Machine learning helps find favorable combinations of salt and organic solvents to make de-icing easier

A research team from Osaka Metropolitan University used machine learning to analyze the ice-melting mechanisms of aqueous solutions of 21 types of salt and 16 types of organic solvents to discover a highly effective de-icing mixture with low environmental impact. Scientific Reports June 7, 2024.

The dangers of icy roads, airplane engines, and runways are well known, but the use of commercial products often prioritizes short-term safety over long-term environmental degradation. In search of a better product, researchers at Osaka Metropolitan University developed an anti-freeze mixture that outperforms commercial anti-freezes but has less environmental impact.

The research team, consisting of graduate student Kai Ito, Assistant Professor Arisa Fukatsu, Associate Professor Kenji Okada, and Professor Masahide Takahashi of the Graduate School of Engineering, used machine learning to analyze the ice melting mechanism of aqueous solutions of 21 types of salt and 16 types of organic solvents. After conducting experiments, they found that a mixture of propylene glycol and sodium formate solution showed the best ice penetration ability.

The effectiveness of this mixture means less material is used, reducing the impact on the environment, and it is non-corrosive, meaning it can be used on airport runways, for example, to prevent damage.

“We are proposing an effective and environmentally friendly deicing agent that combines the advantages of salt and organic solvents,” said Dr. Fukatsu.

The results of this study also provide new insights into the ice melting process.

“The development of high-performance deicing agents is expected to make deicing and anti-icing operations easier,” Professor Takahashi added. “This will also reduce the amount of deicing agent used and its impact on the environment.”