Abstract: One of the most challenging and recurring problems when modeling plasmas is the lack of data on the key atomic and molecular reactions that drive plasma processes. Even when there are data for some reactions, complete and validated datasets of chemistries are rarely available. This hinders research on plasma processes and curbs development of industrial applications. The QDB project aims to address this problem by providing a platform for provision, exchange, and validation of chemistry datasets. A new data model developed for QDB is presented. QDB collates published data on both electron scattering and heavy-particle reactions. These data are formed into reaction sets, which are then validated against experimental data where possible. This process produces both complete chemistry sets and identifies key reactions that are currently unreported in the literature. Gaps in the datasets can be filled using established theoretical methods. Initial validated chemistry sets for SF6/CF4/O2 and SF6/CF4/N2/H2 are presented as examples.

Abstract: When studying paintings with active infrared thermography (IRT), minimizing the temperature fluctuations and thermal shock during a measurement becomes important. Under these conditions, it might be beneficial to use lock-in thermography instead of the conventionally used pulse thermography (PT). This study compared the observations made with lock-in thermography (LIT) and pulse phase thermography (PPT) with halogen light excitation. Three distinctly different paintings were examined. The LIT measurements caused smaller temperature fluctuations and, overall, the phase images appeared to have a higher contrast and less noise. However, in the PPT phase images, the upper paint layer was less visible, an aspect which is of particular interest when trying to observe subsurface defects or the structure of the support. The influence of the spectral range of the cameras on the results was also investigated. All measurements were taken with a mid-wave infrared (MWIR) and long wave infrared (LWIR) camera. The results show that there is a significant number of direct reflection artifacts, caused by the use of the halogen light sources when using the MWIR camera. Adding a long-pass filter to the MWIR camera eliminated most of these artifacts. All results are presented in a side-by-side comparison.

Abstract: The present contribution gives a review of recent quantification work of atom displacements, atom site occupations and level of crystallinity in various systems and based on aberration corrected HR(S)TEM images. Depending on the case studied, picometer range precisions for individual distances can be obtained, boundary widths at the unit cell level determined or statistical evolutions of fractions of the ordered areas calculated. In all of these cases, these quantitative measures imply new routes for the applications of the respective materials.

Abstract: We present an efficient method for the quantification of crystalline versus amorphous phase content in mesoporous materials, making use of electron energy loss spectroscopy. The method is based on fitting a superposition of core-loss edges using the maximum likelihood method with measured reference spectra. We apply the method to mesoporous TiO2 samples. We show that the absolute amount of the crystalline phase can be determined with an accuracy below 5%. This method takes also the amorphous phase into account, where standard X-ray diffraction is only quantitative for crystalline phases and not for amorphous phase. (c) 2006 Elsevier B.V.. All rights reserved.

Abstract: Chirality in inorganic nanoparticles and nanostructures has gained increasing scientific interest, because of the possibility to tune their ability to interact differently with left- and right-handed circularly polarized light. In some cases, the optical activity is hypothesized to originate from a chiral morphology of the nanomaterial. However, quantifying the degree of chirality in objects with sizes of tens of nanometers is far from straightforward. Electron tomography offers the possibility to faithfully retrieve the three-dimensional morphology of nanomaterials, but only a qualitative interpretation of the morphology of chiral nanoparticles has been possible so far. We introduce herein a methodology that enables us to quantify the helicity of complex chiral nanomaterials, based on the geometrical properties of a helix. We demonstrate that an analysis at the single particle level can provide significant insights into the origin of chiroptical properties.

Abstract: An important issue in biodiversity valuation is gaining a better understanding of how biodiversity conservation affects economic activities and human welfare. Quantifying the economic benefits of biodiversity for human well-being is not straightforward. Here, we expand the ecosystem service cascade by (i) attributing a methodology to the different steps of the cascade to assess the effects of changes in functional group diversity on economic activities; (ii) including multiple attributes for defining functional diversity and (iii) integrating a dynamic ecological model simulating complex interactions and feedbacks between species with an economic model assessing the effects of changes in functional group diversity for gross revenues. The stepwise methodological framework integrates a production function approach with a market price-based approach in order to investigate the indirect use value of functional group diversity based on the ecological role of species in the ecosystem. The methodology is applied to estimate the relationship between the gross economic value of Chinook salmon (Pacific Northwest, United States) and the diversity of freshwater macroinvertebrates. The results of our analysis emphasize the importance of biological diversity for sustaining ecosystem goods and services. The analysis provides a tractable framework for quantitatively exploring the economic consequences of changes in functional group diversity.

Abstract: It is generally believed that β00 precipitates, rather than β0 precipitates, are the major strengthening precipitates in
aged Al–Mg–Si alloys. The reason for this difference is not well understood. To clarify this, two samples of the
same Al–Mg–Si alloy but with different aging states were prepared. The under-aged sample only contains nanoprecipitates
of the β00 type, while the peak-aged one contains nearly equal volumes of β00 and β0 precipitates. We
have, for the first time, separated the strengthening effect of the contribution from βʺ and βʹ precipitates,
respectively, by an indirect approach based on high-precision measurements of volume fractions, number densities,
sizes, proportions of the precipitates, their lattice strains, the composition and grain size of the matrix. The
β0 precipitates, which take 45.6% of the total precipitate volume in the peak-aged sample, contribute to the entire
precipitation strengthening by only 31.6%. The main reason why they are less useful compared to β00 precipitates
has been found to be associated with their smaller lattice strains relative to the matrix, which is 0.99% versus
2.10% (for β00 ).

