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The mechanism of action of zirconium permanent modifiers on graphite surfaces was investigated in order to understand its influence on the analytical signal in atomic and molecular absorption spectrometry (AAS/MAS). For this, the molecule formation of CaF was studied, which is used for the indirect analytical determination of fluorine in high-resolution continuum source graphite furnace molecular absorption spectrometry (HR-CS-GFMAS). The kinetics of this reaction was established by monitoring its molecular spectrum at different atomisation temperatures. An Arrhenius plot showed a pseudo-first order reaction with respect to fluorine (n = 1). An intermediate state was isolated, and its structure was elucidated by spectroscopic methods: scanning electron microscopy with energy dispersive X-ray spectroscopy (SEMEDX), X-ray photoelectron spectroscopy (XPS), X-ray absorption spectroscopy (XANES and EXAFS), and Raman microspectroscopy. We propose here a mechanism, where ZrO2 acts as a heterogeneous catalyst: after a pyrolytic step, an intermediate state of ZrO(OCaF) is activated, and at higher temperatures, CaF(g) is released from the zirconium-coated graphite surface. No evidence of the formation of zirconium carbide was found. Consequently, as the CaF formation is catalysed by a heterogeneous catalyst, surface modifications with ZrO2 nanoparticles and ZrO xerogels were investigated in order to increase the surface area. Their influence was evaluated in the molecule formation of CaF, CaCl, CaBr, and CaI. Graphite furnace modification with zirconium oxide nanoparticles proves to be the best choice for fluorine analysis with a signal enhancement of more than eleven times with respect a non-coated graphite furnace. However, the influence of zirconium modifications in the analytical signals of Cl, and I is lower than the F signals or even negative in case of the Br. Understanding zirconium modifiers as heterogeneous catalysts offers a new perspective to AAS and MAS, and reveals the potential of surface analytical methods for development of improved permanent modifiers and graphite furnace coatings.
A variety of methods used to prepare nano-objects for surface analysis are described along with information about when they might be best applied. Intrinsic properties of NPs which complicate their characterization and need to be considered when planning for surface or other analyses of NPs are identified, including challenges associated with reproducible synthesis and functionalization of the particles as well as their dynamic nature. The relevant information about the sample preparation processes, along with analysis details and data that need to be added to the collection of material provenance information is identified. Examples of protocols that have been successfully used for preparation of nano-objects for surface analysis are included in an annex.
The main objective was to assess homogeneity of two bimodal gold materials, namely nPsize1 and nPSize2, containing approximately 1:1 and 10:1 particle number-based ratio of ~30nm and ~60nm particles. Particle number-based concentration within the two size fractions was determined with spICP-MS using the particle frequency method of calibration.
One aim of the EMPIR nPSize project 17NRM04 was to develop and validate three classes of candidate reference (test) materials (RTMs), with i) well-defined non-spherical shape, ii) relatively high polydispersity index, and iii) accurate particle concentrations.
To fulfil the requirements of the project, 11 different types of materials were prepared. Following the initial assessment of the materials suitability, nPSize5_PT_UNITO, nPSize6_AC_UNITO and nPSize7_GN_CEA materials were found unsuitable for the project, due to various reasons. PT material was deemed unsuitable due to its predominantly agglomerated nature. AC material contained relatively high amount of impurities (other particle forms). GN material was found too heterogeneous in both the length and width for the purpose of the project. The remaining 8 candidate RTMs were assessed for their homogeneity and stability and used for successful delivery of the associated activities within the nPSize project.
A series of different nanoparticle suspensions (Gold, Latex, and SiO2 in varying concentrations) were microprinted onto TEM grids in a 4 x 4 array in the concentration range 7x10^8 to 1x10^11 NP/mL and imaged with SEM and TSEM. Concentrations and printing conditions (temperature, relative humidity) were varied in order to minimize the coffee ring effect.
As part of the development of a library of accurate and efficient methods for measurement of nanoparticle properties, we develop and optimize a method for the efficient analysis of nanoparticle size distribution from suspensions via microprinting and digital analysis of electron microscopy (SEM and TEM) images, with the ultimate aim of automated quantitative concentration analysis (calculated from drop volume). A series of different nanoparticle suspensions (gold, latex, and SiO2 in varying sizes and concentrations) were printed onto TEM grids in a 4 x 4 array in the concentration range 7x10^8 to 1x10^11 nanoparticles/mL and imaged with SEM. Concentrations and printing conditions (temperature, relative humidity) were varied in order to minimize the coffee-ring effect.
Coating, stabilization layers, functionalization of particles or simple contamination are common variants of a core-shell system. For smaller nanoparticles this is of major importance. A particle with 16 nm diameter and a usual surface layer of 2 nm will have the same volume for the core as for the shell. In this case the material of the particle doesn’t have a clear definition. It is a common case that a particle consists of four different layers: Core, shell, stabilization layer and contamination. The properties of the particles differ according to this structure. For example silver particles might have a different dissolution rate for pure particles and for particles which are grown on top of a core.
Different solubility or defined other properties of materials is a common reason for producing core-shell systems. Gold cores are surrounded by silica to stabilize them or to get a defined distance between the cores. Silica might be surrounded by gold and the silica dissolved afterwards. This delivers hollow shells. Another important example for core-shell systems are quantum dots. A small core is surrounded by a different material for increasing the photoluminescence. Furthermore there a stabilization layer is needed. The smallest part of the final particles is the initial core. The photoluminescence is based on this core, but the shells contain much more material. Categorization should address this.
Core-shell systems are not covered by most of the existing decision trees for grouping. They are either regarded as special case or a singular layer. This disqualifies core-shell systems for grouping within the common models. There might be a very easy way to avoid this problem and even to combine some of the different decision trees. Starting the decision tree with the solubility of the outer shell and subsequently addressing the inner layers will be a pragmatic approach to solve the problem. If there is no shell, the categorization can start with a tiered approach or with the proposed “stawman” chemical categorization. If a shell is covering the surface there is a need to check if the shell is stable. If it is stable, the particle can be categorized based on this shell. If it is soluble, the ions need to be addressed as in the classic case. Furthermore the shell might increase the uptake by the cells. If the ions and the uptake are not critical the categorization can continue with the next layer.
With this not perfect but pragmatic approach, the surface layers can be addressed with very limited additional efforts. Most criteria are based on classically tabulated data. Including a rating system like the precautionary matrix approach might even address the fact that some parameters are not always Yes/No, e.g. solubility, ion toxicity and uptake.
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).
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.
Thermoplastic modified thermosets are of great interest especially due to their improved fracture toughness. Comparable enhancements have been achieved by adding different nanofillers including inorganic particles such as nanosized boehmite. Here, we present a nanomechanical study of two composite systems, the first comprising a polycarbonate (PC) layer in contact with epoxy resin (EP) and the second consisting of a PC layer containing boehmite nanoparticles (BNP) which is also in contact with an EP layer. The interaction between PC and EP monomer is tested by in situ Fourier transformed infrared (FT-IR) analysis, from which a reaction induced phase separation of the PC phase is inferred. Both systems are explored by atomic force microscopy (AFM) force spectroscopy. AFM force-distance curves (FDC) show no alteration of the mechanical properties of EP at the interface to PC. However, when a PC phase loaded with BNP is put in contact with an epoxy system during curing, a considerable mechanical improvement exceeding the rule of mixture was detected.
The trend of BNP to agglomerate preferentially around EP dominated regions and the stiffening effect of BNP on EP shown by spatial resolved measurements of Young's modulus, suggest the effective presence of BNP within the EP phase.