A model flow reactor provides a narrow particle temperature-residence time distribution with well-defined conditions and is mandatory to measure changes of the particle structure precisely. The experimental data of iron and iron oxide agglomerates are used to determine the sintering kinetics considering the temperature-time history of the particles. Thousand particle trajectories are tracked in a validated CFD model at three different furnace temperatures each. Strongly agglomerated particles with a small primary particle size (∼4 nm) are synthesized by spark discharge and are size-selected (25–250 nm) before sintering. The structure development is measured simultaneously with different online instrumentations and the structure calculated by means of structure models. A simple sintering model, based on the reduction of surface energy, is numerically quantified with the experimental results. The surface of the particles is strongly dependent on the primary particle size and the agglomerate structure. The chemical phase is analyzed using the offline techniques XANES, XRD, and EELS. It is observed that the addition of hydrogen led to a reduction of iron oxide to iron nanoparticles and to changes of the sintering kinetics. The sintering exponent (Formula presented.) = 1 was found to be optimal. For Fe, an activation energy (Formula presented.) of 59.15 kJ/mol and a pre-exponential factor (Formula presented.) of 1.57 104 s/m were found, for Fe3O4 an activation energy (Formula presented.) of 55.22 kJ/mol and a pre-exponential factor (Formula presented.) of 2.54 104 s/m. Copyright © 2022 American Association for Aerosol Research. © 2022 American Association for Aerosol Research.

In this work, we introduce a new particle mass spectrometer (AP-PMS) that is able to detect particle-size distributions at ambient pressure using a three-stage pumping design. This device is demonstrated for direct sampling from the particle formation in spray-flame synthesis of iron oxide nanoparticles. Aerosol sampling is performed by a probe with integrated dilution that has been characterized and configured by computational fluid dynamics simulations and the chamber-skimmer system has been investigated by schlieren imaging. The system was validated by detailed characterization of a standardized sooting flame and by iron oxide nanoparticles generated in the SpraySyn burner from iron nitrate dissolved in a mixture of ethanol and 2-ethylhexanoic acid. The PMS results are compared to additional inline measurements with SMPS and ELPI + as well as with TEM measurements of thermophoretically sampled materials from the same location in the spray flame. © 2021 The Authors

The formation of a nanocomposite structure is thermodynamically driven by spinodal decomposition in at least two phases. With respect to the suppression of solid solution formation, artificial nc-TiN/nc-CrN composites were deposited using a novel hybrid-process, in which TiN nanoparticles and CrN thin film were separately synthesized and simultaneously deposited during composite growth. The bias-voltage is known as a crucial deposition parameter concerning the structural and mechanical properties in thin film technology. However, it is still unclear whether an externally injected nanoparticle jet is influenced by the bias-voltage applied to the substrate. In this work, composite thin films were DC sputtered applying bias-voltages of 0 V, -100 V and -200 V in DC mode, as well as -100 V in MF and HiPIMS mode. TEM-investigations reveal the successful embedment of the nanoparticles in the film. Growth defects in the interface between nanoparticle and thin film can be reduced using a pulsed bias-voltage. Based on 2D GI-XRD experiments using synchrotron radiation, a bias-voltage of -200 V DC and -100 V MF enables the reinforcement of a higher nanoparticle content in the thin films. Similar to an increased bias-voltage, the injection of nanoparticles results in a decrease of the crystallite size. In principle, the residual stresses are increased by the nanoparticle embedding, as is the case for an increasing bias-voltage. In the event of a pulsed-bias voltage, however, the residual stresses can be reduced by the embedding of the nanoparticles. The mechanical properties of the CrN thin films can be maintained when nanoparticles are injected. © 2021

Soot is an important material with impacts that depend on particle morphology. Transmission electron microscopy (TEM) represents one of the most direct routes to qualitatively assess particle characteristics. However, producing quantitative information requires robust image processing tools, which is complicated by the low image contrast and complex aggregated morphologies characteristic of soot. The current work presents a new convolutional neural network explicitly trained to characterize soot, using pre-classified images of particles from a natural gas engine; a laboratory gas flare; and a marine engine. The results are compared against other existing classifiers before considering the effect that the classifiers have on automated primary particle size methods. Estimates of the overall uncertainties between fully automated approaches of aggregate characterization range from 25% in dp,100 to 85% in DTEM. A consistent correlation is observed between projected-area equivalent diameter and primary particle size across all of the techniques. © 2021 Elsevier B.V.

Fiber-shaped materials (e.g. carbon nano tubes) are of great relevance, due to their unique properties but also the health risk they can impose. Unfortunately, image-based analysis of fibers still involves manual annotation, which is a time-consuming and costly process. We therefore propose the use of region-based convolutional neural networks (R-CNNs) to automate this task. Mask R-CNN, the most widely used R-CNN for semantic segmentation tasks, is prone to errors when it comes to the analysis of fiber-shaped objects. Hence, a new architecture – FibeR-CNN – is introduced and validated. FibeR-CNN combines two established R-CNN architectures (Mask and Keypoint R-CNN) and adds additional network heads for the prediction of fiber widths and lengths. As a result, FibeR-CNN is able to surpass the mean average precision of Mask R-CNN by 33% (11 percentage points) on a novel test data set of fiber images. © 2020 Elsevier B.V.

CrTiN thin films are known to form a solid solution independent from the Ti content. Using a novel spatially separated synthesis approach, consisting of magnetron sputtering and atmospheric-pressure arc evaporation, artificial CrTiN nanocomposites were deposited. For the nanocomposite formation, TiN nanoparticles were synthesized using a transferred arc reactor and directly injected into growing CrN thin films using an aerodynamic lens system. The CrN and CrTiN thin films were deposited using various deposition conditions, such as heating power, substrate rotation velocity, nanoparticle injection distance, and cathode setup. The deposited thin films were analyzed regarding their physical structure, microstructure and mechanical properties. Based on the investigations, between 0.02 and 0.11 at.-% of TiN nanoparticles are embedded in the CrN matrix dependent on the deposition parameters. 2D GI-XRD experiments using synchrotron radiation confirm the nanocomposite structure for the two thin films with the highest TiN nanoparticle content. The crystallite size of the CrN thin film decreases from 9.4 ± 2.3 nm to 5.3 ± 1.2 nm due to the embedding of the nanoparticles. Concerning the physical structure, the nanoparticle injection leads to a change of the texture, as shown by the Debbye-Scherrer rings. Based on TEM-investigations, TiN nanoparticle agglomerates lead to a coarser microstructure of the CrN matrix. The hardness of the thin films is not significantly affected by the nanoparticle embedment. The nanoparticle injection distance and cathode setup reveal the highest impact on the film properties. © 2021 Elsevier B.V.

