Multiple interval thixotropic test (miTT)—an advanced tool for the rheological characterization of emulsions and other colloidal systems

Stadler, Florian J.; Cui, Shuming; Hashmi, Saud; Handschuh‐Wang, Stephan; Li, Wenqiang; Wang, Shichang; Yan, Zhi-Chao; Zhu, Guorui

doi:10.1007/s00397-021-01323-y

Cited by 7 publications

(8 citation statements)

References 54 publications

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“…79 For example, the nonlinearity limit of the same suspensions as used here but with cellulose nanofibers as fillers have nonlinearity limits around 1–30%. 29,77 This indicates that the nonlinearity limit is to a large extent determined by the GO sheets, which behave as a colloidal suspension, analogously to what was discussed for the miTT results (GO-building up a jamming network in the aqueous phase).…”

Section: Resultssupporting

confidence: 66%

“…Actually, G 0 (_ g prev = 1000 s À1 ) 4 G 0 (_ g prev = 1 s À1 ) is the result that would be expected for normal viscoelastic materials, such as for the cellulose nanofiber emulsions, for which the miTT-protocol was previously applied as well. 29 This finding can be explained by the fact that 0.5 wt% DDAB in chloroform has such a strong influence on the behavior that the impact of 1 wt% GO is outweighed, i.e., the sample behavior is dominated by ''normal'' DDAB-residing on the interfaces, making them so strong that they can outweigh the relatively low amounts of GO in terms of preventing the increase in the modulus.…”

Section: B Dielectric Resultsmentioning

confidence: 99%

“…The miTT-protocol was described in detail elsewhere, 29 and contains alternating steps of start-up flows (SUF, 120 s) at varying (_ g = 0.1-1000 s À1 ) and dynamic mechanical tests (DMT, 300 s, o = 1 rad s À1 ) at small strain (g 0 = 0.1%), as shown in Table 3. The data was evaluated, as described previously, 29 by obtaining the terminal values of each step using a Matlab script.…”

Section: Rheologymentioning

confidence: 99%

“…19,27,28 In our previous research, we introduced multiple interval thixotropy tests (miTT) to check how different shear rates influence the rheological properties. 29 The miTT profile set a series of shear rate ramps to destroy the sample and after each specific shear, identical time sweep intervals were used to monitor structural recovery. Combining various rheological profiles, such as start-up flow, miTT, strain sweep, and frequency sweep, is a versatile, comprehensive, and novel approach to characterize the mechanical properties of Pickering emulgels, which will be discussed in the ''Results'' section in great depth.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Rheology of graphene oxide stabilized Pickering emulsions

Cui

Hashmi

et al. 2023

Soft Matter

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Section: Resultssupporting

confidence: 66%

Section: B Dielectric Resultsmentioning

confidence: 99%

Section: Rheologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Rheology of graphene oxide stabilized Pickering emulsions

Cui

Hashmi

et al. 2023

Soft Matter

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“…These results were compared with the startup experiments of the multiple interval thixotropic test (miTT), which was described in detail by us before [ 51 ]. Essentially, the data were obtained by shearing the sample at constant

for 120 s and taking the last datapoint as viscosity.…”

Section: Methodsmentioning

confidence: 99%

Influence of Cellulose Nanofibers on the Behavior of Pickering Emulsions. Part 1. Microscopy and Startup Flow Test

Cui

Hashmi

et al. 2022

Materials

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The dispersibility of flexible polymer chains present at the emulsion’s interface between the dispersed and continuous phase has obvious effects on rheology and dielectric properties of the whole emulsion. Cellulose nanofiber (CNF)-based Pickering emulsions are good systems to research these properties with respect to their microscopic phase structure, dielectric, and rheological properties by using CNF as a water-dispersible Pickering emulsifier, liquid paraffin as an oil phase, and didodecyldimethylammonium bromide (DDAB) as a cationic auxiliary surfactant. The CNF and DDAB contents were systematically varied while the water-to-paraffin oil ratio was kept constant to discern the influence of the Pickering emulsifiers. Polarized optical microscopic images reveal that the droplets tend to shrink at higher CNF content but grow bigger when increasing the DDAB content, which is proved by fluorescence analysis of the CNF dispersibility with varying DDAB content. The dielectric damping exhibits a minimum, whose value decreases with increasing DDAB and CNF content. Increasing the DDAB content promotes the solubilization of CNF in the aqueous phase, which will increase the overall viscosity and yield points. Similarly, a higher CNF content leads to a higher viscosity and yield point, but at high DDAB contents, the viscosity function exhibits an S-shape at intermediate CNF contents. To evaluate the results further, they were compared with CNF dispersions (without oil phase), which showed a surfactant effect slightly on maximum stress but strongly on yield stress τy, indicating that DDAB can promote the formation of a CNF network rather than the viscosity of the whole system. This paper provides information on how a systematical variation of the composition influences morphology and physico-chemical interactions as detected by broadband dielectric spectroscopy and rheological behavior.

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The Mnemosyne number and the rheology of remembrance

Jamali

McKinley

2022

Journal of Rheology

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The concept of a Deborah number is widely used in the study of viscoelastic materials to represent the ratio of a material relaxation time to the time scale of observation and to demarcate transitions between predominantly viscous or elastic material responses. However, this construct does not help quantify the importance of long transients and nonmonotonic stress jumps that are often observed in more complex time-varying systems. Many of these nonintuitive effects are lumped collectively under the term thixotropy; however, no proper nouns are associated with the key phenomena observed in such materials. Thixotropy arises from the ability of a complex structured fluid to remember its prior deformation history, so it is natural to name the dimensionless group representing such behavior with respect to the ability to remember. In Greek mythology, Mnemosyne was the mother of the nine Muses and the goddess of memory. We, thus, propose the definition of a Mnemosyne number as the dimensionless product of the thixotropic time scale and the imposed rate of deformation. The Mnemosyne number is, thus, a measure of the flow strength compared to the thixotropic time scale. Since long transient responses are endemic to thixotropic materials, one also needs to consider the duration of flow. The relevant dimensionless measure of this duration can be represented in terms of a mutation number, which compares the time scale of experiment/observation to the thixotropic time scale. Collating the mutation number and the Mnemosyne number, we can construct a general two-dimensional map that helps understand thixotropic behavior. We quantify these ideas using several of the simplest canonical thixotropic models available in the literature.

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Multiple interval thixotropic test (miTT)—an advanced tool for the rheological characterization of emulsions and other colloidal systems

Cited by 7 publications

References 54 publications

Rheology of graphene oxide stabilized Pickering emulsions

Rheology of graphene oxide stabilized Pickering emulsions

Influence of Cellulose Nanofibers on the Behavior of Pickering Emulsions. Part 1. Microscopy and Startup Flow Test

The Mnemosyne number and the rheology of remembrance

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