journal article·2024-06-11

Improving Li-Ion Anodes with Systematic Elemental Doping in Titanium Niobate

J. Michael Sieffert, Christopher J. Lang, Sophia Frazzini, Nooshin Zeinali Galabi, Stephanie Bazylevych, Paloma López Sarmiento, Marzieh Abdolhosseini, Eric McCalla

Chemistry of Materials· Volume 36· Issue 11
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Abstract

Lithium-ion batteries for high-power applications have become an increasingly important area of development as these devices have been used in implantable medical devices, where extreme safety and long lifetimes are essential. TiNb 2 O 7 has emerged as a promising candidate to replace the current industrial standard Li 4 Ti 5 O 12 as a safe high-power anode. In this study, we use combinatorial methods to screen the effects of 52 different dopants (M) in the composition (TiNb 2 ) 0.98 M 0.06 O 7 with 52 unique elemental dopants. The materials were studied with high throughput by X-ray diffraction and cyclic voltammetry to reveal the performance of the doped materials. Structural analysis revealed a change in the lattice parameters dependent on the substituent present, and some extremely large dopants were able to partially substitute into the materials. Several doped materials, particularly with large dopants, show excellent discharge capacities of 326.7 mAh g –1 at room temperature, an improvement of over 20% over the undoped material despite moderate doping levels (2% of the metals). Many of the doped TNO samples show excellent extended cycling, especially at 37 °C. The dramatic improvements with the addition of large dopants (most of which are electrochemically inactive) are attributed to distortions in the local structure improving the Li diffusion paths, thereby enabling higher capacities, and establish a new design principle in optimizing these safe anodes.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advancements in Battery Materials · Semiconductor materials and devices · Advanced Battery Materials and Technologies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Chemistry, McGill University, Montreal H3A 0B8, Canada

Funding

Natural Sciences and Engineering Research Council of Canada

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