Hydrogen Storage in Microporous Titanium Oxides Reduced by Early Transition Metal Organometallic Sandwich Compounds
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Bibliographic record
Abstract
Microporous titanium oxides synthesized using a hexylamine template were reduced by excess bis(benzene) chromium, bis(cyclopentadienyl) chromium, bis(benzene) vanadium, and bis(cyclopentadienyl) vanadium. These new composite materials were characterized by nitrogen adsorption, powder X-ray diffraction, X-ray photoelectron spectroscopy, and elemental analysis. The V and Cr sandwich compounds proved less effective in reducing the Ti oxide surface than bis(toluene) titanium, which was studied previously. The hydrogen sorption properties were measured at 77 K. The gravimetric sorption capacity decreased in each case as compared to that of the unreduced sample, possibly due to increased density or the reduced surface areas after reduction. However, the overall volumetric storage capacities increased, with a high of 33.42 kg/m 3 recorded for the bis(benzene) vanadium reduced material at 100 atm. This is less than that previously obtained for bis(toluene) titanium (40.46 kg/m 3 ). The improved performance of this series of composite materials relative to the untreated sample was attributed to the increased reduction level of the metal centers in the framework of the structure, which allows for more facile π-back-donation to the H−H σ-bond. Unlike MOFs and porous carbons, the performance does not depend greatly on surface area. Maximum H 2 binding enthalpies ranging from 4.57 to 8.35 kJ/mol were calculated for all samples. The increasing enthalpies with hydrogen adsorption capacity are consistent with a different adsorption mechanism than physisorption, possibly involving a Kubas-type interaction. These results indicate that further efforts are required to find a suitable reducing reagent in order to reach even higher volumetric storage densities and tune the hydrogen binding enthalpies to over 15 kJ/mol, which is proposed to be ideal for porous samples operating at ambient temperature.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.003 | 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