Urquidi O, Barbosa N, Brazard J, Adachi TBM. Toward time resolved dynamic light scattering microscopy: Retrieving particle size distributions at high temporal resolutions.
Rev Sci Instrum 2023;
94:083101. [PMID:
37526515 DOI:
10.1063/5.0160156]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 07/13/2023] [Indexed: 08/02/2023]
Abstract
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.
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