Pulse Explore Journal Club Debates Trending Researchers Journals

Join discussions, follow papers, and never miss your next session.

Download on theApp Store

Home Explore Journal Club Trending

⌘+K

Research Paper | Synapse

January 25, 2026

View Full Paper

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

BHBo HanNanyang Technological University MCMarcus de CarvalhoNanyang Technological University JZJie ZhangNanyang Technological University

Key Points

The aim is to explore how machine learning can enhance the design of MOF electrocatalysts for ammonia production.
Utilizing machine learning algorithms to analyze electrocatalyst performance
Designing metal-organic frameworks (MOFs) based on computational predictions
Evaluating electrocatalytic efficiency for ammonia synthesis
Demonstrated improved efficiency of MOF-based electrocatalysts
Showed potential for reduced energy consumption in ammonia production

Abstract

Machine learning is reshaping the design of MOF electrocatalysts for sustainable ammonia synthesis.

Ask AI

Helpful

Bookmark

Share

View Full Paper

Ask AI

Helpful

Bookmark

Share

View Full Paper

Cite This Study

Han et al. (Thu,) studied this question.

synapsesocial.com/papers/6975b1eafeba4585c2d6d6b4 https://doi.org/https://doi.org/10.1039/d5cc07118f

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1An overview of multi-task learning2017 · 1,133 citations
2Investigation of the Influence of Functionalization Strategy on Urea 2D MOF Catalytic Performance2023 · 17 citations
3Breathing porous liquids based on responsive metal-organic framework particles2023 · 47 citations
4MOF-enabled confinement and related effects for chemical catalyst presentation and utilization2022 · 375 citations
5Enhanced electrocatalytic performance of TiO <sub>2</sub> nanoparticles by Pd doping toward ammonia synthesis under ambient conditions2022 · 12 citations