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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.
A facile and efficient methodology is described for the solvothermal synthesis of size-tunable, stable, and uniform NiCu core–shell nanoparticles (NPs) for application in catalysis. The diameter of the NPs is tuned in a range from 6 nm to 30 nm and to adjust the Ni:Cu ratio from 30:1 to 1:1. Furthermore, the influence of different reaction parameters on the final NPs is studied. The NPs are structurally characterized by a method combination of transmission electron microscopy, anomalous small-angle X-ray scattering, X-ray absorption fine structure, and X-ray photoelectron spectroscopy. Using these analytical methods, it is possible to elucidate a core–shell–shell structure of all particles and their chemical composition. In all cases, a depletion from the core to the shell is observed, with the core consisting of NiCu alloy, surrounded by an inner Ni-rich shell and an outer NiO shell. The SiO2-supported NiCu core–shell NPs show pronounced selectivity of >99% for CO in the catalytic reduction of CO2 to CO using hydrogen as reactant (reverse water–gas shift reaction) independent of size and Ni:Cu ratio.
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.
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.
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.
NanoDefiner e-Tool: An Implemented Decision Support Framework for Nanomaterial Identification
(2019)
The European Commission’s recommendation on the definition of nanomaterial (2011/696/EU) established an applicable standard for material categorization. However, manufacturers face regulatory challenges during registration of their products. Reliable categorization is difficult and requires considerable expertise in existing measurement techniques (MTs). Additionally, organizational complexity is increased as different authorities’ registration processes require distinct reporting.
The NanoDefine project tackled these obstacles by providing the NanoDefiner e-tool: A decision support expert system for nanomaterial identification in a regulatory context. It providesMT recommendations for categorization of specific materials using a tiered approach (screening/confirmatory), and was constructed with experts from academia and industry to be extensible, interoperable, and adaptable for forthcoming revisions of the nanomaterial definition. An implemented MT-driven material categorization scheme allows detailed description. Its guided workflow is suitable for a variety of user groups. Direct feedback and explanation enable transparent decisions. Expert knowledge is Held in a knowledge base for representation of MT performance criteria and physicochemical particle type
properties. Continuous revision ensured data quality and validity. Recommendations were validated by independent case studies on industry-relevant particulate materials. Besides supporting material identification and registration, the free and open-source e-tool may serve as template for other expert systems within the nanoscience domain.
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.
Although the use of noble metal catalysts can increase the efficiency of hydrogen evolution reaction, the process is still limited by the characteristics of the metal-hydrogen (M−H) bond, which can be too strong or too weak, depending on the metal employed. Studies revealed that the hydrogen affinity for the metal surface (i.e. H absorption/desorption) is regulated also by the potential at the metal nanoparticles. Through controlled periodic illumination (CPI) of a series of metal/TiO2 suspensions, here we demonstrated that an increase of the HER efficiency is possible for those photodeposited metals which have a Tafel slope below 125 mV. Two possible explanations are here reported, in both of them the M−H interaction and the metal covering level play a prominent role, which also depend on the prevailing HER mechanism (Volmer-Heyrovsky or Volmer-Tafel).
The roughness as a property of core–shell (CS) microparticles plays a key role in their functionality. Quantitative evaluation of the roughness of CS microparticles is, however, a challenging task with approaches using electron microscopy images being scarce and showing pronounced differences in terms of methodology and results. This work presents a generalized method for the reliable roughness determination of nonplanar specimens such as CS particles from electron microscopic images, the method being robust and reproducible with a high accuracy. It involves a self-written software package (Python) that analyzes the recorded images, extracts corresponding data, and calculates the roughness based on the deviation of the identified contour. Images of single particles are taken by a dual mode scanning electron microscopy (SEM) setup which permits imaging of the same field-of-view of the sample with high resolution and surface sensitive in SE InLens mode as well as in transmission mode (TSEM). Herein, a new type of polystyrene core–iron oxide shell–silica shell particles is developed to serve as a set of lower micrometer-sized study objects with different surface roughness; the analysis of their images by the semiautomatic workflow is demonstrating that the particles’ profile roughness can be quantitatively obtained.
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.