Molybdenum Dithiolene Complexes as Structural Models for the Active Sites of Molybdenum(IV) Sulfide Hydrodesulfurization Catalysts
Bibliographic record
Abstract
Abstract The removal of sulfur (as H2S) from organosulfur species in petroleum feedstocks (hydrodesulfurization, HDS) is carried out on an enormous scale by using heterogeneous catalysts based on MoS2 (usually doped with Co). Partially hydrogenated thiophenes are postulated intermediates in the MoS2‐catalyzed hydrodesulfurization of thiophene. The present contribution describes new molecular models for the proposed active sites in HDS catalysis. The models are derived from a mixed‐ligand (push–pull) molybdenum trisdithiolene {[Mo(tfd)2(bdt)]; tfd = S2C2(CF3)2, bdt = S2C6H4}: selective intraligand alkyne binding converts the bdt group to a labile Mo‐chelating benzodithiin, which can be substituted with a variety of weak donor ligands. The complexes [Mo(tfd)2(dht)2] and [Mo(tfd)2(tht)2] (dht = 2,5‐dihydrothiophene; tht = tetrahydrothiophene) were synthesized and crystallographically characterized. The Mo(tfd)2 substructures closely resemble the presumed active site in MoS2 HDS catalysts. The coordination geometries at molybdenum are approximately trigonal prismatic, and the metal bears two strongly bound dithiolene (tfd) groups and two comparatively weakly bound thioether ligands (dht or tht). Competitive binding experiments establish that tht binds more strongly to the Mo center than dht (Keq = 6.5 ± 0.5). Preliminary reactivity studies reveal that [Mo(tfd)2(dht)2] decomposes to [Mo(tfd)3], thiophene, and unidentified species upon heating. Further, [Mo(tfd)2(tht)2] induces the isomerization of 1,4‐cyclohexadiene to 1,3‐cyclohexadiene at elevated temperatures.
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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".