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Updated: Jun 7, 2026

Advanced Compositional Analysis of Nanoparticle-polymer Composites Using Direct Fluorescence Imaging

Advanced Compositional Analysis of Nanoparticle-polymer Composites Using Direct Fluorescence Imaging

Published on: July 19, 2016

Structural analysis of soft multicomponent nanoparticle clusters.

Leonard F Pease¹, Jeremy I Feldblyum, Silvia H Depaoli Lacaerda

¹Department of Chemical Engineering, University of Utah, Salt Lake City, Utah 84112, United States. pease@eng.utah.edu

|November 6, 2010

Summary

This summary is machine-generated.

This study enhances electrospray differential mobility analysis (ES-DMA) to analyze complex nanobioclusters. The improved method accurately determines the size and composition of soft and hard components in various nanoparticle structures.

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Last Updated: Jun 7, 2026

Advanced Compositional Analysis of Nanoparticle-polymer Composites Using Direct Fluorescence Imaging

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Published on: September 13, 2020

Area of Science:

Nanotechnology
Biophysics
Analytical Chemistry

Background:

Analyzing soft multicomponent nanobioclusters requires advanced quantitative techniques.
Existing methods often struggle with complex nanoparticle structures and compositions.

Purpose of the Study:

To extend the electrospray differential mobility analysis (ES-DMA) framework for analyzing diverse nanobiocluster geometries.
To accurately determine the size and composition of soft and hard components within nanoparticle complexes.

Main Methods:

Combined electrospray differential mobility analysis (ES-DMA) for rapid cluster size measurement with transmission electron microscopy (TEM) for hard component detection.
Developed analytical models to interpret combined ES-DMA and TEM data for nanoparticle complex analysis.

Main Results:

Successfully extended ES-DMA analysis to accommodate protein corona-coated nanorods, heterogeneously sized nanospheres, and mixed nanosphere-nanorod clusters.
Demonstrated the method's critical role in quantifying quantum dots on lambda phage for pathogen detection.

Conclusions:

The enhanced ES-DMA framework provides a powerful tool for characterizing complex nanobioclusters.
This advancement is crucial for developing rapid diagnostic methods, such as bacterial pathogen detection.