Real-Time Ultrasonic Monitoring of Dynamic Material Properties in Soft Hydrogels: Distinguishing Concurrent Degradation and Shrinkage Mechanisms

Real-time monitoring of degradation mechanisms in soft hydrogel materials remains challenging due to the limitations of conventional measurement techniques. Here, we present a comprehensive ultrasonic framework that overcomes these limitations by introducing the bulk modulus as a primary diagnostic parameter, enabling discrimination between degradation pathways that time-of-flight measurements cannot distinguish. Our multiparameter approach simultaneously tracks acoustic velocity, attenuation, dynamic bulk modulus, temporal waveforms, phase shift contours, and frequency spectral characteristics in both immersion and air-coupled configurations. Critically, this methodology detects material softening even during concurrent physical shrinkage conditions, where traditional measurements remain unchanged despite substantial material degradation. By leveraging acoustic pressure variations and temporal delays, the dynamic bulk modulus provides unambiguous identification of material property changes independent of geometric effects. Experimental validation on agar and gelatin gels reveals 4 distinct degradation processes: swelling-induced softening, surface melting, dehydration-induced shrinkage with hardening, and shrinkage-induced surface roughening with crack propagation. The air-coupled configuration demonstrates superior sensitivity for detecting surface deformation and crack initiation, with frequency-domain analysis providing early indicators of geometric distortion up to 10 h before visual confirmation. Coupling material stability testing verified reliable operation for 45-h continuous monitoring periods. The framework successfully differentiates between these competing mechanisms in real time, addressing a fundamental challenge in soft materials’ characterization. This work establishes the first comprehensive platform for real-time degradation monitoring in soft materials, with immediate applications in biomedical device development, food processing optimization, tissue phantom preservation, and advanced materials engineering, where conventional techniques fail to capture the full complexity of material evolution. The methodology shows strong potential for extension to elastomeric materials in harsh environments, providing a robust foundation for industrial monitoring applications.