Synthesis and Electrochemical Study of Pd-Based Trimetallic Nanoparticles for Enhanced Hydrogen Storage
Bibliographic record
Abstract
The success of acceptable hydrogen storage capacities on high surface area carbon materials at ambient temperature requires the combination of both physisorption and chemisorption. Despite the sole reliance on physisorption for hydrogen uptake in carbon, the dispersal of transition metal catalysts on carbon materials significantly enhances hydrogen uptake at ambient temperatures, via the process of hydrogen spillover. In the present study, hydrogen electrosorption onto activated carbon materials modified with different trimetallic dissociation catalysts (Pd–Ag–Cd) was investigated in an acidic medium using cyclic voltammetry and chronoamperometry. A significant synergistic effect on hydrogen storage was observed, which could be attributed to the electrochemical reduction of hydrogen ions initially at the Pd-based nanoparticles and the hydrogen surface diffusion subsequently to the activated carbon. Utilizing electrochemical methods, the optimized composition of the Pd–Ag–Cd alloys was determined to be Pd 80 Ag 10 Cd 10, with the highest hydrogen sorption capacity at a hydrogen desorption charge of 18.49 C/cm 2 ·mg. With increased kinetics and a decrease in the phase transition, the significant enhancement of hydrogen sorption, in comparison to the Pd–Ag and Pd–Cd bimetallic alloys, was further demonstrated, making Pd–Ag–Cd catalysts attractive for use as hydrogen dissociation catalysts for applications in both hydrogen purification and storage.
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How this classification was reachedexpand
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) | 0.000 | 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 teacher head, 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".