Abstract：
Dark field scattering microscopy can create large hyperspectral data sets that contain a wealth of information on the properties and the molecular environment of noble metal nanoparticles. For a quick screening of samples of microscopic dimensions that contain many different types of plasmonic nanostructures, we propose a multivariate analysis of data sets of thousands to several hundreds of thousands of scattering spectra. By using non-negative matrix factorization for decomposing the spectra, components are identified that represent individual plasmon resonances and relative contributions of these resonances to particular microscopic focal volumes in the mapping data sets. Using data from silver and gold nanoparticles in the presence of different molecules, including gold nanoparticle-protein agglomerates or silver nanoparticles forming aggregates in the presence of acrylamide, plasmonic properties are observed that differ from those of the original nanoparticles. For the case of acrylamide, we show that the plasmon resonances of the silver nanoparticles are ideally suited to support surface enhanced Raman scattering (SERS) and the two-photon excited process of surface enhanced hyper Raman scattering (SEHRS). Both vibrational tools give complementary information on the in situ formed polyacrylamide and the molecular composition at the nanoparticle surface.
摘要：
暗场散射显微镜可以创建大型高光谱数据集，其中包含有关贵金属纳米粒子的性质和分子环境的丰富信息。为了快速筛选包含许多不同类型的等离子体纳米结构的微观尺寸的样品，我们建议对数千到数十万散射光谱的数据集进行多变量分析。通过使用非负矩阵分解来分解光谱，在映射数据集中，识别代表单个等离子体共振和这些共振对特定微观聚焦体积的相对贡献的分量。使用不同分子存在的银和金纳米颗粒的数据，包括在丙烯酰胺存在下形成聚集体的金纳米颗粒-蛋白质聚集体或银纳米颗粒，观察到与原始纳米粒子不同的等离子体性质。对于丙烯酰胺，我们表明，银纳米粒子的等离子体共振非常适合支持表面增强拉曼散射（SERS）和表面增强超拉曼散射（SEHRS）的双光子激发过程。两种振动工具都提供了关于原位形成的聚丙烯酰胺和纳米颗粒表面处的分子组成的补充信息。
