2023 journal article

AlphaFlow: autonomous discovery and optimization of multi-step chemistry using a self-driven fluidic lab guided by reinforcement learning

Nature Communications.

By: A. Volk n, R. Epps n, D. Yonemoto n, B. Masters n, F. Castellano n, K. Reyes*, M. Abolhasani n

TL;DR: The capabilities of closed-loop, reinforcement learning-guided systems in exploring and solving challenges in multi-step nanoparticle syntheses, while relying solely on in-house generated data from a miniaturized microfluidic platform are demonstrated. (via Semantic Scholar)
Source: ORCID
Added: March 27, 2023

Abstract