Tip‐Enhanced Oxygen Reduction on Pt@Ni Cones via Concentrated Electric and Magnetic Fields
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 oxygen reduction reaction (ORR) is crucial for energy conversion technologies, yet its sluggish kinetics remain a significant challenge. Beyond optimizing the catalyst's intrinsic properties, field effects can also profoundly impact the microenvironment at the catalyst/electrolyte interface, thereby affecting electrocatalytic performance. This study explores the tip‐enhanced ORR by leveraging the coupled effects of electric and magnetic fields at the reaction interface. The Pt‐loaded ferromagnetic Ni cone electrode generates strong localized electric fields that reorganize interfacial water molecules into a more ordered structure. This strengthens hydrogen bonding between the electrolyte and reaction intermediates, which in turn facilitates proton‐coupled electron transfer and accelerates the rate‐limiting *OH desorption into interfacial water matrix. Additionally, the amplified electric fields at tips accelerate OH − electromigration away from the catalyst surface, while the migration current couples with the concentrated magnetic fields near tips to drive strong magnetohydrodynamic flows. These intensified flows effectively enhance O 2 molecule delivery to wider electrode surface and facilitate better OH − product removal, thus improving the overall reaction efficiency. This strategy of concentrating both E/M fields using the field‐effect catalyst optimizes the ORR kinetics at the interface as well as the mass transport dynamics near interface, offering an effective approach for advancing ORR performance.
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 | 0.001 |
| 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) | 0.000 | 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 it