Lithium nitride (Li3N) formation in lithium-mediated electrochemical ammonia synthesis can be enhanced with the right proton donor
Bibliographic record
Abstract
Lithium-mediated electrochemical ammonia synthesis (LiMEAS) hinges on the formation of lithium nitride (Li 3 N) from dissociated nitrogen at a lithium surface. Although proton donors (PDs) are known to influence nitrogen activation, their specific role in promoting Li 3 N formation is still being investigated. Herein, we employ density functional theory (DFT) to examine the effects of 17 PDs on the stability and energetics of Li 3 N formation. We show that in the absence of PD, Li 3 N formation is consistently outcompeted by subsurface N 2 embedding and, in some cases, by surface N 2 adsorption. However, the introduction of PD species yields three distinct outcomes: (i) the PD remains intact during Li 3 N formation, (ii) the PD protonates Li 3 N, or (iii) the PD undergoes structural change. Notably, configurations in which the PD remains intact exhibited greater stability compared to subsurface embedding, driven by PD-induced surface reconstruction. We quantify this reconstruction using a two-layer displacement metric and find a strong correlation between the magnitude of displacement and the system’s overall stability. Further charge analyses show that the enhanced Li 3 N stability correlates with a greater electron transfer to nitrogen. Finally, we link the basicity , acidity and polarity of PD with the results of the formation of nitride , demonstrating that the basicity of PD promotes intact configurations Li 3 N. In contrast, higher acidity and polarity lead to protonation and alteration of PD. These insights pinpoint a region in the Kamlet–Taft β – π space where PDs remain intact and foster stable Li 3 N, informing future strategies to design more efficient LiMEAS systems.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".