Big Data of Steel and Low Carbon Intelligent Smelting
A special issue of Metals (ISSN 2075-4701).
Deadline for manuscript submissions: closed (30 May 2023) | Viewed by 10469
Special Issue Editors
Interests: mineral-phase feature identification and extraction; CO emission reduction and pollutant treatment of sintering flue gas; metallurgical energy saving and resource optimization
Special Issues, Collections and Topics in MDPI journals
Interests: ironmaking raw materials; low-carbon ironmaking; comprehensive utilization of metallurgical resources
Interests: non-metallic inclusion; clean-steel smelting theory and technology; low-density steel product development
Interests: new technology for sintering pellets; new technology for low-carbon iron making; metallurgical resources value-added processing
Interests: big data of steel industry; complex network big data; machine learning; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Interests: artificial intelligence; network security; big data modeling; numerical calculation; green metallurgy; precision medicine
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue focus on the analysis of state data and image/video streams in the metallurgical reaction process using intelligent algorithms to extract characteristic data and explores the best practice to obtain useful information from the data to strengthen the metallurgical reaction process. With the help of machine vision and other means, research on the metallurgical reaction process has gradually shifted its focus from qualitative, descriptive and local research to precision, quantification and integration. This Special Issue’s scope not only includes studies on molecular, atomic and microscopic mineral phase analysis, but also those on the overall development law of the metallurgical reaction process. Theoretical breakthroughs or new ideas for low-carbon metallurgy driven by dual carbon goals are of particular interest. We also welcome research on: 1. intelligent low-carbon ore blending of iron ore powder; 2. integrated treatment of multi-pollutants in sintering flue gas; 3. intelligent ore blending driven by sintering big data; 4. the evolution law of iron ore mineral phase characteristics; 5. extraction of characteristic parameters of iron ore microstructure; 6. liquid-phase formation and crystallization behavior during metallurgical reaction; 7. the dissolution behavior of flux in high-temperature molten pools; 8. intelligent control of furnace temperature based on deep mining of big data in the blast furnace smelting process; 9. steelmaking end-point prediction model based on deep mining of flue gas big data; 10. comprehensive utilization of metallurgical solid-waste resources; 11. hydrogen metallurgy technology; and 12. non-blast furnace ironmaking technology.
Dr. Jie Li
Dr. Zhenggen Liu
Dr. Hangyu Zhu
Dr. Hao Liu
Prof. Dr. Chunying Zhang
Prof. Dr. Aimin Yang
Dr. Weixing Liu
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metals is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- sintering flue gas
- intelligent ore matching
- big data of steel
- study on mineral facies characteristics
- blast furnace temperature
- quality prediction of sinter
- metallurgical solid waste
- hydrogen metallurgy
- non-blast furnace ironmaking technology
- energy saving and resource optimization in metallurgy
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.
Further information on MDPI's Special Issue policies can be found here.