Standing Surface Acoustic Waves (SSAWs) generated on a piezoelectric substrate are largely used to create stable surface force patterns in active lab-on-a-chip devices. This study presents the development and experimental validation of a full-domain 3D digital twin for a SSAW device based on 128° YX LiNbO3, commonly used for acoustofluidic applications. The model is developed in COMSOL Multiphysics to accurately capture the electromechanical interactions that govern SSAW generation and its interaction with the substrate. Its predictive accuracy is validated through electrical characterization with a vector network analyzer and surface displacement mapping with a laser Doppler vibrometer, demonstrating strong agreement between simulations and experimental data. This validation proves the reliability of digital twins for predictive modeling and design optimization of SSAW devices, offering a more precise and efficient alternative to traditional models and trial-and-error approaches.

Full‐Domain 3D Digital Twin for Comprehensive Analysis and Validation of Standing Surface Acoustic Wave Generation on LiNbO 3 Substrate

Sfregola, Felice Alberto;Zifarelli, Andrea;Spagnolo, Vincenzo;Patimisco, Pietro
2026-01-01

Abstract

Standing Surface Acoustic Waves (SSAWs) generated on a piezoelectric substrate are largely used to create stable surface force patterns in active lab-on-a-chip devices. This study presents the development and experimental validation of a full-domain 3D digital twin for a SSAW device based on 128° YX LiNbO3, commonly used for acoustofluidic applications. The model is developed in COMSOL Multiphysics to accurately capture the electromechanical interactions that govern SSAW generation and its interaction with the substrate. Its predictive accuracy is validated through electrical characterization with a vector network analyzer and surface displacement mapping with a laser Doppler vibrometer, demonstrating strong agreement between simulations and experimental data. This validation proves the reliability of digital twins for predictive modeling and design optimization of SSAW devices, offering a more precise and efficient alternative to traditional models and trial-and-error approaches.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11586/578845
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