The road to carbon neutrality in the metallurgical industry: Hydrogen metallurgy processes represented by hydrogen-rich coke oven gas, short-process metallurgy of scrap and low-carbon policy
Bibliographic record
Abstract
Abstract With the acceleration of global industrialization, the concentration of carbon dioxide is increasing in the atmosphere, and its negative impacts have seriously affected all walks of human life, so achieving carbon neutrality has become an urgent task for achieving sustainable development. As an important energy-intensive industry, the metallurgical industry occupies an important position in the global carbon-neutral agenda. In China, the metallurgical industry is actively researching and developing a new green metallurgical model of “replacing carbon with hydrogen”, exploring the feasibility of utilizing renewable energy sources to produce hydrogen from electrolysis to reduce iron ore, and at the same time utilizing hydrogen-rich coke oven gas to get rid of the over-reliance on coke; at the same time, the government’s policies provide support and incentives to elevate sustainable development and technological innovation in the metallurgical industry. support and incentives to elevate sustainable development and technological innovation in the metallurgical industry. Against this background, this paper describes the key initiatives taken by the metallurgical industry in the process of achieving carbon neutrality, including the metallurgy using hydrogen processes using hydrogen-rich coke oven gas as a source of reducing gas, short-process metallurgy of scrap, and technology that reduce emissions and save energy. Through case studies and policy analyses of new green metallurgy, this study demonstrates the potential and achievements of the metallurgical industry in achieving global carbon neutrality. It concludes with a call for the metallurgical industry to continue to strengthen innovation and work with governments and academia to pave the way toward carbon neutrality. Through new metallurgical technologies, improved energy and resource efficiency, and sustainable development, the metallurgical industry will make a significant contribution to the goal of global carbon neutrality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".