journal article·2026-05-20

A Fully Potentiometric Electronic Tongue Enabling Comprehensive Physical and Chemical Sensations

Chun Liang, Ruili Zhou, Xuyi Zhang, Yaoyu Xiao, Xiaodong Wu

ACS Applied Materials & Interfaces· Volume 18· Issue 19
Publisher page

Abstract

The human tongue perceives food through the synergistic sensation of both chemical (taste) and physical (temperature, texture, softness) cues. Inspired by such functionalities, electronic tongues (e-tongues) have been developed for applications ranging from food analysis to biomedical sensing. However, most reported e-tongues primarily capture chemical tastes, overlooking critical physical attributes. In addition, current e-tongues typically rely on heterogeneous sensor outputs (e.g., current, capacitance, impedance), which complicates circuit design and signal processing and leads to high system power consumption. Here, we present a fully potentiometric, monolithically integrated multimodal e-tongue capable of simultaneously sensing chemical attributes (e.g., salinity and acidity) and physical attributes (e.g., temperature, texture, softness) of food. Importantly, all integrated sensors self-generate a unified output─potential difference (mV)─thereby eliminating the need for external power. Such a fully potentiometric sensor integration also greatly simplifies the signal acquisition circuitry and drastically reduces the system power consumption. Assisted by machine learning algorithms, the proposed fully potentiometric e-tongue achieves high accuracy in discrimination of both fruits and beverages, outperforming conventional single-modality e-tongues. This work demonstrates a practical route toward holistic gustatory sensing and offers new opportunities for the development of biomimetic intelligent systems that closely replicate natural taste perception.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Chemical Sensor Technologies · Gas Sensing Nanomaterials and Sensors · Olfactory and Sensory Function Studies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Mechanical Engineering

Sichuan University

College of Computer Science

School of Engineering Science

Royal Institute of Technology

Funding

Sichuan University · Fundamental Research Funds for the Central Universities · Department of Science and Technology of Sichuan Province

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