Algorithmic Modelling of Advanced Chlorination Procedures for Multimetal Recovery
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In: Metals, Vol. 11, No. 10, 1595, 08.10.2021.
Research output: Contribution to journal › Article › Research › peer-review
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TY - JOUR
T1 - Algorithmic Modelling of Advanced Chlorination Procedures for Multimetal Recovery
AU - Höber, Lukas
AU - Lerche, Roberto
AU - Steinlechner, Stefan
N1 - Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/10/8
Y1 - 2021/10/8
N2 - In the course of developing an innovative process for CO2-optimised valuable metal recovery from precipitation residues accumulating in the zinc industry or nickel industry, the chlorination reactions were investigated. As the basis of small-scale pyrometallurgical experiments, the selected reaction systems were evaluated by means of thermodynamic calculations. With the help of the thermochemical computation software FactSage (Version 8.0), it is possible to simulate the potential valuable metal recovery from residual materials such as jarosite and goethite. In the course of the described investigations, an algorithmically supported simulation scheme was developed by means of Python 3 programming language. The algorithm determines the optimal process parameters for the chlorination of valuable metals, whereby up to 10,000 scenarios can be processed per iteration. This considers the mutual influences and secondary conditions that are neglected in individual calculations.
AB - In the course of developing an innovative process for CO2-optimised valuable metal recovery from precipitation residues accumulating in the zinc industry or nickel industry, the chlorination reactions were investigated. As the basis of small-scale pyrometallurgical experiments, the selected reaction systems were evaluated by means of thermodynamic calculations. With the help of the thermochemical computation software FactSage (Version 8.0), it is possible to simulate the potential valuable metal recovery from residual materials such as jarosite and goethite. In the course of the described investigations, an algorithmically supported simulation scheme was developed by means of Python 3 programming language. The algorithm determines the optimal process parameters for the chlorination of valuable metals, whereby up to 10,000 scenarios can be processed per iteration. This considers the mutual influences and secondary conditions that are neglected in individual calculations.
KW - Advanced chlorination
KW - Goethite
KW - Jarosite
KW - Multimetal recovery
KW - goethite
KW - multimetal recovery
KW - advanced chlorination
KW - jarosite
UR - http://www.scopus.com/inward/record.url?scp=85116598212&partnerID=8YFLogxK
U2 - 10.3390/met11101595
DO - 10.3390/met11101595
M3 - Article
AN - SCOPUS:85116598212
VL - 11
JO - Metals
JF - Metals
SN - 2075-4701
IS - 10
M1 - 1595
ER -