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NanoDefiner e-Tool: An Implemented Decision Support Framework for Nanomaterial Identification
(2019)
The European Commission’s recommendation on the definition of nanomaterial (2011/696/EU) established an applicable standard for material categorization. However, manufacturers face regulatory challenges during registration of their products. Reliable categorization is difficult and requires considerable expertise in existing measurement techniques (MTs). Additionally, organizational complexity is increased as different authorities’ registration processes require distinct reporting.
The NanoDefine project tackled these obstacles by providing the NanoDefiner e-tool: A decision support expert system for nanomaterial identification in a regulatory context. It providesMT recommendations for categorization of specific materials using a tiered approach (screening/confirmatory), and was constructed with experts from academia and industry to be extensible, interoperable, and adaptable for forthcoming revisions of the nanomaterial definition. An implemented MT-driven material categorization scheme allows detailed description. Its guided workflow is suitable for a variety of user groups. Direct feedback and explanation enable transparent decisions. Expert knowledge is Held in a knowledge base for representation of MT performance criteria and physicochemical particle type
properties. Continuous revision ensured data quality and validity. Recommendations were validated by independent case studies on industry-relevant particulate materials. Besides supporting material identification and registration, the free and open-source e-tool may serve as template for other expert systems within the nanoscience domain.
Metal carbides have shown great promise in a wide range of applications due to their unique catalytic, electrocatalytic and magnetic properties. However, the scalable production of dispersible metal carbide nanoparticles remains a challenge. Here, we report a simple and scalable route to dispersible iron carbide (Fe3C) nanoparticles. This uses MgO nanoparticles as a removable ‘cast’ to synthesize Fe3C nanoparticles from Prussian blue (KFeIII[FeII(CN)6]). Electron tomography demonstrates how nanoparticles of the MgO cast encase the Fe3C nanoparticles to prevent sintering and agglomeration during the high-temperature synthesis. The MgO cast is readily removed with ethylenediaminetetraacetic acid (EDTA) to generate Fe3C nanoparticles that can be used to produce a colloidal ferrofluid or dispersed on a support material.
The importance of plasmonic heating for the plasmondriven photodimerization of 4-nitrothiophenol
(2019)
Metal nanoparticles form potent nanoreactors, driven by the optical generation of energetic electrons and nanoscale heat. The relative influence of these two factors on nanoscale chemistry is strongly debated. This article discusses the temperature dependence of the dimerization of 4-nitrothiophenol (4-NTP) into 4,4′-dimercaptoazobenzene (DMAB) adsorbed on gold nanoflowers by Surface-Enhanced Raman Scattering (SERS). Raman thermometry shows a significant optical heating of the particles. The ratio of the Stokes and the anti-Stokes Raman signal moreover demonstrates that the molecular temperature during the reaction rises beyond the average crystal lattice temperature of the plasmonic particles. The product bands have an even higher temperature than reactant bands, which suggests that the reaction proceeds preferentially at thermal hot spots. In addition, kinetic measurements of the reaction during external heating of the reaction environment yield a considerable rise of the reaction rate with temperature. Despite this significant heating effects, a comparison of SERS spectra recorded after heating the sample by an external heater to spectra recorded after prolonged illumination shows that the reaction is strictly photo-driven. While in both cases the temperature increase is comparable, the dimerization occurs only in the presence of light. Intensity dependent measurements at fixed temperatures confirm this finding.
We present a versatile and simple method using electrochemistry for the exclusive functionalization of the edge of a graphene monolayer with metal nanoparticles or polymeric amino groups. The attachment of metal nanoparticles allows us to exploit surface-enhanced Raman scattering to characterize the chemistry of both the pristine and the functionalized graphene edge. For the pristine patterned graphene edge, we observe the typical edge-related modes, while for the functionalized graphene edge we identify the chemical structure of the functional layer by vibrational fingerprinting. The ability to obtain single selectively functionalized graphene edges routinely on an insulating substrate opens an avenue for exploring the effect of edge chemistry on graphene properties systematically.
