School of Engineering, Royal Melbourne Institute of Technology University, Melbourne, VIC 3001, Australia.
Physics of Fluids Group, Max Planck Center Twente, J. M. Burgers Centre for Fluid Dynamics, University of Twente, 7500 AE Enschede, The Netherlands.
Proc Natl Acad Sci U S A. 2017 Sep 26;114(39):10332-10337. doi: 10.1073/pnas.1704727114. Epub 2017 Sep 11.
We report the self-organization of universal branching patterns of oil nanodroplets under the Ouzo effect [Vitale S, Katz J (2003) 19:4105-4110]-a phenomenon in which spontaneous droplet formation occurs upon dilution of an organic solution of oil with water. The mixing of the organic and aqueous phases is confined under a quasi-2D geometry. In a manner analogous to the ramification of ground stream networks [Devauchelle O, Petroff AP, Seybold HF, Rothman DH (2012) 109: 20832-20836 and Cohen Y, et al. (2015) 112:14132-14137] but on a scale 10 orders of magnitude smaller, the angles between the droplet branches are seen to exhibit remarkable universality, with a value around 74° ± 2°, independent of the various control parameters of the process. Numerical simulations reveal that these nanodroplet branching patterns are governed by the interplay between the local concentration gradient, diffusion, and collective interactions. We further demonstrate the ability of the local concentration gradient to drive autonomous motion of colloidal particles in the highly confined space, and the possibility of using the nucleated nanodroplets for nanoextraction of a hydrophobic solute. The understanding obtained from this work provides a basis for quantitatively understanding the complex dynamical aspects associated with the Ouzo effect. We expect that this will facilitate improved control in nanodroplet formation for many applications, spanning from the preparation of pharmaceutical polymeric carriers, to the formulation of cosmetics and insecticides, to the fabrication of nanostructured materials, to the concentration and separation of trace analytes in liquid-liquid microextraction.
我们报告了在 Ouzo 效应[Vitale S,Katz J(2003)19:4105-4110]下油纳米液滴的普遍分支模式的自组织现象-在这种现象中,当油的有机溶液与水稀释时会自发形成液滴。有机相与水相的混合被限制在准 2D 几何形状下。以类似于地面水流网络分支的方式[Devauchelle O,Petroff AP,Seybold HF,Rothman DH(2012)109:20832-20836和Cohen Y,等。(2015)112:14132-14137],但规模要小 10 个数量级,液滴分支之间的角度表现出显著的通用性,其值约为 74°±2°,与过程的各种控制参数无关。数值模拟表明,这些纳米液滴分支模式受局部浓度梯度、扩散和集体相互作用的相互作用控制。我们进一步证明了局部浓度梯度能够驱动胶体粒子在高度受限的空间中自主运动,并且可以利用成核纳米液滴来从疏水性溶质中进行纳米萃取。这项工作获得的理解为定量理解与 Ouzo 效应相关的复杂动力学方面提供了基础。我们预计,这将有助于改进许多应用中的纳米液滴形成的控制,这些应用涵盖从制备药物聚合物载体,到化妆品和杀虫剂的配方,再到纳米结构材料的制造,以及在液-液微萃取中浓缩和分离痕量分析物。