Oxidative roasting experimentation and optimum predictive model development for copper and iron recovery from a copper smelter dust

Daniel O. Okanigbe, Michael K. Ayomoh, Olawale M. Popoola, Patricia A. Popoola, Victor S. Aigbodion

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

The success of a treatment option depends on selection of suitable process variables at which response attains optimum. Hence, this study aimed at investigating the effects of time, temperature and time-temperature on changes in mineralogy (copper sulphate (CuSO4), copper oxide (CuO), ferrous oxide (Fe2O3) and ferric oxide (Fe3O4)) of a copper smelter dust (CSD) during oxidative roasting. This aim was achieved by 2-way analysis of variance and mathematical model development of data obtained. Results showed time as most influential factor with an optimum time of 2 ​hrs for the production of high yield roast products. Furthermore, it was observed that a maximum of 23.31% proportion of CuSO4 was recovered from an input with 7.86% proportion of CuSO4 at a temperature of 680 ​°C within a time frame of 2 ​hrs and for a furnace door opening of 25 ​mm. Similarly, a maximum of 18.37% of CuO was recovered from an input with 23.91% CuO at a temperature of 800 ​°C, for a duration of 3 ​hrs and 25 ​mm opening of the furnace door. Whereas, an optimum 0.44 ratio value of Fe2O3:Fe3O4 was recovered at a temperature 680 ​°C, for a duration of 2 ​hrs and 25 ​mm furnace door opening. These maximum outputs and associated experimental conditions depict optimum operating conditions of experiment. Furthermore, predicted output proportions obtained from developed constraint interpolant models were well aligned with experimental outputs. A maximum percentage error of 0.07% was recorded in the predictive output for both water and acid soluble mineral fractions.

Original languageEnglish
Article number100125
JournalResults in Engineering
Volume7
DOIs
Publication statusPublished - Sept 2020
Externally publishedYes

Keywords

  • Copper smelter dust
  • Full factorial experimental design
  • Optimum predictive model
  • Oxidative roasting

ASJC Scopus subject areas

  • General Engineering

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