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Materials that undergo ion-insertion coupled electron transfer are important for energy storage, energy conversion, and optoelectronics applications. Cyclic voltammetry is a powerful technique to understand electrochemical kinetics. However, the interpretation of the kinetic behavior of ion insertion electrodes with analytical solutions developed for ion blocking electrodes has led to confusion about their rate-limiting behavior. The purpose of this manuscript is to demonstrate that the cyclic voltammetry response of thin film electrode materials undergoing solid-solution ion insertion without significant Ohmic polarization can be explained by well-established models for finite diffusion. To do this, we utilize an experimental and simulation approach to understand the kinetics of Li⁺insertion-coupled electron transfer into a thin film material (Nb₂O₅). We demonstrate general trends for the peak current vs scan rate behavior, with the latter parameter elevated to an exponent between limiting values of 1 and 0.5, depending on the solid-state diffusion characteristics of the film (diffusion coefficient, film thickness) and the experiment timescale (scan rate). We also show that values < 0.5 are possible depending on the cathodic potential limit. Our results will be useful to fundamentally understand and guide the selection and design of intercalation materials for multiple applications.

 

Branch lengths and topology of a species tree are essential in most downstream analyses, including estimation of diversification dates, characterization of selection, understanding adaptation, and comparative genomics. Modern phylogenomic analyses often use methods that account for the heterogeneity of evolutionary histories across the genome due to processes such as incomplete lineage sorting. However, these methods typically do not generate branch lengths in units that are usable by downstream applications, forcing phylogenomic analyses to resort to alternative shortcuts such as estimating branch lengths by concatenating gene alignments into a supermatrix. Yet, concatenation and other available approaches for estimating branch lengths fail to address heterogeneity across the genome.

In this article, we derive expected values of gene tree branch lengths in substitution units under an extension of the multispecies coalescent (MSC) model that allows substitutions with varying rates across the species tree. We present CASTLES, a new technique for estimating branch lengths on the species tree from estimated gene trees that uses these expected values, and our study shows that CASTLES improves on the most accurate prior methods with respect to both speed and accuracy.

CASTLES is available at https://github.com/ytabatabaee/CASTLES.

 

Massive and fast-evolving news articles keep emerging on the web. To efectively summarize and provide concise insights into real-world events, we propose a new event knowledge extraction task Event Chain Mining in this paper. Given multiple documents abouta super event, it aims to mine a series of salient events in temporal order. For example, the event chain of super event Mexico Earthquake in 2017 is {earthquake hit Mexico, destroy houses, kill people,block roads}. This task can help readers capture the gist of textsquickly, thereby improving reading efciency and deepening text comprehension. To address this task, we regard an event as a cluster of diferent mentions of similar meanings. In this way, we can identify the diferent expressions of events, enrich their semantic knowledge and replenish relation information among them. Taking events as the basic unit, we present a novel unsupervised framework, EMiner. Specifcally, we extract event mentions from texts and merge them with similar meanings into a cluster as a single event. By jointly incorporating both content and commonsense, essential events are then selected and arranged chronologically to form an event chain. Meanwhile, we annotate a multi-document benchmark to build a comprehensive testbed for the proposed task. Extensive experiments are conducted to verify the efectiveness of EMiner in terms of both automatic and human evaluations.