Abstract: The growing concern for the increase of the global warming effects due to anthropogenic activities raises the challenge of finding novel technological approaches to stabilize CO2 emissions in the atmosphere and counteract impinging interconnected issues such as desertification and loss of biodiversity. Biological-CO2 mitigation, triggered through biological fixation, is considered a promising and eco-sustainable method, mostly owing to its downstream benefits that can be exploited. Microorganisms such as cyanobacteria, green algae and some autotrophic bacteria could potentially fix CO2 more efficiently than higher plants, due to their faster growth. Some examples of the potential of biological-CO2 mitigation are reported and discussed in this paper. In arid and semiarid environments, soil carbon sequestration (CO2 fixation) by cyanobacteria and biological soil crusts is considered an eco-friendly and natural process to increase soil C content and a viable pathway to soil restoration after one disturbance event. Another way for biological-CO2 mitigation intensively studied in the last few years is related to the possibility to perform carbon dioxide sequestration using microalgae, obtaining at the same time bioproducts of industrial interest. Another possibility under study is the exploitation of specific chemotrophic bacteria, such as Ralstonia eutropha (or picketii) and related organisms, for CO2 fixation coupled with the production chemicals such as polyhydroxyalkanoates (PHAs). In spite of the potential of these processes, multiple factors still have to be optimized for maximum rate of CO2 fixation by these microorganisms. The optimization of culture conditions, including the optimal concentration of CO2 in the provided gas, the use of metabolic engineering and of dual purpose systems for the treatment of wastewater and production of biofuels and high value products within a biorefinery concept, the design of photobioreactors in the case of phototrophs are some of the issues that, among others, have to be addressed and tested for cost-effective CO2 sequestration.

Abstract: Quantitative atomic resolution annular dark field scanning transmission electron microscopy (ADF STEM) has become a powerful technique for nanoparticle atom-counting. However, a lot of nanoparticles provide a severe characterisation challenge because of their limited size and beam sensitivity. Therefore, quantitative ADF STEM may greatly benefit from statistical detection theory in order to optimise the instrumental microscope settings such that the incoming electron dose can be kept as low as possible whilst still retaining single-atom precision. The principles of detection theory are used to quantify the probability of error for atom-counting. This enables us to decide between different image performance measures and to optimise the experimental detector settings for atom-counting in ADF STEM in an objective manner. To demonstrate this, ADF STEM imaging of an industrial catalyst has been conducted using the near-optimal detector settings. For this experiment, we discussed the limits for atomcounting diagnosed by combining a thorough statistical method and detailed image simulations.