Worldwide there is a variety of regulatory provisions addressing nanomaterials. The identification as nanomaterial in a regulatory context often has the consequence that specific legal rules apply. In identifying nanomaterials, and to find out whether nanomaterial-specific provisions apply, the external size of particles is globally used as a criterion. For legal certainty, its assessment for regulatory purposes should be based on measurements and methods that are robust, fit for the purpose and ready to be accepted by different stakeholders and authorities. This should help to assure the safety of nanomaterials and at the same time facilitate their international trading. Therefore, we propose a categorisation scheme which is driven by the capabilities of common characterisation techniques for particle size measurement. Categorising materials according to this scheme takes into account the particle properties that are most important for a determination of their size. The categorisation is exemplified for the specific particle number based size metric of the European Commission's recommendation on the definition of nanomaterial, but it is applicable to other metrics as well. Matching the performance profiles of the measurement techniques with the material property profiles (i) allows selecting the most appropriate size determination technique for every type of material considered, (ii) enables proper identification of nanomaterials, and (iii) has the potential to be accepted by regulators, industry and consumers alike. Having such a scheme in place would facilitate the regulatory assessment of nanomaterials in regional legislation as well as in international relations between different regulatory regions assuring the safe trade of nanomaterials.
Quantification of nanoparticle (NP) uptake in cells or tissues is very important for safety assessment. Often, electron microscopy based approaches are used for this purpose, which allow imaging at very high resolution. However, precise quantification of NP numbers in cells and tissues remains challenging. The aim of this study was to present a novel approach, that combines precise quantification of NPs in individual cells together with high resolution imaging of their intracellular distribution based on focused ion beam/ scanning electron microscopy (FIB/SEM) slice and view approaches.
The excitation of localized surface plasmons in noble metal nanoparticles (NPs) results in different nanoscale effects such as electric field enhancement, the generation of hot electrons and a temperature increase close to the NP surface. These effects are typically exploited in diverse fields such as surface-enhanced Raman scattering (SERS), NP catalysis and photothermal therapy (PTT). Halogenated nucleobases are applied as radiosensitizers in conventional radiation cancer therapy due to their high reactivity towards secondary electrons. Here, we use SERS to study the transformation of 8-bromoadenine (8BrA) into adenine on the surface of Au and AgNPs upon irradiation with a low-power continuous wave laser at 532, 633 and 785 nm, respectively. The dissociation of 8BrA is ascribed to a hot-electron transfer reaction and the underlying kinetics are carefully explored. The reaction proceeds within seconds or even milliseconds. Similar dissociation reactions might also occur with other electrophilic molecules, which must be considered in the interpretation of respective SERS spectra. Furthermore, we suggest that hot-electron transfer induced dissociation of radiosensitizers such as 8BrA can be applied in the future in PTT to enhance the damage of tumor tissue upon irradiation.
Safety assessment of nanoparticles (NPs) requires techniques that are suitable to quantify tissue and cellular uptake of NPs. The most commonly applied techniques for this purpose are based on inductively coupled plasma mass spectrometry (ICP-MS). Here we apply and compare three different ICP-MS methods to investigate the cellular uptake of TiO2 (diameter 7 or 20 nm, respectively) and Ag (diameter 50 or 75 nm, respectively) NPs into differentiated mouse neuroblastoma cells (Neuro-2a cells). Cells were incubated with different amounts of the NPs. Thereafter they were either directly analyzed by laser ablation ICP-MS (LA-ICP-MS) or were lysed and lysates were analyzed by ICP-MS and by single particle ICP-MS (SP-ICP-MS).
