High Performance Pseudocapacitors Based on Multicomponent Transition Metal Oxides By Local Distortion of Oxygen Octahedra
Bibliographic record
Abstract
As pseudo-capacitors store the charge based on the dual (‘faradaic’ and ‘capacitive’) modes, they have the advantages of both ultracapacitors and rechargeable batteries.[1] One of the main directions in pseudo-capacitor research in the past decade has been the integration of nanostructured metal oxides, hydroxides, and chalcogenides with conductive carbon nanomaterials,[2] such as graphene and carbon nanotubes. Nanostructures bring the benefits of high rate capability as well as long cycle life related to the improved mechanical stability of active phases, as nanomaterials are better at releasing the strains. The nanostructure effect of metal oxides was verified for a variety of morphologies with diverse transition metals.[3]Nonetheless, a majority of studies have focused solely on the nanostructure effects, and the impact of the TM choice or mixing of multiple TMs on the electrochemical performance has not been examined in depth. Here, we have systematically investigated the impact of multiple TMs, particularly those commonly adopted as pseudo-capacitor active materials: Ni, Co, and Mn. Interestingly, when the three TMs are mixed in equal amounts, the specific capacitance rises far beyond those of their individual cases, indicating a synergistic effect from the TM mixing. A combined experimental and theoretical analysis reveals that the enhanced performance originates from permanent local distortions of [NiO6] octahedra in the presence of aliovalent cations (Co3+ and Mn4+) and transition metal vacancies (V M), among which V M has the largest effect on distorting the nearest neighboring [NiO6] octahedra. The degenerate eg level in Ni2+, the primary redox center for capacitance acquisition, is split via this permanent distortion, thus enabling the energetically more facile redox swing of Ni2+/3+by alleviating the structural variation from a Jahn-Teller effect. This study introduces a new opportunity to improve the electrochemical performance of pseudo-capacitors through the mixing of multiple TM cations. The solid solution mixing of multiple TMs pre-distorts the framework and consequently mitigates Jahn–Teller-type structural variation during the redox reaction, resulting in the significantly wider redox swing of Ni and the larger pseudo-capacitance of the solid solutions. The findings of this study demonstrate the importance of structure-property relation in designing and improving key active materials in emerging energy storage systems. References [1] Simon, P., Gogotsi, Y., Nat. Mater. 2008, 7, 845-854. [2] Yu, G., Hu, L., Liu, N., Wang, H., Vosgueritchian, M., Yang, Y., Cui, Y., Bao, Z., Nano Lett. 2011, 11, 4438-4442 [3] Lu, Q., Chen, J. G. G., Xiao, J. Q., Angew. Chem. Int. Ed. 2013, 52, 1882-1889
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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 | 0.001 |
| Open science | 0.001 | 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".