Long-wavelength density fluctuations as nucleation precursors

Nucleation precursors compatible with a single energy barrier: catching the nonclassical culprit

In this work we link experimental results of SrSO4 precipitation with a mesoscopic nucleation model (MeNT) to stride towards a cohesive view of the nucleation process integrating both classical and...

Out-of-equilibrium processes in crystallization of organic-inorganic perovskites during spin coating

Complex phenomena are prevalent during the formation of materials, which affect their processing-structure-function relationships. Thin films of methylammonium lead iodide (CH₃NH₃PbI₃, MAPI) are processed by spin coating, antisolvent drop, and annealing of colloidal precursors. The structure and properties of transient and stable phases formed during the process are reported, and the mechanistic insights of the underlying transitions are revealed by combining in situ data from grazing-incidence wide-angle X-ray scattering and photoluminescence spectroscopy. Here, we report the detailed insights on the embryonic stages of organic-inorganic perovskite formation. The physicochemical evolution during the conversion proceeds in four steps: i) An instant nucleation of polydisperse MAPI nanocrystals on antisolvent drop, ii) the instantaneous partial conversion of metastable nanocrystals into orthorhombic solvent-complex by cluster coalescence, iii) the thermal decomposition (dissolution) of the stable solvent-complex into plumboiodide fragments upon evaporation of solvent from the complex and iv) the formation (recrystallization) of cubic MAPI crystals in thin film.

Complex phenomena are prevalent during the formation of materials, and they affect the processing structure-function relationship. Here the authors elucidate the stochastic transformation processes happening during the spin coating of perovskite colloidal precursors by multimodal characterization.

Impact of Surface Roughness on Crystal Nucleation

We examine the effect of rough surfaces on crystal nucleation by means of kinetic Monte Carlo simulations. Our work makes use of three-dimensional kMC models, explicit representation of transport in solution and rough surfaces modeled as randomly varying height fluctuations (roughness) with exponentially decaying correlation length (topology). We use Forward-Flux Sampling to determine the nucleation rate for crystallization for surfaces of different roughness and topology and show that the effect on crystallization is a complex interplay between the two. For surfaces with low roughness, small clusters form on the surface but as clusters become larger they are increasingly likely to be found in the bulk solution while rougher surfaces eventually favor heterogeneous nucleation on the surface. In both cases, the rough surface raises the local supersaturation in the solution thus leading to another mechanism of enhanced nucleation rate.