Advanced optical assessment and modeling of extrusion bioprinting | Scientific Reports

Summary

The article discusses a modular imaging setup for bioprinting that leverages machine learning for improved data analysis and quality control. The setup enables real-time monitoring and calculation of parameters like strut width and throughput, which can be crucial for understanding fluid dynamics, non-Newtonian fluid behavior, and related mathematical identities. These improvements can aid in analyzing complex behaviors such as vorticity and the Clausius–Duhem inequality in bioprinting environments. The key concept 'machine learning' relates to the tags and article by providing a method to enhance the accuracy and automation of the bioprinting process, optimizing control over fluid dynamics and ensuring consistency in non-Newtonian fluid applications.