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A first-principles tool to discover new pyrometallurgical refining options
No full textWe demonstrate the opportunities of first-principles density functional theory (DFT) calculations for the development of new metallurgical refining processes. As such, a methodology based on DFT calculations is developed to discover new pyrometallurgical refining processes that use the addition of a third element to remove an impurity from a molten host material. As a case study, this methodology is applied to the refining of lead. The proposed method predicts the existing refining routes as well as alternative processes. The most interesting candidate for the removal of arsenic from lead is experimentally verified, which confirms the suitability of the remover element. The method is therefore considered as a useful approach to speed up the discovery of new pyrometallurgical refining processes, as it provides an ordered set of interesting candidate remover elements.sponsorship: Computational resources have been provided by the supercomputing facilities of the Universite catholique de Louvain (CISM/UCL) and the Consortium des Equipements de Calcul Intensif en Federation Wallonie Bruxelles (CECI) funded by the Fonds de la Recherche Scientifique de Belgique (FRS-FNRS). Funding via the Agency for Innovation and Entrepreneurship (VLAIO) project HBC.2016.0733 of the Flemish region with Campine is acknowledged. (Fonds de la Recherche Scientifique de Belgique (FRS-FNRS), Agency for Innovation and Entrepreneurship (VLAIO)|HBC.2016.0733)status: Publishe
Improving Accuracy and Transferability of Machine Learning Chemical Activation Energies by Adding Electronic Structure Information
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