Can Doping of Transition Metal Oxide Cathode Materials Increase Achievable Voltages with Multivalent Metals?
Bibliographic record
Abstract
We investigate from first principles the use of substitutional p-doping as a means to enhance the insertion energies of multivalent metals in transition metal oxides, and therefore the resulting voltages in an electrochemical cell, due to bandstructure modulation. Multivalent and earth-abundant metals such as magnesium or aluminium are attractive candidates to replace lithium in future high-performance secondary batteries with intercalation-type electrodes. Unfortunately, the achievable voltages obtained with this kind of elements still remain uncompetitively low. We study and compare the changes in insertion energetics (voltages) of single- and multivalent metals in semiconducting and insulating transition metal oxides upon substitutional p-doping with different metals, introducing different numbers of hole states. We use a single vanadium pentoxide monolayer as model system to study the effect of p-doping on achievable voltages and deduce general trends for transition metal oxides. Our investigations reveal the formation of n-hole polarons (with n>1) in form of oxygen dimers in p-doped vanadia caused by localized p holes on oxide ions in agreement with previous findings. We find that the oxygen dimer formation has an adverse effect on adsorption energetics compared to the single-hole case without dimerization. We find an analogous oxygen dimerization in other TMOs with oxygen-dominated valence bands like molybdenum trioxide and titanium dioxide, while strained systems like trigonal nickel- or titanium dioxide, or Mott-type systems like monoclinic vanadium dioxide with qualitatively different valence band composition do not exhibit oxygen dimerization with multi-hole doping. Our results demonstrate the advantages and limitations of TMO electrode p-doping and show a path to possible strategies to overcome detrimental effects.
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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 | 0.001 | 0.001 |
| 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".