Fernando Delgado Licona

Delgado-Licona, F., Addington, D., Alsaiari, A., & Abolhasani, M. (2025, May 16). Engineering principles for self-driving laboratories. Nature Chemical Engineering, Vol. 2, pp. 277–280. https://doi.org/10.1038/s44286-025-00217-7

Delgado-Licona, F., Alsaiari, A., Dickerson, H., Klem, P., Ghorai, A., Canty, R. B., … Abolhasani, M. (2025, July 14). Flow-driven data intensification to accelerate autonomous inorganic materials discovery. Nature Chemical Engineering, Vol. 2, pp. 436–446. https://doi.org/10.1038/s44286-025-00249-z

Jha, P., Mukhin, N., Ghorai, A., Morshedian, H., Canty, R. B., Delgado‐Licona, F., … Abolhasani, M. (2025, February 11). Photo‐Induced Bandgap Engineering of Metal Halide Perovskite Quantum Dots In Flow. Advanced Materials, Vol. 2. https://doi.org/10.1002/adma.202419668

Sadeghi, S., Canty, R. B., Mukhin, N., Xu, J., Delgado-Licona, F., & Abolhasani, M. (2024, August 6). Engineering a Sustainable Future: Harnessing Automation, Robotics, and Artificial Intelligence with Self-Driving Laboratories. ACS Sustainable Chemistry & Engineering, Vol. 8. https://doi.org/10.1021/acssuschemeng.4c02177

López-Guajardo, E. A., Galluzzi, R., Delgado-Licona, F., & Morales-Menendez, R. (2024, April 12). Process intensification of a catalytic-wall Taylor-Couette reactor through unconventional modulation of its angular speed. Chemical Engineering Journal. https://doi.org/10.1016/j.cej.2024.151174

Epps, R. W., Delgado‐Licona, F., Yang, H., Kim, T., Volk, A. A., Han, S., … Abolhasani, M. (2023, January 29). Accelerated Multi‐Stage Synthesis of Indium Phosphide Quantum Dots in Modular Flow Reactors. Advanced Materials Technologies, Vol. 1. https://doi.org/10.1002/admt.202201845

Sadeghi, S., Bateni, F., Kim, T., Son, D. Y., Bennett, J. A., Orouji, N., … Abolhasani, M. (2023, December 13). Autonomous nanomanufacturing of lead-free metal halide perovskite nanocrystals using a self-driving fluidic lab. Nanoscale, Vol. 12. https://doi.org/10.1039/d3nr05034c

López-Guajardo, E. A., Delgado-Licona, F., Álvarez, A. J., Nigam, K. D. P., Montesinos-Castellanos, A., & Morales-Menendez, R. (2021, October 18). Process intensification 4.0: A new approach for attaining new, sustainable and circular processes enabled by machine learning. Chemical Engineering and Processing - Process Intensification. https://doi.org/10.1016/j.cep.2021.108671