Deep Learning Models for Colloidal Nanocrystal Synthesis.

ABSTRACT: Colloidal synthesis of nanocrystals usually includes complex chemical reactions and multistep synthesis processes. Despite the great success in the past 30 years, it remains challenging to clarify the correlations between the synthetic parameters of the chemical reaction and the physical properties of nanocrystals. Here, we developed a deep learning-based nanocrystal synthesis model that correlates synthetic parameters with the final size and shape of target nanocrystals, using a data set of 3508 recipes covering 348 distinct nanocrystal compositions. The size and shape labels were obtained from transmission electron microscope images using a segmentation model trained with a semi-supervised algorithm on a data set comprising around 1.2 million nanocrystals. By applying the reaction interm

SUBMITTER: Gu K 

PROVIDER: S-EPMC12632179 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature