Abstract

The ability to measure the bulk dynamic behavior of soft materials with combined time- and frequency-resolution is instrumental for improving our fundamental understanding of connections between the microstructural dynamics and the macroscopic mechanical response. Current state-of-the-art techniques are often limited by a compromise between resolution in the time and frequency domain, mainly due to the use of elementary input signals that have not been designed for fast time-evolving systems such as materials undergoing gelation, curing or self-healing. In this work, we develop an optimized and robust excitation signal for time-resolved mechanical spectroscopy through the introduction of joint frequency- and amplitude-modulated exponential chirps. Inspired by the biosonar signals of bats and dolphins, we optimize the signal profile to maximize the signal-to-noise ratio while minimizing spectral leakage with a carefully-designed modulation of the envelope of the chirp. A combined experimental and numerical investigation reveals that there exists an optimal range of window profiles that minimizes the error with respect to standard single frequency sweep methods. The minimum error is set by the noise floor of the instrument, suggesting that the accuracy of an optimally windowed chirp signal is directly comparable to that achievable with a standard frequency sweep, while the acquisition time can be reduced by up to two orders of magnitude, for comparable spectral content. Finally, we demonstrate the ability of this optimized signal to provide time- and frequency-resolved rheometric data by studying the fast gelation process of an acid-induced protein gel. The use of optimally windowed chirps enables a robust rheological characterization of a wide range of soft materials undergoing rapid mutation and has the potential to become an invaluable tool for researchers across different disciplines.

Highlights

  • Many soft materials that are of interest for industrial [1,2,3] or biomedical [4,5] applications often undergo microstructural changes during their synthesis or assembly as a result of chemical, thermal, or mechanical processes

  • By applying the optimally windowed chirp (OWCh) signal to a mutating protein gel undergoing gelation, we further show how time-resolved mechanical spectroscopy allows us to capture the evolution in the material viscoelastic properties of the gel in detail within a single experiment

  • Time-resolved mechanical spectroscopy is very important in the quest to relate microscopic dynamics to the bulk material behavior of soft materials

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Summary

INTRODUCTION

Many soft materials that are of interest for industrial [1,2,3] or biomedical [4,5] applications often undergo microstructural changes during their synthesis or assembly as a result of chemical, thermal, or mechanical processes. Standard test protocols for measuring the linear viscoelastic spectra of soft materials are typically based on periodic signals consisting of sine steps of constant frequency and amplitude [see Fig. 1(a)] These can either be combined sequentially as in frequency sweeps [7] or be additively superposed for a discrete number of frequencies, such as in multiwave techniques [40]. Combining experiments and detailed simulations on a model polymer solution, we show that it is possible to define an optimized chirp signal that reduces the residual error in estimation of the linear viscoelastic spectrum by almost 2 orders of magnitude compared to a constant amplitude sine sweep This optimally windowed chirp (OWCh) allows us to determine the relaxation spectrum with essentially the same precision of the current discrete frequency sweep standard while dramatically reducing the total test duration. As a consequence of these features, chirps are widely used as excitation signals in a range of different applications [38,39,44], but they commonly arise in nature from birdsong [53] to gravitational waves [54], and, most notably, they are the signal forms used by both bats and dolphins for echolocation [55,56]

Chirp signal construction
Windowed chirp
Optimization of windowed chirps
Constitutive equation for PIB solution
Numerical simulations of windowed chirps
APPLICATION TO A MUTATING SYSTEM
SUMMARY
Findings
SNRðωÞ
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