Abstract

The development of fast and precise systems for biofluid characterization has become increasingly important due to the complexity of their kinetics and the dynamic molecular interactions within them. These interactions reveal structural changes in biopolymers when interacting with other agents. Monitoring these processes is essential to understand the underlying mechanisms of such interactions. This study presents an open-source software solution designed to control and monitor ultrasonic transducers and real-time measurement of biofluid properties. It was developed in Python and integrated with custom hardware to perform frequency sweeps 650% faster than commercial devices such as the LCR-8101G; therefore, it reduces data acquisition time to 0.169 seconds per sample. This improvement enables detailed kinetic studies of biofluids, as demonstrated by the characterization of Bovine Serum Albumin (BSA)-urea interactions. The system's modular design allows for easy integration of additional sensors, such as temperature probes, which can enhance the characterization process by providing more comprehensive data. Furthermore, the software's compatibility with machine learning models opens the door to advanced predictive capabilities, potentially allowing for real-time identification of biofluid properties based on ultrasonic response. The findings of this study validate the effectiveness of the software in accelerating data acquisition without compromising sensitivity; hence, it is a valuable tool for researchers studying evolving phenomena in biofluids. Future work will focus on further expanding the system's capabilities, standardizing the software for broader adoption, and exploring its application in various experimental scenarios to enhance the understanding of biofluid behavior under different conditions.