Ostwald ripening describes how the size distribution of colloidal particles evolves with time due to thermodynamic driving forces. Typically, small particles shrink and provide material to larger particles, which leads to size defocusing. Semiconductor nanoplatelets, thin quasi-two-dimensional (2D) particles with thicknesses of only a few atomic layers but larger lateral dimensions, offer a unique system to investigate this phenomenon. Experiments show that the distribution of nanoplatelet thicknesses does not defocus during ripening, but instead jumps sequentially from m to (m + 1) monolayers, allowing precise thickness control. We investigate how this counterintuitive process occurs in CdSe nanoplatelets. We develop a microscopic model that treats the kinetics and thermodynamics of attachment and detachment of monomers as a function of their concentration. We then simulate the growth process from nucleation through ripening. For a given thickness, we observe Ostwald ripening in the lateral direction, but none perpendicular. Thicker populations arise instead from nuclei that capture material from thinner nanoplatelets as they dissolve laterally. Optical experiments that attempt to track the thickness and lateral extent of nanoplatelets during ripening appear consistent with these conclusions. Understanding such effects can lead to better synthetic control, enabling further exploration of quasi-2D nanomaterials.

In this work, we investigate a comprehensive model describing nucleation, growth and Ostwald ripening based on the kinetic rate equation and compare it to commonly used population balance equation models that either describe nucleation and crystal growth or crystal growth and Ostwald ripening. The kinetic rate equation gives a microscopic description of crystallization, i.e., the process is seen as an attachment

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A protocol for the estimation of growth kinetics for complex-shaped particles is presented. The estimation is based on multidimensional particle size distribution (nD PSD) and concentration data. While the latter is obtained by an in situ mid-infrared absorption probe, nD PSD data is measured via an imaging based setup presented earlier. The data is fitted to the output of a morphological population balance equation, which is solved by a customized high resolution algorithm. The procedure is first validated in silico using a virtual implementation of the measurement setup before it is applied to seeded desupersaturation experiments of the β polymorph of l-glutamic acid. Prominent broadening of the product PSD is observed and different size (in)­dependent growth models are fitted to the data. Confidence intervals, local identifiability, and correlation of the parameters are studied. Finally, the estimated growth rate is compared to literature results.