La–Ni Modified Calcined Dolomite for Enhanced Hydrogen Production from Biomass Gasification: A Combined Experimental and DFT Study
Bibliographic record
Abstract
This study investigates the enhancement of hydrogen production from corn stalk gasification using modified calcined dolomite (CD) catalysts. A Ni/CD catalyst was first synthesized, followed by La 2 O 3 promotion to produce La–Ni/CD. Both catalysts were evaluated for gasification performance, anticoking ability, and cyclic stability. Results show that La–Ni/CD significantly improved hydrogen yield to 166.7 mL/g, surpassing unmodified CD (110.3 mL/g), and maintained 138.9 mL/g after seven cycles. Complementary density functional theory (DFT) simulations via CASTEP revealed that La modification induced a shift of the Ca-p and O-s electronic states to lower energies. This electronic redistribution promotes H-s and Ni-p orbital hybridization, thereby enhancing H 2 adsorption. Bond population analysis confirmed strengthened O–La bonds (population: 0.50) and stabilized H–C bonds (0.80–0.84), while reduced O–Ni populations mitigated carbon deposition. These synergistic effects demonstrate the role of La–Ni/CD in optimizing pathways toward hydrogen-rich syngas, supporting its potential for efficient biomass gasification.
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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".