No Arabic abstract
The development of science-based categorization strategies for regulatory purposes is not a simple task. It requires understanding the needs and capacity of a wide variety of stakeholders and should consider the potential risks and unintended consequences. For an evolving science area, such as nanotechnologies, the overall uncertainties of designing an effective categorization scheme can be significant. Future nanomaterials may be far more complex and may integrate far different functionalities than modern nanomaterials. There is much that has been learned from our experience with legacy nanomaterials and particulate substances in general. Most of the modern nanomaterials are not new nor dramatically different from parent or existing chemical substances, however there are some nuances. Applying these learnings to define reasonable science-based categories that consider how different emerging nanomaterials might be from existing known substances (while integrating sound concepts as they develop) would be a pragmatic and flexible path forward. However, there are many barriers down this road including a need for improvement and updates to chemical classification systems to improve hazard and risk communications, while promoting transparency and consistency.
Nanotechnology is a so-called key-emerging technology that opens a new world of technological innovation. The novelty of engineered nanomaterials (ENMs) raises concern over their possible adverse effect to man and the environment. Thereupon, risk assessors are challenged with ever decreasing times-to-market of nano-enabled products. Combined with the perception that it is impossible to extensively test all new nanoforms, there is growing awareness that alternative assessment approaches need to be developed and validated to enable efficient and transparent risk assessment of ENMs. Associated with this awareness, there is the need to use existing data on similar ENMs as efficiently as possible, which highlights the need of developing alternative approaches to fate and hazard assessment like predictive modelling, grouping of ENMs, and read across of data towards similar ENMs. In this contribution, an overview is given of the current state of the art with regard to categorization of ENMs and the perspectives for implementation in future risk assessment. It is concluded that the qualitative approaches to grouping and categorization that have already been developed are to be substantiated, and additional quantification of the current sets of rules-of-thumb based approaches is a key priority for the near future. Most of all, the key question of what actually drives the fate and effects of (complex) particles is yet to be answered in enough detail, with a key role foreseen for the surface reactivity of particles as modulated by the chemical composition of the inner and outer core of particles. When it comes to environmental categorization of ENMs we currently are in a descriptive rather than in a predictive mode.
A new class of materials, Topological Crystalline Insulators (TCIs) have been shown to possess exotic surface state properties that are protected by mirror symmetry. These surface features can be enhanced if the surface-area-to-volume ratio of the material increases, or the signal arising from the bulk of the material can be suppressed. We report the experimental procedures to obtain high quality crystal boules of the TCI, SnTe, from which nanowires and microcrystals can be produced by the vapour-liquid-solid (VLS) technique. Detailed characterisation measurements of the bulk crystals as well as of the nanowires and microcrystals produced are presented. The nanomaterials produced were found to be stoichiometrically similar to the source material used. Electron back-scatter diffraction (EBSD) shows that the majority of the nanocrystals grow in the vicinal {001} direction to the growth normal. The growth conditions to produce the different nanostructures of SnTe have been optimised.
Molecular dynamics simulations play an increasingly important role in the rational design of (nano)-materials and in the study of biomacromolecules. However, generating input files and realistic starting coordinates for these simulations is a major bottleneck, especially for high throughput protocols and for complex multi-component systems. To eliminate this bottleneck, we present the polyply software suite that leverages 1) a multi-scale graph matching algorithm designed to generate parameters quickly and for arbitrarily complex polymeric topologies, and 2) a generic multi-scale random walk protocol capable of setting up complex systems efficiently and independent of the target force-field or model resolution. We benchmark quality and performance of the approach by creating melt simulations of six different polymers using two force-fields with different resolution. We further demonstrate the power of our approach by setting up a multi lamellar microphase-separated block copolymer system for next generation batteries, and by generating a liquid-liquid phase separated polyethylene oxide-dextran system inside a lipid vesicle, featuring both branching and molecular weight distribution of the dextran component.
Interfacial nucleation is the dominant process of dislocation generation during the plastic deformation of nano-crystalline materials. Solute additions intended to stabilize nano-crystalline metals against grain growth, may segregate to the grain boundaries and triple junctions where they can affect the process of the dislocation emission. In this Letter we demonstrate that the effect of solute addition in a nano-crystalline material containing competing solute segregation sites and dislocation sources can be very complex due to different rates of segregation at different interfaces. Moreover, at large concentrations, when the solutes form clusters near the grain boundaries or triple junctions, the interfaces between these clusters and the matrix can introduce new dislocation emission sources, which can be activated under lower applied stress. Thus, the strength maximum can occur at a certain solute concentration: adding solutes beyond this optimal solute concentration can reduce the strength of the material.
Metal nano-aerogels combine a large surface area, a high structural stability, and a high catalytic activity towards a variety of chemical reactions. The performance of such nanostructures is underpinned by the atomic-level distribution of their constituents. Yet monitoring their sub-nanoscale structure and composition to guide property optimization remains extremely challenging. Here, we synthesized Pd nano-aerogels from a K2PdCl4 precursor and two different NaBH4 reductant concentrations in distilled water. Atom probe tomography reveals that the aerogel is poly-crystalline and that impurities (Na, K) are integrated from the solution into grain boundaries. Ab initio calculations indicate that these impurities preferentially bound to the Pd-metal surface and are ultimately found in grain boundaries forming as the particles coalesce during synthesis, with Na atoms thermodynamically equilibrating with the surrounding solution and K atoms remaining between growing grains. If controlled, impurity integration, i.e. grain boundary decoration, may offer opportunities for designing new nano-aerogels.