2026-04-28T04:36:37Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/111992026-03-09T11:01:20Zcom_10259_6168com_10259_5086com_10259_2604com_10259_3924col_10259_6775col_10259_7224col_10259_5684
Dataset of the work 'A five-indicator methodology for early-stage sustainable selection of metal scraps and raw materials: application in the steel industry'
Carreira Barral, Israel
García-Moral, Ana
Iñigo-Martínez, María Emilia
Díez Hernández, Julieta
Ibáñez Porras, Jesús
Alonso-Terán, Mario
Fuente Gamero, Patricia de la
Barros García, Rocío
Martel Martín, Sonia
Circularity assessment
Criticality assessment
Early-stage evaluation
Metal scrap
Raw material
Steel
Sustainability index
Industria siderúrgica
Residuos metálicos
Steel industry and trade
Scrap metals
This dataset contains the data provided by ArcelorMittal España (commercial names, quality and elemental composition of the studied metal scraps and raw materials) in the context of the 'IRIDISCENTE' research project, and the analysis, results and conclusions for each of the 11 scenarios considered in the work 'A five-indicator methodology for early-stage sustainable selection of metal scraps and raw materials: application in the steel industry'
This work was funded by the Spanish Agencia Estatal de Investigación (AEI) through the ‘Artificial Intelligence for the sustainable design of efficient alloys and processes (IRIDISCENTE)’ research project (PLEC2023-010190)
2026-01-12T12:34:41Z
2026-01-12T12:34:41Z
2025-12-15
dataset
info:eu-repo/semantics/acceptedVersion
Carreira-Barral, I., García Moral, A., Iñigo Martinez, M. E., Díez-Hernández, J., Ibanez, J., Mario Alonso Terán, De La Fuente, P., Barros Garcia, R., & Martel-Martín, S. (2025). Dataset of the work 'A five-indicator methodology for early-stage sustainable selection of metal scraps and raw materials: application in the steel industry' [Data set]. Universidad de Burgos. https://doi.org/10.71486/MCTS-0K15
https://hdl.handle.net/10259/11199
10.71486/mcts-0k15
eng
https://hdl.handle.net/10259/11472
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica, Técnica y de Innovación 2021-2023/PLEC2023-010190/ES/Inteligencia artificial para el diseño sostenible de aleaciones y procesos eficientes/IRIDISCENTE/
Atribución-NoComercial 4.0 Internacional
http://creativecommons.org/licenses/by-nc/4.0/
info:eu-repo/semantics/openAccess
text/plain
application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
Universdad de Burgos