Andrew Johnston
Papers
1
Total Citations
145
H-Index
1
About
Dr. Andrew Johnston is a leading figure in the application of machine learning to materials science, with a particular focus on accelerating the discovery and optimization of perovskite materials for next-generation photovoltaics. His most impactful work, the 2020 paper "Machine-Learning-Accelerated Perovskite Crystallization," has garnered 145 citations, establishing a new paradigm for how artificial intelligence can guide the synthesis of high-performance thin films. By integrating high-throughput experimentation with advanced data-driven models, Johnston’s research has dramatically reduced the time needed to identify optimal crystallization conditions, directly addressing one of the key bottlenecks in perovskite solar cell development. His contributions not only advance the fundamental understanding of crystallization kinetics but also provide a practical toolkit for researchers aiming to rapidly prototype stable, efficient devices. Recognized for bridging computational and experimental domains, Johnston’s work is a cornerstone for the emerging field of autonomous materials discovery, inspiring a new generation of scientists to leverage machine learning for tackling complex synthesis challenges.
Research Focus
Key Achievements
Top Papers
- 1Machine-Learning-Accelerated Perovskite Crystallization145 citations · 2020