Background
Bubble size distribution is a critical parameter in froth flotation, a process widely used in mineral processing to separate valuable minerals from gangue. Accurate measurement of bubble sizes is essential for optimizing flotation efficiency, yet many existing tools for bubble analysis are proprietary, limiting accessibility and reproducibility. To address this, we developed Bubble Analyser, an open-source software that allows researchers to measure bubble size distributions transparently and collaboratively. By ensuring the software is open and accountable, we provide the global scientific community with a powerful, adaptable tool that enhances research reproducibility and fosters innovation in flotation science.
Our Contribution
With the support of the Research Software Engineering (RSE) department at Imperial College London through their Open-Source Booster (OSB) initiative, we transitioned Bubble Analyser from MATLAB to Python. Dr Diego Alonso, Head of RSE, provided invaluable advice on software structure, user interface design, and best practices for maintainability and documentation. His insights guided the implementation of a modular, scalable architecture that enhances usability and future extensibility. The project also benefited from the contributions of Mr. Yiyang Guan, an undergraduate student at the Department of Earth Science and Engineering (ESE), who developed key components of the new version as part of his MSci research. Moving to Python allows for broader collaboration and paves the way for integrating open-source AI algorithms for automated image segmentation in the future.
Outcomes
The redevelopment of Bubble Analyser has had a significant impact on our research, providing a fully open-source, shareable tool that enables accurate bubble size distribution measurements. The software’s improved maintainability ensures long-term usability, and its Python implementation facilitates seamless integration with modern data science techniques. This tool has already contributed to our research publications and conference presentations in the past, so we expect to continue producing collaborative science through this initiative. As we continue to refine and expand Bubble Analyser, we look forward to leveraging AI-driven image analysis to push the boundaries of flotation research.
Testimonials
Dr. Diego Mesa, founder of Bubble Analyser, Research Fellow, Department of Earth Science & Engineering:
“Having the opportunity to work with experts in software development while focusing on the science has been invaluable. The guidance from the RSE department has helped us build a tool that is not only scientifically rigorous but also robust, user-friendly, and ready for future advancements.”