Journal: Nanoscale | https://doi.org/10.1039/D3NR05034C

This paper presents an autonomous approach to synthesizing lead-free copper-based metal halide perovskite nanocrystals (Cs3Cu2I5 NCs) by integrating a microfluidic platform with machine learning. The self-driving fluidic lab enables rapid synthesis optimization and accelerated materials science studies, addressing the toxicity concerns of lead-based perovskites while advancing their development for optoelectronic applications.

Read the article: https://doi.org/10.1039/D3NR05034C