Issue 28, 2023

Exploring low-cost high energy NASICON cathodes for sodium-ion batteries via a combined machine-learning, ab initio, and experimental approach

Abstract

Sodium-ion batteries (SIBs) display the essential properties required of a reliable energy-storage device, such as vast availability, good voltage output, and cost-effectiveness. Although initial SIB cathodes delivered a significantly lower capacity than their lithium-ion battery counterparts, new high-capacity cathode materials for SIBs continue to be developed today. This study employed a combined machine-learning (ML), ab initio density functional theory (DFT), and experimental approach to develop low-cost and high-energy cathode materials, i.e. Na3.5MnV0.5Ti0.5(PO4)3 (NMVTP), Na3.5MnV0.5Fe0.5(PO4)3 (NMVFP), and Na3.5MnV0.5Al0.5(PO4)3 (NMVAP). Among these materials, the carbon-coated Na3.5MnV0.5Ti0.5(PO4)3 (NMVTP/C) with the most stable formation energy (−1.99 eV) registered an exceedingly high specific capacity of 133.14 mA h g−1, a satisfactory Na+ (de)insertion voltage of 3.42 V, and a superior energy output of 455 W h kg−1 in the half-cell configuration. NMVTP/C also exhibits a rapid sodium storage capability for 8000 cycles with a capacity retention of 75% at a considerably high current rate of 14C and an impressive rate proficiency of 59.2 mA h g−1 at 17.5C.

Graphical abstract: Exploring low-cost high energy NASICON cathodes for sodium-ion batteries via a combined machine-learning, ab initio, and experimental approach

Supplementary files

Article information

Article type
Paper
Submitted
17 abr 2023
Accepted
26 jun 2023
First published
30 jun 2023

J. Mater. Chem. A, 2023,11, 15518-15531

Exploring low-cost high energy NASICON cathodes for sodium-ion batteries via a combined machine-learning, ab initio, and experimental approach

V. Soundharrajan, M. H. Alfaruqi, G. Alfaza, J. Lee, S. Lee, S. Park, S. Nithiananth, D. T. Pham, J. Hwang and J. Kim, J. Mater. Chem. A, 2023, 11, 15518 DOI: 10.1039/D3TA02291A

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