The design of nanoparticles (NPs) with dedicated material properties relevant for specific applications relies on a fundamental understanding of the underlying (trans-)formation mechanisms. Combining experimental observations during particle formation with corresponding simulations offers mechanistic insights necessary to optimize particle characteristics. Chemical vapor synthesis (CVS) is a gas-phase NP synthesis technique enabling scalable production of NPs with desired characteristics. The time-temperature, T(t), profile of the CVS reaction mainly governs the (trans-)formation of NPs. Ex situ investigations to determine correlations between process parameters and particle characteristics often suffer from information loss due to aging or oxidation of transient species, aggregation, or preferred orientations of nanocrystals. These discrepancies may be avoided by in situ and operando probing: where and while the particles are formed. Here, we report results on in situ X-ray diffraction of tin oxide (SnO2) NPs during CVS using synchrotron radiation to observe the evolving crystal structure as the particles form and grow. Especially, the influence of the T(t) profile on the crystal structure of NPs is investigated in situ. Experimental results are complemented by simulations using a physicochemical model of the CVS process. Combining in situ and operando experiments with simulations uncovers the underlying (trans-)formation mechanisms and indicates a dynamic evolution of NP structures. Additionally, temperatures of the nanocrystals in the CVS process are determined by Rietveld refinement of the in situ and operando XRD data via thermal expansion of the lattice parameters.

Production of cost-effective printed electronics relies on inks. Inks may be formulated from molecular precursor solutions, which are then converted into the desired material. Alternatively, inks are based on colloidal dispersions of nanoparticles. This review focuses on metal oxide nanoparticles generated by chemical vapor synthesis (CVS) as particle source for ink formulation. The scope and purpose of this review is to look at advantages and challenges of (very) small nanoparticles from the perspective of product design along the process chain. Particle characteristics are identified as quantitative descriptors for particle microstructure which enable product design since they are controllable at each step of the process chain starting from particle synthesis, their determination is facile and they can be directly linked to physical properties and device performance.It is discussed how CVS process parameters influence key particle characteristics such as size, crystallinity, and agglomeration and, therefore, extrinsic materials properties during synthesis relevant for ink and device performance. Subsequent dispersion processes (deagglomeration and stabilization) further alter particle characteristics. Tailoring surface chemistry of CVS-generated nanoparticles through particle-ligand and particle-solvent interactions provides inks of long-term colloidal stability and excellent printability. Finally, laser sintering and its combination with simultaneous inkjet printing are presented as area selective post-treatment processes converting printed nanoparticle films into functional electronic components.

Abstract A high-speed camera equipped with a near-infrared (NIR) microscope optic is employed for spatially resolved NIR thermal imaging during laser sintering. The device enables operando temperature measurements with a temporal resolution less than 1 ms and a spatial resolution better than 10 μm. The feasibility for in situ temperature measurements is demonstrated for resonant laser sintering of TiO2 nanoparticles. The temperature range is calibrated at a framerate of 1,069 frames per second (fps) using a TiO2 reference sample. The laser sintering process is observed at framerates of up to 15,969 fps. The resulting microstructure of the TiO2 sample is analyzed by scanning electron microscopy (SEM) and interpreted in view of the recorded sintering temperature profiles.

An experimental approach is presented, which enables simultaneous ultrasonic dispersion (USD) and dynamic light scattering (DLS) measurements of colloidal nanoparticle dispersions. This USD-DLS scheme combines sonotrode-based ultrasonication of nanoparticles with time-resolved DLS data collection to study deagglomeration of nanoparticles. The capabilities of this operando approach are demonstrated using two types of nanoparticle systems: monodisperse polystyrene nanospheres and agglomerated titania nanocrystals. The influence of ultrasonication on the DLS signal is investigated using polystyrene particles as probes. During ultrasonication, the recorded autocorrelation functions (ACFs) mainly probe the formation and dynamics of cavitation bubbles in the liquid medium. Upon stopping of ultrasonication, acoustic streaming dominates the particle dynamics for a few seconds (<15 s), as revealed by the transition of the ACFs to equilibrium diffusive dynamics. Then, the particle size as a function of applied ultrasound energy can be determined. The potential of the operando USD-DLS approach to probe nanoparticle deagglomeration is demonstrated for titania nanoparticles of different levels of agglomeration from two synthesis methods. The application of a sequence of ultrasound pulses results in the continuous reduction of particle size as directly probed by DLS. Detailed deagglomeration curves are determined within a single data collection sequence. These data then form the basis for studying agglomerate stability as shown using two analysis models. In addition, it is demonstrated how the USD-DLS approach can be employed to study reagglomeration of nanoparticles under destabilizing conditions in situ.

