Machine learning-based framework to enhance hydrogen flow rate in proton-exchange membrane water electrolysis: From prediction to cell design suggestion

Key Points

• Enhanced hydrogen flow rates were identified using a machine learning-based framework, indicating potential design improvements.
• The analysis showed a notable increase in efficiency related to the electrolysis process through optimized parameters.
• The approach involved a machine learning framework that predicts flow rates and suggests design modifications for better outcomes.
• These findings highlight the potential for machine learning to optimize water electrolysis for hydrogen production, emphasizing the need for practical applications.