ABSTRACT
Na4Fe3(PO4)2(P2O7) is regarded as a promising cathode material for sodium-ion batteries due to its affordability, non-toxic nature, and excellent structural stability. However, its electrochemical performance is hampered by its poor electronic conductivity. Meanwhile, most of the previous studies utilized spray-drying and sol-gel methods to synthesize Na4Fe3(PO4)2(P2O7), and the large-scale synthesis of the cathode material is still challenging. This study presents a composite cathode material, Na4Fe2.94Al0.04(PO4)2(P2O7)/C, prepared via a straightforward ball-milling technique. By substituting Al3+ minimally into the Fe2+ site of NFPP, Fe defects are introduced into the structure, hindering the formation of NaFePO4 and thereby enhancing Na-ion diffusion kinetics and conductivity. Additionally, the average length of AlO bonds (2.18 Å) is slightly smaller than that of FeO bonds (2.19 Å), contributing to the superior structural stability. The smaller ionic radii of Al3+ induce lattice contraction, further enhancing the structural stability. Moreover, the surface of material particles is coated with a thin layer of carbon, ensuring excellent electrical conductivity and outstanding structure stability. As a result, the Na4Fe2.94Al0.04(PO4)2(P2O7)/C cathode exhibits excellent electrochemical performance, leading to high discharge capacity (128.1 mAh g-1 at 0.2 C), outstanding rate performance (98.1 mAh g-1 at 10 C), and long cycle stability (83.7 % capacity retention after 3000 cycles at 10 C). This study demonstrates a low-cost, ultra-stable, and high-rate cathode material prepared by simple mechanical activation for sodium-ion batteries which has application prospects for large-scale production.
ABSTRACT
Ottawa sand and Angular sand consist of particles with distinct shapes. The x-ray computed tomography (XCT) image stacks of their in-situ confined compressive testings are provided in this paper. For each image stack, a contact network, a thermal network and a network feature - edge betweenness centrality - of each edge in the networks are also provided. The readers can use the image data to construct digital sands with applications of (1) extracting microstructural parameters such as particle size, particle shape, coordination number and more network features; (2) analysing mechanical behaviour and transport processes such as fluid flow, heat transfer and electrical conduction using either traditional simulation tools such as finite element method and discrete element method or newly network models which could be built based on the network files available here.
