Automated primary particle sizing of nanoparticle aggregates by TEM image analysis

A simple circularity-based approach for nanoparticle size histograms beyond the spherical approximation

Conventional Transmission Electron Microscopy (TEM) is widely used for routine characterization of the size and shape of an assembly of (nano)particles. While the most basic approach only uses the projected area of each particle to infer its size (the "circular equivalent diameter" corresponding to the so-called "spherical approximation"), other shape descriptors can be determined and used for more elaborate analyses. In this article we present a generic model of particles, considered to be made of a few individual grains, and show how the equivalent size (i.e. a particle volume information) can be reliably deduced using only two basic parameters: the projected area and the perimeter of a particle. We compare this simple model to the spherical and ellipsoidal approximations and discuss its benefits. Then, partial coalescence of grains in a particle is also considered and we show how a simple analytical approximation, based on the circularity parameter of each particle, can improve the experimental determination of a particle size histogram. The analysis of experimental observations on nanoparticles assemblies obtained by mass-selected cluster deposition is presented, to illustrate the efficiency of the proposed approach for the determination of particle size just from conventional TEM images. We show how the presence of multimers offers an excellent opportunity to validate our improved and simple procedure. In addition, since the circularity plays a central role in this approach, attention is attracted on the perimeter determination in a pixelated image.

Quantification of monodisperse and biocompatible gold nanoparticles by single-particle ICP-MS

Bioanalytical and biomedical applications often require nanoparticles that exhibit narrow size distributions and biocompatibility. Here, we demonstrate how different synthesis methods affect gold nanoparticle (AuNPs) monodispersity and cytotoxicity. Using single particle inductively coupled plasma mass spectrometry (SP-ICP-MS), we found that the size distribution of AuNPs synthesized with a cetyltrimethylammonium chloride (CTAC) cap was significantly improved compared to AuNPs synthesized with citrate capping agents. We determined an up to 4× decrease in the full width at half maximum (FWHM) value of the normal distributions of AuNP diameter and up to a 12% decrease in relative standard deviation (RSD). While the CTAC-capped AuNPs exhibit narrow nanoparticle size distributions, they are cytotoxic, which limits safe and effective bioanalytical and biomedical applications. We sought to impart biocompatibility to CTAC-capped AuNPs through a PEGylation-based surface ligand exchange. We developed a unique ligand exchange method driven by physical force. We demonstrated the successful PEGylation using various PEG derivatives and used these PEGylated nanoparticles to further bioconjugate nucleic acids and peptides. Using cell viability quantification, we confirmed that the monodisperse PEGylated AuNPs were biocompatible. Our monodisperse and biocompatible nanoparticles may advance safe and effective bioanalytical and biomedical applications of nanomaterials.

On determining soot maturity: A review of the role of microscopy- and spectroscopy-based techniques

Incomplete combustion is the main source of airborne soot, which has negative impacts on public health and the environment. Understanding the morphological and chemical evolution of soot is important for assessing and mitigating the impact of soot emissions. Morphological and chemical structures of soot are commonly studied using microscopy or spectroscopy, and the best technique depends on the parameter of interest and the stage of soot formation considered (i.e., maturity). For the earliest stages of soot formation, particles exhibit simple morphology yet complex and reactive chemical composition, which is best studied by spectroscopic techniques sensitive to the large number of soot precursor species. The only microscope that can offer some morphological information at this stage is the scanning probe microscopy, which can image single polycyclic aromatic hydrocarbons, the precursors of soot. A broader range of types of spectrometers and microscopes can be used by increasing the soot maturity. Mature soot is primarily carbon, and exhibits complex fractal-like morphology best studied with electron microscopy and techniques sensitive to thin oxide or organic coatings. Each characterization technique can target different morphological and chemical properties of soot, from the early to the late stage of its formation. Thus, a guideline for the selection of the appropriate technique can facilitates studies on environmental samples involving the presence of soot.

Automatic detection of particle size distribution by image analysis based on local adaptive canny edge detection and modified circular Hough transform

To obtain size distribution of nanoparticles, scanning electron microscope (SEM) and transmission electron microscopy (TEM) have been widely adopted, but manual measurement of statistical size distributions from the SEM or TEM images is time-consuming and labor-intensive. Therefore, automatic detection methods are desirable. This paper proposes an automatic image processing algorithm which is mainly based on local adaptive Canny edge detection and modified circular Hough transform. The proposed algorithm can utilize the local thresholds to detect particles from the images with different degrees of complexity. Compared with the results produced by applying global thresholds, our algorithm performs much better. The robustness and reliability of this method have been verified by comparing its results with manual measurement, and an excellent agreement has been found. The proposed method can accurately recognize the particles with high efficiency.

Relationship between Coating-Induced Soot Aggregate Restructuring and Primary Particle Number

The restructuring of monodisperse soot aggregates due to coatings of secondary organic aerosol (SOA) was investigated in a series of photo-oxidation chamber experiments. Soot aggregates were generated by one of three sources (an ethylene premixed burner, a methane inverted diffusion burner, or a diesel generator), treated by denuding, size-selected by a differential mobility analyzer, and injected into a smog chamber, where they were exposed to the photo-oxidation products of p-xylene, which partitioned to form SOA coatings. The evolution of aggregates from their initial to final morphologies was investigated in situ by mobility and mass measurements and ex situ by transmission electron microscopy. At a given initial aggregate mobility diameter, diesel aggregates are less dense and composed of smaller primary particles than those generated by the two burners, and they restructure to a smaller final mobility diameter. Remarkably, the final degrees of restructuring of aggregates from all three sources exhibit the same linear dependence on the number of primary particles per aggregate. The observed linear relationship, valid for the atmospherically relevant SOA coating investigated here, could allow modelers to predict the evolution of aggregate morphology based on a single property of the aggregates.

An automatic algorithm for determination of the nanoparticles from TEM images using circular hough transform

Nanoparticles have a wide range of applications in science and technology, and the size distribution of nanoparticles is one of the most important statistical properties. Transmission electron microscopy (TEM) or X-ray diffraction is commonly used for the characterization and measuring particle size distributions, but manual analysis of the micrographs is extremely labor-intensive. Here, we have developed an image processing algorithm for measuring particle size distributions from TEM images in the presence of overlapped particles and uneven background. The approach is based on the modified circular Hough transform, and pre and post processing techniques on TEM image to improve the accuracy and increase the detection rate of the nano particles. Its application is presented through several images with different noises, uneven backgrounds and over lapped particles. The merits of this robust quantifying method are demonstrated by comparing the results with the data obtained through manual measurement. The algorithm allows particles to be detected and characterized with high accuracy.