Our paper, “Self-driving AMADAP laboratory: Accelerating the discovery and optimization of emerging perovskite photovoltaics,” has been published in the latest volume of the MRS Bulletin, which is dedicated to Halide Perovskite Photovoltaics.
The development of new solar materials for perovskite photovoltaics entails complex multi-objective optimization challenges within a high-dimensional composition and parameter space, often involving millions of potential candidates. This work introduces a transformative approach to addressing these challenges through automated, reproducible, and intelligent experimental methodologies.
Key aspects of the research include:
- Materials Acceleration Platforms (MAPs): AI-driven systems integrating robotic synthesis, characterization, and data analysis to enable rapid exploration of new materials.
- Device Acceleration Platforms (DAPs): Focused on optimizing processing conditions for disordered semiconductors, particularly functional energy films and multilayer stacks.
- AMADAP Laboratory Concept: A proposed self-driven, autonomous laboratory combining MAPs and DAPs to accelerate solar material discovery through AI-guided combinatorial experimentation.
This publication highlights recent advancements in automated laboratories for perovskite material discovery and photovoltaic device optimization, demonstrating the potential of these platforms to replace traditional trial-and-error methods with precise, high-throughput experimentation.
The article is now available in the latest volume of the MRS Bulletin.
Our paper, “Self-driving AMADAP laboratory: Accelerating the discovery and optimization of emerging perovskite photovoltaics,” has been published in the latest volume of the MRS Bulletin, which is dedicated to Halide Perovskite Photovoltaics.
The development of new solar materials for perovskite photovoltaics entails complex multi-objective optimization challenges within a high-dimensional composition and parameter space, often involving millions of potential candidates. This work introduces a transformative approach to addressing these challenges through automated, reproducible, and intelligent experimental methodologies.
Key aspects of the research include:
This publication highlights recent advancements in automated laboratories for perovskite material discovery and photovoltaic device optimization, demonstrating the potential of these platforms to replace traditional trial-and-error methods with precise, high-throughput experimentation.
The article is now available in the latest volume of the MRS Bulletin.