Square-Pyramidal Fe-N4 with Defect-Modulated O-Coordination: Two-Tier Electronic Structure Fine-Tuning for Enhanced Oxygen Reduction
Bibliographic record
Abstract
Engineering the structure of molecularly dispersed 3d-transition metal phthalocyanines is emerging as an effective avenue for developing low-cost and efficient atomically dispersed catalysts (ADC). The strategy of using axial coordination to adjust the electronic structure of the M-N4 active site is effective for improving the performance of the catalysts, but the question to be asked is how to go beyond that. In this study, we propose and demonstrate a two-tier electronic modulation strategy, for the first time using carbon defects to regulate the tuning power of O-coordination, which in turn provides a more desirable electronic modulation on the Fe center of FePc, as compared to that of bare O-coordination. Such FePc-O-defect ADC was achieved using a one-step wet-ball-milling process with ethylene glycol as liquid media. The mechanochemically constructed active site is a square-pyramidal Fe-N4, with the Fe atom located out of the N4-plane towards an axially coordinated O that is singly bonded to graphene at vacancy defects. The resulting FePc-O-defect ADC with defect-modulated O-coordination exhibits excellent ORR activity in alkaline media, in terms of E1/2 and mass-specific activity. Compared to the baseline with bare O-coordination whose performance is already among the best reported nonprecious metal electrocatalysts, the defect-modulated O-coordination further enhanced the halfwave potential and doubled the kinetic current density. Combining with theoretical investigations, we elucidate how defect-modulated O-coordination would adjust the electronic and geometric structures of the Fe center and thus affect the electrocatalytic ORR. Also, resolving the structural configuration of bilayer catalysts with axial coordination is very challenging. The existed literature on bilayer catalyst, which either relies on 2D FT-EXAFS fitting analysis or simply assumes a bilayer configuration to work on, is in our opinion far from unambiguous structural determination. In this study, we differentiate our work from the existed literature, through a systematic structural determination process by comparing the experimental XANES with the simulated ones, based on various structural models predicted by DFT calculations. Such analysis is especially necessary for catalysts with a 3D atomistic arrangement, but only a handful of studies have used this step of analysis (e.g., Nature Catalysis 1, 63-72 (2018)). We believe that our study presents significant advances regarding the atomistic structure of bilayer catalysts with complex axial coordination. Overall, this work demonstrates a conceptually advanced two-tier electronic modulation strategy, through defect-modulated O-coordination, to further optimize the electronic structure of the Fe center in FePc toward ORR. The concept can be extended to modulate the electrocatalytic properties of molecular catalysts toward other electrochemical processes. Moreover, our catalysts were prepared at room temperature using an industrially available ball milling process. Such a facile pyrolysis-free synthetic approach is ready for scaleup with potentially 100 % usage of the FePc and graphene precursors.
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.
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".