Selection Rules of Transition Metal Dopants for Prussian Blue Analogs Enabling Highly Reversible Sodium Storage
Bibliographic record
Abstract
Abstract Rational element doping is demonstrated as an effective strategy to optimize crystal stability and enhance the electronic conductivity of Prussian blue analogs (PBAs) to achieve a satisfactory sodium storage performance. However, unraveling the dopant selection principles is still a big challenge. Herein, the integrated crystal orbital Hamilton population (ICOHP) function is adopted to evaluate the strength of chemical bonds of N‐transition metals (N‐TM) and guide the dopant selection. Among the series of ICOHP values for N‐TM (TM = Mn, Fe, Co, Ni, Cu, Zn), the Cu─N bond exhibits the lowest ICOHP value, which indicates that Cu doping can improve the stability of PBAs compared to other dopants. Experimentally, among TM‐substituted Fe‐based PBAs (TMFeHCFs), the as‐prepared sample with 20 at.% Cu doping (CuFeHCF‐2) exhibits the best cycling performance, with a capacity retention of 83.5% after 400 cycles at 1 C, which is consistent with the theoretical calculation results. In addition, in situ XRD and in situ, Raman reveal a highly reversible monoclinic‐cubic two‐phase conversion and redox‐active pairs, respectively. This study provides valuable guidelines for dopant selection to enhance the performance of PBAs cathodes.
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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 | 0.000 | 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 | 0.000 | 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".