Interlaboratory Comparison Reveals State of the Art in Microplastic Detection and Quantification Methods.

In this study, we investigate the current accuracy of widely used microplastic (MP) detection methods through an interlaboratory comparison (ILC) involving ISO-approved techniques. The ILC was organized under the prestandardization platform of VAMAS (Versailles Project on Advanced Materials and Standards) and gathered a large number (84) of analytical laboratories across the globe. The aim of this ILC was (i) to test and to compare two thermo-analytical and three spectroscopical methods with respect to their suitability to identify and quantify microplastics in a water-soluble matrix and (ii) to test the suitability of the microplastic test materials to be used in ILCs.

In-depth analysis of FeNi-based nanoparticles for the oxygen evolution reaction.

This study investigates the effect of varying iron-to-nickel ratios on the catalytic performance of Fe-Ni oxide nanoparticles (NPs) for the oxygen evolution reaction (OER). Addressing the issue of high energy wastage due to large overpotentials in OER, we synthesized and characterized different NP catalysts with different Fe: Ni oxide ratios. Transmission Electron Microscopy (TEM), Energy Dispersive X-ray Spectroscopy (EDS), and X-ray Diffraction (XRD) were employed to determine the morphology, elemental and phase composition of the NPs.

Development of a one-pot synthesis of rGO in water by optimizing Tour's method parameters.

Since its first synthesis in 2004, graphene has been widely studied and several different synthesis methods has been developed. Solvent exfoliation of graphite and the reduction of graphene oxide previously obtained through graphite oxidation are the most employed. In this work, we exploited synthesis conditions of a method usually employed for obtaining graphene oxide (the Tour's method) for directly obtaining a very poorly oxidised material with characteristics like reduced graphene oxide.

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-R) 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.

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".

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.

Iron Oxide Nanocubes as a New Certified Reference Material for Nanoparticle Size Measurements.

The rational design and increasing industrial use of nanomaterials require a reliable characterization of their physicochemical key properties like size, size distribution, shape, and surface chemistry. This calls for nanoscale reference materials (nanoRMs) for the validation and standardization of commonly used characterization methods closely matching real-world nonspherical nano-objects. This encouraged us to develop a nonspherical nanoRM of very small size consisting of 8 nm iron oxide nanocubes (BAM-N012) to complement spherical gold, silica, and polymer nanoRMs.

Knowledge, Information, and Data Readiness Levels (KaRLs) for Risk Assessment, Communication, and Governance of Nano-, New, and Other Advanced Materials.

The obvious benefits derived from the increasing use of engineered nano-, new, and advanced materials and associated products have to be weighed out by a governance process against their possible risks. Differences in risk perception (beliefs about potential harm) among stakeholders, in particular nonscientists, and low transparency of the underlying decision processes can lead to a lack of support and acceptance of nano-, new, and other advanced material enabled products. To integrate scientific outcomes with stakeholders needs, this work develops a new approach comprising a nine-level, stepwise categorization and guidance system entitled "Knowledge, Information, and Data Readiness Levels" (KaRLs), analogous to the NASA Technology Readiness Levels.

Metrological Protocols for Reaching Reliable and SI-Traceable Size Results for Multi-Modal and Complexly Shaped Reference Nanoparticles.

The study described in this paper was conducted in the framework of the European nPSize project (EMPIR program) with the main objective of proposing new reference certified nanomaterials for the market in order to improve the reliability and traceability of nanoparticle size measurements. For this purpose, bimodal populations as well as complexly shaped nanoparticles (bipyramids, cubes, and rods) were synthesized. An inter-laboratory comparison was organized for comparing the size measurements of the selected nanoparticle samples performed with electron microscopy (TEM, SEM, and TSEM), scanning probe microscopy (AFM), or small-angle X-ray scattering (SAXS).

NanoDefiner Framework and e-Tool Revisited According to the European Commission's Nanomaterial Definition 2022/C 229/01.

The new recommended definition of a nanomaterial, 2022/C 229/01, adopted by the European Commission in 2022, will have a considerable impact on European Union legislation addressing chemicals, and therefore tools to implement this new definition are urgently needed. The updated NanoDefiner framework and its e-tool implementation presented here are such instruments, which help stakeholders to find out in a straightforward way whether a material is a nanomaterial or not. They are two major outcomes of the NanoDefine project, which is explicitly referred to in the new definition.

Template-free synthesis of mesoporous and amorphous transition metal phosphate materials.

We present how mesoporosity can be engineered in transition metal phosphate (TMPs) materials in a template-free manner. The method involves the transformation of a precursor metal phosphate phase, called M-struvite (NHMPO·6HO, M = Mg, Ni, Co, NiCo). It relies on the thermal decomposition of crystalline M-struvite precursors to an amorphous and simultaneously mesoporous phase, which forms during degassing of NH and HO.

Assessing the influence of microwave-assisted synthesis parameters and stabilizing ligands on the optical properties of AIS/ZnS quantum dots.

Luminescent semiconductor quantum dots (QDs) are frequently used in the life and material sciences as reporter for bioimaging studies and as active components in devices such as displays, light-emitting diodes, solar cells, and sensors. Increasing concerns regarding the use of toxic elements like cadmium and lead, and hazardous organic solvents during QD synthesis have meanwhile triggered the search for heavy-metal free QDs using green chemistry syntheses methods. Interesting candidates are ternary AgInS (AIS) QDs that exhibit broad photoluminescence (PL) bands, large effective Stokes shifts, high PL quantum yields (PL QYs), and long PL lifetimes, which are particularly beneficial for applications such as bioimaging, white light-emitting diodes, and solar concentrators.