The synthesis of nanocomposites is limited to thermodynamically immiscible phases or to phase separation by exceeding the limits of solution. Hence, the formation of nanocomposites based on transition metals, revealing a nanocrystalline Metal-Nitride/nanocrystalline Metal-Nitride structure, is restricted. These restrictions can be overruled by a spatially separated synthesis of the two phases and a recombination during the deposition. With this approach, the limits of current systems can be expanded, enabling the synthesis of artificial nanocomposites based on a variety of materials. We demonstrate the synthesis of a composite of two nanocrystalline phases of the miscible transition metal-nitrides CrN and TiN. TiN nanoparticles were synthesized using an atmospheric-pressure arc reactor and in-situ injected into a growing CrN thin film. The thin films are analyzed regarding their physical- and microstructure using two-dimensional GIXRD, XPS based on synchrotron radiation and TEM. The CrTiN thin film reveals a two-phase structure consisting of nanocrystalline CrN and TiN phases with crystallite sizes of 9 nm and 4 nm according to GIXRD. XPS indicates bonding of Cr-N, Cr-Cr, and Ti-N. No hint for Cr-Ti bonding was found, excluding (Cr,Ti)N solid solution formation. Based on the TEM-investigations, TiN nanoparticles are embedded as agglomerates in the CrN matrix. © 2020 Elsevier B.V.

Structure formation models describe the change of the particle structure, e.g., by sintering or coating, as a function of the residence time and temperature. For the validation of these models, precise experimental data are required. The precise determination of the required data is difficult due to simultaneously acting mechanisms leading to particle structure formation as well as their dependency on various particle properties and process conditions in the reactor. In this work, a model flow reactor (MFR) is designed and optimized, supported by a validated computational fluid dynamic simulation, to determine the structure formation of nanoparticles under well-defined conditions. Online instrumentation is used to measure the particle mass and different equivalent diameter to detect changes of the particle shape and to calculate the particle structure, defined by the primary particle size, the number of primary particles per agglomerate, coating thickness, effective density, and fractal dimension, by means of structural models. High precision is achieved by examining size-selected particles in a low number concentration and a laminar flow field. Coagulation can be neglected due to the low particle number concentration. Structure formation is restricted to a defined region by direct particle trajectories from the water-cooled aerosol inlet to the water-cooled outlet. A preheated sheath gas is used to concentrate the aerosol on the centerline. The simulated particle trajectories exhibit a well-defined and narrow temperature residence time distribution. Residence times of at least 1 s in the temperature range from 500 K to 1400 K are achieved. The operation of the MFR is demonstrated by the sintering of size-selected FexOy agglomerates with measurements of the particle size and mass distribution as a function of the temperature. An increase of the effective density, resulting from the decreasing particle size at constant particle mass, is observed. © 2020 Author(s).

Arc discharge synthesis has industrial relevance due to its low cost and scale-up potential. The production of titanium nitride nanoparticles was achieved by direct current arc discharge in an atmospheric-pressured ambient composed of N2 and Ar. We systematically investigated the effect of the synthesis parameters, including quench gas velocity, quench gas composition, and applied arc current, on the particle quality, yield, and size. It is found that increasing quench gas velocity enables to produce particles with a primary size of 10–15 nm, while titanium nitride particles of 20–50 nm are produced at low quench gas velocity based on scanning electron microscope (SEM) analysis. X-ray diffraction (XRD) results indicated that titanium nitride particles produced at various nitrogen compositions are almost stoichiometric, while the crystallite size increases almost 20 nm when increasing nitrogen contents in the quench gas. Quench gas composition also has a significant impact on the arc voltage as well as particle production rate. When increasing the nitrogen concentration from 20% to 100%, the production rate can be enhanced by a factor of three. Besides, raising the applied arc current from 12 A to 50 A leads to a yield enhancement of factor 10. According to the Brunauer-Emmett-Teller (BET) measurement, the increase of applied arc current has a limited impact on primary particle size. The enhancement in particle production rate is mainly reflected by the larger agglomerate sizes and agglomerate number concentration. Additionally, based on experimental observations and previous studies, a mechanism is presented to explain the growth of deposits on the cathode tip. © 2020 The Society of Powder Technology Japan

Stochastic simulation techniques for the solution of a network of population balance equations (PBE) are discussed in this chapter. The application of weighted Monte Carlo (MC) particles for the solution of compartmental PBE systems is summarized and its computational efficacy in form of a parallel GPU implementation is pointed out. Solution strategies for coagulation, nucleation, breakage, growth and evaporation are thereby presented. An application example treats the simultaneous coagulation, nucleation, evaporation and growth encountered during particle production through the aerosol route. Furthermore, the simulation of a compartmental network is discussed and parallel simulation techniques for the transport of weighted MC particles are presented. The proposed methodology is benchmarked by comparison with a pivot method for a variety of test cases with an increasing degree of complexity. Simulation conditions are identified, for which conventional, non-weighted MC simulation techniques are not applicable. It is found, that the specific combination of a screen unit with tear-streams cannot be simulated by conventional methods, termed ‘random removal’, and make thus other techniques-like the here introduced merging techniques necessary. © Springer Nature Switzerland AG 2020.

Copper nanoparticles (NPs) are considered as a promising alternative for silver and gold NPs in conductive inks for the application of printing electronics, since copper shows a high electrical conductivity but is significantly cheaper than silver and gold. In this study, copper NPs were synthesized in the gas phase by transferred arc discharge, which has demonstrated scale-up potential. Depending on the production parameters, copper NPs can be continuously synthesized at a production rate of 1.2-5.5 g h-1, while their Brunauer-Emmett-Teller sizes were maintained below 100 nm. To investigate the suitability in electronic printing, we use ball milling technique to produce copper conductive inks. The effect of ball milling parameters on ink stability was discussed. In addition, the electrical resistivity of copper films sintered at 300 °C in reducing atmosphere was measured to be 5.4 ± 0.6 μΩ cm which is about three times higher than that of bulk copper (1.7 μΩ cm). This indicates that conductive inks prepared from gas-phase synthesized copper NPs are competitive to the conductive inks prepared from chemically synthesized copper NPs. © 2019 IOP Publishing Ltd.

The application of standard online instrumentation, such as scanning mobility particle sizer (SMPS), centrifugal particle mass analyzer or aerosol particle mass analyzer (CPMA/APM), and electrical low-pressure impactor (ELPI+) to low-pressure processes is only possible with extensive modification of the devices and extensive calibrations. A low-pressure ejector is a suitable device to transfer aerosol nanoparticles from low-pressure regions to atmospheric pressure and allows the direct use of standard online instrumentation. In this work, a commercial low-pressure ejector is investigated in the pressure range from 20–180 mbar with fully-sintered and size-selected nanoparticles (15–80 nm) in order to extend the application range of online instruments to low-pressure processes and open up a new variety of analysis methods. Results are compared to our previous work which was limited to pressures above 120 mbar. A change in particle size during the measurements for fully-sintered silver particles was not observed. A particle dilution factor between 60–6500 was found. High particle losses in the ejector for large particle sizes are compensated by a lower gas dilution factor. © 2020 Elsevier Ltd

Nanomaterials with very specific features (purity, colloidal stability, composition, size, shape, location…) are commonly requested by cutting-edge technologic applications, and hence a sustainable process for the mass-production of tunable/engineered nanomaterials would be desirable. Despite this, tuning nano-scale features when scaling-up the production of nanoparticles/nanomaterials has been considered the main technological barrier for the development of nanotechnology. Aimed at overcoming these challenging frontier, a new gas-phase reactor design providing a shorter residence time, and thus a faster quenching of nanoclusters growth, is proposed for the green, sustainable, versatile, cost-effective, and scalable manufacture of ultrapure engineered nanomaterials (ranging from nanoclusters and nanoalloys to engineered nanostructures) with a tunable degree of agglomeration, composition, size, shape, and location. This method enables: (1) more homogeneous, non-agglomerated ultrapure Au-Ag nanoalloys under 10 nm; (2) 3-nm non-agglomerated ultrapure Au nanoclusters with lower gas flow rates; (3) shape-controlled Ag NPs; and (4) stable Au and Ag engineered nanostructures: nanodisks, nanocrosses, and 3D nanopillars. In conclusion, this new approach paves the way for the green and sustainable mass-production of ultrapure engineered nanomaterials. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.

