Switching Optimally Balanced Fe–N Interaction Enables Extremely Stable Energy Storage
Bibliographic record
Abstract
The interaction between electrode materials and charge carriers is one of the central issues dominating underlying energy storage mechanisms. To address the notoriously significant volume changes accompanying intercalation or formation of alloy/compounds, we aim to introduce and utilize a weak, reversible Fe–N interaction during the (de)intercalation of ammonium ions (NH4+) within iron(III) hexacyanoferrate (FeHCF), inspired by manipulating the electrostatic adsorption between N and Fe in the early stages of ammonia synthesis (Bosch‐Harber Process, Chemical Engineering) and steel nitriding processes (Metal Industry). Such strategy of switching well‐balanced Fe–N interaction is confirmed in between the nitrogen of ammonium ions and high‐spin Fe in FeHCF, as observed by using X‐ray absorption spectroscopy. The resulting material provided an extremely stable energy storage (58 mAh g−1 after 10 000 cycles at current density of 1 A g−1) as well as high‐rate performance (23.6 mAh g−1 at current density of 10 A g−1).
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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".