Quantifying the Coarsening Kinetics of Supported Metal Nanoparticles Using Time-resolved Electron Microscopy, Data Analytics and Simulations

非技术摘要：金属纳米颗粒在各种工业中有重要的应用，尤其是在化学工业中，它们被用作催化剂，用于制造燃料和相关的化学副产品。这是因为它们的小尺寸暴露了它们表面的许多原子：这些表面原子有助于提高它们的反应性。然而，它们长期有效运作的能力与它们保持这种小尺寸的能力有关，即使暴露在高温和恶劣环境中也是如此，而高温和恶劣环境通常会导致颗粒生长。这项研究将通过使用先进的显微镜直接观察这些过程，测量单个颗粒和颗粒整体中发生的变化，并使用计算模型来澄清哪些过程是导致颗粒生长的最主要原因，从而阐明不需要的纳米颗粒生长的基本过程。这些研究将提供基础知识，可用于提高催化材料的长期性能，从而降低能源成本和提高工业产量。该项目将包括通过接触前沿材料表征工作、实验与理论之间的深度互动、使用先进的数据分析方法以及参观IBM T.J.沃森研究中心和布鲁克海文国家实验室(BNL)的领先实验室，为参与该项目的学生做好劳动力准备。BNL的夏季本科生实验室实习(Suli)项目和Louis Stokes少数民族参与联盟(LS-AMP)将引入波多黎各大学的学生参与数据分析代码的开发，以及将向更广泛社区传播的显微镜图像分析软件的开发。技术摘要：将结合先进的透射电子显微镜方法来研究纳米颗粒粗化中表面应力和颗粒间扩散相互作用的作用，量化所支持的纳米颗粒系统中蒸发、粗化和成熟之间的相互作用，并调查衬底修饰和纳米颗粒氧化和还原的相对水平对这些现象的影响。这项工作将利用高帧速率图像采集和半自动数据分析例程，从图像中产生准确的定量数据。这些数据将以一种自洽的方式使用，为计算模拟提供输入并证实其结果。由此产生的研究将使人们能够定量地了解纳米级工艺如何影响粗化和成熟，并将提出在受支持的金属纳米结构系统中缓解这些过程的策略。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Non-Technical Abstract:Metallic nanoparticles find important applications in a variety of industries, most notably as catalysts in the chemical industry where they are used for the creation of fuels and related chemical byproducts. This is because their small size exposes many atoms on their surface: these surface atoms are the ones that help to improve their reactivity. However, their ability to function effectively for long periods is related to their ability to maintain this small size, even when being exposed to high temperatures and harsh environments that would normally lead to particle growth. This study will clarify the fundamental processes by which unwanted nanoparticle growth occurs by directly observing these processes using advanced microscopies, measuring the changes that occur in both individual particles and particle ensembles, and using computational modeling to clarify what processes are most responsible for particle growth. The studies will provide fundamental knowledge that can be used to increase the long-term performance of catalytic materials, leading to reduced energy cost and greater industrial yields. The project will include workforce preparation for the student involved via exposure to forefront materials characterization efforts, a deep interaction between experiment and theory, utilization of advanced data analytics approaches and visits to leading laboratories at IBM T.J. Watson Research Center and Brookhaven National Laboratory (BNL). The Summer Undergraduate Laboratory Internship (SULI) program and the Louis Stokes Alliances for Minority Participation (LS-AMP) at BNL will bring in students from the University of Puerto Rico, Rio Piedras to participate in data analytics code development, as well the development of software for microscope image analysis that will be disseminated to the broader community.Technical Abstract:A combination of advanced transmission electron microscopy methods will be used to investigate the role of surface stress and interparticle diffusional interactions in nanoparticle coarsening, to quantify the interplay between evaporation, coarsening and ripening in supported nanoparticles systems, and to investigate the effects of substrate modification and relative levels of nanoparticle oxidation and reduction on these phenomena. The work will exploit high-frame rate image acquisition and semi-automated data analysis routines to produce accurate quantitative data from images. This data will be used in a self-consistent fashion to both provide inputs to and corroborate outcomes from computational simulations. The resulting studies will allow, quantitative understanding of how nanoscale processes affect coarsening and ripening and will suggest strategies to mitigate these process in supported metallic nanostructure systems.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.