This article reviews progress in the application of electrophoretic techniques for the separation of nanoparticles. Numerous types of nanoparticles have recently been synthesised and integrated into different products and procedures. Consequently, analytical methods for the efficient characterisation of nanoparticles are now required. Several studies have revealed that gel electrophoresis can readily be used for separating nanoparticles according to their size or shape. However, many other studies focused on separation of nanoparticles by CE. In some cases nanoparticles could be separated by CZE, simply using pure buffer as the BGE. In other studies, buffer additives (most often SDS) were used, enabling fast separations of metallic nanoparticles by size. Other CE methods also allowed for separation of nanoparticle conjugates with biomolecules. Dielectrophoresis is yet another electrophoretic technique useful in separation and characterisation of nanoparticles; particularly nanotubes. Detection methods often used after electrophoretic separation include UV/Vis absorption and fluorescence spectroscopy. Examples of recent and relevant older reports are presented here. The authors conclude that electrophoretic methods for nanoanalysis can provide inexpensive and efficient tools for quality assurance and safety control; and as a consequence, they can augment transfer of nanotechnologies from research to industry.
The developments in mass spectrometry (MS) in the past few decades reveal the power and versatility of this technology. MS methods are utilized in routine analyses as well as research activities involving a broad range of analytes (elements and molecules) and countless matrices. However, manual MS analysis is gradually becoming a thing of the past. In this article, the available MS automation strategies are critically evaluated. Automation of analytical workflows culminating with MS detection encompasses involvement of automated operations in any of the steps related to sample handling/treatment before MS detection, sample introduction, MS data acquisition, and MS data processing. Automated MS workflows help to overcome the intrinsic limitations of MS methodology regarding reproducibility, throughput, and the expertise required to operate MS instruments. Such workflows often comprise automated off-line and on-line steps such as sampling, extraction, derivatization, and separation. The most common instrumental tools include autosamplers, multi-axis robots, flow injection systems, and lab-on-a-chip. Prototyping customized automated MS systems is a way to introduce non-standard automated features to MS workflows. The review highlights the enabling role of automated MS procedures in various sectors of academic research and industry. Examples include applications of automated MS workflows in bioscience, environmental studies, and exploration of the outer space.