Hydrogen production in integration with CCUS: A realistic strategy towards net zero
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
It is believed that hydrogen will play an essential role in energy transition and achieving the net-zero target by 2050. Currently, global hydrogen production mostly relies on processing fossil fuels such as coal and natural gas, commonly referred to as grey hydrogen production while releasing substantial amounts of carbon dioxide (CO 2 ). Developing economically and technologically viable pathways for hydrogen production while eliminating CO 2 emissions becomes paramount. In this critical review, we examine the common grey hydrogen production techniques by analyzing their technical characteristics, production efficiency and costs. We further analyze the integration of carbon capture, utilization and storage (CCUS) technology, establishing the zero-carbon strategy transiting from grey to blue hydrogen production with CO 2 capture and either utilized or permanently stored. Today, grey hydrogen production exhibits technological diversities, with various commercial maturities. Most methods rely on the effectiveness of catalysts, necessitating a solution to address catalyst fouling and sintering in practice. Although CCUS captures, utilizes or stores CO 2 during grey hydrogen production, its wide application faces multiple challenges regarding the technological complexity, cost, and environmental benefits. It is urgent to develop technologically mature, low-cost and low-energy-consumption CCUS technology, implementing extensive, large-scale integrated pilot projects. • Analyze the value chain of hydrogen production integrated with carbon capture, utilization and storage • Discuss novel techniques on the development of catalyst performance for hydrogen production • Analyze different carbon capture methods specifically for hydrogen production contexts • Conduct techno-economic analysis of hydrogen production integrated with carbon capture, utilization and storage
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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 it