There is a high demand for fully automated methods for the analysis of primary particle size distributions of agglomerated, sintered or occluded primary particles, due to their impact on material properties. Therefore, a novel, deep learning-based, method for the detection of such primary particles was proposed and tested, which renders a manual tuning of analysis parameters unnecessary. As a specialty, the training of the utilized convolutional neural networks was carried out using only synthetic images, thereby avoiding the laborious task of manual annotation and increasing the ground truth quality. Nevertheless, the proposed method performs excellent on real world samples of sintered silica nanoparticles with various sintering degrees and varying image conditions. In a direct comparison, the proposed method clearly outperforms two state-of-the-art methods for automated image-based particle size analysis (Hough transformation and the ImageJ ParticleSizer plug-in), thereby attaining human-like performance. © 2019 Elsevier B.V.

This work is a first direct numerical simulation of a configuration closely related to the SpraySyn burner (Schneider et al. in Rev Sci Instrum 90:085108, 2019). This burner has been recently developed at the University of Duisburg-Essen to investigate experimentally nanoparticle synthesis in spray flames for a variety of materials. The present simulations are performed for ethanol and titanium tetraisopropoxide as a solvent and precursor, respectively, in order to produce titanium dioxide nanoparticles. In the direct numerical simulations, the complete scenario leading to the production of well-defined nanoparticles is taken into account, including evaporation of the liquid mixture (solvent and precursor) injected as a spray, multi-step kinetics for gas-phase combustion, and finally nanoparticle synthesis. The employed models are described in this article. Additionally, the impact of the inlet velocity of the pilot flame on the nanoparticle synthesis is investigated. It has been found that increasing this speed delays spray flame ignition, decreases nanoparticle concentration, but leads to a narrower size distribution at early stage. © 2020, The Author(s).

A flexible stochastic approach is described to model separation processes, in which air-borne particles are separated via a setup of one or more aerodynamic lens orifices. Varying the size of the orifices, the focusing pressure and the mass flow rate through the lens, leads to focusing of particles with distinct aerodynamic properties on the central axis. In this modeling approach a bivariate transfer function is used to describe the passage probability of particles depending on their size and mass. The distribution of feed particles and the changes of the distribution due to the separation process is described via probability densities. The modeling procedure is applicable to various kinds of separation methods and allows optimization of geometric and operation parameters. To this end, the model utilizes flexibly defined separation performance measures which are illustrated in a case study that considers the separation of Cu particles from SiO2 particles. The spherical particles in the considered virtual mixtures are described by their log-normally distributed diameters and their normally distributed mass densities. Furthermore, the cases are selected in such a manner that the mean aerodynamic diameters of both Cu and SiO2 particles are equal. © 2020 The Society of Powder Technology Japan

Conductivity of the electrodes material is an essential factor in sparking process. Therefore, spark-discharge technique is normally used to prepare metallic nanoparticles. The synthesis of semiconducting nanoparticles by means of spark is quite challenging task. Probability of increased 'splashing', a phenomenon which may leads to the formation of more micron sized particles in the case of semiconductors. In the present study, synthesis of Germanium (Ge) nanoparticles, by using spark discharge technique, is reported. Furthermore, the possibility of enhancing production rate of Ge nanoparticles is also investigated. © 2019 Elsevier Ltd.

Nanocomposite coatings are state of the art, nevertheless the possible material combinations are restricted. Therefore, this work demonstrates an approach to synthesize novel nanostructured thin films by producing the nanoparticles and thin films independently. An atmospheric-pressure transferred arc reactor is used to synthesize TiN nanoparticles. The device is linked to a magnetron sputter device with an aerodynamic lens system. The aerodynamic lens enables the in-situ introduction of the synthesized nanoparticles into the PVD chamber by compensating the pressure differences. In this study, the influence of the linkage on the properties of a CrN thin film as well as the chamber conditions (pressure, temperature, bias-voltage, and plasma) on the TiN nanoparticles are analyzed. The CrN thin film is only slightly affected by the incoming working gas of the nanoparticle reactor. The TiN nanoparticles reveal a crystallite size of 9.3 ± 2.3 nm and are successfully introduced into the PVD chamber as agglomerates with sizes of 0.04 μm2 and are then deposited onto substrates. It is shown that the particle distribution, agglomerate size, morphology, and crack behavior can be influenced by the chamber conditions. © 2019 Elsevier B.V.

A new design of a Differential Mobility Analyzer (DMA) was tested with medium aerosol flow rates ranging from 1.5 to 10 slm and high-density particles. The vacuum-tight construction makes it possible to classify pure metal nanoparticles from production processes. The selectable electrical mobility range is comparable to the TSI Long and Nano DMA and covers the full nanometer scale from 15–600 nm. The Medium Flow-DMA (MF-DMA) is characterized by its transfer function, which was determined by a tandem DMA setup using a SMPS with Long DMA downstream. Silver nanoparticles with a density of 10.49 g cm−3 were used to demonstrate the size-selecting performance of high-density particles. The transfer function was calculated for aerosol to sheath gas flow ratios of 1/10, 1/5, and 1/3 directly from the SMPS data by a new method using modeling approach and comparison to the theory. Sufficiently high resolution was reached by increasing the SMPS scan time of the classified size distribution to 300 s. During the investigation, a broadened transfer function could be attributed to an inhomogeneous flow field resulting from the aerosol inlet design. The aerosol inlet of the MF-DMA was optimized by the number of inlet drillings and the opening of the inlet slit to achieve a more homogeneous flow field. CFD simulations of the MF-DMA also confirmed this. The modification improved the transfer function especially for medium aerosol flow rates above 5 slm. Copyright © 2019 American Association for Aerosol Research. © 2019, © 2019 American Association for Aerosol Research.

Hard coatings for wear protection of tools, bearings, and sliding parts play an important role in industrial manufacturing. Nanocomposite coatings are being used in this context to improve the mechanical properties. The technology applied therefore is often based on physical vapor deposition (PVD), in which the different materials are co-deposited. In these processes it is not possible to control the properties of the disperse phase and continuous phase independently. Here, we present a technology which combines aerosol technology with thin film technology to produce nanocomposite coatings directly, which gives us full control over both phases. It is based on an upscaled three-stage aerodynamic lens, which allows to bring nanoparticles from an atmospheric-pressure aerosol reactor into a PVD vacuum chamber operating at low pressure (2 Pa). This requires the use of a higher mass flow rate than conventionally used in aerodynamic lenses, so that a rational upscaling strategy for designing an aerodynamic lens for larger mass flow rates is proposed. Here, an array consisting of eight parallel three-stage aerodynamic lenses having each a mass flow rate of 0.6 slm using argon and 0.71 slm using nitrogen is built and optimized, assisted by CFD and numerical trajectory analysis. The transfer efficiency has been investigated numerically and experimentally. It is possible to transfer 80% of the particles with only 1.3% of the gas into the deposition chamber. A number of coatings consisting of titanium carbonitride nanoparticles embedded in a PVD chromium oxynitride film with varying nanoparticle content were produced. Electron microscopy shows the successful incorporation of the nanoparticles in the thin film. A reduction in film crystallite size with increasing nanoparticle content was found. A reverse Hall–Petch behavior was observed. Copyright © 2019 American Association for Aerosol Research. © 2019, © 2019 American Association for Aerosol Research.

