Prediction of collector flotation performance based on machine learning and quantum chemistry: A case of sulfide minerals-Reference-Cited by-同舟云学术

Prediction of collector flotation performance based on machine learning and quantum chemistry: A case of sulfide minerals

Published:2024-08 Issue: Volume:342 Page:126954
ISSN:1383-5866
Container-title:Separation and Purification Technology
language:en
Short-container-title:Separation and Purification Technology

Author:

Zhang Wanjia,Sun Wei,Zheng Mengjun,Xu Shihong,Zheng Renji,Cao Jian,Jin Xin,Gao Zhiyong,Feng Zhitao

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference77 articles.

1. Bulatovic, S.M., Handbook of Flotation Reagents: Chemistry. Theory and Practice: Flotation of Sulphides Ores, ed. S.M. Bulatovic. 2007, Amsterdam: Elsevier.

2. The interaction of flotation reagents with metal ions in mineral surfaces: a perspective from coordination chemistry;Chen;Miner. Eng.,2021

3. Depression of lead-activated sphalerite by pyrite via galvanic interactions: implications to the selective flotation of complex sulfide ores;Aikawa;Miner. Eng.,2020

4. Bi-functional hydrogen and coordination bonding surfactant: a novel and promising collector for improving the separation of calcium minerals;Zhang;J. Colloid Interface Sci.,2021

5. Improved flotation separation of sulfide minerals by synthesized surfactant based on Para-position methyl effect;Zhang;Sep. Purif. Technol.,2022

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