Abstract: Nanoscience and nanotechnologies are of immense importance across many fields of science and for numerous practical applications. In this context, scanning transmission electron microscopy (STEM) and 4D-STEM are among the most powerful characterization methods at the atomic scale. Annular dark-field (ADF)-STEM can be used to quantify atomic structures in 3D by counting atoms based on a single projection image. In 4D-STEM a full diffraction pattern is recorded at each scan step, which enables more dose efficient imaging and the utilization of various advanced imaging modalities, which can however be complex and slow. Both, STEM and 4D-STEM suffer from noise and distortions. In the first section of this work the most important of these distortions are discussed and it is shown how image restoration with a dedicated convolutional neural network (CNN) can be beneficial for atomic structure quantifications in ADF-STEM. In the second part, a new 4D-STEM imaging method real-time-integrated-centre-of-mass (riCOM) is introduced, which is a very dose-efficient and fast algorithm that enables unprecedented live-imaging capabilities for 4D-STEM. It is based on the integrated centre-of-mass approach, but is reformulated with variable integration ranges and optional filters, which allows for a tunable contrast transfer function. This enables the imaging of light and heavy elements simultaneously at very low doses. In the third part another new 4D-STEM method, coined AIRPI (AI-assisted rapid phase imaging) is introduced, which uses a CNN to retrieve a patch of the specimen's phase image for each scan position, based on the diffraction patterns in the probe's immediate surroundings. This allows also live imaging in principle and surpasses comparable state-of-the-art algorithms in terms of resolution also at low doses. Different atomic columns can be reliably distinguished over a wide range of atomic numbers, enabling a very good image interpretability. Further, AIRPI can recover low frequency image components, which preserves thickness information. This is a unique and important feature which could make quantitative 4D-STEM feasible.

Abstract: Numerical simulations of flow and pollutant dispersion in urban environments have the potential to support design and policy decisions that could reduce the population's exposure to air pollution. Reynolds-averaged Navier-Stokes simulations are a common modeling technique for urban flow and dispersion, but several sources of uncertainty in the simulations can affect the accuracy of the results. The present study proposes a method to quantify the uncertainty related to variability in the inflow boundary conditions. The method is applied to predict flow and pollutant dispersion in downtown Oklahoma City and the results are compared to field measurements available from the Joint Urban 2003 measurement campaign. Three uncertain parameters that define the inflow profiles for velocity, turbulence kinetic energy and turbulence dissipation are defined: the velocity magnitude and direction, and the terrain roughness length. The uncertain parameter space is defined based on the available measurement data, and a non-intrusive propagation approach that employs 729 simulations is used to quantify the uncertainty in the simulation output. A variance based sensitivity analysis is performed to identify the most influential uncertain parameters, and it is shown that the predicted tracer concentrations are influenced by all three uncertain variables. Subsequently, we specify different probability distributions for the uncertain inflow variables based on the available measurement data and calculate the corresponding means and 95% confidence intervals for comparison with the field measurements at 35 locations in downtown Oklahoma City. (C) 2017 Elsevier Ltd. All rights reserved.

Abstract: The rate, selectivity and efficiency of plasma-based conversion processes is strongly affected by nonequilibrium phenomena. High concentrations of vibrationally excited molecules are such a plasma-induced effect. It is frequently assumed that vibrationally excited molecules are important in plasma catalysis because their presence lowers the apparent activation energy of dissociative chemisorption reactions and thus increases the conversion rate. A detailed atomic-level understanding of vibrationally stimulated catalytic reactions in the context of plasma catalysis is however lacking. Here, we couple a recently developed statistical model of a plasma-induced vibrational nonequilibrium to molecular dynamics simulations, enhanced sampling methods, and machine learning techniques. We quantify the impact of a vibrational nonequilibrium on the dissociative chemisorption barrier of H2 and CH4 on nickel catalysts over a wide range of vibrational temperatures. We investigate the effect of surface structure and compare the role of different vibrational modes of methane in the dissociation process. For low vibrational temperatures, very high vibrational efficacies are found, and energy in bend vibrations appears to dominate the dissociation of methane. The relative impact of vibrational nonequilibrium is much higher on terrace sites than on surface steps. We then show how our simulations can help to interpret recent experimental results, and suggest new paths to a better understanding of plasma catalysis.

Abstract: The size, shape and distribution of Ni4Ti3 precipitates in Ni51Ti49 single crystals annealed under stress-free and 〈1 1 1〉B2 compressive conditions are studied via focused ion beam/scanning electron microscopy slice-and-view. The precipitates in the stress-free material grow in autocatalytic pockets with larger size, lower number density, flatter shape and larger inter-particle distance than in the compressed material. Nevertheless, a new quantification method called water penetration reveals that, due to the precipitate alignment, martensite can grow more easily in the compressed material perpendicular to the compression direction.