Transfer learning aided high-throughput computational design of oxygen evolution reaction catalysts in acid conditions

Sluggish oxygen evolution reaction(OER)in acid conditions is one of the bottlenecks that prevent the wide adoption of proton exchange membrane water electrolyzer for green hydrogen production.Despite recent advancements in developing high-performance catalysts for acid OER,the current electrocatalysts still rely on iridium-and ruthenium-based materials,urging continuous efforts to discover better performance catalysts as well as reduce the usage of noble metals.Pyrochlore structured oxide is a family of potential high-performance acid OER catalysts with a flexible compositional space to tune the electrochemical capabilities.However,exploring the large composition space of pyrochlore compounds demands an imperative approach to enable efficient screening.Here we present a highthroughput screening pipeline that integrates density functional theory calculations and a transfer learning approach to predict the critical properties of pyrochlore compounds.The high-throughput screening recommends three sets of candidates for potential acid OER applications,totaling 61 candidates from 6912 pyrochlore compounds.In addition to 3d-transition metals,p-block metals are identified as promising dopants to improve the catalytic activity of pyrochlore oxides.This work demonstrates not only an efficient approach for finding suitable pyrochlores towards acid OER but also suggests the great compositional flexibility of pyrochlore compounds to be considered as a new materials platform for a variety of applications.

Simulation model of self-organizing pedestrian movement considering following behavior

在本文中一种新的力学模型被引入到社会力模型中,用来仿真相向行人流中的跟随行为。这种跟随行为指的是行人通过接近同向行人以避免与反向行人冲突的行为。新的力学模型类似于一种引力模型,在建模过程中考虑了行人的视野范围、自身的运动状态、被跟随行人的运动状态等因素。我们利用新的力学模型对相向行人流进行了仿真,研究了跟随行为对渠化现象、行人间冲突以及双向通道通行效率的影响。仿真结果表明:跟随行为能促进渠化现象形成,并能起到缓解相向行人流拥堵的作用;跟随行为具有降低相向行人流冲突次数的作用,这种作用在入口流量较低时并不明显,但随着行人流量的升高而增强。跟随行为能够提高双向通道的通行效率,并且跟随行为的强度参数越大通道的通行效率越高。