Quantifying nonlinear electric-acoustic mixing in lead zirconium titanate with a vector network analyzer

Published

July 17, 2025

Author(s)

Robert Lirette, Tomasz Karpisz, Malgorzata Musial, Gabriela Petculescu, Aaron Hagerstrom, Nathan Orloff, Angela Stelson

Abstract

Accurate electric and acoustic material properties impact the agreement between modeled and measured piezoelectric device performance. Designing devices such acoustic transducers, filters, and duplexers requires accurate electrical permittivity, piezoelectric coefficients, and acoustic sound speed of the material. While there are methods for measuring some of these properties at a range of frequencies, there are few metrologies for measuring the relationships between nonlinear electric and acoustic properties, as given by the mixing products. Here, we test a method for extracting the properties of lead zirconium titanate by measuring the nonlinear mixing of electric and acoustic waves. Our experiment used a block lead zirconium titanate mounted on top of a coplanar waveguide that was connected to a vector network analyzer. A transducer acoustically actuated lead zirconium titanate from above, which modulated the electrical signal in the coplanar waveguide. A vector network analyzer in frequency offset mode measured the modulation as second order mixing products. The proof-of-concept results show many coupled electric-acoustic modes that are significant relative to the noise floor of the vector network analyzer. Broader impacts of the research could be new metrologies for measuring nonlinear susceptibilities.

Citation

Applied Physics Letters

Pub Type

Journals

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Keywords

electromagnetic, measurement science, microwaves, ultrasound

Citation

Lirette, R. , Karpisz, T. , Musial, M. , Petculescu, G. , Hagerstrom, A. , Orloff, N. and Stelson, A. (2025), Quantifying nonlinear electric-acoustic mixing in lead zirconium titanate with a vector network analyzer, Applied Physics Letters, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=958783 (Accessed January 7, 2026)