TM LDH Meets Birnessite: A 2D‐2D Hybrid Catalyst with Long‐Term Stability for Water Oxidation at Industrial Operating Conditions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Efficient noble‐metal free electrocatalyst for oxygen evolution reaction (OER) is critical for large‐scale hydrogen production via water splitting. Inspired by Nature's oxygen evolution cluster in photosystem II and the highly efficient artificial OER catalyst of NiFe layered double hydroxide (LDH), we designed an electrostatic 2D‐2D assembly route and successfully synthesized a 2D LDH(+)‐Birnessite(−) hybrid. The as‐constructed LDH(+)‐Birnessite(−) hybrid catalyst showed advanced catalytic activity and excellent stability towards OER under a close to industrial hydrogen production condition (85 °C and 6 M KOH) for more than 20 h at the current densities larger than 100 mA cm −2 . Experimentally, we found that besides the enlarged interlayer distance, the flexible interlayer NiFe LDH(+) also modulates the electronic structure of layered MnO 2 , and creates an electric field between NiFe LDH(+) and Birnessite(−), wherein OER occurs with a greatly decreased overpotential. DFT calculations confirmed the interlayer LDH modulations of the OER process, attributable to the distinct electronic distributions and environments. Upshifting the Fe‐3d orbitals in LDH promotes electron transfer from the layered MnO 2 to LDH, significantly boosting up the OER performance. This work opens a new way to fabricate highly efficient OER catalyst for industrial water oxidation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.004 | 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 it