Multifunctional composite nanoprobes consisting of iron oxide nanoparticles linked to silver and gold nanoparticles, Ag–Magnetite and Au–Magnetite, respectively, were introduced by endocytic uptake into cultured fibroblast cells. The cells containing the non-toxic nanoprobes were shown to be displaceable in an external magnetic field and can be manipulated in microfluidic channels. The distribution of the composite nanostructures that are contained in the endosomal system is discussed on the basis of surfaceenhanced Raman scattering (SERS) mapping, quantitative laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) micromapping, and cryo soft X-ray tomography (cryo soft-XRT). Cryo soft-XRT of intact, vitrified cells reveals that the composite nanoprobes form intra-endosomal aggregates. The nanoprobes provide SERS signals from the biomolecular composition of their surface in the endosomal environment. The SERS data indicate the high stability of the nanoprobes and of their plasmonic properties in the harsh environment of endosomes and lysosomes. The spectra point at the molecular composition at the surface of the Ag–Magnetite and Au–Magnetite nanostructures that is very similar to that of other Composite structures, but different from the composition of pure silver and gold SERS nanoprobes used for intracellular investigations. As shown by the LA-ICP-MS data, the uptake efficiency of the magnetite composites is approximately two to three times higher than that of the pure gold and silver nanoparticles.
Titanium dioxide (TiO₂) nanoparticles (NPs) are one of the main sources of the nanoparticulate matter to which humans are directly exposed and several studies have demonstrated their potential toxic effects. The in vivo detailed spatial distribution of TiO₂ NPs is investigated herein for the first time, using a 2D chemical imaging analysis based on confocal Raman spectroscopy. The invertebrate nematode C. elegans was employed as a prototypical model of living organisms. Rod, bipyramidal and quasispherical engineered TiO₂ NPs with different primary particle sizes and agglomeration states were prepared, characterized and then administered to nematodes. Exploiting the typical fingerprint of TiO₂ in the Raman spectrum, we monitored the biodistribution of NPs inside the worm using a non-invasive, label-free method. The high spatial resolution chemical imaging and the specificity of the Raman technique in the localization of TiO₂ NPs helped in the design of behavioral C. elegans studies aimed at elucidating the relationship among the size, shape, and agglomeration state of NPs and their ability to induce specific toxic effects. Rod-shaped NPs were the most toxic, greatly impairing pharyngeal function, reproduction and larval growth; this indicates that the rod shape, more than the bipyramidal and spherical shapes, enables NPs to interact with biological systems. These findings indicate that this Raman-nematode combined approach represents a step forward in the field of detection of NPs in living organisms, and being rapid and inexpensive enough, it can be applied as the first screening for the ability of NPs to biodistribute and exert toxicological properties in vivo.
In this study, a new reliable, economic, and environmentally-friendly one-step synthesis is established to obtain carbon nanodots (CNDs) with well-defined and reproducible photoluminescence (PL) properties via the microwave-assisted hydrothermal treatment of starch and Tris-acetate-EDTA (TAE) buffer as carbon sources. Three kinds of CNDs are prepared using different sets of above mentioned starting materials. The as-synthesized CNDs: C-CND (starch only), N-CND 1 (starch in TAE) and N-CND 2 (TAE only) exhibit highly homogenous PL and are ready to use without need for further purification.
The CNDs are stable over a long period of time (>1 year) either in solution or as freeze-dried powder. Depending on starting material, CNDs with PL quantum yield (PLQY) ranging from less than 1% up to 28% are obtained. The influence of the precursor concentration, reaction time and type of additives on the optical properties (UV-Vis absorption, PL emission spectrum and PLQY) is carefully investigated, providing insight into the chemical processes that occur during CND formation. Remarkably, upon freeze-drying the initially brown CND-solution turns into a non-fluorescent white/slightly Brown powder which recovers PL in aqueous solution and can potentially be applied as fluorescent marker in bio-imaging, as a reduction agent or as a photocatalyst.
