Experimental Study on Enhanced Gasification of Biomass and Simulation of a CO<sub>2</sub> Adsorption Mechanism Based on a Modified Ca-Based Catalyst
Bibliographic record
Abstract
This study examines the gasification properties of solid waste biomass under a steam atmosphere and the catalytic activity of Ca-based catalysts. Al and Ti metal-modified Ca-based catalysts, using calcium oxide (CaO) as a carrier, were prepared and analyzed. The gasification characteristics of straw biomass under various reaction conditions and with the addition of modified Ca-based catalysts were studied by using a fixed-bed gasification reaction device. The cycling performance of the catalysts before and after modification was also investigated. The CASTEP module of Materials Studio software facilitated a mechanistic simulation of CO 2 adsorption over the modified catalyst. This explored changes in stable configurations, particle density-of-state (PDOS) energy distributions, and bonding populations of both the modified and adsorbed catalysts. The findings demonstrate that the gasification performance of CaO significantly improved with the addition of Al metal. The H 2 yield was 347.7 mL/g at 800 °C, with a steam/biomass mass ratio of 1.5 and a Ca/C molar ratio of 1.0. The H 2 yield for CaAlO after five cycles was 154.39 mL/g under identical conditions, compared to only 137.39 mL/g for unmodified CaO. The adsorption energy of the catalysts before and after modification increased in the order of CaO < CaTiO < CaAlO, with values of −0.99, −3.67, and −5.92 eV, respectively. Doping CaO with Al and Ti and the adsorption of CO 2 molecules enhanced the activity of O surf atoms on the catalyst surface, leading to an increase in the surface PV of C atoms. This enhancement was evident as the PDOS of C atoms on the CO 2 surface shifted to the left, which improved its adsorption capacity. The number of Ca–O bond populations and bonding positions in the material increased, and the number of Al–Ca and Ti–O bond populations reached 0.66, making it more conducive for recycling during intensified hydrogen production.
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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) | 0.002 | 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".