Department of Chemical Engineering Massachusetts Institute of Technology, 77 Massachusetts Avenue 66-570b, Cambridge, MA, 02139, USA.
Small. 2019 Sep;15(37):e1901468. doi: 10.1002/smll.201901468. Epub 2019 Jul 24.
Colloidal dispersions of nanomaterials are often polydisperse in size, significantly complicating their characterization. This is particularly true for materials early in their historical development due to synthetic control, dispersion efficiency, and instability during storage. Because a wide range of system properties and technological applications depend on particle dimensions, it remains an important problem in nanotechnology to identify a method for the routine characterization of polydispersity in nanoparticle samples, especially changes over time. Commonly employed methods such as dynamic light scattering or analytical ultracentrifugation (AUC) accurately estimate only the first moment of the distribution or are not routine. In this work, the use of single-particle tracking (SPT) to probe size distributions of common nanoparticle dispersions, including polystyrene nanoparticles, single-walled carbon nanotubes, graphene oxide, chitosan-tripolyphosphate, acrylate, hexagonal boron nitride, and poly(lactic-co-glycolic acid), is proposed and explored. The analysis of particle tracks is conducted using a newly developed Bayesian algorithm that is called Maximum A posteriori Nanoparticle Tracking Analysis. By combining SPT and AUC techniques, it is shown that it is possible to independently estimate the mean aspect ratio of anisotropic particles, an important characterization property. It is concluded that SPT provides a facile, rapid analytical method for routine nanomaterials characterization.
纳米材料的胶体分散体通常在尺寸上是多分散的，这使得它们的特性分析变得非常复杂。对于那些处于早期发展阶段的材料来说，这种情况尤其如此，因为其合成控制、分散效率以及在储存过程中的不稳定性等因素都会导致多分散性的出现。由于一系列系统性能和技术应用都依赖于颗粒尺寸，因此，确定一种常规方法来对纳米颗粒样品的多分散性进行特征描述，尤其是随时间的变化情况，仍然是纳米技术中的一个重要问题。通常采用的方法，如动态光散射或分析超速离心（AUC），只能准确估计分布的第一阶矩，或者不常用。在这项工作中，提出并探讨了使用单颗粒跟踪（SPT）来探测常见纳米颗粒分散体的尺寸分布的方法，包括聚苯乙烯纳米颗粒、单壁碳纳米管、氧化石墨烯、壳聚糖-三聚磷酸酯、丙烯酸酯、六方氮化硼和聚（乳酸-共-羟基乙酸）。使用一种新开发的贝叶斯算法，即最大后验纳米颗粒跟踪分析，对粒子轨迹进行分析。通过将 SPT 和 AUC 技术相结合，结果表明，可以独立地估计各向异性粒子的平均纵横比这一重要特征参数。研究结论认为，SPT 为常规纳米材料的特征描述提供了一种简便、快速的分析方法。
