key advantage of the air-cavity droplet design lies in its physical stability. Unlike conventional droplets, A-droplets resist rebound, fragmentation, and surface instability upon impact with the sensor.
The internal air cushion suppresses fluid disturbances such as Kelvin-Helmholtz instability, leading to highly repeatable contact areas and reduced signal noise.
This hydrodynamic control contributes to an output stability of 96.2 %, a critical factor for reliable sensing in real-world environments.
The sensor responds linearly to ammonia concentrations between 0 and 200 parts per million and shows negligible response to other common gases, including hydrogen sulfide, methane, oxygen, nitrogen, and carbon monoxide.
This selectivity arises from ammonia’s strong tendency to dissolve in water, in contrast to gases that interact only weakly with the droplet.
Long-term tests demonstrated stable operation over temperatures from 0 to 50 °C and relative humidity levels from 50 % to 90 %. Variations caused by environmental conditions can be corrected through algorithmic calibration.
Moving from Sensor to Smart Monitoring
To demonstrate practical use, the researchers integrated the droplet sensor into a wireless monitoring system. Electrical signals are processed by a microcontroller, converted from analogue to digital form, and transmitted via Bluetooth to display devices in real time.
The team further applied a deep-learning classification model based on a YOLO11 convolutional neural network to analyse time-frequency patterns in the sensor signals.
This approach enabled automated identification of five discrete ammonia concentration levels, achieving a peak classification accuracy of 98.4 %.
By combining bioinspired droplet design, hydro-electrochemical sensing, and machine-learning-assisted signal analysis, the study demonstrates an alternative pathway for gas detection that avoids the speed limitations of traditional solid-state sensors.
The authors suggest that the air-cavity droplet concept could be extended to other gases and sensing scenarios, offering a foundation for future multifunctional and intelligent gas-monitoring systems.
Journal Reference
Liu T., et al. (2026). Bioinspired triboelectric droplet sensor for ammonia monitoring. Nature Communications. DOI: 10.1038/s41467-026-68974-4