Literature DB >> 28806506

Quantifying Recycling and Losses of Cr and Ni in Steel Throughout Multiple Life Cycles Using MaTrace-Alloy.

Shinichiro Nakamura1, Yasushi Kondo1, Kenichi Nakajima2, Hajime Ohno3, Stefan Pauliuk4.   

Abstract

Alloying metals are indispensable ingredients of high quality alloy steel such as austenitic stainless steel, the cyclical use of which is vital for sustainable resource management. Under the current practice of recycling, however, different metals are likely to be mixed in an uncontrolled manner, resulting in function losses and dissipation of metals with distinctive functions, and in the contamination of recycled steels. The latter could result in dilution loss, if metal scrap needed dilution with virgin iron to reduce the contamination below critical levels. Management of these losses resulting from mixing in repeated recycling of metals requires tracking of metals over multiple life cycles of products with compositional details. A new model (MaTrace-alloy) was developed that tracks the fate of metals embodied in each of products over multiple life cycles of products, involving accumulation, discard, and recycling, with compositional details at the level of both alloys and products. The model was implemented for the flow of Cr and Ni in the Japanese steel cycle involving 27 steel species and 115 final products. It was found that, under a high level of scrap sorting, greater than 70% of the initial functionality of Cr and Ni could be retained over a period of 100 years, whereas under a poor level of sorting, it could plunge to less than 30%, demonstrating the relevance of waste management technology in circular economy policies.

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Year:  2017        PMID: 28806506     DOI: 10.1021/acs.est.7b01683

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  1 in total

1.  Alloy information helps prioritize material criticality lists.

Authors:  T E Graedel; Barbara K Reck; Alessio Miatto
Journal:  Nat Commun       Date:  2022-01-10       Impact factor: 17.694

  1 in total

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