Flexible Sensory Platform Based on an Electrolyte-Gated Oxide Neuron Transistor
Ning Liu, Li Qiang Zhu, Ping Feng, Chang Jin Wan, Yang Hui Liu, Yi, Shi, Qing Wan

TL;DR
This paper presents a flexible electrolyte-gated oxide neuron transistor platform inspired by biological neurons, demonstrating high sensitivity, rapid response, and ultralow power consumption for biochemical sensing, surpassing traditional limits.
Contribution
The work introduces a novel flexible neuron transistor with dual-gate sensing and spike operation modes, achieving enhanced pH sensitivity and energy efficiency for biochemical detection.
Findings
Achieved pH sensitivity of ~105 mV/pH exceeding Nernst limit
Single-spike mode improves sensitivity and reduces response time
Depression on sensing gate further enhances sensitivity and lowers power consumption
Abstract
Inspired by the dendritic integration and spiking operation of a biological neuron, flexible oxide-based neuron transistors gated by solid-state electrolyte films are fabricated on flexible plastic substrates for biochemical sensing applications. When a quasi-static dual-gate laterally synergic sensing mode is adopted, the neuron transistor sensor shows a high pH sensitivity of ~105 mV/pH, which is higher than the Nernst limit. Our results demonstrate that single-spike dynamic mode can remarkably improve the pH sensitivity, reduce response/recover time and power consumption. We also find that appropriate depression applied on the sensing gate electrode can further enhance the pH sensitivity and reduce the power consumption. Our flexible neuron transistors provide a new-concept sensory platform for biochemical detection with high sensitivity, rapid response and ultralow power consumption.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAnalytical Chemistry and Sensors · Advanced Memory and Neural Computing · Neuroscience and Neural Engineering
