Interference-fit adhesive-free miniature class IV flextensional transducer for high-amplitude precision bone surgery

Abstract

Precision bone surgery requires ultrasonic devices capable of delivering large blade displacement with low cutting force, high precision, tissue selectivity, and minimal collateral damage. Conventional ultrasonic surgical devices are predominantly based on bolted Langevin transducers (BLTs), which rely on stacked piezoelectric elements sandwiched between metallic end masses. Although effective, BLT configurations require resonant operation to achieve sufficient blade amplitude and typically involve elongated waveguides, restricting miniaturisation and manoeuvrability for robotically assisted minimally invasive procedures. Flextensional transducers offer an alternative actuation approach by mechanically amplifying the small strains of a piezoelectric element through flexural deformation of a metallic shell. However, conventional class IV designs rely on adhesive bonding between the piezoelectric element and the shell, introducing viscoelastic damping, thermal degradation, and increased risk of interfacial failure under high excitation levels required for bone cutting. In this work, we present a novel adhesive-free miniature class IV flextensional transducer that employs a monolithic titanium shell and a negative interference-fit assembly to impose structural pre-stress on a piezoelectric plate. This configuration eliminates epoxy bonding while enabling stable high-power excitation and enhanced mechanical robustness. Electromechanical characterisation demonstrates that, with appropriate impedance matching and resonance tracking, the device achieves continuous blade displacement amplitudes exceeding 100 µm peak-to-peak. Ex vivo porcine bone cutting experiments confirm effective material removal at low ultrasonic power with precise cut morphology. The proposed adhesive-free flextensional architecture provides a compact, high-amplitude, and mechanically reliable solution for precision bone surgery and establishes a promising pathway toward integration with robotic platforms for minimally invasive surgical applications.

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ORCID for Xuan Li: orcid.org/0000-0002-5655-8631

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