Significance It is of fundamental importance to establish the microscopic picture of crystal nucleation for both academic and industrial research. Here, we report an in situ time-resolved Raman spectroscopy to study crystallization from solution, one crystal nucleation at a time. The observed dynamics of α-glycine crystallization from water without any additive supports the nonclassical nucleation pathway, where prenucleation aggregates form and convert to a crystal. By the direct comparison of Raman spectrum of the aggregates between the experiment and simulation, we propose the structure of these aggregates as linear hydrogen-bonded networks. We demonstrate the power of studying one nucleation event at a time, which can accelerate the investigation of crystal nucleation by optical spectroscopy.

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Dynamic light scattering (DLS) is a widely applied technique in multiple scientific and industrial fields for the size characterization of nanoscale objects in solution. While DLS is typically applied to characterize systems under static conditions, the emerging interest in using DLS on temporally evolving systems stimulates the latent need to improve the time resolution of measurements. Herein, we present a DLS microscopy setup (micro-DLS) that can accurately characterize the size of particles from autocorrelation functions built from sub-100 ms time windows, several orders of magnitude faster than previously reported. The system first registers the arrival time of the scattered photons using a time-correlated single photon counting module, which allows the construction of the autocorrelation function for size characterization based on a time window of freely chosen position and width. The setup could characterize both monomodal (60 or 220 nm polystyrene particles; PS) and multimodal size distributions (e.g., mixture of 20 nm LUDOX and 80 nm PS) with high accuracy in a sub-100 ms time window. Notably, the width of the size distribution became narrower as a shorter time window was used. This was attributed to the ability of the system to resolve the sub-ensemble of the broad size distribution, as the broad distribution could be reconstructed by accumulating the distribution obtained by consecutive 80 ms time windows. A DLS system with high temporal resolution will accelerate the expansion of its application toward systems that evolve as a function of time beyond its conventional use on static systems.