Computational and Experimental Investigations of Phase-Separated Monolayers on Ultrasmall Noble Metal Nanoparticles

金属纳米粒子包含一个小的金属核心，可能由几千个原子组成，周围是一层有机分子，这决定了它与环境的相互作用。由两种不同类型的分子组成的层在表面分离时可以形成复杂的图案，如条状或斑点状，就像油和水一样。操纵这些图案的能力可能会导致需要精确控制纳米粒子与周围环境相互作用的新技术。然而，由于金属芯的小尺寸和弯曲形状，表征现有图案是困难的。在化学系大分子、超分子和纳米化学项目的支持下，弗吉尼亚大学的David Green教授和Kateri DuBay教授正在使用实验和计算技术相结合的方法来研究纳米颗粒表面的模式形成。他们的发现可以在光电子学、传感和医学应用方面实现创新。该项目也在培养未来的科学家和工程师。此外，通过让夏洛茨维尔地区的K-12学生、弗吉尼亚大学（University of Virginia）、传统黑人学院和大学以及东南部少数族裔服务机构的本科生参与进来，他们正在为STEM领域中代表性不足的少数族裔学生提供教育和研究机会。本项目旨在开发一个紧密结合理论、计算和实验的项目，以研究超小贵金属纳米颗粒（NPs）上的自组装单层（SAMs），其中单层由有机配体的混合物组成，可以在表面上移动并自组织形成平衡的纳米相。这项工作将多种分析工具和算法结合在一个集成策略中，以阐明在NP-SAM系统中控制SAM形态的驱动力。特别是，计算工具可以全面检查配体之间的长度和化学不匹配以及NP大小的影响，通过调整这些特征来促进SAM形态的从头设计。为了确定配体类型和NP大小如何影响SAM形态，需要进行单个NP统计。研究计划包括：(1)合成定义良好的单层保护NPs；(2)利用NP碎片利用激光解吸电离质谱技术绘制NP表面配体分布；(3)通过与实验数据的比较，以原子模拟为基础预测和可视化SAM形态。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Metal nanoparticles contain a small metallic core that might consist of just a few thousand atoms, surrounded by a layer of organic molecules, which determines its interaction with the environment. Layers made from two different types of molecules can form complex patterns such as strips or spots as they separate on the surface, like oil and water. The ability to manipulate these patterns could lead to new technologies that require precise control of the nanoparticle interaction with its surroundings. However, characterizing existing patterns is difficult due to the small size and curved shape of the metallic core. With support from the Macromolecular, Supramolecular and Nanochemistry Program in the Division of Chemistry, Professors David Green and Kateri DuBay at the University of Virginia are using a combination of experimental and computational techniques to study pattern formation on the nanoparticle surface. Their discoveries could enable innovations in optoelectronics, sensing, and medical applications. The project is also training future scientists and engineers. In addition, by engaging K-12 students in the Charlottesville area, as well as undergraduates at the University of Virginia and at historically black colleges and universities and minority-serving institutions in the southeast, they are providing educational and research opportunities to underrepresented minority students in STEM fields.This project aims to develop a tightly integrated program of theory, computation, and experiment to study self-assembled monolayers (SAMs) on ultra-small noble metal nanoparticles (NPs), where the monolayer is composed of a mixture of organic ligands that can move about on the surface and self-organize to form equilibrated nanophases. The work combines multiple analytic tools and algorithms in an integrated strategy to elucidate the driving forces that govern SAM morphology in NP-SAM systems. In particular, the computational tools enable comprehensive examination of the effects of length and chemical mismatches between ligands as well as NP size, facilitating the de novo design of SAM morphologies by tuning these characteristics. To determine how ligand type and NP size affect SAM morphology, single NP statistics are required. The research plans include: (1) synthesizing well-defined monolayer protected NPs; (2) mapping ligand distributions on NP surfaces with laser desorption ionization mass spectroscopy using NP fragments; and (3) predicting and visualizing SAM morphology with atomic simulation anchored by comparisons to experimental data.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.