Secondary Structure in Enzyme‐Inspired Polymer Catalysts Impacts Water Oxidation Efficiency
Bibliographic record
Abstract
Protein structure plays an essential role on their stability, functionality, and catalytic activity. In this work, the interplay between the β-sheet structure and its catalytic implications to the design of enzyme-inspired materials is investigated. Here, inspiration is drawn from the active sites and β-sheet rich structure of the highly efficient multicopper oxidase (MCO) to engineer a bio-inspired electrocatalyst for water oxidation utilizing the abundant metal, copper. Copper ions are coordinated to poly-histidine (polyCuHis), as they are in MCO active sites. The resultant polyCuHis material effectively promotes water oxidation with low overpotentials (0.15 V) in alkaline systems. This activity is due to the 3D structure of the poly-histidine backbone. By increasing the prevalence of β-sheet structure and decreasing the random coil nature of the polyCuHis secondary structures, this study is able to modulates the electrocatalytic activity of this material is modulated, shifting it toward water oxidation. These results highlight the crucial role of the local environment at catalytic sites for efficient, energy-relevant transformations. Moreover, this work highlights the importance of conformational structure in the design of scaffolds for high-performance electrocatalysts.
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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".