Modulation of Electronic Structure in Kraft Lignin‐Derived Mo Single‐Atom Catalysts for Optimized Electrochemical Oxygen Reduction
Bibliographic record
Abstract
The sluggish kinetics of the oxygen reduction reaction (ORR) remain a major bottleneck for energy conversion systems such as fuel cells and metal-air batteries. Here, the synthesis of molybdenum single-atom catalysts (Mo SACs) derived from abundant and low-cost Kraft lignin is reported. By tuning nitrogen incorporation during carbonization, agglomerated Mo carbide clusters are progressively converted into atomically dispersed Mo active centers anchored on N-doped carbon. Extensive spectroscopic analyses confirm this structural evolution, while density functional theory calculations reveal that the optimized Mo coordination environment downshifts the d-band center, enabling the balanced adsorption of oxygen intermediates and thereby improving the intrinsic ORR activity. Electrochemical measurements demonstrate enhanced half-wave potential, near-four-electron transfer pathway, superior selectivity, and excellent durability, with ≈85% current retention over 50 h. Beyond performance, the use of minimally processed Kraft lignin underscores both the economic and environmental advantages of this approach, offering a scalable and sustainable pathway to practical ORR 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".