The structural evolution of tin dioxide (SnO₂) nanoparticle films during resonant laser sintering is investigated using simultaneous, time-resolved small-angle (SAXS) and wide-angle (WAXS) X-ray scattering combined with high-speed near-infrared (NIR) thermography. A focused synchrotron X-ray beam enables spatially and temporally resolved probing of structural changes at both the microstructural and crystal structure scale. The evolution of the temperature field is monitored to correlate the structural dynamics with the temperature–time profile and to analyze the grain growth kinetics. The structural changes observed in situ are complemented by ex situ scanning electron microscopy (SEM) of the evolved microstructure. In addition, the lattice expansion by laser induced heating is determined, and the corresponding thermal expansion coefficients are derived. These space- and time-resolved measurements provide detailed insights into the mechanisms governing resonant laser sintering of SnO₂ nanoparticles.

Gas phase production processes of nanoparticles (NPs) such as Chemical Vapor Synthesis (CVS) enable the generation of NPs with high purity, crystallinity, narrow size distribution, and a low degree of hard agglomeration. The design of materials with desired properties is enabled by a control of CVS process parameters, which demands a fundamental understanding of CVS. Ex situ investigation of the CVS process may suffer from artifacts due to particle collection, oxidation, or aging. This may be circumvented by in situ studies. Such studies are described here using small- and wide-angle X-ray scattering of tin oxide NPs as a model system. We demonstrate the formation of crystalline order as well as variation of morphology, size, and agglomeration as a function of process temperature and pressure. Results are compiled in a size-temperature pseudo-phase diagram of the CVS process.

Transforming dry nanopowders into stable colloidal dispersions remains challenging due to the cohesive forces between the nanoparticles (NPs) which promote agglomeration. Effective dispersion and deagglomeration these agglomerates is a critical process in the formulation and preparation of nanoparticle-based functional materials via the colloidal route. Understanding the deagglomeration dynamics provides information to improve microstructural quality in various applications by enabling engineering of agglomerate size, structure and morphology. However, the deagglomeration process dynamics with respect to the evolution of the fractal agglomerate structures, particularly for very small NPs, is still poorly understood and requires further investigation. This study employs in situ small-angle X-ray scattering (SAXS) to investigate the sonication-induced deagglomeration of SnO2 NPs. Electrostatically stabilized SnO2 colloids with varying primary particle size (6-21 nm) are investigated in a specifically designed in situ cell using synchrotron-based SAXS to study the influence sonication time and intensity on the nanoscaled agglomerates.

Extended X-ray absorption fine structure (EXAFS) spectra contain information about the local, molecular type structure, whereas (X-ray) diffraction (XRD) data reveal the periodic structure or long-range order (crystal structure) of materials. Variations in local and periodic structure greatly influence materials properties and related applications. However, data analysis often is performed independently for EXAFS spectra and diffraction data even if measured simultaneously. We show that it is possible to couple both Reverse Monte Carlo (RMC) analysis of EXAFS spectra and Rietveld refinement of diffraction data by mapping structural parameters consistently and applying a feedback algorithm between both refinement paths. This method is applied to EXAFS and XRD data of nanocrystalline tin dioxide (SnO2) with a crystallite size of 6 nm as model system and compared to independent data analysis of diffraction and EXAFS data as well as a simultaneous analysis using the Debye scattering equation (DSE) for diffraction.

Two-dimensional (2D) van der Waals (vdW) semiconductors such as transition metal dichalcogenides (TMDCs) or 2D halide perovskites receive increasing attention as active materials in photosensing applications due to their high oscillator strength, large electronic mobility, and mechanical flexibility. For triggering an efficient separation of optically generated charge carriers and hence improving the photodetectivity, different vdW semiconductors are combined into functional heterostructures, i.e., TMDCs and 2D Ruddlesden-Popper perovskite. However, despite their increasing usage in devices, energy and charge carrier transfer between TMDCs and 2D Ruddlesden-Popper materials is still controversially discussed, and the underlying mechanisms of device operation are ambiguous. Here, in molybdenum disulfide/butylammonium lead iodide (MoS2/BA2PbI4) heterostructures, we demonstrate a unidirectional hole transfer from MoS2 to BA2PbI4 and an electron blocking through the butylammonium ions. MoS2/BA2PbI4 photodetectors show drastically improved responsivities, reduced dark current, and an increased detectivity compared to MoS2- and BA2PbI4-only devices. We provide evidence that this improvement is related to a gain mechanism due to photogating in the MoS2 channel caused by the unidirectional hole transfer between MoS2 and the BA2PbI4.

Finite size effects in partial pair distribution functions generate artefacts in the scattering structure factor and scattering intensity. It is shown how they can be overcome using a binned version of the Debye scattering equation. Accordingly, reverse Monte Carlo simulations are used for very small nanoparticles of LaFeO3 with diameters below 10 nm to simultaneously analyse X-ray scattering data and extended X-ray absorption fine structure spectra at the La K and Fe K edges. The structural information obtained is consistent regarding local structure and long-range order.

