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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.
Exploring the influence of counterpart materials on tribological behaviors of epoxy composites
(2016)
The dependence of the friction and wear of epoxy (EP) composites materials on counterpart materials, such as standard bearing steel, medium carbon steel and chrome-plating (Cr), was investigated. The conventional composite filled with short carbon fiber (SCF) and graphite shows the highest tribological performance when rubbing against Cr, whereas, the hybrid nanocomposite (EP filled with SCF, graphite and silica nanoparticles) exhibits the lowest friction and wear when sliding against the standard bearing steel. The role of nanoparticles in the tribological performance is distinctly different when sliding against with various counterpart materials. It is demonstrated that counterpart materials exert an important influence on material transfer, tribo-oxidation and mechanical mixing of wear products, resulting in the different formation mechanisms of transfer film.
Simple, fast, and versatile methods for the quantification of thiol groups are of considerable interest not only for protein analysis but also for the characterization of the surface chemistry of nanomaterials stabilized with thiol ligands or bearing thiol groups for the subsequent (bio-) functionalization via maleimide−thiol chemistry. Here, we compare two simple colorimetric assays, the widely used Ellman’s assay performed at alkaline pH and the aldrithiol assay executed at acidic and neutral pH, with respect to their potential for the quantification of thiol groups and thiol ligands on different types of nanoparticles like polystyrene nanoparticles, semiconductor nanocrystals (SC NC), and noble metal particles, and we derive criteria for their use. In order to assess the underlying reaction mechanisms and to obtain stoichiometry factors mandatory for reliable thiol quantification, both methods were studied photometrically and with electrospray ionization time-of-flight mass spectrometry (ESI-TOF-MS), thereby demonstrating the influence of different thiols on the reaction mechanism. Our results underline the suitability of both methods for the quantification of directly accessible thiol groups or ligands on the surface of 2D- and 3D-supports, here exemplarily polystyrene nanoparticles. Moreover, we could derive strategies for the use of these simple assays for the determination of masked (i.e., not directly accessible) thiol groups like disulfides such as lipoic acid and thiol stabilizing ligands coordinatively bound to Cd and/or Hg surface atoms of II/VI and ternary SC NC and to gold and silver nanoparticles.
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.
A combined methodical approach is tested with respect to the characterization of the inner structure of porous TiO2 layers as typically used in modern dye sensitized solar cells (DSSC). Their performance is directly linked to the surface area of the pore network. The micrometer thick layer employed was manufactured by screen-printing of a starting TiO2 powder constituted of shape-controlled, bipyramidal anatase nanoparticles on FTO/glass substrates. The analytical methods exploited in our study are Focused Ion Beam (FIB) slicing followed by 3D reconstruction as well as the new approach transmission Kikuchi diffraction (TKD) technology in the scanning electron microscope (SEM). Size and shape distribution of the TiO2 NPs within the layer can be extracted. SEM in transmission mode and atomic force microscopy (AFM) have been used to verify the dimensional data obtained by the new combined methodical approach. Its analytical benefits but also the challenges and limitations are highlighted.
A combined methodical approach is tested for the first time with respect to the characterization of the inner structure of porous TiO2 layers infiltrated with ruthenium molecular sensitizer as typically used in modern dye sensitized solar cells (DSSC). Their performance is directly linked to the surface area ‘offered’ by the pore Network to the dye. The micrometer thick layer employed was manufactured by screen-printing of a starting TiO2 powder constituted of shape-controlled, bipyramidal anatase nanoparticles (NPs) on FTO/glass substrates. The
analytical methods exploited in our study are Focused Ion Beam (FIB) slicing followed by 3D reconstruction as well as the new approach transmission Kikuchi diffraction (TKD) technology in the scanning electron microscope (SEM). While the first method results in the visualization of the 3D pore network within the TiO2 layer, the second one can be successfully applied to analyze the crystal orientation of grains (i.e. NPs in our case) in nanometer resolution. Moreover, size and shape distribution of the TiO2 NPs within the layer can be extracted.
SEM in transmission mode and atomic force microscopy (AFM) have been used to verify the dimensional data obtained by the new combined methodical approach. Its analytical benefits but also the challenges and limitations
are highlighted.
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.
