Abstract

Giant thermal and solutal non-equilibrium fluctuations are observed in shadowgraphy experiments on liquid mixtures subjected to a temperature gradient. For large temperature differences, both the temperature and the composition dependence of the relevant thermophysical parameters and the nonlinear terms in the diffusion equation need to be taken into account, leading to a nonlinear concentration profile. For temperature differences exceeding the inverse of the Soret coefficient, in our example approximately 10 K, the usual data evaluation yields increasingly wrong diffusion and Soret coefficients that are off by almost a factor of two for a temperature difference of 50 K. A local model that treats the measured shadowgraph signal as a superposition of the contributions from every layer of the sample is able to capture the essential trend and yields a good agreement with experimental data. The results are important for the application of shadowgraphy as a tool for the measurement of Soret and diffusion coefficients, where large temperature gradients promise a good signal-to-noise ratio.

Graphical abstract

中文翻译：

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聚合物溶液中非平衡波动的阴影成像实验中的非线性

摘要

在受到温度梯度的液体混合物的阴影成像实验中观察到巨大的热和溶质非平衡波动。对于较大的温差，需要考虑相关热物理参数的温度和成分依赖性以及扩散方程中的非线性项，从而导致非线性浓度分布。对于超过 Soret 系数倒数的温差，在我们的示例中大约为 10 K，通常的数据评估会产生越来越多的错误扩散和 Soret 系数，对于 50 K 的温差，这些系数几乎相差两倍。将测量的阴影图信号视为样本每一层贡献的叠加的局部模型能够捕捉基本趋势并与实验数据产生良好的一致性。该结果对于应用阴影成像作为测量 Soret 和扩散系数的工具非常重要，其中大的温度梯度保证了良好的信噪比。

图形概要