Spatially Sensitive Electron Energy Loss Spectroscopy

Over the last decade electron energy loss spectroscopy has been increasingly used as a microanalytical technique. Under favorable conditions a spatial resolution better than 1 nm has been achieved. It is therefore possible to obtain spectroscopic information at an atomic scale. Such a spectrum can be used for the investigation of - the elemental composition - defect levels - surface excitations - the fine structure. The spatial sensitivity of such experiments implies, that the initial or the final state of the scattered electrons must have a spatial structure. The theory for the scattering of wave packets will be discussed, focussing on the implications for the attainable spatial sensitivity in energy filtered images as well as in site-specific electron energy loss spectroscopy

Interaction between oxygen activity of Fe2O3 doped soda-lime-silica glass melts and physically dissolved oxygen

The oxidation state of molten soda-lime-silica glass was studied by an electrochemical oxygen-sensor, based on an yttria-stabilized zirconia solid electrolyte. It is shown that the iron concentration of the glass melt influences the extent of oxygen activity variation during cooling. If the iron concentration is 0.2 mol% Fe2O3 or less, the redox ratio [Fe3+]/[Fe2+] cannot be assumed to be independent of temperature because the redox equilibrium is shifted by the reactivity of physically dissolved oxygen

Disruption of Individual Mobility Ahead? A Longitudinal Study of Risk and Benefit Perceptions of Self-Driving Cars on Twitter

In this paper, we address the question if there is a disruption of individual mobility by self-driving cars ahead. In order to answer this question, we take the user perspective and conduct a longitudinal study of social media data about self-driving cars from Twitter. The study analyzes 601,778 tweets from March 2015 to July 2016. We use supervised machine learning classification to extract relevant information from this huge amount of unstructured text. Based on the classification, we analyze how risk and benefit perceptions of self-driving cars develop over time, and how they are influenced by certain events. Based on the perceived risks and benefits, we draw conclusions for the acceptance of self-driving cars. Our study shows that a disruptive innovation of self-driving cars is not likely as risk and benefit perception issues indicate a lack of acceptance. We provide suggestions for improving the acceptance of self-driving cars

Using the Default Option Bias to Influence Decision-Making While Driving

Gaining a better understanding of human–computer interaction in multiple-goal environments, such as driving, is critical as people increasingly use information technology to accomplish multiple tasks simultaneously. Extensive research shows that decision biases can be utilized as effective cues to guide user interaction in single-goal environments. This article is a first step toward understanding the effect of decision biases in multiple-goal environments. This study analyzed data from a field experiment during which a comparison was made between drivers’ decisions on parking lots in a single-goal environment and drivers’ decisions in a multiple-goal environment when being exposed to the default option bias. The article shows that the default option bias is effective in multiple-goal environments. The results have important implications for the design of human–computer interaction in multiple-goal environments

Binding Energy Referencing for XPS in Alkali Metal-Based Battery Materials Research (II): Application to Complex Composite Electrodes

X-ray photoelectron spectroscopy (XPS) is a key method for studying (electro-)chemical changes in metal-ion battery electrode materials. In a recent publication, we pointed out a conflict in binding energy (BE) scale referencing at alkali metal samples, which is manifested in systematic deviations of the BEs up to several eV due to a specific interaction between the highly reactive alkali metal in contact with non-conducting surrounding species. The consequences of this phenomenon for XPS data interpretation are discussed in the present manuscript. Investigations of phenomena at surface-electrolyte interphase regions for a wide range of materials for both lithium and sodium-based applications are explained, ranging from oxide-based cathode materials via alloys and carbon-based anodes including appropriate reference chemicals. Depending on material class and alkaline content, specific solutions are proposed for choosing the correct reference BE to accurately define the BE scale. In conclusion, the different approaches for the use of reference elements, such as aliphatic carbon, implanted noble gas or surface metals, partially lack practicability and can lead to misinterpretation for application in battery materials. Thus, this manuscript provides exemplary alternative solutions