Giant Fluctuations Induced by Thermal Diffusion in Complex Liquids

Vailati, Alberto; Philipp, B.; Bataller, Henri; Bolis, Serena; Braibanti, Marco; Carpineti, Marina; Cerbino, Roberto; Croccolo, Fabrizio; Dewandel, Jean Luc; Donev, Aleksandar; García-Fernández, L.; Giavazzi, Fabio; Haslinger, Robert; Hens, Steven; Knauer, Maria; Kufner, E.; Zárate, José M. Ortiz de; Peeters, Jeroen; Schwarz, Christian; Silkina, Inese; Xu, Shenghua; Zapf, Daniel

doi:10.1007/s12217-020-09815-x

Cited by 21 publications

(14 citation statements)

References 54 publications

(68 reference statements)

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“…The presence of convective instabilities in ground-based experiments calls for the need of performing experiments under reduced-gravity conditions [ 5 ]. This is one of the main reasons at the basis of the projects Diffusion Coefficient Measurements in ternary Mixtures (DCMIX) [ 6 , 7 ] and Giant Fluctuations [ 8 , 9 ]. Both projects aim at investigating ternary mixtures in microgravity.…”

Section: Introductionmentioning

confidence: 99%

Stabilized convection in a ternary mixture with two Soret coefficients of opposite sign

et al. 2022

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We performed ground-based experiments on the sample polystyrene–toluene–cyclohexane in order to complement the experimental activities in microgravity conditions related to the ESA projects DCMIX4 and Giant Fluctuations. After applying a stabilizing thermal gradient by heating from above a layer of the fluid mixture, we studied over many hours the density variations in the bidimensional horizontal field by means of a Shadowgraph optical setup. The resulting images evidence the appearance of convective instability after a diffusive time associated with the binary molecular solvent consisting of toluene and cyclohexane, confirming the negative sign of the Soret coefficient of this mixture. After a larger diffusive time related to mass diffusion of the polystyrene in the binary solvent, convection was suppressed by the increasing stabilizing density gradient originated by the Soret-induced concentration gradient of the polymer. This is compatible with a positive sign of the Soret coefficient of the polymer in the binary solvent. Graphic Abstract

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Section: Introductionmentioning

confidence: 99%

Stabilized convection in a ternary mixture with two Soret coefficients of opposite sign

et al. 2022

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“…Furthermore, if only one Soret coefficient, out of two in ternary mixtures, is negative, it is in some cases impossible to identify the presence of instability, even with the most advanced optical methods. Studies of thermodiffusion in liquid ternary mixtures are currently performed not only in ground laboratories 11 , 13 – 16 but also under microgravity aboard the International Space Station (ISS) 17 – 22 . Measurements under microgravity conditions serve as a benchmark 23 because the destabilizing effect of buoyant convection is reduced.…”

Section: Introductionmentioning

confidence: 99%

Soret vector for description of multicomponent mixtures

Mialdun

Bou-Ali

Shevtsova

2021

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The Soret effect describes the transport of constituent species in multicomponent mixtures that occurs due to a temperature gradient. This cross-coupling effect of heat and mass transfer has been successfully examined in binary liquid mixtures, while experiments with ternary mixtures are rare as they impose significant difficulties. We introduce a new and innovative concept, the Soret vector, for the characterization of Soret driven separation in ternary mixtures. The presentation of the component separation in the vector form offers several advantages: (i) to predict the Soret sign of a ternary mixture from knowledge of the Soret coefficients in binary subsystems; (ii) to control consistency of measured coefficients, this is especially important when results are obtained using different instruments and methods; (iii) to determine in which regions and which components cause the greatest separation; (iv) to identify the regions where the Soret separation is inaccessible for optical techniques or gravitationally unstable. We demonstrate these features by exploring ternary mixtures of different origins: (a) nearly ideal mixture composed by THN–IBB–nC12 when Soret coefficients in binary subsystems ($$S_{T}^{bin}$$ S T bin ) are positive, (b) non-ideal mixture containing water and ethanol TEG–Wat–EtOH when $$S_{T}^{bin}$$ S T bin are positive and negative and (c) Tol–MeOH–Ch mixture containing demixing zone with positive and negative $$S_{T}^{bin}$$ S T bin . Our approach provides a promising systematic framework for the future research of an important and challenging problem of thermodiffusion in multicomponent liquids.

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“…For this reason, they have gained popularity, especially in the field of soft matter physics. In fact, the combination of the robustness of the structure function analysis applied to simple and/or already available optical setups has allowed them to be used both in traditional laboratories [10][11][12], and in orbiting experi-ments on the ISS [14][15][16] for investigating the dynamics of rather different samples ranging from colloidal particles [10] to bacteria [17], but also from biological cells [18] to density fluctuations in and outside thermal equilibrium [4,19], and many others, as also witnessed by several review articles [12,13,20,21].…”

Section: Introductionmentioning

confidence: 99%

The modern structurator: increased performance for calculating the structure function

et al. 2021

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The autocorrelation function is a statistical tool that is often combined with dynamic light scattering (DLS) techniques to investigate the dynamical behavior of the scattered light fluctuations in order to measure, for example, the diffusive behavior of transparent particles dispersed in a fluid. An alternative approach to the autocorrelation function for the analysis of DLS data has been proposed decades ago and consists of calculating the autocorrelation function starting from difference of the signal at different times by using the so-called structure function. The structure function approach has been proven to be more robust than the autocorrelation function method in terms of noise and drift rejection. Therefore, the structure function analysis has gained visibility, in particular in combination with imaging techniques such as dynamic shadowgraphy and differential dynamic microscopy. Here, we show how the calculation of the structure function over thousands of images, typical of such techniques, can be accelerated, with the aim of achieving real-time analysis. The acceleration is realized by taking advantage of the Wiener–Khinchin theorem, i.e., by calculating the difference of images through Fourier transform in time. The new algorithm was tested both on CPU and GPU hardware, showing that the acceleration is particularly large in the case of CPU.

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Giant Fluctuations Induced by Thermal Diffusion in Complex Liquids

Cited by 21 publications

References 54 publications

Stabilized convection in a ternary mixture with two Soret coefficients of opposite sign

Stabilized convection in a ternary mixture with two Soret coefficients of opposite sign

Soret vector for description of multicomponent mixtures

The modern structurator: increased performance for calculating the structure function

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