Flow field-based data analysis in interfacial shear rheometry.

Adv Colloid Interface Sci

Departamento de Física Fundamental, Facultad de Ciencias, Universidad Nacional de Educación a Distancia, UNED, 28040 Madrid, Spain.

Published: February 2021

Developments in interfacial shear rheometers have considerably improved the quality of experimental data. However, data analysis in interfacial shear rheometry is still an active field of research and development due to the intrinsic complexity introduced by the unavoidable contact of the interface with, at least, one supporting bulk subphase. Nonlinear velocity profiles, both at the interface and the bulk phases, pervade the system dynamical behavior in the most usual experimental geometries, particularly in the case of soft interfaces. Such flow configurations demand data analysis schemes based on the explicit calculation of the flow field in both the interface and the bulk phases. Such procedures are progressively becoming popular in this context. In this review, we discuss the most recent advances in interfacial shear rheology data analysis techniques. We extensively review some recently proposed flow field-based data analysis schemes for the three most common interfacial shear rheometer geometries (magnetic needle, double wall-ring, and bicone), showing under what circumstances the calculation of the flow field is mandatory for a proper analysis of the experimental data. All cases are discussed starting at the appropriate hydrodynamical models and using the equation of motion of the probe to set up an iterative procedure to compute the value of the complex Boussinesq number and, from it, the complex interfacial viscosity or, equivalently, the complex interfacial modulus. Moreover, two examples of further extensions of such techniques are proposed, concerning the micro-button interfacial shear rheometer and the potential application of interfacial rheometry instruments, together with adapted flow field-based data analysis techniques, for bulk rheometry, particularly in the case of soft samples.

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http://dx.doi.org/10.1016/j.cis.2020.102332DOI Listing

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