Nanoscale NEXAFS for Probing TiO2 B Nanoribbons

TiO2 nanostructures exist in different crystallographic phases including brookite, anatase, rutile, and TiO2 amp; 8722;B bronze . Among these, due to its open channel like crystal structure which can enhance ion mobility, the TiO2 amp; 8722;B phase has been reported as an optimal anode material for lithium ion batteries, particularly in the form of nanowires [1]. In view of device applications, where different phases may coexist and TiO2 amp; 8722;B particles may transform to the thermodynamically stable anatase phase, it is important to identify and understand the structural and electronic differences between these two phases. Here we have studied the electronic structure of TiO2 nanoribbons in TiO2 amp; 8722;B and anatase phases using polarization dependent near edge X ray absorption fine structure spectroscopy NEXAFS in the transmission X ray microscope TXM and density functional theory DFT [2,3]. NEXAFS at both the O K edge and the Ti L edge is very sensitive to the local bonding environment in TiO2 based materials and thus provides diagnostic information about the crystal structures and oxidation states. We report the observation of strong linear dichroism in the O K edge spectra of single TiO2 amp; 8722;B nanoribbons. Using DFT calculations we show that the dichroism is a consequence of the directional Ti amp; 8722;O bonding in the monoclinic crystal structur

Tunability of the elastocaloric response in main-chain liquid crystalline elastomers

Materials exhibiting a large caloric effect could lead to the development of a new generation of heat-management technologies that will have better energy efficiency and be potentially more environmentally friendly. The focus of caloric materials investigations has shifted recently from solid-state materials towards soft materials, such as liquid crystals and liquid crystalline elastomers. It has been shown recently that a large electrocaloric effect exceeding 6 K can be observed in smectic liquid crystals. Here, we report on a significant elastocaloric response observed by direct elastocaloric measurements in main-chain liquid crystal elastomers. It is demonstrated that the character of the nematic to paranematic/isotropic transition can be tuned from the supercritical regime towards the first-order regime, by decreasing the density of crosslinkers. In the latter case, the latent heat additionally enhances the elastocaloric response. Our results indicate that a significant elastocaloric response is present in main-chain liquid crystalline elastomers, driven by stress fields much smaller than in solid elastocaloric materials. Therefore, elastocaloric soft materials can potentially play a significant role as active cooling/heating elements in the development of new heat-management devices

The Effects of Twitter Sentiment on Stock Price Returns

Social media are increasingly reflecting and influencing behavior of other complex systems. In this paper we investigate the relations between a well-know micro-blogging platform Twitter and financial markets. In particular, we consider, in a period of 15 months, the Twitter volume and sentiment about the 30 stock companies that form the Dow Jones Industrial Average (DJIA) index. We find a relatively low Pearson correlation and Granger causality between the corresponding time series over the entire time period. However, we find a significant dependence between the Twitter sentiment and abnormal returns during the peaks of Twitter volume. This is valid not only for the expected Twitter volume peaks (e.g., quarterly announcements), but also for peaks corresponding to less obvious events. We formalize the procedure by adapting the well-known "event study" from economics and finance to the analysis of Twitter data. The procedure allows to automatically identify events as Twitter volume peaks, to compute the prevailing sentiment (positive or negative) expressed in tweets at these peaks, and finally to apply the "event study" methodology to relate them to stock returns. We show that sentiment polarity of Twitter peaks implies the direction of cumulative abnormal returns. The amount of cumulative abnormal returns is relatively low (about 1-2%), but the dependence is statistically significant for several days after the events

"Come Together!": Interactions of Language Networks and Multilingual Communities on Twitter

Emerging tools and methodologies are providing insight into the factors that promote the propagation of information in online social networks following significant activities, such as high-profile international social or societal events. This paper presents an extensible approach for analysing how different language communities engage and interact on the social networking platform Twitter via an analysis of the Eurovision Song Contest held in Stockholm, Sweden, in May 2016. By utilising language information from user profiles (N=1,226,959) and status updates (N=7,926,746) to identify and categorise communities, our approach is able to categorise these interactions, as well as construct network graphs to provide further insight on these multilingual communities. The results show that multilingualism is positively correlated with activity whilst negatively correlated with posting in the user’s own language

Chemical Bond Modification upon Phase Transformation of TiO2 Nanoribbons Revealed by Nanoscale X ray Linear Dichroism

Titanium dioxide in the TiO2 amp; 8722;B phase, which can be stabilized in nanoparticle form, is a promising anode material for lithium ion batteries. Here the structural and electronic changes between nanoribbons in TiO2 amp; 8722;B and the thermodynamic stable anatase phase are studied using nanoscale X ray absorption spectroscopy and first principles calculations. The oxygen K edge spectra of the two phases display marked differences which are very well reproduced in the calculations. Strong linear dichroism is observed in single nanoribbons, reflecting preferential O 2p to Ti 3d bond orientation in the low symmetry crystal structures. A simple bond counting model is developed which semiquantitatively accounts for the major dichroic effect. It is shown that the crystal orientation of the nanoparticles can be inferred from the dichroic spectr

Sentiment of Emojis

There is a new generation of emoticons, called emojis, that is increasingly being used in mobile communications and social media. In the past two years, over ten billion emojis were used on Twitter. Emojis are Unicode graphic symbols, used as a shorthand to express concepts and ideas. In contrast to the small number of well-known emoticons that carry clear emotional contents, there are hundreds of emojis. But what are their emotional contents? We provide the first emoji sentiment lexicon, called the Emoji Sentiment Ranking, and draw a sentiment map of the 751 most frequently used emojis. The sentiment of the emojis is computed from the sentiment of the tweets in which they occur. We engaged 83 human annotators to label over 1.6 million tweets in 13 European languages by the sentiment polarity (negative, neutral, or positive). About 4% of the annotated tweets contain emojis. The sentiment analysis of the emojis allows us to draw several interesting conclusions. It turns out that most of the emojis are positive, especially the most popular ones. The sentiment distribution of the tweets with and without emojis is significantly different. The inter-annotator agreement on the tweets with emojis is higher. Emojis tend to occur at the end of the tweets, and their sentiment polarity increases with the distance. We observe no significant differences in the emoji rankings between the 13 languages and the Emoji Sentiment Ranking. Consequently, we propose our Emoji Sentiment Ranking as a European language-independent resource for automated sentiment analysis. Finally, the paper provides a formalization of sentiment and a novel visualization in the form of a sentiment bar