Nanoparticle Tracking for Fluidic Self Assembly

One challenge of nanomanufacturing is to establish methods to assemble solution-based nanoparticles into organized structures with nanometer precision, with an eye toward doing so on an industrial scale. To address this challenge, we are measuring the forces and interactions that particles experience in liquids. By developing new techniques to precisely track and analyze the motion of individual nanoparticles moving in solution and interacting with other particles and surfaces, this research aims to determine the forces and interactions that govern fluidic self-assembly of nanoparticles into organized structures.

Over the last few decades, scientists have developed a sizable library of nanoscale “building blocks.” These nanoparticles have novel thermal, optical, mechanical, and chemical properties relative to their macroscopic counterparts, and organized assemblies of these components promise vast improvements in several technological areas, including optics, electronics, catalysis, and medicine. Tracking and characterizing the motion of these particles in the fluids used to deliver them is crucial to developing manufacturing processes to assemble large numbers of building blocks.

The motion of a nanoparticle in a liquid is governed by a complex interplay of fluid flow, external forces, and random Brownian motion. Tracking and analyzing particle motion provides information on each of these processes; the resulting interplay between them determines the eventual result of multi-particle assembly. One of the key barriers to visualizing and understanding these interactions is the lack of measurement methods that allow determination of the three-dimensional position of individual nanoparticles with few-nanometer resolution and few-millisecond time resolution. 

In one project, we developed a fast, robust data processing algorithm that allows particle positions to be determined from optically measured, digital images. The new algorithm can locate particles with nanometer resolution and is relatively immune to changes in background (stray light) or details of a particle’s shape or size. These types of changes often arise when tracking a particle drifting through focus in a microscope and can significantly affect the performance of other algorithms.

In another project, we fabricated several micrometer-sized fluid wells with angled mirrored sides, which allows microscopic observation and imaging of nanoparticles simultaneously both from directly above and from a reflected side-on view. To determine the location of an individual nanoparticle to within an approximate 20 nm range, we combine the position information from the orthogonal (perpendicular) reflected image plane and the direct image plane, to yield the position in all three dimensions. We are studying the capabilities and limitations of this promising new technique, named “Orthogonal Tracking Microscopy,” and are actively pursuing it as a method for studying the fine-scale interactions between particles and particles and surfaces in liquids.

• Theoretical Model of Errors in Micromirror-Based Three-Dimensional Particle Tracking, A. J. Berglund, M. D. McMahon, J. J. McClelland, and J. A. Liddle, Optics Letters 35, 1905-1907 (2010).
  
• 3D Particle Trajectories Observed by Orthogonal Tracking Microscopy, M. D. McMahon, A. J. Berglund, P. T. Carmichael, J. J. McClelland, and J. A. Liddle, ACS Nano 3, 609-614 (2009).
• Fast, Bias-Free Algorithm for Tracking Single Particles with Variable Size and Shape, A. J. Berglund, M.D. McMahon, J.J. McClelland, and J. A. Liddle, Optics Express 16, 14064-14075 (2008).