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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Bibliografiska uppgifter

Huvudupphov:	Claudio Ronchetti, Sara Marchio, Francesco Buonocore, Simone Giusepponi, Sergio Ferlito, Massimo Celino
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	MDPI AG 2024-12-01
Serie:	Batteries
Ämnen:	DFT calculations neural networks machine learning electrochemical energy storage Na-ion high-throughput calculations
Länkar:	https://www.mdpi.com/2313-0105/10/12/431
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