The application of the Monte Carlo (MC) simulation technique for the modelling of nucleation processes with an existing background particle concentration is presented in this paper. Next to the nucleation of novel particles, the coagulation of an existing particle population as well as the condensational growth and evaporation of unstable particles (whose diameter is smaller than the critical Kelvin diameter) are included into the simulation. The usage of statistically weighted MC particles allows the description of particle size distribution (PSD), whose concentrations differ in several orders of magnitude. It is shown, that this approach allows to model the complex interplay between freshly nucleated particles and an existing background particle population. In this work, the nucleation of novel particles is modelled by three different nucleation theories discussed by [Girshick, S. L. and C.-P. Chiu (1990), The Journal of Chemical Physics 93], which comprise of (1) the classical nucleation theory, (2) a mathematical correction to (1) and (3) a self-consistency correction of (2). For the chosen simulation conditions, the resulting PSDs are independent of the used nucleation theory for longer simulation times, in which the simulations are described by the coagulation mechanism only. The time-frame is identified for which relevant discrepancies of the PSDs have to be taken into account. © 2019, © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

In this study, feasibility of spark discharge technique to generate mixed metal nanoparticles is demonstrated. Two immiscible metals Au and Zn are selected to prepare AuZn mixed nanoparticles. Ignition of spark between Au and Zn electrodes under normal pressure, in the presence of carrier gas, leads to formation of mixed nanoparticles by condensation and nucleation. Online particle size-distribution is monitored by a scanning mobility particle sizer on changing carrier gas flow rate and capacitor charging current during co-sparking between Au and Zn electrodes. The technique provides flexibility to generate binary mixture of AuZn nanoparticles in the size range of 10-80 nm. Distribution of Au and Zn in the prepared mixed nanoparticles is mapped by scanning electron microscopy and high resolution electron microscopy. © Materials Research Society 2019.

The Dual Population Balance Monte Carlo Method (DPBMC) takes into account the full size spectrum of the droplet and particle phase. Droplet and particle size distributions are rendered by weighted simulation particles. This allows for an accurate description of particle nucleation and coagulation and droplet combustion, simultaneously. Internal droplet properties such as temperature and concentrations fields are used to define criteria for the onset of droplet breakage in the framework of weighted Monte Carlo droplets. We discuss the importance of droplet polydispersity on particle formation in metal oxide particle synthesis, which is shown to strongly affect particle formation and growth. The method is applied to particle synthesis from metal nitrate precursor solutions with flame spray pyrolysis (FSP) and compared to experiments from literature. © 2018 by the authors.

Online measurements of nanoparticles are necessary when rapid information about the particle size and mass distribution is needed. Currently, the application of online measurement techniques with commonly used instruments such as SMPS, CPMA and ELPI+ is not possible at low-pressure conditions. In this work, a commercial vacuum ejector is used as a simple tool to transfer nanoparticles from a low-pressure region to atmospheric pressure. The vacuum ejector is investigated for different process pressures between 120 and 170 mbar to measure size-selected aerosols in the range from 10 to 100 nm. It was found that the sampling with the vacuum ejector does not change the particle size. The gas and particle dilution factors as well as the particle losses are determined, so that quantitative measurements of the aerosol size distribution can be obtained. Additionally, the applicability of the vacuum ejector is tested during particle synthesis in a low-pressure microwave plasma reactor with a combination of online instrumentation. The direct transfer of the aerosol to atmospheric pressure allows real-time measurements. The primary particle size, mass mobility exponent and effective density are calculated exemplary based on parallel online ELPI+, SMPS and CPMA measurements and are compared to offline TEM analysis. © 2018 Elsevier Ltd

The event-driven acceptance rejection (AR) method is a computationally very advantageous Monte Carlo (MC) simulation technique for the solution of population balance equations (PBE) of coagulating systems. In the scope of the event-driven simulation approach, the simulation time is stepwise increased by a simulation time step τ which is given be the simulated particle properties. Within this time step τ exactly one coagulation event takes place. The method is therefore not applicable in situations, for which specific time points have to be reached by the simulation, or the time step has to be reset to a smaller value. We propose a methodology termed ‘fractional MC step’ which allows to reset the simulation time step of the AR method to any arbitrary smaller value than the one initially proposed. The proposed method is validated by simulations of coagulation for different initial conditions and comparison with results gained from the discrete sectional method. The potential increase of the stochastic noise is investigated by comparisons with the results from conventional MC simulation techniques. The advantages of a parallel implementation are briefly discussed. © 2018 Institution of Chemical Engineers

There is a high demand for fully automated methods for the analysis of primary particle size distributions of agglomerates on transmission electron microscopy images. Therefore, a novel method, based on the utilization of artificial neural networks, was proposed, implemented and validated. The training of the artificial neural networks requires large quantities (up to several hundreds of thousands) of transmission electron microscopy images of agglomerates consisting of primary particles with known sizes. Since the manual evaluation of such large amounts of transmission electron microscopy images is not feasible, a synthesis of lifelike transmission electron microscopy images as training data was implemented. The proposed method can compete with state-of-the-art automated imaging particle size methods like the Hough transformation, ultimate erosion and watershed transformation and is in some cases even able to outperform these methods. It is however still outperformed by the manual analysis. © 2018 Elsevier B.V.

The performance of particle-based products depends on a multiple set of particle properties. To monitor them during particle manufacturing, three novel aerosol measurement techniques were developed: wide-angle light scattering (WALS), three-dimensional laser scattering (3D-LSS), and differential aerodynamic particle sizing (DAPS). They measure particle shape, aggregate structure, and particle size, i.e., radius of gyration and aerodynamic diameter. The techniques were tested for rod-like organic pigments and partially sintered SiO2 aggregates, which were produced by two new aerosol generators. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

The number of applications and products containing metal nanomaterials has significantly increased over the past years. In order to address the upcoming demand for metal nanoparticles, new scale-up strategies are required. The scale-up of nanoparticle synthesis, especially for metals, is however very challenging. This study reports about a production facility with a new scale-up approach for pure metal nanoparticles. The scale-up approach is the parallelization of multiple transferred arcs in one reactor, which were previously individually optimized. Furthermore, a novel filtration and bagging system is introduced, which is designed to handle pyrophoric metal nanoparticles. It is shown that the production rate of the process scales linearly with the number of transferred arcs, while the particle size stays on the nanoscale. © 2018 The Society of Powder Technology Japan

Monte Carlo simulations based on weighted simulation particles can solve a variety of population balance problems and allow thus to formulate a solution-framework for many chemical engineering processes. This study presents a novel concept for the calculation of coagulation rates of weighted Monte Carlo particles by introducing a family of transformations to non-weighted Monte Carlo particles. The tuning of the accuracy (named ‘stochastic resolution’ in this paper) of those transformations allows the construction of a constant-number coagulation scheme. Furthermore, a parallel algorithm for the inclusion of newly formed Monte Carlo particles due to nucleation is presented in the scope of a constant-number scheme: the low-weight merging. This technique is found to create significantly less statistical simulation noise than the conventional technique (named ‘random removal’ in this paper). Both concepts are combined into a single GPU-based simulation method which is validated by comparison with the discrete-sectional simulation technique. Two test models describing a constant-rate nucleation coupled to a simultaneous coagulation in 1) the free-molecular regime or 2) the continuum regime are simulated for this purpose. © 2017 Elsevier Inc.