What to measure? is a key question in nanoscience, and it is not straightforward to address as different physicochemical properties define a nanoparticle sample. Most prominent among these properties are size, shape, surface charge, and porosity. Today researchers have an unprecedented variety of measurement techniques at their disposal to assign precise numerical values to those parameters. However, methods based on different physical principles probe different aspects, not only of the particles themselves, but also of their preparation history and their environment at the time of measurement. Understanding these connections can be of great value for interpreting characterization results and ultimately controlling the nanoparticle structure–function relationship. Here, the current techniques that enable the precise measurement of these fundamental nanoparticle properties are presented and their practical advantages and disadvantages are discussed. Some recommendations of how the physicochemical parameters of nanoparticles should be investigated and how to fully characterize these properties in different environments according to the intended nanoparticle use are proposed. The intention is to improve comparability of nanoparticle properties and performance to ensure the successful transfer of scientific knowledge to industrial real‐world applications.
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.
We report on ultrasmall zinc oxide single-crystalline nanoparticles of narrow size distribution and long-term colloidal stability. These oleate-stabilized nanoparticles were synthesized using microwave-assisted synthesis for 5 min, corresponding to a 99% decrease in synthesis time, when compared to the conventional synthesis method. It was observed that the average particle radius increases from 2.6 ± 0.1 to 3.8 ± 0.1 nm upon increasing synthesis temperature from 125 to 200 °C. This change also corresponded to observed changes in the optical band gap and the fluorescence energy of the particles, from 3.44 ± 0.01 to 3.36 ± 0.01 eV and from 2.20 ± 0.01 to 2.04 ± 0.01 eV, respectively. Small-angle X-ray scattering, dynamic light scattering, and UV–vis and fluorescence spectroscopy were employed for particle characterization. Debye–Scherrer analysis of the X-ray diffraction (XRD) pattern reveals a linear increase of the crystallite size with synthesis temperature. The consideration of the convolution of a Lorentz function with a Gaussian function for data correction of the instrumental peak broadening has a considerable influence on the values for the crystallite size. Williamson–Hall XRD analyses in the form of the uniform deformation model, uniform stress deformation model, and uniform deformation energy density model revealed a substantial increase of strain, stress, and deformation energy density of the crystallites with decreasing size. Exponential and power law models were utilized for quantification of strain, stress, and deformation energy density.
Most real core-shell nanoparticle (CSNP) samples deviate from an ideal core-shell structure potentially having significant impact on the particle properties. An ideal structure displays a spherical core fully encapsulated by a shell of homogeneous thickness, and all particles in the sample exhibit the same shell thickness. Therefore,
analytical techniques are required that can identify and characterize such deviations.
This study demonstrates that by analysis of the inelastic background in X-ray photoelectron spectroscopy (XPS) survey spectra, the following types of deviations can be identified and quantified: the nonuniformity of the shell thickness within a nanoparticle sample and the incomplete encapsulation of the cores by the shell material. Furthermore, CSNP shell thicknesses and relative coverages can be obtained. These results allow for a quick and straightforward comparison between several batches of a specific CSNP, different coating approaches, and so forth. The presented XPS methodology requires a submonolayer distribution of CSNPs on a substrate.
Poly(tetrafluoroethylene)-poly(methyl methacrylate) and poly(tetrafluoroethylene)-polystyrene polymer CSNPs serve as model systems to demonstrate the applicability of the approach.
Challenges and opportunities in the bottom-up mechanochemical synthesis of noble metal nanoparticles
(2020)
Mechanochemistry is a promising alternative to solution-based protocols across the chemical sciences, enabling different types of chemistries in solvent-free and environmentally benign conditions. The use of mechanical energy to promote physical and chemical transformations has reached a high level of refinement, allowing for the design of sophisticated molecules and nanostructured materials. Among them, the synthesis of noble metal nanoparticles deserves special attention due to their catalytic applications. In this review, we discuss the recent progress on the development of mechanochemical strategies for the controlled synthesis of noble metal nanostructures. We start by covering the fundamentals of different preparation routes, namely top-down and bottom-up approaches. Next, we focus on the key examples of the mechanochemical synthesis of non-supported and supported metal nanoparticles as well as hybrid nanomaterials containing noble metals. In these examples, in addition to the principles and synthesis mechanisms, their performances in catalysis are discussed. Finally, a perspective of the field is given, where we discuss the opportunities for future work and the challenges of mechanochemical synthesis to produce well-defined noble metal nanoparticles.
The characteristics of TiO2 coatings can greatly influence their final performance in large‐scale applications. In the present study, self‐assembly of TiO2 nanoparticles (NPs) in multiple layers was selected as a deposition procedure on various substrates. For this, the main prerequisite constitutes the surface modification of both NPs and substrate with, for example, silane coupling agents. A set of functionalized TiO2 NPs has been produced by reaction with either (3‐aminopropyl)triethoxysilane (APTES) or (3‐aminopropyl)phosphonic acid (APPA) to functionalize the NP surface with free amino‐groups. Then, the complementary functionalized NP set can be obtained from an aliquot of the first one, through the conversion of free surface amino groups to aldehydes by reaction with glutaraldehyde (GA). Several types of TiO2 NPs differing in size, shape, and specific surface area have been functionalized. Fourier‐transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), SEM/ energy‐dispersive X‐ray spectroscopy (EDS), XPS, Auger electron spectroscopy (AES), and Time‐of‐Flight (ToF)‐SIMS analyses have been carried out to evaluate the degree of functionalization, all the analytical methods employed demonstrating successful functionalization of TiO2 NP surface with APTES or APPA and GA.
Polymer nanoparticles (NPs) can be highly attractive in numerous applications including biomedicine where the use of inorganic matter may be detrimental for living tissues. In conventional wet chemistry, polymerization and functionalization of NPs with specific chemical groups involves complex and often numerous reactions. Here, we report on a solvent-free, single-step, low temperature plasma-based synthesis of carboxylated NPs produced by polymerization of acrylic acid under the conditions of a glow discharge. In a monomer-deficient regime, strong fragmentation of the monomer molecules by electron impact results in the formation of 15 nm-sized NPs with <1% retention of the carboxyl groups. In an energy-deficient regime, larger 90 nm-sized NPs are formed with better retention of the carboxyls that reaches 16 %. All types of the NPs exhibit the glass transition above the room temperature which makes them highly stable under aqueous environment with no dissolution or swelling. They are also found to degrade thermally when heated above 150 °C with a decrease of the mean NP size, yet with the retention of the chemical composition. Thus, plasma polymerization proves to be a versatile approach for the production of polymer NPs with tuneable size distribution, chemical composition and physical properties.
In the present work a series of design rules are developed in order to tune the morphology of TiO2 nanoparticles through hydrothermal process. Through a careful experimental design, the influence of relevant process parameters on the synthesis outcome are studied, reaching to the develop predictive models by using Machine Learning methods. The models, after the validation and training, are able to predict with high accuracy the synthesis outcome in terms of nanoparticle size, polydispersity and aspect ratio. Furthermore, they are implemented by reverse engineering approach to do the inverse process, i.e. obtain the optimal synthesis parameters given a specific product characteristic. For the first time, it is presented a synthesis method that allows continuous and precise control of NPs morphology with the possibility to tune the aspect ratio over a large range from 1.4 (perfect truncated bipyramids) to 6 (elongated nanoparticles) and the length from 20 to 140 nm.
The present study addresses the capability of measurement of relative particle number concentration by scanning electron microscopy for model bimodal silica and gold samples prepared in the frame of the European research project “nPSize - Improved traceability chain of nanoparticle size measurements” as candidate reference nanoparticles.
In this paper one refined approach is applied to determine the exact orientation of bipyramidal TiO2 nanoparticles prepared with good dispersion as almost isolated particles on a carbon TEM grid. The advantages of the recently developed high-throughput Transmission Kikuchi Diffraction (TKD) are used to identify quickly and reliably the geometrical orientation of the crystalline TiO2 nanoparticle bipyramids (anatase) on a statistically relevant number of particles.
In this contribution different ways are explored with the aim to generate suitable training data for ‘non-ideal’ samples using various approaches, e.g., computer-generated images or unsupervised learning algorithms such as generative adversarial networks (GANs). We used these data to train simple CNNs to produce segmentation masks of SEM images and tested the trained networks on real SEM images of complex nanoparticle samples. The novel use of CNN for the automated analysis of the size of nanoparticles of complex shape and with a high degree of agglomeration has proved to be a promising tool for the evaluation of particle size distribution on a large number of constituent particles. Further development and validation of the preliminary model, respectively larger training and validation data sets are necessary.
Large-scale nanoimprinted metasurfaces based on silicon photonic crystal slabs were produced and coated with a NaYF4:Yb3+/Er3+ upconversion nanoparticle (UCNP) layer. UCNPs on these metasurfaces yield a more than 500-fold enhanced upconversion emission compared to UCNPs on planar surfaces. It is also demonstrated how the optical response of the UCNPs can be used to estimate the local field energy in the coating layer. Optical simulations using the finite element method validate the experimental results and the calculated spatial three-dimensional field Energy distribution helps us to understand the emission enhancement mechanism of the UCNPs closely attached to the metasurface. In addition, we analyzed the spectral shifts of the resonances for uncoated and coated metasurfaces and metasurfaces submerged in water to enable a prediction of the optimum layer thicknesses for different excitation wavelengths, paving the way to applications such as electromagnetic field sensors or bioassays.