Molten metal methane pyrolysis for distributed hydrogen production: Reactor design, hydrodynamics, and technoeconomic insights
Bibliographic record
Abstract
Methane pyrolysis offers a compelling pathway for low-carbon hydrogen production by avoiding CO 2 emissions and enabling distributed deployment in locations with natural gas supply, thereby eliminating the need for costly hydrogen transport. While promising, the commercial deployment is constrained by the lack of detailed reactor modeling and technoeconomic assessment at small production scales. This study addresses these gaps by designing and modeling a small-scale (1–10 t-H 2 /day) bubble column reactor employing molten Ni Bi alloy catalyst for methane pyrolysis. A coupled kinetic–hydrodynamic model was developed to simulate gas holdup, bubble behavior, and conversion under different operating conditions. The reactor design was integrated into an Aspen Plus simulation of the full process, including heat recovery and hydrogen purification. Optimization of pressure, temperature, and single-pass conversion revealed that operation at 1100 °C, 15 bar, and 70–75 % conversion minimized reactor volume and cost. The lowest levelized cost of hydrogen (LCOH) achieved was $3.06/kg-H 2 without sale of carbon, significantly lower than green H 2 produced from water electrolysis and competitive with blue H 2 produced via centralized reforming when transportation costs are included. Sensitivity analysis reveals that carbon byproduct is a key economic lever; carbon sale at $250/t-C reduces LCOH by 25 %, while a price of $700/t-C would meet U.S. DOE $1/kg-H₂ target. These results demonstrate the technoeconomic viability of molten metal methane pyrolysis and highlight future opportunities. • Low-carbon H 2 production via molten metal methane pyrolysis was studied. • Reactor design was optimized by a coupled kinetic–hydrodynamic mathematical model. • Full process simulation by Aspen Plus, including novel recycle system and heat recovery. • Optimized TEA at a temperature of 1100 °C, and single-pass conversion of 70 % • Lowest LCOH of $3.06 and $2.28/kg H 2 without/with carbon sale of $250/ton
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".