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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.
We present a workflow for obtaining fully trained artificial neural networks that can perform automatic particle segmentations of agglomerated, non-spherical nanoparticles from scanning electron microscopy images “from scratch”, without the need for large training data sets of manually annotated images. The whole process only requires about 15 minutes of hands-on time by a user and can typically be finished within less than 12 hours when training on a single graphics card (GPU). After training, SEM image analysis can be carried out by the artificial neural network within seconds. This is achieved by using unsupervised learning for most of the training dataset generation, making heavy use of generative adversarial networks and especially unpaired image-to-image translation via cycle-consistent adversarial networks. We compare the segmentation masks obtained with our suggested workflow qualitatively and quantitatively to state-of-the-art methods using various metrics. Finally, we used the segmentation masks for automatically extracting particle size distributions from the SEM images of TiO2 particles, which were in excellent agreement with particle size distributions obtained manually but could be obtained in a fraction of the time.
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.
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.
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.
BAM is currently building up a platform of novel nanoRMs relying on iron oxide nanoparticles of different shape, size and surface chemistry. Iron oxide was chosen as a core material because of its relevance to the material and life sciences.
As a first candidate of this series, we present cubic iron oxide nanoparticles with a nominal edge length of 8 nm. These particles were synthesized by thermal decomposition of iron oleate in high boiling organic solvents adapting well-known literature procedures. After dilution to a concentration suitable for electron microscopy (TEM and SEM) as well as for small-angle X-ray scattering (SAXS) measurements, the candidate nanoRM was bottled and assessed for homogeneity and stability by both methods following the guidelines of ISO 17034 and ISO Guide 35.
The particle sizes obtained by both STEM-in-SEM and TEM are in excellent agreement with a minimum Feret of 8.3 nm ± 0.7 nm. The aspect ratio (AR) of the iron oxide cubes were extracted from the images as the ratio of minimum Feret to Feret resulting in an AR of 1.18 for TEM to 1.25 for SEM. Alternatively, a rectangular bounding box was fitted originating from the minimum Feret and the longest distance through the particle in perpendicular direction. This led to AR values of 1.05 for TEM and 1.12 for SEM, respectively. The results confirm the almost ideal cubic shape.
We show that complex physical and chemical interactions between boehmite nanoparticles and epoxy drastically affect matrix properties, which in the future will provide tuning of material properties for further optimization in applications from automotive to aerospace. We utilize intermodulation atomic force microscopy (ImAFM) for probing local stiffness of both particles and polymer matrix. Stiff particles are expected to increase total stiffness of nanocomposites and the stiffness of polymer should remain unchanged. However, ImAFM revealed that stiffness of matrix in epoxy/boehmite nanocomposite is significantly higher than unfilled epoxy. The stiffening effect of the boehmite on epoxy also depends on the particle concentration. To understand the mechanism behind property alteration induced by boehmite nanoparticles, network architecture is investigated using dynamic mechanical thermal analysis (DMTA). It was revealed that although with 15 wt% boehmite nanoparticles the modulus at glassy state increases, crosslinking density of epoxy for this composition is drastically low.
We present how mesoporosity can be engineered in transition metal phosphate (TMPs) materials in a template-free manner. The method involves a transformation of a precursor metal phosphate phase, called M-struvite (NH4MPO4·6H2O, M = Mg2+, Ni2+, Co2+, NixCo1-x2+). It relies on the thermal decomposition of crystalline M-struvite precursors to an amorphous and simultaneously mesoporous phase, which forms while degassing of NH3 and H2O. The temporal evolution of mesoporous frameworks and the response of the metal coordination environment were followed with in-situ and ex-situ scattering and diffraction, as well as X -ray spectroscopy. Despite sharing the same precursor struvite structure, different amorphous and mesoporous structures were obtained depending on the involved transition metal. We highlight the systematic differences in absolute surface area, pore shape, pore size, and phase transitions depending on a metal cation present in the analogous M-struvites. The amorphous structures of thermally decomposed Mg-, Ni- and NixCo1-x-struvites exhibit high surface areas and pore volumes (240 m²g-1 and 0.32 cm-3 g-1 for Mg and 90 m²g-1 and 0.13 cm-3 g-1 for Ni). We propose that the low-cost, environmentally friendly M-struvites could be obtained as recycling products from industrial and agricultural wastewaters. These waste products could be then upcycled into mesoporous TMPs through a simple thermal treatment for further applications, for instance, in (electro)catalysis.
Low-cost, high-efficient catalysts for water splitting can be potentially fulfilled by developing earthabundant metal oxides. In this work, surface galvanic formation of Co-OH on K0.45MnO2 (KMO) was achieved via the redox reaction of hydrated Co2+ with crystalline Mn4+. The synthesis method takes place at ambient temperature without using any surfactant agent or organic solvent, providing a clean, green route for the design of highly efficient catalysts. The redox reaction resulted in the formation of ultrathin Co-OH nanoflakes with high electrochemical surface area. X-ray absorption spectroscopy (XAS) and X-ray photoelectron spectroscopy (XPS) analysis confirmed the changes in the oxidation state of the bulk and
surface species on the Co-OH nanoflakes supported on the KMO. The effect of the anions, such as chloride, nitrate and sulfate, on the preparation of the catalyst was evaluated by electrochemical and spectrochemical means. XPS and Time of flight secondary ion mass spectrometry (ToF-SIMS) analysis demonstrated that the layer of CoOxHy deposited on the KMO and its electronic structure strongly depend on the anion of the precursor used during the synthesis of the catalyst. In particular, it was found that Cl- favors the formation of Co-OH, changing the rate-determining step of the reaction, which enhances the catalytic activity towards the OER, producing the most active OER catalyst in alkaline media.
Singlet oxygen generation potential of two novel free-base-porphyrin photocatalysts was investigated. The freebase-porphyrin-sensitized Fe3O4 magnetic nanoparticles (MNPs) were tested for the degradation of the model pollutant Bisphenol A (BPA) in aqueous solution, for the first time. MNPs with either cubic or spherical shape were synthesized using the sonochemical approach, followed by sensitizing with photoactive 4,4′,4′′,4′′′- (Porphine-5,10,15,20-tetrayl)tetrakis(benzoic acid) (TCPP). The resulted photocatalysts were characterized in detail by scanning and transmission electron microscopy, Brunauer–Emmett–Teller analysis, spectral techniques and vibrating sample magnetometry. The electron spin resonance experiments have confirmed the high activity of the photocatalysts through the efficient formation of singlet oxygen in solution. The optimum operational parameters for BPA degradation were established as follows: 1.0 μmol L−1 BPA, 1.0 g L−1 of photocatalyst, 100 μmol L−1 H2O2, under UVA irradiation. In these conditions, the results for both photocatalysts revealed that after only 10 min of reaction, over 64% and ca. 90% of BPA have been removed from solution in the absence and presence of H2O2, respectively. Whereas after 60 minutes of treatment, only 24% of BPA in real wastewater effluent samples were removed under UVA irradiation in the absence of H2O2, showing the high complexity of real wastewater. Moreover, both photocatalysts were successfully used for BPA removal in three consecutive runs, without significant loss of catalytic features.