Diffusion Measurements of Mg in High Capacity Thiospinel Mg<sub>x</sub>Ti<sub>2</sub>S<sub>4</sub>
Bibliographic record
Abstract
The demand for smaller batteries capable of storing the same amount of energy as conventional Li-ion technology has led to the pursuit of several new technologies including rechargeable Mg batteries. Mg metal is attractive as a negative electrode material because it has a higher volumetric capacity density (3833 mAh/mL) than Li metal (2062 mAh/mL), is the 8 th most abundant element in the earth’s crust, is safe to handle in ambient atmosphere, and can be electrodeposited (charged) without the formation of dendrites. 1 The seminal work by Aurbach et al. in 2000 2 established an electrolyte and a positive electrode material, the Chevrel phase (Mo 6 S 8 ), that was paired with Mg metal to form the first rechargeable Mg battery. Mg 2+ intercalation in host materials is more difficult than that of Li + or Na + , displaying lower ion mobility in solid oxide hosts 3 and a probable higher desolvation energy penalty. 4 No further positive electrode materials with both notable capacity and cycle life have been demonstrated since the Chevrel phase, until now. In this presentation, we will demonstrate that the thiospinel Ti 2 S 4 reversibly intercalates Mg 2+ with a 2 nd cycle capacity of about 165 mAh/g, which drops to only 140 mAh/g after 40 cycles at C/10 as shown in Figure 1. Of crucial scientific importance is that Ti 2 S 4 provides a second example of a material that supports facile Mg 2+ diffusion, which could help elucidate why Mg 2+ intercalation is so difficult in other potential cathode materials. In exploring Mg 2+ diffusion, the first step is to measure the chemical diffusion coefficient, D. The galvanostatic intermittent titration technique (GITT) 5 is a versatile method of carrying this out for an intercalant like Mg 2+ if a reliable cell can be constructed that has a long enough diffusion length to produce a linear potential vs time response reflecting Fick’s laws of diffusion. Figure 2 shows a typical GITT experiment on thiospinel Mg x Ti 2 S 4 , which displays the required potential vs time response. This talk will elaborate on the results of the diffusion measurements we have performed and compare those results to theory. References J. Muldoon, C. B. Bucur, and T. Gregory. Chem. Rev. 114 , 11683-11720 (2014). D. Aurbach, Z. Lu, A. Schechter, Y. Gofer, H. Gizbar, R. Turgeman, Y. Cohen, M. Moshkovich and E. Levi. Nature 407 , 724-727 (2000). E. Levi, Y. Gofer, and D. Aurbach. Chem. Mater. 22 , 860-868 (2010). L. F. Wan, B. R. Perdue, C. A. Apblett and D. Prendergast. Chem. Mater. 27 , 5932-5940 (2015). W. Weppner and R. A. Huggins. Solid-State Science and Technology 124 , 1569-1578 (1977). Figure 1
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".