Argon Cluster Sputtering Reveals Internal Chemical Distribution in Submicron Polymeric Particles

Abstract

The ability to measure the internal chemical distribution of particles is of significant benefit to the development and testing of products relevant to the pharmaceutical, agrichemical, and food industries. These include nanomedicine particle carriers, such as those used in anticancer drugs, vaccines, and viral carriers for gene therapies. In this work, we carefully investigated the sputtering behavior of spherical organic particles using an argon cluster beam and scanning electron microscopy (SEM). Based on these observations, we then developed a geometrical model to interpret useful chemical depth profiles of polymeric particles by X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectrometry (TOF-SIMS) in conjunction with argon cluster sputtering. We found that change in the shape of isolated particles may be modeled in a simple manner by assuming a constant sputtering yield across the particle surface. Furthermore, packed particles undergo an interesting geometry transition during the sputtering process, which can primarily be explained and modeled by a shadowing effect from other particles in the vicinity. We successfully applied this model to analyze the structure and chemistry of nonideal polymeric core−shell particles. We show that with some knowledge of the materials' sputtering yields, the particle diameter can approximately be determined by using XPS or calibrated SIMS and that the fractional volume of the core in the particle can be measured. Furthermore, the analysis provides a radial distribution of the core material within the particle. This distribution is in accord with transmission electron microscopy data available on the same materials. The radial distribution demonstrates that the cores are randomly positioned within the particles but avoid a region close to the surface. This work demonstrates that it is possible to use a simple model to describe the shape change of organic spherical particles during argon cluster sputtering and interpret chemical measurements by XPS and SIMS methods.

Characterization of buried interfaces using Ga Kα hard X-ray photoelectron spectroscopy (HAXPES)

“…89 For the largest particle type (with a shell thickness of 35.5 nm), the core could not be detected and sputter depth profiling using argon cluster ions was necessary to obtain detail on the internal distribution of the materials. 91…”

“…89 For the largest particle type (with a shell thickness of 35.5 nm), the core could not be detected and sputter depth proling using argon cluster ions was necessary to obtain detail on the internal distribution of the materials. 91 Fig. 12(a) and (b) demonstrate that the core material may be detected for particles with nominal shell thicknesses of 12 nm, 23.5 nm and 35.5 nm using Ga Ka HAXPES.…”

Composition, thickness, and homogeneity of the coating of core–shell nanoparticles—possibilities, limits, and challenges of X-ray photoelectron spectroscopy

“…An alternative to this non-destructive approach is soft sputtering with modern Ar cluster ion guns. Therefore, an understanding of the sputtering process is necessary [ 76 ]. All in all, these recent technological innovations can boost the application of XPS for core–shell nanoparticles, especially addressing the question of intermixing which is often controversially discussed [ 16 ].…”

“…Another exciting possibility to obtain insights into the internal structure of polymer nanoparticles provides modern Ar cluster sputtering which was used for the same PTFE-PMMA core–shell particles presented here. It was definitively shown that the nanoparticles have a complete PMMA shell but with randomly positioned internal cores, which was an assumption in the QUASES simulation [ 76 ]. Using the argon cluster sputtering approach, the total volume fraction of PTFE was accurately measured and, with knowledge of the sputtering yield, the particle diameter could also be estimated.…”

A two‐point calibration method for quantifying organic binary mixtures using secondary ion mass spectrometry in the presence of matrix effects

“…In some cases, it is possible to use XPS to obtain calibration data for SIMS, and this has been useful, for example, in interpreting SIMS data from sputterdepth profiling of organic core-shell nanoparticles. 27 The application of SIMS to drug delivery vehicles 11,[28][29][30][31][32][33][34][35][36][37][38][39] is an important area where simple quantification schemes are required as well as in the analysis of a number of technical products. 40,41 In the case of more complicated, multicomponent and multiphase materials such as biological samples, these methods are not applicable but represent a step on the road to obtaining quantitative information.…”