Mansoor Ani Najeeb
Papers
4
Total Citations
199
H-Index
3
About
Mansoor Ani Najeeb is a materials science researcher specializing in the automated discovery and characterization of metal halide perovskites — a cutting-edge class of materials with significant promise for next-generation photovoltaic and optoelectronic applications. His most recognized contribution, "Robot-Accelerated Perovskite Investigation and Discovery" (2020), has garnered 179 citations and represents a landmark effort in applying robotic automation to accelerate crystal growth and materials characterization, addressing a long-standing bottleneck in single-crystal X-ray diffraction studies. This work, alongside its companion publications introducing the RAPID framework for inverse temperature crystallization, established a systematic, high-throughput methodology for perovskite exploration. More recently, Najeeb has pushed further into data-driven science, demonstrating how active learning algorithms combined with high-throughput experimentation can guide the dimensional control of perovskite crystallization — work that highlights his commitment to integrating machine learning with experimental materials discovery. Collectively, his research sits at the exciting intersection of robotics, artificial intelligence, and materials chemistry, positioning him as a contributor to the emerging field of autonomous laboratories and self-driving experimentation in solid-state chemistry.
Research Focus
Key Achievements
Top Papers
- 1Robot-Accelerated Perovskite Investigation and Discovery179 citations · 2020
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