Scientific Achievement
Harnessed high-throughput, deep learning-assisted computer vision to identify and measure geometric features of individual cobalt oxide nanocrystals with sizes less than 10 nm.
Significance and Impact
The new approach enables a detailed statistical analysis that allows for the study of size dependency of growth regimes in shaping nanocrystals, allowing for precise correlation between geometry and material properties.
Research Details
- The researchers utilized high-throughput, deep learning-assisted computer vision to identify and measure the features of over 441,067 Co3O4 nanocrystals, analyzing their characteristics and revealing previously unobserved size-resolved shape evolution.
- By correlating synthetic variables with nanocrystal size and shape, they can optimize synthesis conditions to achieve desired properties more accurately than traditional methods.
Cho, M.G., Sytwu, K., DaCosta, L.R., Groschner, C., Oh, M.H., Scott, M.C. 2024 ACS Nano, 18, 43, 29736-29747. DOI: 10.1021/acsnano.4c09312
Research Summary
Precise size and shape control in nanocrystal synthesis is essential for utilizing nanocrystals in various industrial applications, such as catalysis, sensing, and energy conversion. However, traditional ensemble measurements often overlook the subtle size and shape distributions of individual nanocrystals, hindering the establishment of robust structure–property relationships. In this study, the researchers uncover intricate shape evolutions and growth mechanisms in Co3O4 nanocrystal synthesis at a subnanometer scale, enabled by deep-learning-assisted statistical characterization. By first controlling synthetic parameters such as cobalt precursor concentration and water amount then using high resolution electron microscopy imaging to identify the geometric features of individual nanocrystals, this study provides insights into the interplay between synthesis conditions and the size-dependent shape evolution in colloidal nanocrystals.
The findings provide experimental quantification of the growth regime transition based on the size of the crystals, specifically (i) for faceting and (ii) from thermodynamic to kinetic, as evidenced by transitions from convex to concave polyhedral crystals. Additionally, they introduce the concept of an “onset radius,” which describes the critical size thresholds at which these transitions occur. This discovery has implications beyond achieving nanocrystals with desired morphology; it enables finely tuned correlation between geometry and material properties, advancing the field of colloidal nanocrystal synthesis and its applications.
