journal article·2022-02-23

A Soft Sponge Sensor for Multimodal Sensing and Distinguishing of Pressure, Strain, and Temperature

Li-Wei Lo, Junyi Zhao, Haochuan Wan, Yong Wang, Shantanu Chakrabartty, Chuan Wang

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Abstract

Soft wearable sensors are essential components for applications such as motion tracking, human-machine interface, and soft robots. However, most of the reported sensors are either specifically designed to target an individual stimulus or capable of responding to multiple stimuli (e.g., pressure and strain) but without the necessary selectivity to distinguish those stimuli. Here we report an elastomeric sponge-based sensor that can respond to and distinguish three different kinds of stimuli: pressure, strain, and temperature. The sensor utilizes a porous polydimethylsiloxane (PDMS) sponge fabricated from a sugar cube sacrificial template, which was subsequently coated with a poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) conductive polymer through a low-cost dip-coating process. Responses to different types of stimuli can be distinguished by simultaneously recording resistance and capacitance changes. Because pressure, tensile strain, and temperature change result in different trends in resistance and capacitance change, those stimuli can be clearly distinguished from each other by simultaneously measuring the resistance and capacitance of the sensor. We have also studied the effect of the pore size on the sensor performance and have found that the sponge sensor with smaller pores generally offers greater resistance change and better sensitivity. As a proof-of-concept, we have demonstrated the use of the porous sponge sensor on an artificial hand for object detection, gesture recognition, and temperature sensing applications.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Conducting polymers and applications · Tactile and Sensory Interactions

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

Affiliations

Department of Electrical & Systems Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States

Institute of Materials Science and Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States

Department of Obstetrics & Gynecology, Washington University in St. Louis, St. Louis, Missouri 63130, United States

Funding

Bill and Melinda Gates Foundation

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