Synthesis and Electrochemical Evaluation of Multivalent Vanadium Hydride Gels for Lithium and Hydrogen Storage
Bibliographic record
Abstract
A vanadium aryl hydride gel was prepared by thermal decomposition and subsequent hydrogenation of tetraphenyl vanadium and evaluated for electrochemical and hydrogen storage performance. Characterization by IR, XRD, XPS, nitrogen adsorption, and TGA suggests that the material consists predominantly of a mixture of vanadium centers in oxidation states of II–IV bound together by bridging hydride and phenyl groups. Electrochemical properties were explored to probe the reversible oxidation state behavior and possible applications to Li batteries, with the hypothesis that the low mass of the hydride ligand may lead to superior gravimetric performance relative to heavier vanadium oxides and phosphates. The material shows reversible redox activity and has a promising peak capacity of 131 mAh g –1, at a discharge rate of 1 mA cm –2, comparable to bulk VO 2 samples also tested in this study. After repeated charge–discharge cycling for 50 cycles, the material retained 36% of its capacity. The material also shows improved hydrogen storage performance relative to previously synthesized VH 3 based gels, reaching a reversible gravimetric storage capacity of 5.8 wt % at 130 bar and 25 °C. Based on the measured density, this corresponds to a volumetric capacity of 79.77 kg H 2 m –3, demonstrating that the 2017 U.S. DOE system goals of 5.5 wt % and 40 kg H 2 m –3 may be achievable upon containment in a Type 1 tank and coupling to a fuel cell.
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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".