Coventry University

About: Coventry University is a education organization based out in Coventry, United Kingdom. It is known for research contribution in the topics: Population & Higher education. The organization has 4964 authors who have published 12700 publications receiving 255898 citations. The organization is also known as: Lanchester Polytechnic & Coventry Polytechnic.

Genetics of superionic conductivity in lithium lanthanum titanates

Abstract: The self-diffusion of ions is a fundamental mass transport process in solids and has a profound impact on the performance of electrochemical devices such as the solid oxide fuel cell, batteries and electrolysers. The perovskite system lithium lanthanum titanate, La2/3−xLi3xTiO3 (LLTO) has been the subject of much academic interest as it displays very high lattice conductivity for a solid state Li conductor; making it a material of great technological interest for deployment in safe durable mobile power applications. However, so far, a clear picture of the structural features that lead to efficient ion diffusion pathways in LLTO, has not been fully developed. In this work we show that a genetic algorithm in conjunction with molecular dynamics can be employed to elucidate diffusion mechanisms in systems such as LLTO. Based on our simulations we provide evidence that there is a three-dimensional percolated network of Li diffusion pathways. The present approach not only reproduces experimental ionic conductivity results but the method also promises straightforward investigation and optimisation of the properties relating to superionic conductivity in materials such as LLTO. Furthermore, this method could be used to provide insights into related materials with structural disorder.

The Middle Pleistocene deposits of Waverley Wood Pit, Warwickshire, England

Abstract: A complex of channels underlying the Baginton-Lillington Gravel (Baginton Formation) at Waverley Wood Quarry, Warwickshire is described. Fossil pollen and plant macrofossils, Coleoptera, Ostracoda, Mollusca and Mammalia are described from the channel-fill deposits. Consideration of all the evidence allows the identification of four separate stages of channel fill which largely occurred under a cool temperate climate. At the top of Channel 2 evidence for a cold, continental climatic episode can be recognised, suggesting that the whole complex was deposited under a fluctuating climate at the end of a temperate stage. At two levels in the channels human artefacts were recovered confirming the presence of Palaeolithic people in Warwickshire during the deposition of the sediments. Amino-acid geochronology suggests an age within the ‘Cromerian Complex’ Stage for the channels. The small vertebrate and molluscan faunas indicate that the deposits are no older than the latter part of the ‘Cromerian Complex’ Stage of East Anglia. The regional stratigraphic significance of the Waverley Wood succession is outlined.

Rainfall Prediction: A Deep Learning Approach

Abstract: Previous work has shown that the prediction of meteorological conditions through methods based on artificial intelligence can get satisfactory results. Forecasts of meteorological time series can help decision-making processes carried out by organizations responsible of disaster prevention. We introduce an architecture based on Deep Learning for the prediction of the accumulated daily precipitation for the next day. More specifically, it includes an autoencoder for reducing and capturing non-linear relationships between attributes, and a multilayer perceptron for the prediction task. This architecture is compared with other previous proposals and it demonstrates an improvement on the ability to predict the accumulated daily precipitation for the next day.