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: Recently, the maximum a posteriori (MAP) probability rule has been proposed as an objective and quantitative method to detect atom columns and even single atoms from high-resolution high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) images. The method combines statistical parameter estimation and model-order selection using a Bayesian framework and has been shown to be especially useful for the analysis of the structure of beam-sensitive nanomaterials. In order to avoid beam damage, images of such materials are usually acquired using a limited incoming electron dose resulting in a low contrast-to-noise ratio (CNR) which makes visual inspection unreliable. This creates a need for an objective and quantitative approach. The present paper describes the methodology of the MAP probability rule, gives its step-by-step derivation and discusses its algorithmic implementation for atom column detection. In addition, simulation results are presented showing that the performance of the MAP probability rule to detect the correct number of atomic columns from HAADF STEM images is superior to that of other model-order selection criteria, including the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC). Moreover, the MAP probability rule is used as a tool to evaluate the relation between STEM image quality measures and atom detectability resulting in the introduction of the so-called integrated CNR (ICNR) as a new image quality measure that better correlates with atom detectability than conventional measures such as signal-to-noise ratio (SNR) and CNR.

Abstract: In an increasingly complex waste market, market-based policy instruments, such as disposal taxes, can give incentives for sustainable progress while leaving flexibility for innovation. However, implementation of disposal taxes is often criticised by domestic waste handlers that fear to be outcompeted by competitors in other countries. The article discusses three innovative market-based instruments that limit the impact on international competitiveness: Tradable recycling credits, refunded disposal taxes and differentiated disposal taxes. All three instruments have already been implemented for distinct environmental policies in Europe. In order to illustrate how these instruments can be used for waste policy, the literature review is complemented with a case study on shredder residues from metal-containing waste streams in Belgium. The analysis shows that a conventional disposal tax remains the most efficient, simple and transparent instrument. However, if international competition is a significant issue or if political support is weak, refunded and differentiated disposal taxes can have an added value as second-best instruments. Tradable recycling credits are not an appropriate instrument for use in small waste markets with market power. In addition, refunded taxes create similar incentives, but induce lower transactions costs.