RT dataset
T1 Dataset of the work 'A five-indicator methodology for early-stage sustainable selection of metal scraps and raw materials: application in the steel industry'
A1 Carreira Barral, Israel
A1 García-Moral, Ana
A1 Iñigo Martínez, María Emilia
A1 Díez Hernández, Julieta
A1 Ibáñez Porras, Jesús
A1 Alonso-Terán, Mario
A1 Fuente Gamero, Patricia de la
A1 Barros García, Rocío
A1 Martel Martín, Sonia
K1 Circularity assessment
K1 Criticality assessment
K1 Early-stage evaluation
K1 Metal scrap
K1 Raw material
K1 Steel
K1 Sustainability index
K1 Industria siderúrgica
K1 Steel industry and trade
K1 Residuos metálicos
K1 Scrap metals
AB 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'
PB Universdad de Burgos
YR 2025
FD 2025-12-15
LK https://hdl.handle.net/10259/11199
UL https://hdl.handle.net/10259/11199
LA eng
NO 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
NO 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)
DS Repositorio Institucional de la Universidad de Burgos
RD 28-abr-2026