Monte Carlo (MC) simulations based on weighted particles offer novel and more precise techniques for the solution of the population balance equation for particulate systems. A recent constant-number approach named stochastic weighted algorithm (SWA) (Lee et al. (2015), J. Comput. Phys. (303) 1–18) has been developed, which renders the breakage of a simulation particle by an alteration of its properties, without the creation of novel simulation particles. The theoretic justification of the general formulation for all possible SWAs is limited to binary breakage kernels. We present a novel approach for the derivation of the properties of the MC particles representing fragments, which is applicable for all sorts of breakage kernels. This general scheme encompasses the already introduced SWA schemes, especially a number-based (SWA1, named NBS in this paper) and volume-based (SWA2, named VBS in this paper) breakage scheme, and it makes novel formulations possible: the low volume scheme (LVS), which renders preferably lower fragment sizes, and the combination of LVS with the NBS (LVS-NBS) or VBS (LVS-VBS). The implementation of these breakage schemes in the context of a GPU-based time-driven method is presented and the gained results are validated by comparison with results of the analytic solutions of a homogeneous binary breakage kernel. It is found, that the SWA methods (NBS and VBS) are only able to render large particle sizes, and that LVS, NBS-LVS and VBS-LVS are able to render the whole spectrum of particle sizes. Smaller noise levels are found for VBS and specific VBS-LVS schemes, making both more suitable for prolonged simulations than the other presented methods. © 2017 Elsevier B.V.

A simulation method is presented which encompasses all relevant mechanisms, which are necessary for the description of the early stages of particle formation in arc discharges. Next to discrete coagulation and nucleation events, a continuous surface growth process is included into the simulation, making thus the description of the evaporation of thermodynamic unstable particles possible. The driving force for the nucleation and growth/evaporation is coupled to the monomer concentration in the gaseous phase and thus subject to change in the further course of the simulation. It is shown, that the simulation results gained by the incorporation of all three of these processes cannot be reproduced, if one of those processes is not simulated. © 2017 Materials Research Society.

In this report a methodology is described and demonstrated for preparing Au-Ge pair nanoparticles with known compositions by extending and modifying the basic steps normally used to synthesize nanoparticles in carrier gas. For the formation of pair nanoparticles by bipolar mixing, two oppositely charged aerosols of nanoparticles having the desired size are produced with the help of two differential mobility analyzers. Then both are allowed to pass through a tube, which provides sufficient residence time to result in nanoparticle pair formation due to Brownian collisions influenced by Coulomb forces. The effect of residence time on the formation of nanoparticle pairs as well as the influence of diffusion and discharging is described. Subsequently, necessary modifications to the experimental setup are demonstrated systematically. The kinetics of nanoparticles pair formation in a carrier gas is also calculated and compared with measurements made with the help of an online aerosol size analysis technique. This synthesis of nanoparticle pairs can be seen as a possible route towards Janus-type nanoparticles. © 2016 IOP Publishing Ltd.

The demand for metal nanoparticles is increasing strongly. Transferred arc synthesis is a promising process in this respect, as it shows high production rates, good quality particles and the ability of up-scaling. The influence of several process parameters on the performance of the process in terms of production rate and particle size is investigated. These parameters are the electrode design and adjustment, the gas flow rate and power input. A novel feeding mechanism allows process operation over an extended time period. It is shown that the process is capable of producing pure metal nanoparticles with variable primary particle sizes and comparatively high production rates. Optimal process conditions for a single transferred arc electrode pair are found, which allow further scale-up by numbering up. © 2016, The Author(s).

A major challenge in nanotechnology is that of determining how to introduce green and sustainable principles when assembling individual nanoscale elements to create working devices. For instance, textile nanofinishing is restricted by the many constraints of traditional pad-dry-cure processes, such as the use of costly chemical precursors to produce nanoparticles (NPs), the high liquid and energy consumption, the production of harmful liquid wastes, and multistep batch operations. By integrating low-cost, scalable, and environmentally benign aerosol processes of the type proposed here into textile nanofinishing, these constraints can be circumvented while leading to a new class of fabrics. The proposed one-step textile nanofinishing process relies on the diffusional deposition of aerosol NPs onto textile fibers. As proof of this concept, we deposit Ag NPs onto a range of textiles and assess their antimicrobial properties for two strains of bacteria (i.e., Staphylococcus aureus and Klebsiella pneumoniae). The measurements show that the logarithmic reduction in bacterial count can get as high as ca. 5.5 (corresponding to a reduction efficiency of 99.96%) when the Ag loading is 1 order of magnitude less (10 ppm; i.e., 10 mg Ag NPs per kg of textile) than that of textiles treated by traditional wet-routes. The antimicrobial activity does not increase in proportion to the Ag content above 10 ppm as a consequence of a "saturation" effect. Such low NP loadings on antimicrobial textiles minimizes the risk to human health (during textile use) and to the ecosystem (after textile disposal), as well as it reduces potential changes in color and texture of the resulting textile products. After three washes, the release of Ag is in the order of 1 wt %, which is comparable to textiles nanofinished with wet routes using binders. Interestingly, the washed textiles exhibit almost no reduction in antimicrobial activity, much as those of as-deposited samples. Considering that a realm of functional textiles can be nanofinished by aerosol NP deposition, our results demonstrate that the proposed approach, which is universal and sustainable, can potentially lead to a wide number of applications. © 2016 American Chemical Society.

The inversion of the particle size distribution from electrical mobility measurements is analyzed. Three different methods are adapted for a dot-matrix approach to the problem, especially for non-square or singular matrices, and applied to electrical mobility measurements from fixed or scanning voltages. Multiply charged particles, diffusion losses, arbitrary voltage steps and noise were considered, which results in non-adjoining and overlapping transfer functions. The individual contribution of the transfer functions in each size interval was geometrically estimated, which requires only its characteristic mobilities. The methodology is applied to mobility measurements from particles charged with unipolar and bipolar chargers. However, the method can be extrapolated to any charging method with a defined charge distribution, and retrieval of the singly charged particle distribution and mean charge from a tandem differential mobility analysis configuration was successfully demonstrated. © 2014 Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy ofSciences. Published by Elsevier B.V. All rights reserved.

