Nanoparticles (NPs) with controlled surface modification have unique properties and broad applications, ranging from biomedicine to catalysis. However, surface modification processes usually generate a mixture of NPs with a range of different surface structures. Herein, based upon coarse-grained molecular simulations, we propose a facile two-step approach for recognition of targeted nanoparticles (TNPs) by a second type of nanostructure, followed by selective precipitation driven by an external force, to extract TNPs from NP mixture with similar surface structures. As an example, we consider mixtures of partially functionalized nanosheets representing graphene flakes of uniform size and shape but varying surface modification. Our results show that Janus particles can effectively recognize and selectively adsorb on targeted graphene NPs (TGNPs) to allow their separation from NP mixture. In our molecular simulations, high purity TGNPs (up 99.9%) could be extracted from a mixture containing only ∼10% TGNPs after three to four rounds of separation.

中文翻译：

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通过简便的两步法纳米分离具有相似表面结构的纳米颗粒混合物

具有受控的表面修饰的纳米颗粒（NPs）具有独特的特性和广泛的应用，范围从生物医学到催化。但是，表面修饰过程通常会生成具有一系列不同表面结构的NP混合物。本文中，基于粗粒度分子模拟，我们提出了一种简便的两步方法，通过第二种纳米结构识别目标纳米颗粒（TNP），然后通过外力驱动选择性沉淀，从NP混合物中提取TNP。相似的表面结构。例如，我们考虑部分功能化的纳米片的混合物，这些纳米片代表尺寸和形状均一但表面改性不同的石墨烯薄片。我们的结果表明，Janus颗粒可以有效识别并选择性吸附在目标石墨烯NPs（TGNPs）上，从而允许它们从NP混合物中分离出来。在我们的分子模拟中，经过三到四轮分离，可以从仅含约10％TGNP的混合物中提取高纯度TGNP（高达99.9％）。