Particle-wall hydrodynamic effects on optical trapping viscometry
Juarez, Jaime J.
Is Version Of
Optical tweezers are a versatile setup used to measure forces in soft materials and characterize the rheological properties of fluids and gels. An accurate measurement of these forces is complicated by the interaction between the optically trapped materials and nearby substrate walls. This work presents a comprehensive Brownian Dynamic (BD) model that accounts for the hydrodynamic interactions between an optically trapped particle and a nearby boundary. The model is based on a midpoint algorithm, which simplifies accounting for diffusion gradients that arise from hydrodynamic interactions. Experiments using an optical tweezer and a quadrant position detector (QPD) are performed to validate these experiments. We conduct experiments by varying input laser current from 100 mA to 300 mA. Our experiments show that measured viscosity at 100 mA is ~19% higher than the value expected for room temperature water (0.89 mPa-s). The discrepancy diminishes to 4% when a 300 mA current is used. Simulations performed with the BD model show that, for a nominal spring constant of 𝑘𝑠 = 4.332 × 10−4𝐼𝑙𝑎𝑠𝑒𝑟 [𝑝𝑁/𝜇𝑚], the discrepancy can be explained via hydrodynamic interactions that influence the measured effective viscosity. Wide variability in confidence interactions observed in our data can be replicated by using a range of diameters in our simulation. This is consistent with DLS measurements of the particles used in this study, which show that the mean diameter was (1.63 ± 0.28) m. This work has implications for measuring Newtonian media viscosities up to ~63 mPa-s, as determined by a scaling analysis of limitations for our measurement system.
This is a pre-proof article published as Ghosh, Richa, Sarah A. Bentil, and Jaime J. Juárez. "Particle-wall Hydrodynamic Effects on Optical Trapping Viscometry." Colloids and Surfaces A: Physicochemical and Engineering Aspects (2023): 132942. doi: https://doi.org/10.1016/j.colsurfa.2023.132942. © 2023 Elsevier. CC BY-NC-ND