Abstract: To obtain a nanocrystalline SnO2 matrix and mono- and bimetallic nanocomposites SnO2/Pd, SnO2/Pt, and SnO2/PtPd, a flame spray pyrolysis with subsequent impregnation was used. The materials were characterized using X-ray diffraction (XRD), a single-point BET method, transmission electron microscopy (TEM), and high angle annular dark field scanning transmission electron microscopy (HAADF-STEM) with energy dispersive X-ray (EDX) mapping. The electronic state of the metals in mono- and bimetallic clusters was determined using X-ray photoelectron spectroscopy (XPS). The active surface sites were investigated using the Fourier Transform infrared spectroscopy (FTIR) and thermo-programmed reduction with hydrogen (TPR-H-2) methods. The sensor response of blank SnO2 and nanocomposites had a carbon monoxide (CO) level of 6.7 ppm and was determined in the temperature range 60-300 degrees C in dry (Relative Humidity (RH) = 0%) and humid (RH = 20%) air. The sensor properties of the mono- and bimetallic nanocomposites were analyzed on the basis of information on the electronic state, the distribution of modifiers in SnO2 matrix, and active surface centers. For SnO2/PtPd, the combined effect of the modifiers on the electrophysical properties of SnO2 explained the inversion of sensor response from n- to p-types observed in dry conditions.

Abstract: Colloidal CsPbBr3 nanocrystals (NCs) have emerged as promising candidates for various opto-electronic applications, such as light-emitting diodes, photodetectors, and solar cells. Here, we report on the self-assembly of cubic NCs from an organic suspension into ordered cuboidal supraparticles (SPs) and their structural and optical properties. Upon increasing the NC concentration or by addition of a nonsolvent, the formation of the SPs occurs homogeneously in the suspension, as monitored by in situ X-ray scattering measurements. The three-dimensional structure of the SPs was resolved through high-angle annular dark-field scanning transmission electron microscopy and electron tomography. The NCs are atomically aligned but not connected. We characterize NC vacancies on superlattice positions both in the bulk and on the surface of the SPs. The occurrence of localized atomic-type NC vacancies-instead of delocalized ones-indicates that NC-NC attractions are important in the assembly, as we verify with Monte Carlo simulations. Even when assembled in SPs, the NCs show bright emission, with a red shift of about 30 meV compared to NCs in suspension.

Abstract: We study the mechanisms of CO2 conversion in a nanosecond repetitively pulsed (NRP) discharge, by means of a chemical kinetics model. The calculated conversions and energy efficiencies are in reasonable agreement with experimental results over a wide range of specific energy input values, and the same applies to the evolution of gas temperature and CO2 conversion as a function of time in the afterglow, indicating that our model provides a realistic picture of the underlying mechanisms in the NRP discharge and can be used to identify its limitations and thus to suggest further improvements. Our model predicts that vibrational excitation is very important in the NRP discharge, explaining why this type of plasma yields energy-efficient CO2 conversion. A significant part of the CO2 dissociation occurs by electronic excitation from the lower vibrational levels toward repulsive electronic states, thus resulting in dissociation. However, vibration−translation (VT) relaxation (depopulating the higher vibrational levels) and CO + O recombination (CO + O + M → CO2 + M), as well as mixing of the converted gas with fresh gas entering the plasma in between the pulses, are limiting factors for the conversion and energy efficiency. Our model predicts that extra cooling, slowing down the rate of VT relaxation and of the above recombination reaction, thus enhancing the contribution of the highest vibrational levels to the overall CO2 dissociation, can further improve the performance of the NRP discharge for energy-efficient CO2 conversion.

Abstract: To broaden the activity window of TiO2, a broadband plasmonic photocatalyst has been designed and optimized. This plasmonic ‘rainbow’ photocatalyst consists of TiO2 modified with gold–silver composite nanoparticles of various sizes and compositions, thus inducing a broadband interaction with polychromatic solar light. However, these nanoparticles are inherently unstable, especially due to the use of silver. Hence, in this study the application of the layer-by-layer technique is introduced to create a protective polymer shell around the metal cores with a very high degree of control. Various TiO2 species (pure anatase, PC500, and P25) were loaded with different plasmonic metal loadings (0–2 wt %) in order to identify the most solar active composite materials. The prepared plasmonic photocatalysts were tested towards stearic acid degradation under simulated sunlight. From all materials tested, P25 + 2 wt % of plasmonic ‘rainbow’ nanoparticles proved to be the most promising (56% more efficient compared to pristine P25) and was also identified as the most cost-effective. Further, 2 wt % of layer-by-layer-stabilized ‘rainbow’ nanoparticles were loaded on P25. These layer-by-layer-stabilized metals showed superior stability under a heated oxidative atmosphere, as well as in a salt solution. Finally, the activity of the composite was almost completely retained after 1 month of aging, while the nonstabilized equivalent lost 34% of its initial activity. This work shows for the first time the synergetic application of a plasmonic ‘rainbow’ concept and the layer-by-layer stabilization technique, resulting in a promising solar active, and long-term stable photocatalyst.

Abstract: Cold atmospheric plasma and nanomedicine originally emerged as individual domains, but are increasingly applied in combination with each other. Most research is performed in the context of cancer treatment, with only little focus yet on the possible synergies. Many questions remain on the potential of this promising hybrid technology, particularly regarding regenerative medicine and tissue engineering. In this perspective article, we therefore start from the fundamental mechanisms in the individual technologies, in order to envision possible synergies for wound healing and tissue recovery, as well as research strategies to discover and optimize them. Among these strategies, we demonstrate how cold plasmas and nanomaterials can enhance each other’s strengths and overcome each other’s limitations. The parallels with cancer research, biotechnology and plasma surface modification further serve as inspiration for the envisioned synergies in tissue regeneration. The discovery and optimization of synergies may also be realized based on a profound understanding of the underlying redox- and field-related biological processes. Finally, we emphasize the toxicity concerns in plasma and nanomedicine, which may be partly remediated by their combination, but also partly amplified. A widespread use of standardized protocols and materials is therefore strongly recommended, to ensure both a fast and safe clinical implementation.

Abstract: Morphological characterization of nanoparticle assemblies and hybrid nanomaterials is critical in determining their structure-property relationships as well as in the development of structures with desired properties. Electron tomography has become a widely utilized technique for the three-dimensional characterization of nanoparticle assemblies. However, the extraction of quantitative morphological parameters from the reconstructed volume can be a complex and labor-intensive task. In this study, we aim to overcome this challenge by automating the volumetric segmentation process applied to three-dimensional reconstructions of nanoparticle assemblies. The key to enabling automated characterization is to assess the performance of different volumetric segmentation methods in accurately extracting predefined quantitative descriptors for morphological characterization. In our methodology, we compare the quantitative descriptors obtained through manual segmentation with those obtained through automated segmentation methods, to evaluate their accuracy and effectiveness. To show generality, our study focuses on the characterization of assemblies of CdSe/CdS quantum dots, gold nanospheres and CdSe/CdS encapsulated in polymeric micelles, and silica-coated gold nanorods decorated with both CdSe/CdS or PbS quantum dots. We use two unsupervised segmentation algorithms: the watershed transform and the spherical Hough transform. Our results demonstrate that the choice of automated segmentation method is crucial for accurately extracting the predefined quantitative descriptors. Specifically, the spherical Hough transform exhibits superior performance in accurately extracting quantitative descriptors, such as particle size and interparticle distance, thereby allowing for an objective, efficient, and reliable volumetric segmentation of complex nanoparticle assemblies.