Machine-learning-guided design of MOF-based electrocatalysts for sustainable ammonia production

-reduction prototypes into advanced catalysts that can convert nitrates and nitrites into ammonia. This offers a broader perspective on the electrochemical nitrogen cycle. However, their structural complexity poses significant challenges to traditional design and optimization approaches. This review first critically summarizes the recent advances in MOF development for electrochemical ammonia synthesis. Next, this review systematically explores the transformative role of machine learning (ML) in advancing MOF research. It also addresses the 8 major challenges and limitations currently facing this intersection, including data scarcity, model interpretability, and inverse design. To address these challenges and…

• MO
  Ministry of Education - Singapore

  Awards: 2020-T1-001-031, RT6/22
• MO
  Ministry of Education, India