Mirza Aamish Hassan Khan
Papers
1
Total Citations
9
H-Index
1
About
Mirza Aamish Hassan Khan is an emerging researcher at the forefront of computational materials science, with a focused expertise in the intersection of metal-organic frameworks (MOFs) and artificial intelligence. His work centers on leveraging machine learning algorithms to revolutionize the discovery, design, and synthesis of MOFs, particularly for carbon capture applications. Khan’s most-cited paper, a comprehensive 2026 state-of-the-art review, systematically explores how AI can predict CO₂ capture capacity, offering a roadmap for accelerating the development of next-generation porous materials. This work, already garnering 9 citations, underscores his ability to synthesize complex interdisciplinary knowledge and identify transformative pathways in sustainable chemistry. By bridging advanced computational methods with experimental synthesis, Khan is contributing to a paradigm shift in how researchers approach material discovery—moving from trial-and-error to data-driven prediction. His contributions are particularly timely given the global urgency for efficient carbon mitigation technologies. As a rising voice in this niche, Khan’s research not only advances fundamental understanding but also holds practical promise for industrial-scale CO₂ capture, marking him as a researcher to watch in the evolving landscape of AI-driven materials innovation.
Research Focus
Key Achievements
Top Papers
- 1