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Printing a Pacinian Corpuscle: Modeling and Performance.

Kieran Barrett-Snyder^1,2, Susan Lane¹, Nathan Lazarus¹

¹Sensors and Electron Devices Directorate, U.S. Army Research Laboratory, Adelphi, MD 20783, USA.

|June 2, 2021

Summary

This summary is machine-generated.

Researchers developed a scalable mechanical model of the Pacinian corpuscle, a vibration-sensing cell. This model accurately predicts the performance of 3D-printed artificial corpuscles, paving the way for new vibration sensors.

Keywords:

3D printing biomimetic soft robotics vibration sensing

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Area of Science:

Biophysics
Mechanical Engineering
Materials Science

Background:

Pacinian corpuscles are mammalian mechanoreceptors with unique band-pass vibration sensitivity.
Their function relies on multiple elastic layers and entrapped viscous fluid.
This structure enables precise detection of mechanical vibrations.

Purpose of the Study:

To develop a scalable mechanical model of the Pacinian corpuscle.
To predict the vibration response of synthetic Pacinian corpuscles.
To explore the potential of 3D-printed artificial corpuscles as novel vibration sensors.

Main Methods:

A scalable mechanical model of the Pacinian corpuscle was developed.
Artificial corpuscles were fabricated using stereolithography (SLA) 3D printing with uncured photoresist.
Multi-layer artificial corpuscles were created with trapped fluid layers analogous to biological structures.
Vibration testing was performed on artificial corpuscles from 20-3000 Hz.

Main Results:

The mechanical model accurately mimicked the -3dB point of biological Pacinian corpuscles.
3D-printed artificial corpuscles demonstrated good agreement with the model's predictions.
The fabricated artificial corpuscles successfully replicated the layered structure with trapped fluid.

Conclusions:

A scalable mechanical model for Pacinian corpuscles has been successfully established.
3D printing offers a viable method for creating artificial Pacinian corpuscles with tunable properties.
These artificial corpuscles show promise as a basis for developing advanced vibration sensors.