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

超小贵金属纳米颗粒上相分离单分子层的计算和实验研究

• 批准号: 1904884
• 负责人: David Green
• 金额: $ 49万
• 依托单位: University of Virginia Main Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1904884&HistoricalAwards=false
• 关键词: Computational; Experimental; Investigations; Phase; Separated

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.

金属纳米粒子包含一个小的金属核，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可以形成复杂的图案，例如当它们在表面分离时，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颗粒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，难以表征现有图案。在化学系大分子、超分子和纳米化学项目的支持下，弗吉尼亚大学的大卫绿色教授和卡特里·杜贝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图案形成。他们的发现可以实现光电子学，传感和医疗应用的创新。该项目还培养未来的科学家和工程师。此外，通过吸引夏洛茨维尔地区的K-12学生，以及弗吉尼亚大学和东南部历史悠久的黑人学院和大学以及少数民族服务机构的本科生，他们正在为STEM领域代表性不足的少数民族学生提供教育和研究机会。和实验研究超小贵金属纳米颗粒（NP）上的自组装单分子层（SAM），其中单层由有机配体的混合物组成，这些配体可以在表面上移动并自组织形成平衡的纳米相。这项工作结合了多种分析工具和算法，在一个综合的战略，以阐明驱动力，管理SAM形态在NP-SAM系统。特别是，计算工具能够全面检查配体之间的长度和化学错配以及NP大小的影响，通过调整这些特性来促进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，需要单个NP统计。研究计划包括：（2）使用NP片段用激光解吸电离质谱法绘制NP表面上的配体分布;以及（3）通过与实验数据的比较，利用原子模拟来预测和可视化SAM形态。该奖项反映了NSF的法定使命，并通过利用基金会的智力价值和更广泛的影响进行评估，被认为值得支持审查标准。