Efficient and Selective Methane Borylation Through Pore Size Tuning of Hybrid Porous Organic‐Polymer‐Based Iridium Catalysts
Why this work is in the frame
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Bibliographic record
Abstract
Abstract As a new energy source that could replace petroleum, the global reserves of methane hydrate (combustible ice) are estimated to be approximately 20 000 trillion cubic meters. A large amount of methane hydrate has been found under the seabed, but the transportation and storage of methane gas far from coastlines are technically unfeasible and expensive. The direct conversion of methane into value‐added chemicals and liquid fuels is highly desirable but remains challenging. Herein, we prepare a series of iridium complexes based on porous polycarbazoles with high specific areas and good thermochemical stabilities. Through structure tuning we optimized their catalytic activities for the selective monoborylation of methane. One of these catalysts (CAL‐3‐Ir) can produce methyl boronic acid pinacol ester (CH 3 Bpin) in 29 % yield in 9 h with a turnover frequency (TOF) of approximately 14 h −1 . Because its pore sizes favor monoborylated products, it has a high chemoselectivity for monoborylation (CH 3 Bpin:CH 2 (Bpin) 2 =16:1).
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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 | 0.000 |
| 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 it