Luminescence Lifetime-Based Sensing Platform Based on Cyclometalated Iridium(III) Complexes for the Detection of Perfluorooctanoic Acid in Aqueous Samples.

Luminescence lifetimes are an attractive analytical method for detection due to its high sensitivity and stability. Iridium probes exhibit luminescence with long excited-state lifetimes, which are sensitive to the local environment. Perfluorooctanoic acid (PFOA) is listed as a chemical of high concern regarding its toxicity and is classified as a "forever chemical". In addition to strict limits on the presence of PFOA in drinking water, environmental contamination from industrial effluent or chemical spills requires rapid, simple, accurate, and cost-effective analysis in order to aid containment. Herein, we report the fabrication and function of a novel and facile luminescence sensor for PFOA based on iridium modified on gold surfaces. These surfaces were modified with lipophilic iridium complexes bearing alkyl chains, namely, IrC6 and IrC12, and Zonyl-FSA surfactant. Upon addition of PFOA, the modified surfaces IrC6-FSA@Au and IrC12-FSA @Au show the largest change in the red luminescence signal with changes in the luminescence lifetime that allow monitoring of PFOA concentrations in aqueous solutions. The platform was tested for the measurement of PFOA in aqueous samples spiked with known concentrations of PFOA and demonstrated the capacity to determine PFOA at concentrations >100 µg/L (240 nM).

Embedding and cross-sectioning as a sample preparation procedure for accurate and representative size and shape measurement of nanopowders.

Reliable measurement of the size of polydisperse, complex-shaped commercial nanopowders is a difficult but necessary task, e.g., for regulatory requirements and toxicity risk assessment. Suitable methods exist for the accurate characterization of the size of non-aggregated, stabilized, spherical and monodisperse nanoparticles. In contrast, industrial nanoscale powders usually require dedicated sample preparation procedures developed for the analysis method of choice. These nano-powders tend to agglomerate and/or aggregate, a behavior which in combination with an innate broad particle size distribution and irregular shape often significantly alters the achievable accuracy of the measured size parameters. The present study systematically tests two commercially available nanoscale powders using different sample preparation methods for correlative analysis by scanning electron microscopy, dynamic light scattering, Brunauer-Emmet-Teller method and differential mobility analysis. One focus was set on the sample preparation by embedding nanoparticles in carbon-based hot-mounting resin. Literature on this topic is scarce and the accuracy of the data extracted from cross sections of these particles is unclearly stated. In this paper systematic simulations on the deviation of the size parameters of well-defined series of nanoparticles with different shapes from the nominal value were carried out and the contributing factors are discussed.

Towards 3D determination of the surface roughness of core-shell microparticles as a routine quality control procedure by scanning electron microscopy.

Recently, we have developed an algorithm to quantitatively evaluate the roughness of spherical microparticles using scanning electron microscopy (SEM) images. The algorithm calculates the root-mean-squared profile roughness (RMS-RQ) of a single particle by analyzing the particle's boundary. The information extracted from a single SEM image yields however only two-dimensional (2D) profile roughness data from the horizontal plane of a particle. The present study offers a practical procedure and the necessary software tools to gain quasi three-dimensional (3D) information from 2D particle contours recorded at different particle inclinations by tilting the sample (stage). This new approach was tested on a set of polystyrene core-iron oxide shell-silica shell particles as few micrometer-sized beads with different (tailored) surface roughness, providing the proof of principle that validates the applicability of the proposed method. SEM images of these particles were analyzed by the latest version of the developed algorithm, which allows to determine the analysis of particles in terms of roughness both within a batch and across the batches as a routine quality control procedure. A separate set of particles has been analyzed by atomic force microscopy (AFM) as a powerful complementary surface analysis technique integrated into SEM, and the roughness results have been compared.