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

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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Bibliographic Details
Main Authors: Claudio Ronchetti, Sara Marchio, Francesco Buonocore, Simone Giusepponi, Sergio Ferlito, Massimo Celino
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Batteries
Subjects:
DFT calculations
neural networks
machine learning
electrochemical energy storage
Na-ion
high-throughput calculations
Online Access:https://www.mdpi.com/2313-0105/10/12/431
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