Plasma methods using the direct evaporation of a transition metal are well suited for the cost-efficient production of ceramic nanoparticles. In this paper, we report on the development of a simple setup for the production of titanium-ceramics by reactive anodic arc evaporation and the characterization of the aerosol as well as the nanopowder. It is the first report on TiCXN1 − X synthesis in a simple anodic arc plasma. By means of extensive variations of the gas composition, it is shown that the composition of the particles can be tuned from titanium nitride over a titanium carbonitride phase (TiCXN1 − X) to titanium carbide as proven by XRD data. The composition of the plasma gas especially a very low concentration of hydrocarbons around 0.2 % of the total plasma gas is crucial to tune the composition and to avoid the formation of free carbon. Examination of the particles by HR-TEM shows that the material consists mostly of cubic single crystalline particles with mean sizes between 8 and 27 nm. © 2015, Springer Science+Business Media Dordrecht.

Differential mobility analyzers (DMAs) are commonly used to generate monodisperse nanoparticle aerosols. Commercial DMAs operate at quasi-atmospheric pressures and are therefore not designed to be vacuum-tight. In certain particle synthesis methods, the use of a vacuum-compatible DMA is a requirement as a process step for producing high-purity metallic particles. A vacuum-tight radial DMA (RDMA) has been developed and tested at low pressures. Its performance has been evaluated by using a commercial NANO-DMA as the reference. The performance of this low-pressure RDMA (LP-RDMA) in terms of the width of its transfer function is found to be comparable with that of other NANO-DMAs at atmospheric pressure and is almost independent of the pressure down to 30 mbar. It is shown that LP-RDMA can be used for the classification of nanometer-sized particles (5-20nm) under low pressure condition (30 mbar) and has been successfully applied to nanoparticles produced by ablating FeNi at low pressures. © 2014 IOP Publishing Ltd.

An existing differential mobility analyzer (DMA) of cylindrical electrodes and a novel DMA of rectangular plate electrodes are demonstrated for size fractionation of nanoparticles at high-aerosol flow rates in this work. The two DMAs are capable of delivering monodisperse size selected nanoparticles (SMPS σg < 1.1) at gas flow rates ranging from 200 slm to 500 slm. At an aerosol flow rate of 200 slm, the maximum attainable particle mean size is of about 20 nm for the cylindrical DMA and of nearly 50 nm for the rectangular plate DMA. The number concentration of the monodisperse nanoparticles delivered by the high-flow DMAs spans from 104 cm-3 to 10 6 cm-3 depending upon the particle mean size and particle size dispersion. Copyright © 2014 American Association for Aerosol Research.

Two-component aggregative mixing of initially bidisperse particle populations results in a Gaussian-type compositional distribution function, which can be fully described by the overall mass fraction of component A (φ) and the mass-normalized power density of excess component A (π, indicating the mixing degree). π will reach a steady-state value once the self-preserving size distribution is attained. The relation between the steady-state value of π (π∞) and its initial value (π0) has not been investigated before. This paper applies population balance modeling to gain insight into the dependence of π∞ on initial feeding conditions. By model fitting from hundreds of systematically varied simulations, it is found that π∞/π0, which depends on φ, can be formalized by the Gaussian-type function for Brownian aggregation in the free-molecular regime as well as in the continuum regime, however with different geometric standard deviations. The present work can help to optimize mixing by properly selecting the initial mass and number concentrations of components A and B in the feed. © 2014 American Chemical Society.

A model for unipolar charging of nanoparticles based on the Fuchs birth-and-death theory is developed. It includes both diffusional and electrical losses for particles and ions. Electrical losses are modeled by inclusion of a radial electric field which is caused by space charge. The model can be used to obtain the initial ion concentration and mean radial electric field from data of charge distribution fractions, without additional measurements. It was successfully applied to results from three different unipolar chargers. In all cases, good agreement between experimental and modeling results has been obtained. The model can be used to assist the operation of unipolar chargers, e.g. by predicting charging efficiencies for particle sizes which are not experimentally accessible. © 2014 Elsevier Ltd.

This work is aimed at investigating the influence of the inter-electrode spacing on the production rate and size of nanoparticles generated by evaporating a cathode on an atmospheric pressure dc glow discharge. Experiments are conducted in the configuration of two vertically aligned cylindrical electrodes in upward coaxial flow with copper as a consumable cathode and nitrogen as a carrier gas. A constant current of 0.5 A is delivered to the electrodes and the inter-electrode distance spanned from 0.5 to 10 mm. Continuous stable nanoparticle production is attained by optimal coaxial flow convection cooling of the cathode. Both the particle production rate and the primary particle size increase with the inter-electrode spacing up to nearly 5 mm and strongly decrease with an increasing inter-electrode distance beyond 5 mm. Production rates in the range of 1 mg h-1of very small nanoparticles (< 10 nm) are attained by a micro glow discharge (< 1 mm); while glow discharges of intermediate sizes (< 5 mm) result in production rates of up to 10 mg h-1and primary particles of sizes between 10 and 20 nm. No correlation is found between the measured spatially averaged plasma parameters and nanoparticle production. Since the latter is largely determined by the properties of the cathode surface, spatially resolved spectrometric measurements are needed to discern between the positive column and the cathode region of the glow discharge plasma. © 2014 IOP Publishing Ltd.

An efficient and a versatile unipolar corona charger was developed. It has indirect charging characteristics, with corona and charging regions separated. Ions were generated by a needle electrode and then driven to the charging region by a sheath flow in order to reduce the electrostatic loss of nanoparticles. The distance of the electrode to the walls can be adjusted by a micrometer, modifying the onset voltage and N it-product, and therefore the intrinsic and extrinsic charging efficiencies and loss of charged particles. Experimental results indicate that the generated ion current is practically the same independent of the variation in the applied voltage or corona current, but varying the electrode gap distance seems to be a much more efficient way to regulate the N it-product. The charging efficiency can vary from high values, comparable to the higher efficiency chargers presented in the literature, to lower levels such as reached with bipolar chargers. © 2013 Elsevier Ltd.

At the nanoscale material properties can be tuned by altering the size and shape of the specimen. Such effects are quite well investigated for metallic materials. On the other hand inorganic compounds have received relatively little interest due to the more demanding experimental procedures. While the size effects are similar for any kind of inorganic material, the degree of size-dependent changes depends on the bond strength and bond nature of the material at the surface: the higher the surface energy, the stronger the size dependence. These thoughts are demonstrated in this contribution by investigating the size-dependent thermodynamic properties of monodisperse, size-selected bismuth oxide (Bi2O3) nanoparticles in the range between 6 and 50 nm. This first part is mainly concerned with evaporation, while the second part (J. Phys. Chem. C 2014, 10.1021/jp509841s) covers size-dependent melting. Heating experiments up to the evaporation of the particles were performed with a new, custom method based on loss of matter caused by evaporation. The results in this part show the validity of the Kelvin equation and a size-dependent evaporation behavior of this oxide. (Graph Presented). © 2014 American Chemical Society.

