Toward Standardized Methods for Reproducible Air-Driven Needle-Induced Cavitation Experiments

Abstract

Background

Needle-induced cavitation (NIC) is a commonly used technique for probing the mechanical properties of soft matter. However, its measurements often exhibit substantial variability, limiting reproducibility and interpretability. Such inconsistencies obscure meaningful trends in material behavior and hinder quantitative comparisons across studies.

Objective

This study aims to identify and quantify key experimental factors contributing to variability in NIC measurements and to develop refined protocols that enhance measurement reproducibility for soft polymer gels.

Methods

NIC experiments were systematically conducted on poly(methyl methacrylate)–poly(n-butyl acrylate)–poly(methyl methacrylate) triblock copolymer gels, focusing on the effects of sample preparation, thermal equilibration, and syringe pump configuration on needle-tip pressurization dynamics and cavitation pressure. A predictive framework for pressurization dynamics was developed.

Results

The refined sample preparation protocol, which minimized solvent evaporation and improved temperature control, reduced batch-to-batch variability by up to 70% and improved repeatability in mechanical property extraction. Insufficient thermal equilibration was found to substantially reduce cavitation pressure, with values decreasing by nearly 50% in response to sample temperature increases of only 3\(^\circ \)C prior to testing. Controlled needle retraction had little to no meaningful effect on cavitation pressure values. Model predictions agreed well with experimental results, highlighting the importance of controlling the pressurization rate. Radial position experiments confirmed that changing the sample geometry from cylindrical to annular did not introduce measurable boundary effects.

Conclusions

These findings establish practical guidelines for improving the reproducibility of NIC experiments and provide a validated framework for more robust and quantitative characterization of soft matter systems.