Search Engine Drives the Evolution of Social Networks

The search engine is tightly coupled with social networks and is primarily designed for users to acquire interested information. Specifically, the search engine assists the information dissemination for social networks, i.e., enabling users to access interested contents with keywords-searching and promoting the process of contents-transferring from the source users directly to potential interested users. Accompanying such processes, the social network evolves as new links emerge between users with common interests. However, there is no clear understanding of such a "chicken-and-egg" problem, namely, new links encourage more social interactions, and vice versa. In this paper, we aim to quantitatively characterize the social network evolution phenomenon driven by a search engine. First, we propose a search network model for social network evolution. Second, we adopt two performance metrics, namely, degree distribution and network diameter. Theoretically, we prove that the degree distribution follows an intensified power-law, and the network diameter shrinks. Third, we quantitatively show that the search engine accelerates the rumor propagation in social networks. Finally, based on four real-world data sets (i.e., CDBLP, Facebook, Weibo Tweets, P2P), we verify our theoretical findings. Furthermore, we find that the search engine dramatically increases the speed of rumor propagation.Comment: 9 pages, 11 figure

Bond-Order Time Series Analysis for Detecting Reaction Events in Ab Initio Molecular Dynamics Simulations.

Ab initio molecular dynamics is able to predict novel reaction mechanisms by directly observing the individual reaction events that occur in simulation trajectories. In this article, we describe an approach for detecting reaction events from simulation trajectories using a physically motivated model based on time series analysis of ab initio bond orders. We found that applying a threshold to the bond order was insufficient for accurate detection, whereas peak finding on the first time derivative resulted in significantly improved accuracy. The model is trained on a reference set of reaction events representing the ideal result given unlimited computing resources. Our study includes two model systems: a heptanylium carbocation that undergoes hydride shifts and an unsaturated iron carbonyl cluster that features CO ligand migration and bridging behavior. The results indicate a high level of promise for this analysis approach to be used in mechanistic analysis of reactive AIMD simulations more generally

Room-Temperature Processing of Inorganic Perovskite Films to Enable Flexible Solar Cells

Inorganic lead halide perovskite materials have attracted great attention recently due to their potential for greater thermal stability compared to hybrid organic perovskites. However, the high processing temperature to convert from the non-perovskite phase to cubic perovskite phase in many of these systems has limited their application in flexible optoelectronic devices. Here, we report a room temperature processed inorganic PSC based on CsPbI2Br as the light harvesting layer. By combing this composition with key precursor solvents, we show that the inorganic perovskite film can be prepared by the vacuum-assist method under room temperature conditions in air. Unencapsulated devices achieved the power conversion efficiency up to 8.67% when measured under 1-sun irradiation. Exploiting this room temperature process, flexible inorganic PSCs based on an inorganic metal halide perovskite material is demonstrated.Comment: 23 pages, 4 figures, and supplemental informatio