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Impact of organic phosphates on the structure and composition of short-range ordered iron nanophases
(2024)
Organic phosphates (OP) are important nutrient components for living cells in natural environments, where they readily interact with ubiquitous iron phases such as hydrous ferric oxide, ferrihydrite (FHY). FHY partakes in many key bio(geo)chemical reactions including iron-mediated carbon storage in soils, or iron-storage in living organisms. However, it is still unknown how OP affects the formation, structure and properties of FHY. Here, we document how β-glycerophosphate (GP), a model OP ligand, affects the structure and properties of GP–FHY nanoparticles synthesized by coprecipitation at variable nominal molar P/Fe ratios (0.01 to 0.5). All GP–FHY precipitates were characterized by a maximum solid P/Fe ratio of 0.22, irrespective of the nominal P/Fe ratio. With increasing nominal P/Fe ratio, the specific surface area of the GP–FHY precipitates decreased sharply from 290 to 3 m2 g−1, accompanied by the collapse of their pore structure. The Fe–P local bonding environment gradually transitioned from a bidentate binuclear geometry at low P/Fe ratios to monodentate mononuclear geometry at high P/Fe ratios. This transition was accompanied by a decrease in coordination number of edge-sharing Fe polyhedra, and the loss of the corner-sharing Fe polyhedra. We show that Fe(III) polymerization is impeded by GP, and that the GP–FHY structure is highly dependent on the P/Fe ratio. We discuss the role that natural OP-bearing Fe(III) nanophases have in biogeochemical reactions between Fe–P and C species in aquatic systems.
Nanoforms with at least one dimension below 100 nm have an important part to play in more and more areas of our daily life. Therefore, risk assessment of these materials is becoming increasingly important. In this context, the European Chemical Agency (ECHA) considered eleven physico-chemical properties as relevant, of which the following six are essential for the registration: chemical composition, crystallinity, particle size, particle shape, surface chemistry and specific surface area. Four of these priority properties can be obtained with electron microscopy and surface analytics like XPS and ToF-SIMS. The reliability of this data must be ensured, especially for their use for grouping and read across approaches. On the other hand, the “reproducibility” crisis has revealed major shortcomings in the reliability of published data.
In a case study, we show how the quality of the data can be ensured by using existing standards and protocols of each step in the workflow of sample characterization. As exemplary samples, two Al-coated TiO2 samples as nanopowders were selected from the JRC repository, capped either with a hydrophilic or a hydrophobic organic ultrathin shell. SEM results provided the size and shape of the nanoparticles, a first overview about the composition was obtained with EDS. XPS and ToF-SIMS supplied the surface chemistry, especially information about the shell and the coating of the particles. Standards and protocols of all steps of the analytical workflow including preparation and data reduction are discussed regarding reliable and reproducible data. Additionally, uncertainties for the different steps are specified.
Only such a detailed description of all these factors allows a comprehensive physico-chemical characterization of the nanoparticles with understanding of their potential risk assessment.
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. The results of the analyses of pristine well-defined particles such as 60 nm Au NMs in a simple aqueous suspension showed that laboratories are well capable of determining the sizes of these particles. The analysis of particles in complex matrices or formulations such as consumer products resulted in larger variations in particle sizes within technologies and clear differences in capability between techniques. Sunscreen lotion sample analysis by laboratories using spICP-MS and TEM/SEM identified and confirmed the TiO2 particles as being nanoscale and compliant with the EU definition of an NM for regulatory purposes. In a toothpaste sample orthogonal results by PTA, spICP-MS and TEM/SEM agreed and stated the TiO2 particles as not fitting the EU definition of an NM. In general, from the results of these ILCs we conclude that laboratories are well capable of determining particle sizes of NM, even in fairly complex formulations.
The publicly available document encapsulates the first version of the Catalogue of Services of the future EC4Safenano Centre (CoS 2019).
The CoS 2019 is structured in 12 Service Categories and 27 Service Topics, for each of the 12 categories considered. This architecture configures a 12 x 27 matrix that allows ordering the potential EC4Safenano offer in 324 types of services/groups of services.
Each type of service/group of services is described, in a simple and friendly way, by means of a specific service sheet: the EC4Safenano - Service Data Sheet (EC4-SDS). These EC4-SDSs allow structuring and summarizing the information of each service, providing the customer with a concise view of characteristics of the service and also the contact details with the service provider.
The CoS 2019 deploys a map of services consisting of a set of 100 EC4-SDSs, covering 7 of the 12 Service Categories and 17 of the 27 Service Topics.
The harmonization of services is visualized as a future necessary step in EC4Safenano, in order to strengthen the offer and provide added value to customers with a growing offer of harmonized services in future versions of the CoS.
The information contained in this document is structured in 3 main sections, as follows:
• Catalogue structure. This section describes in short the main characteristics of the CoS 2019.
• Catalogue content. This section represents the core part of the document and encapsulates the set of 100 SDSs displaying the offer proposed by the CoS 2019.
• Online Catalogue. This section describes the resources implemented by EC4Safenano to facilitate the on-line consultation of the CoS 2019 by customers and other interested parties.
The European legislation has responded to the wide use of nanomaterials in our daily life and defined the term “nanoform” in the Annexes to the REACH (Registration, Evaluation, Authorization of Chemicals) Regulation. Now specific information of the nanomaterials is required from the companies when registering the appropriate materials in a dossier.
In the context of REACH eleven physicochemical properties were considered as relevant, of which the following six are essential for registration of nanoforms (priority properties): chemical composition, crystallinity, particle size, particle shape, chemical nature of the surface (“surface chemistry”), and specific surface area (SSA). A key role is the reliable, reproduceable and traceable character of the data of these priority properties.
In this context, we want to discuss which ‘analytical’ information is exactly required to fulfill these conditions. Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) and X-ray Photoelectron Spectroscopy (XPS) were chosen as the most popular surface analytical methods. Both methods allow a detailed understanding of the surface chemistry with an information depth below ten nanometers. As a rather bulk method for the analysis of nanoforms, Electron Probe Microanalysis (EPMA) in the version with energy dispersive X-ray spectroscopy (EDS) is considered for the quick identification of the main chemical elements present in the sample. Furthermore, Scanning Electron Microscopy (SEM) results are discussed which provide results on particle size and shape. Thus, four of the six priority properties can be obtained with these methods.