Structural Order and Plasmonic Response of Nanoparticle Monolayers

Many biological applications require the segmentation of cell bodies, membranes and nuclei from microscopy images. Deep learning has enabled great progress on this problem, but current methods are specialized for images that have large training datasets. Here we introduce a generalist, deep learning-based segmentation method called Cellpose, which can precisely segment cells from a wide range of image types and does not require model retraining or parameter adjustments. Cellpose was trained on a new dataset of highly varied images of cells, containing over 70,000 segmented objects. We also demonstrate a three-dimensional (3D) extension of Cellpose that reuses the two-dimensional (2D) model and does not require 3D-labeled data. To support community contributions to the training data, we developed software for manual labeling and for curation of the automated results. Periodically retraining the model on the community-contributed data will ensure that Cellpose improves constantly.

When a drop of a colloidal solution of nanoparticles dries on a surface, it leaves behind coffee-stain-like rings of material with lace-like patterns or clumps of particles in the interior. These non-uniform mass distributions are manifestations of far-from-equilibrium effects, such as fluid flows and solvent fluctuations during late-stage drying. However, recently a strikingly different drying regime promising highly uniform, long-range-ordered nanocrystal monolayers has been found. Here we make direct, real-time and real-space observations of nanocrystal self-assembly to reveal the mechanism. We show how the morphology of drop-deposited nanoparticle films is controlled by evaporation kinetics and particle interactions with the liquid-air interface. In the presence of an attractive particle-interface interaction, rapid early-stage evaporation dynamically produces a two-dimensional solution of nanoparticles at the liquid-air interface, from which nanoparticle islands nucleate and grow. This self-assembly mechanism produces monolayers with exceptional long-range ordering that are compact over macroscopic areas, despite the far-from-equilibrium evaporation process. This new drop-drying regime is simple, robust and scalable, is insensitive to the substrate material and topography, and has a strong preference for forming monolayer films. As such, it stands out as an excellent candidate for the fabrication of technologically important ultra thin film materials for sensors, optical devices and magnetic storage media.