Advances in scanning electron microscopy (SEM) enable the high-resolution imaging of single nanoparticles (NPs) with sizes well below 10 nm. The SEM analysis in transmission mode (T-SEM) of NPs on thin film supports has many benefits when compared to the analysis of NPs on bulk substrates. The enhanced material (mass – thickness) contrast of the T-SEM imaging mode is well suited for in-depth and, particularly valuable, to very accurate, traceable, lateral dimensional measurements of NPs. Compared to samples prepared on bulk substrates, T-SEM with energy dispersive X-ray spectroscopy (EDS) achieves a drastically improved spatial resolution of the emitted X-rays. The poor signal-to-noise ratio of the X-ray spectra emitted by a single nanoparticle (NP) can be improved by the use of high-sensitivity (high collection solid angle) silicon drift (SDD), energy-dispersive X-ray spectrometers (EDS). The EDS spectral imaging of a single NP with a spatial resolution below 10 nm has become possible. This is demonstrated by means of various examples of nanostructures. Advanced data processing of T-SEM/EDS results sets the stage for the automated classification of NPs by feature analysis. This method combines the detection of morphological structures of interest by image processing of T-SEM micrographs with the chemical classification by EDS.
SASfit: a tool for small-angle scattering data analysis using a library of analytical expressions
(2015)
SASfit is one of the mature programs for small-angle scattering data analysis and has been available for many years. This article describes the basic data processing and analysis workflow along with recent developments in the SASfit program package (version 0.94.6). They include (i) advanced algorithms for reduction of oversampled data sets, (ii) improved confidence assessment in the optimized model parameters and (iii) a flexible plug-in system for custom user-provided models. A scattering function of a mass fractal model of branched polymers in solution is provided as an example for implementing a plug-in. The new SASfit release is available for major platforms such as Windows, Linux and MacOS. To facilitate usage, it includes comprehensive indexed documentation as well as a web-based wiki for peer collaboration and online videos demonstrating basic usage. The use of SASfit is illustrated by interpretation of the small-angle X-ray scattering curves of monomodal gold nanoparticles (NIST reference material 8011) and bimodal silica nanoparticles (EU reference material ERM-FD-102).
In this work, sample losses of silver nanoparticles (Ag NPs) in asymmetrical flow field-flow fractionation (AF4) have been systematically investigated with the main focus on instrumental conditions like focusing and cross-flow parameters as well as sample concentration and buffer composition. Special attention was drawn to the AF4 membrane. For monitoring possible silver depositions on the membrane, imaging laser ablation coupled to inductively coupled plasma mass spectrometry (LA-ICP-MS) was used. Our results show that the sample residue on the membrane was below 0.6% of the total injected amount and therefore could be almost completely avoided at low sample concentrations and optimized conditions. By investigation of the AF4 flows using inductively coupled plasma mass spectrometry (ICP-MS), we found the recovery rate in the detector flow under optimized conditions to be nearly 90%, while the cross-flow, slot-outlet flow and purge flow showed negligible amounts of under 0.5%. The analysis of an aqueous ionic Ag standard solution resulted in recovery rates of over 6% and the ionic Ag content in the sample was found to be nearly 8%. Therefore, we were able to indicate the ionic Ag content as the most important source of sample loss in this study.
A user-friendly open-source Monte Carlo regression package (McSAS) is presented, which structures the analysis of small-angle scattering (SAS) using uncorrelated shape-similar particles (or scattering contributions). The underdetermined problem is solvable, provided that sufficient external information is available. Based on this, the user picks a scatterer contribution model (or 'shape') from a comprehensive library and defines variation intervals of its model parameters. A multitude of scattering contribution models are included, including prolate and oblate nanoparticles, core-shell objects, several polymer models, and a model for densely packed spheres. Most importantly, the form-free Monte Carlo nature of McSAS means it is not necessary to provide further restrictions on the mathematical form of the parameter distribution; without prior knowledge, McSAS is able to extract complex multimodal or odd-shaped parameter distributions from SAS data. When provided with data on an absolute scale with reasonable uncertainty estimates, the software outputs model parameter distributions in absolute volume fraction, and provides the modes of the distribution (e.g. mean, variance etc.). In addition to facilitating the evaluation of (series of) SAS curves, McSAS also helps in assessing the significance of the results through the addition of uncertainty estimates to the result. The McSAS software can be integrated as part of an automated reduction and analysis procedure in laboratory instruments or at synchrotron beamlines.