Data · dataset · 2026
The data of the article "Density Functional Theory Computation of Mo-adsorbed Two-simensional Boron-nitrogen Monolayers for Nitrogen Reduction Reaction"
Listed in ScienceDB
Electrocatalytic nitrogen reduction reaction (NRR) is regarded as a promising route for sustainable ammonia synthesis, but developing highly active and selective catalysts remains a critical challenge.
Description
In this work, the density functional theory calculations were performed to investigate the NRR performance of Mo-adsorbed B2N, B3N and B4N monolayers. The strong interaction between Mo and its substrate ensures the good stability, as reflected by the binding energies of –8.39, –5.91 and –6.75 eV for Mo-adsorbed B2N, B3N and B4N monolayers, respectively.
Furthermore, such The adsorbed Mo sites are able to activate the N2 molecule, elongating the N≡N bond length from 1.108 Å in the gas phase to 1.128, 1.132 and 1.132 Å on Mo-B2N, Mo-B3N and Mo-B4N, respectively. Free energy profiles analysis reveals that, the thermodynamic barriers are 1.21, 1.07 and 0.61 eV for Mo-B2N, Mo-B3N and Mo-B4N, with Mo-B4N exhibiting the highest activity. This trend clearly demonstrates that the Mo reactivity is well-tuned by its coordination.
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Furthermore, the electronic structure analysis, shows a relation between the strength of N≡N bond and the thermodynamic energy, wherein a weaker strength of N≡N bond indicates a better NRR activity. Mo-B4N material also exhibits a high thermodynamic stability, as reflected by the robustness of the structural rigidity wherein no structural collage is observed under the room temperature of 300 K. Therefore, Mo-B4N is expected to be an active and durable catalyst fot the NRR.
This study provides theoretical guidance for the design of NRR electrocatalysts and proposes viable candidate systems for experimental synthesis.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.jim.00043 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Density functional theory 75%
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.jim.00043 | 9 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[method].local:method:dft | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |