Experimental investigation of using coffee waste derived activated carbon effectively as sustainable material for hydrogen storage
Bibliographic record
Abstract
This study presents the synthesis and evaluation of activated carbon derived from spent coffee grounds using three distinct activation methods, namely chemical, ultrasound-assisted and surface magnetized. The characterization studies of materials are used to evaluate hydrogen storage performance under varying pressure and temperature conditions. The gravimetric measurements are employed to assess the physisorption capacities, while electrochemical techniques, such as LSV, CV, and GCD evaluate hydrogen related charge storage behavior. The activation methods affect surface morphology and elemental composition of the activated carbon samples, as confirmed by SEM and EDS analyses. Among the three, chemically activated carbon exhibits the highest hydrogen uptake , achieving 0.362 wt% at 0 °C and 4 kPa, which is attributed to its highly porous structure. The ultrasound-assisted and surface magnetized samples exhibitmaximum capacities of 0.357 wt%, and 0.339 wt%, respectively. This study underlines the potential of coffee waste as a sustainable carbon precursor and introduces a dual-characterization approach.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".