Terahertz metamaterial liquid detector optimized by deep learning
Xuyan Li, Zhibo Wu, Yujie Zhang, Bin Li · 2025
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Description
Xuyan Li and co-authors build in 2025 a terahertz sensor that sniffs ethanol in liquid without any labels or reagents. The detector is a patterned metamaterial: interlaced copper wires and nested double letter rings of a phase change oxide on a plastic film over a copper plate. A liquid drop on its surface shifts the device's absorption peak, and the shift's size reports what is in the drop.
A deep neural network tuned the structure's dimensions, reaching high absorption and strong shifts across working conditions. Simulations showed the peak sliding one way as drop volume grows, the other way as ethanol strength rises, and narrowing its spacing as temperature climbs. Field and current maps revealed the mechanism, including the oxide waking up when hot and steadying the read. The authors pitch the design for food safety checks, environmental monitoring, and biomedical sensing.
Catalog record
| CREATOR | Xuyan Li, Zhibo Wu, Yujie Zhang, Bin Li |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 31 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |