Nastaran Meftahi
Papers
2
Total Citations
46
H-Index
2
About
Nastaran Meftahi is a leading researcher at the intersection of renewable energy and artificial intelligence, specializing in the accelerated discovery and optimization of next-generation photovoltaic materials. Her primary focus lies in quasi-2D Ruddlesden–Popper perovskite solar cells, a promising class of devices that offer superior stability compared to their 3D counterparts. Meftahi’s most impactful contribution is the development of a groundbreaking methodology that integrates machine learning with high-throughput fabrication. Her landmark 2023 paper in *Advanced Energy Materials* (43 citations) demonstrates how this combined approach can efficiently navigate the vast compositional space of these perovskites, rapidly identifying optimal formulations for enhanced performance and stability. This work, featured on the journal’s cover, represents a paradigm shift from traditional trial-and-error synthesis to data-driven optimization. By synergizing computational prediction with automated experimentation, Meftahi has established a powerful framework that dramatically accelerates the development cycle for stable, high-efficiency solar cells, positioning her at the forefront of efforts to make perovskite photovoltaics commercially viable.
Research Focus
Key Achievements
Top Papers
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