2025-07-14 ノースカロライナ州立大学（NCState）
＜関連情報＞
- https://news.ncsu.edu/2025/07/fast-forward-for-self-driving-labs/
- https://www.nature.com/articles/s44286-025-00249-z
フロー駆動型データ集約化により自律的無機材料探索が加速する Flow-driven data intensification to accelerate autonomous inorganic materials discovery
Fernando Delgado-Licona,Abdulrahman Alsaiari,Hannah Dickerson,Philip Klem,Arup Ghorai,Richard B. Canty,Jeffrey A. Bennett,Pragyan Jha,Nikolai Mukhin,Junbin Li,Enrique A. López-Guajardo,Sina Sadeghi,Fazel Bateni & Milad Abolhasani
Nature Chemical Engineering Published:14 July 2025
DOI:https://doi.org/10.1038/s44286-025-00249-z
Abstract
The rapid discovery of advanced functional materials is critical for overcoming pressing global challenges in energy and sustainability. Despite recent progress in self-driving laboratories and materials acceleration platforms, their capacity to explore complex parameter spaces is hampered by low data throughput. Here we introduce dynamic flow experiments as a data intensification strategy for inorganic materials syntheses within self-driving fluidic laboratories by the continuous mapping of transient reaction conditions to steady-state equivalents. Applied to CdSe colloidal quantum dots, as a testbed, dynamic flow experiments yield at least an order-of-magnitude improvement in data acquisition efficiency and reducing both time and chemical consumption compared to state-of-the-art self-driving fluidic laboratories. By integrating real-time, in situ characterization with microfluidic principles and autonomous experimentation, a dynamic flow experiment fundamentally redefines data utilization in self-driving fluidic laboratories, accelerating the discovery and optimization of emerging materials and creating a sustainable foundation for future autonomous materials research.
