Proton Donors Influence Nitrogen Adsorption in Lithium-Mediated Electrochemical Ammonia Synthesis
Bibliographic record
Abstract
Lithium-mediated electrochemical ammonia synthesis (LiMEAS) has recently shown promise toward efficient electrochemical ammonia production. This process relies on the formation of a lithium nitride film which is subsequently protonated to release ammonia. Designing the electrolyte for this technology requires the selection of a proton donor. In this work, we perform a first-principles analysis to investigate the initial step of nitride formation considering 30 different proton donors (PD). As a baseline, modeling nitrogen on a lithium surface without a PD, we observe that N 2 does not spontaneously dissociate on the lithium surface. However, explicitly introducing a PD into the system results in five unique recurring nitrogen configurations on the lithium slab: (1) embedded, (2) adsorbed, (3) standing, (4) buried, and (5) transferred states. We show that these PD-induced states possess an elongated N–N bond and adsorb more strongly on lithium. Using charge analysis, we show that the charge transferred onto these states strongly correlates with the change in their bond length, a crucial parameter for nitrogen dissociation. These results suggest a more involved role of the PD in the initial stages of nitride formation, and motivate greater consideration for their impact on the LiMEAS pathway.
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".