Study of Cathode Materials for Na-Ion Batteries: Comparison Between Machine Learning Predictions and Density Functional Theory Calculations

Energy storage technologies have experienced significant advancements in recent decades, driven by the growing demand for efficient and sustainable energy solutions. The limitations associated with lithium’s supply chain, cost, and safety concerns have prompted the exploration of alternative battery...

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Autors principals:	Claudio Ronchetti, Sara Marchio, Francesco Buonocore, Simone Giusepponi, Sergio Ferlito, Massimo Celino
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2024-12-01
Col·lecció:	Batteries
Matèries:	DFT calculations neural networks machine learning electrochemical energy storage Na-ion high-throughput calculations
Accés en línia:	https://www.mdpi.com/2313-0105/10/12/431
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