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Cited article:

Future Research and Developments on Reuse and Recycling of Steelmaking By-Products

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Machine learning analysis of electric arc furnace process for the evaluation of energy efficiency parameters

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Applied Energy 307 118209 (2022)
https://doi.org/10.1016/j.apenergy.2021.118209

Paving the way for the optimization of water consumption in the steelmaking processes: barriers, analysis and KPIs definition

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Matériaux & Techniques 108 (5-6) 510 (2020)
https://doi.org/10.1051/mattech/2021006

Trends and Advances in Information Systems and Technologies

C. Mocci, A. Maddaloni, M. Vannucci, S. Cateni and V. Colla
Advances in Intelligent Systems and Computing, Trends and Advances in Information Systems and Technologies 746 714 (2018)
https://doi.org/10.1007/978-3-319-77712-2_67

Internal Slags Reuse in an Electric Steelmaking Route and Process Sustainability: Simulation of Different Scenarios Through the EIRES Monitoring Tool

Ismael Matino, Valentina Colla and Stefano Baragiola
Waste and Biomass Valorization 9 (12) 2481 (2018)
https://doi.org/10.1007/s12649-018-0264-3

Electric energy consumption and environmental impact in unconventional EAF steelmaking scenarios

Ismael Matino, Valentina Colla and Stefano Baragiola
Energy Procedia 105 3636 (2017)
https://doi.org/10.1016/j.egypro.2017.03.839

Quantification of energy and environmental impacts in uncommon electric steelmaking scenarios to improve process sustainability

Ismael Matino, Valentina Colla and Stefano Baragiola
Applied Energy 207 543 (2017)
https://doi.org/10.1016/j.apenergy.2017.06.088

Process modelling and simulation of electric arc furnace steelmaking to allow prognostic evaluations of process environmental and energy impacts

Ismael Matino, Erika Alcamisi, Valentina Colla, Stefano Baragiola and Paolo Moni
Matériaux & Techniques 104 (1) 104 (2016)
https://doi.org/10.1051/mattech/2016004

Improving energy and resource efficiency of electric steelmaking through simulation tools and process data analyses

V. Colla, I. Matino, F. Cirilli, et al.
Matériaux & Techniques 104 (6-7) 602 (2016)
https://doi.org/10.1051/mattech/2017001