Advanced search

Filter By:

Journal Check one or more journals to show results from those journals only.

Choose more journals

Article type Check one or more article types to show results from those article types only.
Subject Check one or more subjects to show results from those subjects only.
Date Choose a date option to show results from those dates only.

Custom date range

Clear all filters
Sort by:
Showing 1–3 of 3 results
Advanced filters: Author: Fernando Delgado-Licona Clear advanced filters

  • This study embeds dynamic flow experiments into self-driving laboratories, intensifying data acquisition during autonomous materials synthesis. Demonstrated with colloidal quantum dots, the developed method substantially boosts sampling density over tenfold and reduces time and reagents.

    • Fernando Delgado-Licona
    • Abdulrahman Alsaiari
    • Milad Abolhasani
    Research
    Nature Chemical Engineering
    Volume: 2, P: 436-446

  • The full potential of tunable perovskite nanocrystals is limited by complex synthesis space. Here, authors developed a self-driving lab that autonomously discovers and produces optimal scalable nanocrystals for next-generation photonic technologies.

    • Jinge Xu
    • Christopher H. J. Moran
    • Milad Abolhasani
    ResearchOpen Access
    Nature Communications
    Volume: 16, P: 1-13

  • The chemical engineering field stands at a pivotal moment of transformation, driven in part by the convergence of process automation, robotics and artificial intelligence into self-driving laboratories (SDLs) to accelerate scientific discoveries. This Comment explores how process intensification principles can guide the development of SDLs to accelerate innovation while ensuring efficient use of resources across the multiscale chemical domain.

    • Fernando Delgado-Licona
    • Daniel Addington
    • Milad Abolhasani
    Comments & Opinion
    Nature Chemical Engineering
    Volume: 2, P: 277-280