The article discusses the potential of hydrogen as an alternative energy carrier for emission reduction, focusing on its application in fuel cells, particularly Proton Exchange Membrane Fuel Cells (PEMFCs). PEMFCs are highlighted for their role in generating electricity with no local pollution, attracting interest from major automobile manufacturers like Honda and Toyota. The complexity of modeling PEMFC systems is addressed through advancements in mathematical modeling and studies examining various aspects such as materials, system integration, degradation, and operation modes. Additionally, machine learning algorithms are explored as a promising alternative for modeling PEMFCs due to their robustness and ability to directly link experimental conditions to device performance. The study also delves into high-temperature PEMFCs, emphasizing their simpler fuel processing and waste heat recovery potential. By incorporating deep learning with multiphysics simulation, the researchers aim to establish a hybrid model that optimizes fuel cells efficiently. The sentiment towards hydrogen and PEMFCs in the article is positive, highlighting their potential in revolutionizing energy generation and contributing to environmental sustainability.