Papers

2

Total Citations

30

H-Index

2

About

Fatmah Mish Ebrahim is a rising researcher at the forefront of materials chemistry, specializing in the accelerated discovery and optimization of metal-organic frameworks (MOFs). Her major contribution lies in pioneering the integration of machine learning—specifically genetic algorithms—with experimental synthesis to systematically refine MOF production. In her highly cited 2022 work, she demonstrated this joint approach to dramatically improve the synthesis conditions of Al-PMOF, a porphyrin-based MOF with significant potential in catalysis and gas storage. By using a "synthetic conditions finder," Ebrahim’s methodology replaces slow, trial-and-error experimentation with intelligent, data-driven optimization, enabling researchers to achieve desired crystalline structures more reliably and efficiently. Her work, which has accumulated over 30 citations, is notable for bridging computational prediction and laboratory practice, offering a powerful template for accelerating the development of advanced porous materials. Ebrahim’s research is particularly impactful for students and scientists seeking to harness AI to solve complex synthetic challenges in materials science.

Research Focus

Key Achievements

2
H-Index
2
Papers
30
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
Using genetic algorithms to systematically improve the synthesis conditions of Al-PMOF
26 citations · 2022
📈 Most Prolific Year: 2022 (2 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: University of Cambridge, École Polytechnique Fédérale de Lausanne

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago