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Dissertation
Mémoire, Partim B: OPTIMIZATION OF SODIUM VANADATE (NVO) AS CATHODE MATERIAL FOR ZINC-ION BATTERIES
Authors: --- --- --- ---
Year: 2021 Publisher: Liège Université de Liège (ULiège)

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Abstract

In this paper, the optimization of sodium vanadate (NVO) as cathode material for zinc-ion batteries (ZIBs) and the improvement of the material's synthesis are reported. Following the convincing capacities obtained for ZIBs using vanadium pentoxide (V₂O₅) as a cathode material, it is tried to further enhance the latter’s electrochemical performances through the insertion of sodium ions into the crystallographic structure of V₂O₅. Acting as stabilizing pillars, the added sodium ions allow NVO cathode material to reach extremely high cycling numbers without a considerable loss of capacity. Special attention is paid to the ecological aspect of the synthesizing method, as ZIBs are considered as being a sustainable and eco-friendly alternative to LIBs.


Book
Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS
Authors: --- --- ---
Year: 2021 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

This book is based on Special Issue "Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS" from early 2020 to 2021. This book includes seven papers related to the application of artificial intelligence, machine learning and deep learning algorithms using remote sensing and GIS techniques in urban areas.


Book
Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS
Authors: --- --- ---
Year: 2021 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

This book is based on Special Issue "Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS" from early 2020 to 2021. This book includes seven papers related to the application of artificial intelligence, machine learning and deep learning algorithms using remote sensing and GIS techniques in urban areas.


Book
Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS
Authors: --- --- ---
Year: 2021 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

This book is based on Special Issue "Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS" from early 2020 to 2021. This book includes seven papers related to the application of artificial intelligence, machine learning and deep learning algorithms using remote sensing and GIS techniques in urban areas.

Keywords

Environmental science, engineering & technology --- groundwater potential --- specific capacity --- machine learning --- boosted tree --- ensemble models --- prototype selection --- river pollution --- supervised classification --- WSN --- probabilistic method --- Monte Carlo simulation --- physical slope model --- Mt. Umyeon landslides --- Seoul --- synthetic aperture radar --- land subsidence --- GIS --- time-series --- Jakarta --- land subsidence susceptibility mapping --- time-series InSAR --- StaMPS processing --- seismic vulnerability map --- DPM method --- Sentinel-1 --- seismic literacy --- neural networks --- urban vegetation --- urban open spaces --- Monterrey Metropolitan Area --- sustainable development --- deep learning --- transfer learning --- artificial intelligence --- remote sensing --- earth observation --- DInSAR --- change detection --- space data science --- groundwater potential --- specific capacity --- machine learning --- boosted tree --- ensemble models --- prototype selection --- river pollution --- supervised classification --- WSN --- probabilistic method --- Monte Carlo simulation --- physical slope model --- Mt. Umyeon landslides --- Seoul --- synthetic aperture radar --- land subsidence --- GIS --- time-series --- Jakarta --- land subsidence susceptibility mapping --- time-series InSAR --- StaMPS processing --- seismic vulnerability map --- DPM method --- Sentinel-1 --- seismic literacy --- neural networks --- urban vegetation --- urban open spaces --- Monterrey Metropolitan Area --- sustainable development --- deep learning --- transfer learning --- artificial intelligence --- remote sensing --- earth observation --- DInSAR --- change detection --- space data science


Book
Advances in Electrochemical Energy Materials
Authors: ---
ISBN: 3039286439 3039286420 Year: 2020 Publisher: MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

Electrochemical energy storage is becoming essential for portable electronics, electrified transportation, integration of intermittent renewable energy into grids, and many other energy and power applications. The electrode materials and their structures, in addition to the electrolytes, play key roles in supporting a multitude of coupled physicochemical processes that include electronic, ionic, and diffusive transport in electrode and electrolyte phases, electrochemical reactions and material phase changes, as well as mechanical and thermal stresses, thus determining the storage energy density and power density, conversion efficiency, performance lifetime, and system cost and safety. Different material chemistries and multiscale porous structures are being investigated for high performance and low cost. The aim of this Special Issue is to report the recent advances in materials used in electrochemical energy storage that encompass supercapacitors and rechargeable batteries.

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