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Updated: Feb 10, 2026

Real-Time Force Measurement Between Emulsion Droplets During Enzymatic Breakdown
Published on: June 27, 2025
Optofluidic Force Induction for Online Monitoring of Particle Size Distributions in Emulsion Polymerization Reactions
Usue Olatz Aspiazu1, Marko Šimić2,3,4, Michael Schnur2
1POLYMAT, Kimika Aplikatua Saila, Kimika Fakultatea, University of the Basque Country (EHU), Joxe Mari Korta Zentroa, Donostia-San Sebastián 20018, Spain.
Abstract:
Real-time monitoring of particle size distribution (PSD) during emulsion polymerization is vital for understanding reaction mechanisms and improving process control. Conventional offline methods such as Dynamic Light Scattering (DLS), Transmission Electron Microscopy (TEM), and Capillary Hydrodynamic Fractionation chromatography (CHDF), while accurate, are limited in their ability to capture dynamic changes during the reaction. OptoFluidic Force Induction (OF2i) is a novel optical tweezers-based technology that enables online, in situ particle characterization. Although previously applied in pharmaceutical contexts, its utility in polymer reaction monitoring remains untested. This study evaluates the performance of OF2i in stirred-tank reactors during ab initio and semibatch emulsion polymerizations of styrene and acrylic comonomers. OF2i successfully tracked the evolution of particle size and PSD throughout various reaction stages, including primary nucleation in micelle-free systems, particle growth in seeded semibatch setups, and secondary nucleation simulated through sequential seed additions. It delivered accurate PSD measurements for particles larger than ∼180 nm in polystyrene latexes and ∼200 nm in (meth)-acrylated copolymer systems, with a current temporal resolution of 10 min governed by the system's automated dilution interface. PSD results were consistent with those obtained by established offline techniques such as DLS, TEM, and CHDF. The system's ability to operate without composition-specific calibration and to provide continuous, high-resolution data makes it uniquely suited for monitoring transient dynamics and population shifts in real timecapabilities not achievable with conventional methods.
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