A graphics processing unit (GPU)-based Monte Carlo (MC) algorithm for particle coagulation using an acceptance-rejection (AR) strategy leading to improved computing efficiency has been developed and validated. The use of GPUs in high-performance computing is attractive due to the low cost per core, currently some 1-2 EUR. The GPU-implementation developed takes full advantage of the intrinsic parallel property featured by the AR strategy, namely, multiple AR attempts are carried out independently on many threads simultaneously. It uses an efficient way to obtain an estimation for the maximum coagulation kernel from the mean kernel. The method has been benchmarked by a sectional method validating its computing accuracy. Especially when a large number of cells is being handled at the same time, remarkable speed-up factors are achieved. This makes the method, a choice when population balances have to be solved in a CFD environment, which is demonstrated by means of a case study describing simultaneous coagulation, nucleation and diffusion in 1D. In summary, the simulations show that a MC method for particle coagulation based on the AR strategy can be efficiently parallelized on a GPU. © 2013.

Scaling up metal nanoparticle production is a desired goal of much research, the need of the industry due to the growing market of applications increases significantly. However, a scale up of production rate often leads to an increase in particle size and a broadening of size distribution. Particle characterization in terms of size is mostly done after synthesis. In this work, a transferred arc process is optimized to increase the production rate of pure copper nanoparticles economically. The maximum production rate for different particle sizes is determined by TEOM measurements. While the influence of different carrier gases has been investigated before, different mixtures of nitrogen and argon as carrier gas are used to manipulate the primary particle size. Primary particle size determination is performed by a novel analysis method based on parallel online ELPI and SMPS measurement. An equation is found to calculate the mass mobility exponent directly on the basis of the effective density of an agglomerate. Hence, the method is suitable for determining the primary particle sizes directly online. Copyright © American Association for Aerosol Research.

Metal nanoparticles are used in a great number of applications; an effective and economical production scaling-up is hence desirable. A simple and cost-effective transferred arc process is developed, which produces pure metal (Zn, Cu, and Ag) nanoparticles with high production rates, while allowing fast optimization based on energy efficiency. Different carrier gas compositions, as well as the electrode arrangements and the power input are investigated to improve the production and its efficiency and to understand the arc production behavior. The production rates are determined by a novel process monitoring method, which combines an online microbalance method with a scanning mobility particle sizer for fast production rate and size distribution measurement. Particle characterization is performed via scanning electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray diffraction measurements. It is found that the carrier gas composition has the largest impact on the particle production rate and can increase it with orders of magnitude. This appears to be not only a result of the increased heat flux and melt temperature but also of the formation of tiny nitrogen (hydrogen) bubbles in the molten feedstock, which impacts feedstock evaporation significantly in bi-atomic gases. A production rate of sub 200 nm particles from 20 up to 2,500 mg/h has been realized for the different metals. In this production range, specific power consumptions as low as 0.08 kWh/g have been reached. © 2013 Springer Science+Business Media Dordrecht.

The feasibility of spark discharge technique for preparing metal-semiconductor nanocomposites is demonstrated. In the AuGe system, Au shows only 10-3 atomic percent solid solubility in Ge, whereas 3.1 at.% Ge is soluble in Au. During the co-sparking, Au is used as anode material; the cathode is composed of Ge. The relative atomic percent of Au and Ge in the initially generated mixture can be changed by changing the charging current to the capacitor used to trigger the sparking. Depending upon the atomic ratio of Au and Ge in the initial mixture, AuGe agglomerates form AuGe composite nanoparticles on subsequent sintering, in which AuGe alloy nanoparticles are found dispersed in a Ge matrix. The size of the dispersed AuGe alloy nanoparticles depend on the relative atomic concentration of Au and Ge in the initial mixture as well as on the sintering temperature. AuGe alloy nanoparticles dispersed in the Ge matrix are observed to exhibit an intense photoluminescence between 550 and 600 nm. © 2013 Springer Science+Business Media.

Simulating particle coagulation using Monte Carlo methods is in general a challenging computational task due to its numerical complexity and the computing cost. Currently, the lowest computing costs are obtained when applying a graphic processing unit (GPU) originally developed for speeding up graphic processing in the consumer market. In this article we present an implementation of accelerating a Monte Carlo method based on the Inverse scheme for simulating particle coagulation on the GPU. The abundant data parallelism embedded within the Monte Carlo method is explained as it will allow an efficient parallelization of the MC code on the GPU. Furthermore, the computation accuracy of the MC on GPU was validated with a benchmark, a CPU-based discrete-sectional method. To evaluate the performance gains by using the GPU, the computing time on the GPU against its sequential counterpart on the CPU were compared. The measured speedups show that the GPU can accelerate the execution of the MC code by a factor 10-100, depending on the chosen particle number of simulation particles. The algorithm shows a linear dependence of computing time with the number of simulation particles, which is a remarkable result in view of the n2 dependence of the coagulation. © 2013 Elsevier Inc.

The synthesis of nanoparticles by means of electrical discharges between two electrodes in an inert gas at atmospheric pressure, as driven by a constant current ranging from a few milliamps to tens of amps, is investigated in this work. An extensive series of experiments are conducted with copper as a consumable electrode and pure nitrogen as the inert gas. Three different DC power supplies are used to drive electrical discharges for the entire operating current range. Then, three electrical discharge regimes (spark, glow, and arc) with distinct voltage-current characteristics and plasma emission spectra are recognized. For the first time, nanoparticles are synthesized by evaporation of an electrode by atmospheric pressure inert gas DC glow discharge of a few millimeters in size. The discharge regimes are characterized in terms of the mass output rate and the particle size distribution of the copper aerosols by means of online (tapered element oscillating microbalance, TEOM; and scanning mobility particle sizer, SPMS) and offline (gravimetric analysis; small and wide angle X-ray scattering, SWAXS; and transmission electron microscopy, TEM) techniques. The electrical power delivered to the electrode gap and the gas flow rate are two major parameters determining the aerosol mass output rate and the aerosol particle size distribution. The mass output rate of copper aerosols raises from 2 mg h-1 to 2 g h-1 when increasing the electrical power from 9 to 900 W. The particle mean size (SMPS dg) varies between 20 and 100 nm depending upon the electrical power and the gas flow rate, whereas the particle size dispersion (SMPS σg) ranges from 1.4 to 1.7 and is only weakly dependent on the gas flow rate. © 2013 Springer Science+Business Media.

No method is currently available to combine stochastic, particle-based PBE modeling by means of Monte-Carlo simulation of individual particles and CFD. CFD is based on solving numerically partial differential equations, whereas Monte-Carlo simulation of the PBE bases on converting kinetic rate equations into probabilities and selecting the relevant events by means of random numbers. A joint mathematical framework is thus missing. The goal of this work is to develop a method which allows combining Monte-Carlo based PBE modeling with a CFD model. As a first step towards this goal, a Weighted Random Walk (WRW) method to simulate the particle transport due to convection and diffusion is developed. The simulation particles have no exact position as in Lagrangian particle tracking methods but belong to a CFD cell. The movement of the simulation particles in space is performed by calculation of the transition probability into the neighboring cells and the use of random numbers to simulate the particle transport into these cells. As the particle number concentration can be very different in different regions of the simulated reactor volume, we introduce here also a weighting method which allows fixing the number of simulation particles per cell. The WRW method is combined with a relatively simple constant-number MC method allowing to simulate stochastically the dynamic evolution of the particle population. Four different validative case studies of increasing complexity are performed, comparing the simulation results with those of a CFD-based moment model. © 2011 Elsevier Ltd.

