Departament de Química, Universitat Autònoma de Barcelona, Bellaterra (Cerdanyola del Vallès), 08193, Barcelona, Spain.
Institut Català de Nanociència i Nanotecnologia (ICN2), CSIC and BIST, Campus UAB, Bellaterra, 08193, Barcelona, Spain.
Sci Rep. 2022 Aug 17;12(1):13926. doi: 10.1038/s41598-022-18155-2.
Nanoparticles (NPs) show promising applications in biomedicine, catalysis, and energy harvesting. This applicability relies on controlling the material's features at the nanometer scale. Surfactants, a unique class of surface-active molecules, have a remarkable ability to tune NPs activity; provide specific functions, avoid their aggregation, and create stable colloidal solutions. Surfactants also control nanoparticles' nucleation and growth processes by modifying nuclei solubility and surface energy. While nucleation seems independent from the surfactant, NP's growth depends on it. NP`s size is influenced by the type of functional group (C, O, S or N), length of its C chain and NP to surfactant ratio. In this paper, gold nanoparticles (Au NPs) are taken as model systems to study how nucleation and growth processes are affected by the choice of surfactants by Dissipative Particle Dynamics (DPD) simulations. DPD has been mainly used for studying biochemical structures, like lipid bilayer models. However, the study of solid NPs, and their conjugates, needs the introduction of a new metallic component. To represent the collective phenomena of these large systems, their degrees of freedom are reduced by Coarse-Grained (CG) models. DPD behaved as a powerful tool for studying complex systems and shedding some light on some experimental observations, otherwise difficult to explain.
纳米粒子（NPs）在生物医药、催化和能量收集等领域具有广阔的应用前景。这种适用性依赖于控制材料在纳米尺度上的特性。表面活性剂是一类具有独特表面活性的分子，具有显著的调节 NPs 活性的能力；提供特定的功能，避免其聚集，并形成稳定的胶体溶液。表面活性剂还可以通过改变核的溶解度和表面能来控制纳米颗粒的成核和生长过程。虽然成核似乎与表面活性剂无关，但 NP 的生长取决于它。NP 的尺寸受官能团类型（C、O、S 或 N）、C 链长度和 NP 与表面活性剂的比例的影响。在本文中，金纳米粒子（Au NPs）被用作模型体系，通过耗散粒子动力学（DPD）模拟研究了成核和生长过程如何受表面活性剂选择的影响。DPD 主要用于研究生化结构，如脂质双层模型。然而，对固体 NPs 及其缀合物的研究需要引入新的金属成分。为了表示这些大系统的集体现象，它们的自由度通过粗粒化（CG）模型来降低。DPD 是研究复杂系统的有力工具，并为一些实验观察提供了一些启示，否则这些观察很难解释。
