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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.
A round-robin study has been carried out to estimate the impact of the human element in small-angle scattering data analysis. Four corrected datasets were provided to participants ready for analysis. All datasets were measured on samples containing spherical scatterers, with two datasets in dilute dispersions and two from powders. Most of the 46 participants correctly identified the number of populations in the dilute dispersions, with half of the population mean entries within 1.5% and half of the population width entries within 40%. Due to the added complexity of the structure factor, far fewer people submitted answers on the powder datasets. For those that did, half of the entries for the means and widths were within 44 and 86%, respectively. This round-robin experiment highlights several causes for the discrepancies, for which solutions are proposed.
A versatile software package in the form of a Python extension, named CDEF (computing Debye’s scattering formula for extraordinary form factors), is proposed to calculate approximate scattering profiles of arbitrarily shaped nanoparticles for small-angle X-ray scattering (SAXS). CDEF generates a quasi-randomly distributed point cloud in the desired particle shape and then applies the open-source software DEBYER for efficient evaluation of Debye’s scattering formula to calculate the SAXS pattern (https://github.com/j-from-b/CDEF). If self-correlation of the scattering signal is not omitted, the quasi-random distribution provides faster convergence compared with a true-random distribution of the scatterers, especially at higher momentum transfer. The usage of the software is demonstrated for the evaluation of scattering data of Au nanocubes with rounded edges, which were measured at the four-crystal monochromator beamline of PTB at the synchrotron radiation facility BESSY II in Berlin. The implementation is fast enough to run on a single desktop computer and perform model fits within minutes. The accuracy of the method was analyzed by comparison with analytically known form factors and verified with another implementation, the SPONGE, based on a similar principle with fewer approximations. Additionally, the SPONGE coupled to McSAS3 allows one to retrieve information on the uncertainty of the size distribution using a Monte Carlo uncertainty estimation algorithm.
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 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. The proposed entity, referred to as “the Centre”, will establish a ‘one-stop shop’ for nanosafety-related services and a central contact point for addressing stakeholder questions about nanosafety. Its operation will rely on significant business, legal and market knowledge, as well as other tools developed and acquired through the EU-funded EC4SafeNano project and subsequent ongoing activities. The proposed blueprint adopts a demand-driven service update scheme to allow the necessary vigilance and flexibility to identify opportunities and adjust its activities and services in the rapidly evolving regulatory and nano risk governance landscape.
The proposed Centre will play a major role as a conduit to transfer scientific knowledge between the Research and commercial laboratories or consultants able to provide high quality nanosafety services, and the end-users of such services (e.g., industry, SMEs, consultancy firms, and regulatory authorities). The Centre will harmonise service provision, and bring novel risk assessment and management approaches, e.g. in silico methodologies, closer to practice, notably through SbD/SSbD, and decisively support safe and sustainable innovation of industrial production in the nanotechnology industry according to the European Chemicals Strategy for Sustainability.
Herein, we provide a "systems architecture"-like overview and detailed discussions of the methodological and instrumental components that, together, comprise the "MOUSE" project (Methodology Optimization for UltrafineStructure Exploration). The MOUSE project provides scattering information on a wide variety of samples, with traceable dimensions for both the scattering vector (q) and the absolute scattering cross-section (I). The measurable scattering vector-range of 0.012≤ q (nm-1) ≤ 92, allows information across a hierarchy of structures with dimensions ranging from ca. 0.1 to 400 nm. In addition to details that comprise the MOUSE project, such as the organisation and traceable aspects, several representative examples are provided to demonstrate its flexibility. These include measurements on alumina membranes, the tobacco mosaic virus, and dual-source information that overcomes fluorescence limitations on ZIF-8 and iron-oxide-containing carbon catalyst materials.
Identifying nanomaterials (NMs) according to European Union Legislation is challenging, as there is an enormous variety of materials, with different physico-chemical properties. The NanoDefiner Framework and its Decision Support Flow Scheme (DSFS) allow choosing the optimal method to measure the particle size distribution by matching the material properties and the performance of the particular measurement techniques. The DSFS leads to a reliable and economic decision whether a material is an NM or not based on scientific criteria and respecting regulatory requirements. The DSFS starts beyond regulatory requirements by identifying non-NMs by a proxy Approach based on their volume-specific surface area. In a second step, it identifies NMs. The DSFS is tested on real-world materials and is implemented in an e-tool. The DSFS is compared with a decision flowchart of the European Commission’s (EC) Joint Research Centre (JRC), which rigorously follows the explicit criteria of the EC NM definition with the focus on identifying NMs, and non-NMs are identified by exclusion. The two approaches build on the same scientific basis and measurement methods, but start from opposite ends: the JRC Flowchart starts by identifying NMs, whereas the NanoDefiner Framework first identifies non-NMs.