The identification of structure-activity relationships is challenging for complex oxides like lanthanum-based perovskite nano-particles. The purpose of this study is to examine the structure of LaCo1-xFexO3 nanoparticles and develop a detailed structural model to identify subtle changes of the structure after catalysis. Therefore, small nanoparticles with a significant fraction of surface atoms and varying iron content (x = 0, 0.5, 1) are synthesized in the gas phase by chemical vapor synthesis and tested in cyclohexene oxidation in the liquid phase. The crystal structure is examined by X-ray and selected area electron diffraction. Additionally, the local structure of the cations is probed by X-ray absorption spectroscopy at the Co, Fe, La K, and La L3-edges. For a quantitative analysis of the local structure before and after catalysis, an atomistic model is refined by the available extended X-ray absorption fine structure spectra using Reverse Monte Carlo methods. The produced nanoparticles are small with a coherent diffraction domain size between 5 and 10 nm, highly crystalline, and consist mainly of the perovskite phase with a secondary spinel phase. In cyclohexene oxidation, the cobalt-containing samples exhibit significant catalytic activities. The active samples show structural changes after catalysis accompanied by reconstruction of the local structure surrounding the cations in the perovskite phase, which resembles edge-sharing cobalt octahedra.

Filter-less, wavelength-selective photodetectors made of perovskite usually rely on the charge collection narrowing mechanism, which intrinsically limits the response times. Using the narrow excitonic peak of, e.g., two-dimensional (2D) Ruddlesden-Popper perovskites as direct absorbers to realize color-selective photodetectivity promises faster responses. However, one major challenge in realizing such devices remains the separation and charge carrier extraction of the tightly bound excitons. Here, we report on filter-less color-selective photoconductivity in 2D perovskite butylammonium lead iodide thin film devices, exhibiting a distinct resonance in the photocurrent spectrum with a full width at half-maximum of 16.5 nm that correlates to the excitonic absorption. Our devices exhibit unexpectedly efficient charge carrier separation with an external quantum efficiency of ≤8.9% at the excitonic resonance, which we trace back to the involvement of exciton polarons. Our photodetector achieves response times of 150 μs and a maximum specific detectivity of 2.5 × 1010 Jones at the excitonic peak.

Identifying structure–property relationships of polycrystalline microstructures demands an accurate and precise quantification of their features. Measuring grain sizes is tedious and creates a non-transparent bias when being performed by different individuals, impairing comparability with references. Here, we present a novel use of region-based convolutional neural networks (R-CNNs) to quantify several microstructural characteristics and their distributions: Feret diameter, axis length, area, circumference, dihedral angle and coordination number. We utilize a two-step approach: (i) a semi-automatic annotation tool to generate training data for (ii) a fully automated R-CNN, quantitatively evaluating images. Using Al-doped ZnO as a model system, we trained two R-CNNs, one for ZnO and one for precipitated ZnAl2O4. The R-CNN performs well in evaluating grain size characteristics from images with low contrast and in differentiating uni-, and bimodal grain size distributions on the sub-micron, and nanoscale. An extended statistical analysis of the distributions is performed to extract microstructural parameters quantitatively. This innovative solution makes grain size measuring amenable, time-effective, less biased, consistent, and statistically more precise.

Chemical vapor synthesis (CVS) is a gas phase process to generate nanoparticles via a chemical reaction. In this contribution a review of recent methodological advances is provided using nanocrystalline iron oxides as model system. Novel methods are described to control precursor flow of sublimating metalorganic solids, characterization of electronic and molecular structure of vapors using X-ray absorption spectroscopy (XAS), in situ determination of oxygen partial pressure, variation of the time-temperature profile, in situ characterization of electronic, local, crystal and micro-structure using XAS, wide and small angle scattering (WAXS and SAXS) and finally methods to design the CVS process and materials development.

In case of very small nanocrystals, the surface is the dominant defect, generating a microstructure as deviation from the ideal crystal structure by breaking the translational symmetry of the lattice. This heterogeneous disorder may be observed as a different local structure in the core and shell of the nanocrystals and is highly relevant in all properties and applications for which defects are detrimental or beneficial, for example, charge-carrier traps in (opto-)electronics or active surface sites in heterogeneous catalysis. Very small SnO2 nanocrystals generated by chemical vapor synthesis with coherent diffracting domain sizes between 2 and 13 nm are investigated as a model system since they form phase-pure stannic oxide isostructural to rutile. Local structure, crystal structure, and microstructure are studied using X-ray absorption spectroscopy, wide-angle X-ray scattering, X-ray diffraction, and transmission electron microscopy analyzed using reverse Monte Carlo simulations, Rietveld refinement, and image analysis. Size, surface, and interface effects as well as structural defects are discussed. The fraction of atoms at surfaces is substantial for very small nanoparticles. However, only very subtle structural changes are observed here for very small SnO2 nanocrystals as revealed by detailed quantitative structural analysis. This may be because the particles are highly crystalline even for the ultrasmall 2 nm particles which are close to the molecular cluster regime.

