Real-time monitoring of complex moduli from micro-rheology

TL;DR

This paper introduces a real-time, multi-scale time-correlation method for micro-rheology data analysis, enabling accurate, high-frequency complex modulus measurements without truncation artifacts, suitable for high-volume data streams.

Contribution

The paper presents a novel online analysis technique that improves micro-rheology data processing by reducing artifacts and eliminating the need for pre-selected data acquisition intervals.

Findings

Accurately measures complex moduli in real time.

Outperforms traditional Kramers-Kronig at high frequencies.

Shows good agreement with bulk rheology data.

Abstract

We describe an approach to online analysis of micro-rheology data using a multi-scale time-correlation method. The method is particularly suited to process high-volume data streams and compress the relevant information in real time. Using this, we can obtain complex moduli of visco-elastic media without suffering from the high-frequency artefacts that are associated with the truncation errors in the most widely used versions of micro-rheology. Moreover, the present approach obviates the need to choose the time interval for data acquisition beforehand. We test our approach first on an artificial data set and then on experimental data obtained both for an optically trapped colloidal probe in water and a similar probe in poly-ethylene glycol solutions at various concentrations. In all cases, we obtain good agreement with the bulk rheology data in the region of overlap. We compare our method with the conventional Kramers-Kronig transform approach and find that the two methods agree over most of the frequency regime. For the same data set, the present approach is superior to Kramers-Kronig at high frequencies and can be made to perform at least comparable at low frequencies.