Machine learning helps find advantageous combination of salts and organic solvents for easier anti-icing operations

Researchers at Osaka Metropolitan University used machine learning to identify an effective, environmentally friendly deicing mixture. Analyzing 21 salts and 16 organic solvents, they discovered that a propylene glycol-sodium formate mixture had superior ice penetration capacity. This new deicer requires less material, reducing environmental impact and corrosion, making it suitable for airport runways. The study highlights the advantages of combining salts and organic solvents, providing insights for efficient deicing and anti-icing operations with minimal environmental consequences.

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