Synthesis of a Stable Metallic Niobium Oxide Molecular Sieve and Subsequent Room Temperature Activation of Dinitrogen
Bibliographic record
Abstract
Mesoporous niobium oxide was treated at room temperature with bis(toluene) niobium to make a new black material that exhibits metallic properties. The metallic behavior is attributed to low-valent NbII in the walls of the porous structure and is fully supported by strong emissions at the Fermi level, variable temperature resistivity measurements, and temperature-independent paramagnetism. These materials possess higher conductivities than reported for any molecular sieve and also represent the first example of a metallic oxide-based molecular sieve. For comparison, the conductivity is almost 10 000 times greater than the highest value measured for an open structured mesoporous material. Treatment at room temperature with dinitrogen leads to formation of a thin nitride coat on the surface. Cleavage of dinitrogen is an extremely rare and important reaction that typically requires very forcing conditions in the solid state (high temperatures in excess of several hundred degrees, argon plasmas, etc.) or low-valent coordinatively stressed metal centers in the homogeneous phase. This is the first example of a molecular sieve mediating this process and because of the controlled porosity and high surface areas of these materials they are ideal candidates for model studies for nitrogen reduction and catalytic nitrogen incorporation into organic compounds. Since porous materials are often the catalytic support of choice for industrial processes, these materials may lead to the development of commercial nitrogen incorporation processes.
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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".