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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.
Fluorides are well-known as wood preservatives. One of the limitations of fluoride-based wood preservatives is their high leachability. Alternative to current fluoride salts such as NaF used in wood protection are low water-soluble fluorides. However, impregnation of low water-soluble fluorides into wood poses a challenge. To address this challenge, low water-soluble fluorides like calcium fluoride (CaF2) and magnesium fluoride (MgF2) were synthesized as nanoparticles via the fluorolytic sol−gel synthesis and then impregnated into wood specimens. In this study, the toxicity of nano metal fluorides was assessed by termite mortality, mass loss and visual analysis of treated specimens after eight weeks of exposure to termites, Coptotermes formosanus. Nano metal fluorides with sol concentrations of 0.5 M and higher were found to be effective against termites resulting in 100% termite mortality and significantly inhibited termite feeding. Among the formulations tested, the least damage was found for specimens treated with combinations of CaF2 and MgF2 with an average mass loss less than 1% and visual rating of “1”. These results demonstrate the efficacy of low water-soluble nano metal fluorides to protect wood from termite attack.