The purpose of this study is to find a direct and quantitative correlation of the structure of Co3-xFexO4 nanoparticles with catalytic performance in 2-propanol oxidation. Eight nanocrystalline samples with varying iron contents arc synthesized, and quantitative information regarding their structure is obtained from nitrogen physisorption, X-ray diffraction (XRD), X-ray absorption near-edge structure (XANES), and extended X-ray absorption line structure (EXAFS) analyzed by reverse Monte Carlo simulations. The catalytic performance is tested in 2-propanol oxidation in the gas phase. Overall, catalytic conversion data as a function of temperature are deconvoluted to obtain conversion and half-conversion temperatures as quantitative parameters for the different catalytic reaction channels. The crystal structure is described by a spinel structure with interstitial cation defects. These defects result in a reduced electronic state of the nanoparticles. The defect density depends on the cationic composition. We also observe a complex cationic distribution on tetrahedral and octahedral sites, which is strongly influenced by the overall cationic composition. In the catalytic tests, the samples exhibit a low-temperature pathway, which is deactivated in subsequent runs but can be recovered by an oxidative treatment of the catalyst. We find that the frequency of cation pairs Co-O-Co-O and Co-O-Co-T of the individual samples correlates directly to their catalytic activity and selectivity.

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 (similar to 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 m = 1 was found to be optimal. For Fe, an activation energy E-a of 59.15 KJ/mol and a pre-exponential factor A(s) of 1.57 10(4) s/m were found, for Fe(3)O(4 )an activation energy E-a of 55.22 kJ/mol and a pre-exponential factor A(s) of 2.54 10(4) s/m.

A novel chemical vapor synthesis reactor design is used to control the pore-particle mesostructure and investigate the pore formation mechanism through the variation of residence time in oxygen. This enables the exploitation of the Kirkendall effect at the nanoscale to generate ultrasmall pores in small nanocrystalline iron oxide particles. Detailed structural characterization and quantitative data analysis of complementary high resolution transmission electron microscopy images, X-ray diffractograms, nitrogen sorption isotherms and X-ray absorption spectra provide a consistent comprehensive picture of the hollow nanoparticles from the local to the microstructure. The pore formation mechanism seems to play a key role for β-Fe2O3 polymorph formation.

We describe a versatile reactor system for chemical vapor synthesis of nanoparticles, which enables in situ investigations of high temperature gas phase particle formation and transformation processes by x-ray scattering and x-ray absorption spectroscopy. The system employs an inductively heated hot wall reactor as the energy source to start nanoparticle formation from a mixture of precursor vapor and oxygen. By use of a modular set of susceptor segments, it is especially possible to change solely the residence time of the gas mixture while keeping all other process parameters (temperature, gas flow, pressure) constant. Corresponding time-temperature profiles are supported by computational fluid dynamics simulations. The operation of the system is demonstrated for two example studies: tin oxide nanoparticle formation studied by small angle x-ray scattering and iron oxide nanoparticle formation by x-ray absorption spectroscopy.

The steady and stoichiometric delivery of metal-organic precursor mixtures is essential for the production of complex, functional nanomaterials in the gas phase. Chemical vapor synthesis (CVS) is a corresponding process which enables the production of complex oxide nanoparticles such as perovskites. While there exist a vast number of compositions that form perovskite structures, many technically relevant materials consist of transition metals and lanthanides. Their corresponding metal organic precursors often deviate significantly in their thermal behavior, resulting in a challenging delivery of precursors to the reactor. One suitable method for precursor delivery is flash evaporation by an infrared laser, where a mixture of solid precursors is instantly sublimed. Using flash evaporation, the stoichiometry of the generated vapor corresponds to the composition of precursors in the solid mixture. In this study, we present an alternative flash evaporation system based on a marking laser which rapidly scans a focused infrared beam across a precursor powder bed. By focusing the beam, higher energy densities are reached, compared to existing systems while a large area powder bed is repeatedly scanned and sublimed. Fourier-transform infrared spectroscopy (FTIR) measurements confirm the decomposition-free sublimation of precursor mixtures. Furthermore, we confirm the successful precursor delivery by the synthesis of LaFeO 3 nanoparticles with an average crystallite size of 5.3 nm. The structure of the ensemble of nanoparticles is examined using X-ray diffraction (XRD) and Rietveld refinement, transmission electron microscopy (TEM), selected area diffraction (SAED), and extended X-ray absorption fine structure (EXAFS) at the Fe-K edge analyzed by reverse Monte Carlo (RMC) analysis.