Combinatorial Screening of Nb<sub>1-x-Y</sub>Ti<sub>x</sub>W<sub>y</sub>O<sub>z</sub> Materials for Li-Ion Battery Anodes
Bibliographic record
Abstract
While much attention in recent years has been given to high performance Li-ion batteries for electrical vehicles, other applications require properties that demand a different set of material considerations such as long lifetimes and extremely high safety and reliability. Anodes for such batteries must be carefully selected to properly achieve these goals. The most commonly industrially utilized anode material, graphite, is not ideal for such applications due to particle fracture and Li dendrite growth at high rates. The current state of the art for high power anode materials is Li4Ti5O12 (LTO) where energy density is sacrificed (theoretical capacity of about 170 mAh/g) in order to operate at potentials where the electrolytes are highly stable. Nb-based oxides have been of interest recently in this regard, with materials such as Nb2TiO7 being considered as industrially relevant for applications where LTO currently dominates. To date in the literature, only 3 compositions have been considered.[1-2] Herein, a wide array of Nb based materials are explored for use as anodes by way of high-throughput experimentation. Over 128 different compositions in the Nb-Ti-W-O pseudoternary space are prepared and characterized with both X-ray diffraction and cyclic voltammetry. Of note, this system features a number of promising solid-solutions that extend well into the ternary system. These compositions derive from crystal structures that are found on both the Nb2O5-WO3 and Nb2O5-TiO2 pseudobinaries, but wide substitutions of the third metal are found to be feasible. This dramatically increases the candidate list for potential anodes. Importantly, the electrochemical performance varies dramatically across the solid solutions. Some ternary compositions feature high discharge capacities of up to 300 mAh/g and high reversibility with 98% capacity retention after 10 cycles. It should be noted that the pseudobinaries have been previously studied in our group with a far lower capacity retention than those found here for some pseudoternary compositions. The rate performance is also found to be outstanding. The improved specific capacity at a comparable potential as LTO makes Nb-W-Ti-O materials highly promising for applications where high rates and safety are paramount. Results presented here will guide further exploration of the rich chemistry available for Nb-based anodes. References: K. J. Griffith, K. M. Wiaderek, G. Cibin, L. E. Marbella and C. P. Grey, Nature, 559, 556–563 (2018) H. Ding, Z. Song, H. Zhang and X. Li, Mater. Today Nano, 11, 100082 (2020).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".