Correction: Peters et al. Benchmarking the ACEnano Toolbox for Characterisation of Nanoparticle Size and Concentration by Interlaboratory Comparison. 2021, , 5315.

Due to miscommunication a number of potential co-authors were not listed in the original publication [...

Counting Small Particles in Electron Microscopy Images-Proposal for Rules and Their Application in Practice.

Electron microscopy (EM) is the gold standard for the characterisation of the morphology (size and shape) of nanoparticles. Visual observation of objects under examination is always a necessary first step in the characterisation process. Several questions arise when undertaking to identify and count particles to measure their size and shape distribution.

Blueprint for a self-sustained European Centre for service provision in safe and sustainable innovation for nanotechnology.

The coming years are expected to bring rapid changes in the nanotechnology regulatory landscape, with the establishment of a new framework for nano-risk governance, in silico approaches for characterisation and risk assessment of nanomaterials, and novel procedures for the early identification and management of nanomaterial risks. In this context, Safe(r)-by-Design (SbD) emerges as a powerful preventive approach to support the development of safe and sustainable (SSbD) nanotechnology-based products and processes throughout the life cycle. This paper summarises the work undertaken to develop a blueprint for the deployment and operation of a permanent European Centre of collaborating laboratories and research organisations supporting safe innovation in nanotechnologies.

One-Pot Heat-Up Synthesis of ZnSe Magic-Sized Clusters Using Thiol Ligands.

The synthesis of two new families of ZnSe magic-sized clusters (MSCs) is achieved using the thiol ligand 1-dodecanethiol in a simple one-pot heat-up approach. The sizes of the MSCs are controlled with the thiol ligand concentration and reaction temperature.

Automation and Standardization-A Coupled Approach towards Reproducible Sample Preparation Protocols for Nanomaterial Analysis.

Whereas the characterization of nanomaterials using different analytical techniques is often highly automated and standardized, the sample preparation that precedes it causes a bottleneck in nanomaterial analysis as it is performed manually. Usually, this pretreatment depends on the skills and experience of the analysts. Furthermore, adequate reporting of the sample preparation is often missing.

Correlative Analysis of the Dimensional Properties of Bipyramidal Titania Nanoparticles by Complementing Electron Microscopy with Other Methods.

In this paper, the accurate determination of the size and size distribution of bipyramidal anatase nanoparticles (NPs) after deposition as single particles on a silicon substrate by correlative Scanning Electron Microscopy (SEM) with Atomic Force Microscopy (AFM) analysis is described as a new measurement procedure for metrological purposes. The knowledge of the exact orientation of the NPs is a crucial step in extracting the real 3D dimensions of the particles. Two approaches are proposed to determine the geometrical orientation of individual nano-bipyramides: (i) AFM profiling along the long bipyramid axis and (ii) stage tilting followed by SEM imaging.

Benchmarking the ACEnano Toolbox for Characterisation of Nanoparticle Size and Concentration by Interlaboratory Comparisons.

ACEnano is an EU-funded project which aims at developing, optimising and validating methods for the detection and characterisation of nanomaterials (NMs) in increasingly complex matrices to improve confidence in the results and support their use in regulation. Within this project, several interlaboratory comparisons (ILCs) for the determination of particle size and concentration have been organised to benchmark existing analytical methods. In this paper the results of a number of these ILCs for the characterisation of NMs are presented and discussed.

Carrier Fibers for the Safe Dosage of Nanoparticles in Nanocomposites: Nanomechanical and Thermomechanical Study on Polycarbonate/Boehmite Electrospun Fibers Embedded in Epoxy Resin.

The reinforcing effect of boehmite nanoparticles (BNP) in epoxy resins for fiber composite lightweight construction is related to the formation of a soft but bound interphase between filler and polymer. The interphase is able to dissipate crack propagation energy and consequently increases the fracture toughness of the epoxy resin. Usually, the nanoparticles are dispersed in the resin and then mixed with the hardener to form an applicable mixture to impregnate the fibers.

Reliable Surface Analysis Data of Nanomaterials in Support of Risk Assessment Based on Minimum Information Requirements.

The minimum information requirements needed to guarantee high-quality surface analysis data of nanomaterials are described with the aim to provide reliable and traceable information about size, shape, elemental composition and surface chemistry for risk assessment approaches. The widespread surface analysis methods electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS) and secondary ion mass spectrometry (SIMS) were considered. The complete analysis sequence from sample preparation, over measurements, to data analysis and data format for reporting and archiving is outlined.

Workflow towards automated segmentation of agglomerated, non-spherical particles from electron microscopy images using artificial neural networks.

We present a workflow for obtaining fully trained artificial neural networks that can perform automatic particle segmentations of agglomerated, non-spherical nanoparticles from scanning electron microscopy images "from scratch", without the need for large training data sets of manually annotated images. The whole process only requires about 15 min of hands-on time by a user and can typically be finished within less than 12 h when training on a single graphics card (GPU). After training, SEM image analysis can be carried out by the artificial neural network within seconds.

Machine learning approach for elucidating and predicting the role of synthesis parameters on the shape and size of TiO nanoparticles.

In the present work a series of design rules are developed in order to tune the morphology of TiO nanoparticles through hydrothermal process. Through a careful experimental design, the influence of relevant process parameters on the synthesis outcome are studied, reaching to the develop predictive models by using Machine Learning methods. The models, after the validation and training, are able to predict with high accuracy the synthesis outcome in terms of nanoparticle size, polydispersity and aspect ratio.