The ability to prepare nanoparticles having well-defined size and narrow size distribution is an important advantage for optimising and understanding nanoparticulate gas sensors. It allows to monitor the size effect of SnO 2 particles as well as that of the addition of the noble metal particles on sensing behaviour. The synthesis of monodisperse SnOx, Pd and Ag nanoparticles and the development the thin films deposition technology as well as suitable microchip platforms are described. Sensing results of SnO x:M mixed nanoparticle layers are presented, especially the effects of operating temperature, particle size, type of noble metal additive and electrode distance are investigated. Sensor to sensor reproducibility as well as long-term stability is investigated. Finally, pure Pd nanoparticle layers are demonstrated to show concentration-specific H 2 sensing at room temperature. © Springer-Verlag Berlin Heidelberg 2012.

Monodisperse polyhedral In 2O 3 nanoparticles were synthesized by differential mobility classification of a polydisperse aerosol formed by evaporation of indium at atmospheric pressure. When free molten indium particles oxidize, oxygen is absorbed preferentially on certain planes leading to the formation of polyhedral In 2O 3 nanoparticles. It is shown that the position of oxygen addition, its concentration, the annealing temperature and the type of carrier gas are crucial for the resulting particle shape and crystalline quality. Semiconducting nanopolyhedrals, especially nanocubes used for sensors, are expected to offer enhanced sensitivity and improved response time due to the higher surface area as compared to spherical particles. © 2012 The Royal Society of Chemistry.

The use of well-defined nanoparticles for functional film applications is described. The advantages of applying size-fractionation, e.g. by means of mobility analysis, are described together with the technological obstacles which have to be overcome. The synthesis of Au and Ge nanoparticles by means of spark discharge is described. To prepare alloy nanoparticles, two different approaches have beenutilized. Au-Ge pair nanoparticles are formed by bipolar mixing after separate size selection of both materials. The synthesis of AuGe alloyed nanoparticles is also performed by co-sparking from two different electrodes. The development of an electrostatic precipitator for functional film formation is described. © Springer-Verlag Berlin Heidelberg 2012.

The fabrication of semiconducting functional layers using low-temperature processes is of high interest for flexible printable electronics applications. Here, the one-step deposition of semiconducting nanoparticles from the gas phase for an active layer within a thin-film transistor is described. Layers of semiconducting nanoparticles with a particle size between 10 and 25 nm were prepared by the use of a simple aerosol deposition system, excluding potentially unwanted technological procedures like substrate heating or the use of solvents. The nanoparticles were deposited directly onto standard thin-film transistor test devices, using thermally grown silicon oxide as gate dielectric. Proof-of-principle experiments were done deploying two different wide-band gap semiconducting oxides, tin oxide, SnO x, and indium oxide, In 2O 3. The tin oxide spots prepared from the gas phase were too conducting to be used as channel material in thin-film transistors, most probably due to a high concentration of oxygen defects. Using indium oxide nanoparticles, thin-film transistor devices with significant field effect were obtained. Even though the electron mobility of the investigated devices was only in the range of 10 -6 cm 2V -1s -1, the operability of this method for the fabrication of transistors was demonstrated. With respect to the possibilities to control the particle size and layer morphology in situ during deposition, improvements are expected. © 2012 Springer Science+Business Media B.V.

We report the shape evolution of free gold agglomerates with different morphologies that transform to ellipsoidal and then to spherical shapes during the heating cycle. The shape transformation is associated with a structural transition from polycrystalline to single crystalline. The structural transition temperature is shown to be dependent on the final size of the particles and not on the initial morphologies of the agglomerates. It is also shown that the transition occurs well below the melting temperature which is in contrast with the melt-freeze process reported in the literature. © The Royal Society of Chemistry 2011.

In this study, size dependence of electronic and topographical effects during Pd-H interaction has been investigated by studying H sensing in thin films of size selected and monosized nanoparticles having 15, 20, and 25 nm diameter. By separating the contributions of electronic changes due to H adsorption and topographical changes due to lattice expansion to hydrogen sensing, it has been shown that the magnitude and response time of these changes are sensitive functions of nanoparticle size and measurement temperature. The temperature dependence of saturated resistance corresponding to these changes provides important information about the nature of electronic and topographical changes. © 2011 American Institute of Physics.

Gas-to-particle synthesis under high temperature is one of the most important methods for producing multicomponent nanoparticles. The volume enlargement of particles due to aggregation accompanies the component mixing within particles in a nonreactive system. To tailor nanocomposites, it is essential to gain an insight into the dynamic evolution of compositional distributions. In this paper, the differentially weighted Monte Carlo (DWMC) method for population balance modeling is used to simulate the process of aggregative mixing. On the methodological end, a new shift action is proposed to regulate a limited number of simulation particles to be distributed as homogeneously as possible over high-dimensional and inhomogeneous joint space of multiple components, where some simulation particles in less-populated regions are split into more simulation particles in order to increase sample space for stochastic statistics and then fatigue against statistical noise, at the same time a certain number of simulation particles in densely populated regions are randomly removed from the simulation to reduce computational demands. The DWMC with the new shift action is used to simulate the aggregative mixing process of bicomponent nanoparticles with compositional-independent or -dependent Brownian coagulation kernel in the free-molecular regime. It is found that the compositional distributions satisfy self-preserving formulation as the particle size distribution in monocomponent systems; and the extent of the time evolution of the degree of mixing (the mass-normalized power density of excess component A) corresponds with that of self-preserving distributions. The compositional distributions and the degree of mixing predicted by the DWMC agree well with theoretical models, while the constant-number method (using equally weighted simulation particles) fails in the more advanced stages of aggregative mixing. © 2011 American Chemical Society.

The direct simulation Monte Carlo (DSMC) method for population balance modeling is capable of retaining the history of each simulation particle and is thus able to deal with multivariate properties in a simple and straightforward manner. As opposed to conventional DSMC approaches that track equally weighted simulation particles, a differentially weighted Monte Carlo method is extended to simulate two-component coagulation processes and is thereby able to simulate the micromixing of the components. A new feature of the method for this bivariate population balance modeling is that it is possible to specify how the simulation particles are distributed over the compositional axis. This allows us to obtain information about particles in those regions of the size and composition distribution functions where the non-weighted MC methods place insufficient simulation particles to obtain an inaccurate solution. The new feature results in lower statistical noise for simulating two-component coagulation, which is validated by using two-component coagulation cases for which analytical solutions exist (a discrete process with sum kernel for initial monodisperse populations and a process with constant kernel for initial polydisperse populations). © 2010 Elsevier Inc.

The present study reports for the first time the influence of stoichiometry of SnO2 nanoparticles synthesized in the gas phase at atmospheric pressure towards the field effect behaviour. The field effect was measured by using the nanoparticles as active material in a transistor channel. The transistors fabricated from the stoichiometric SnO2 nanoparticles (∼20 nm) obtained by post-deposition low-temperature (300 °C) oxidation of the SnO nanoparticles clearly demonstrate n-type behaviour in contrast to the high electrical conductance exhibited by the non-stoichiometric SnOx nanoparticles obtained by high temperature (650 °C) in-flight oxidation. X-ray Photoelectron Spectroscopy (XPS) studies confirm the stoichiometry of the in-flight as well as the post-oxidized nanoparticles.