David P. McMeekin
Papers
2
Total Citations
46
H-Index
2
About
David P. McMeekin is a leading researcher at the forefront of next-generation photovoltaics, specializing in the development and optimization of quasi-2D Ruddlesden–Popper perovskite solar cells. His major contributions lie in integrating machine learning with high-throughput fabrication to rapidly explore the vast compositional space of these materials, addressing critical stability challenges that have hindered commercial perovskite adoption. His most cited work (2023, 43 citations) demonstrates a pioneering methodology that accelerates the discovery of stable, high-efficiency solar cell formulations, significantly reducing the time and cost of traditional trial-and-error approaches. This research, featured as the cover article in *Advanced Energy Materials*, highlights his role in bridging computational prediction with experimental validation. McMeekin’s impact is evident in the growing adoption of his data-driven strategies within the perovskite community, where his work has become a key reference for researchers seeking to overcome stability-performance trade-offs. By combining materials science, automation, and artificial intelligence, he is shaping a new paradigm for sustainable energy materials design.
Research Focus
Key Achievements
Top Papers
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