Machine-Learning-Aided Blasted Muckpile Analysis: Prospects for Reducing Ore and Profit Losses Through Developing Blast Techniques DOI
Zhi Yu, Xiuzhi Shi, Zong‐Xian Zhang

et al.

Mining Metallurgy & Exploration, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 18, 2024

Language: Английский

Novel Photoelectron-Assisted Microbial Reduction of Arsenate Driven by Photosensitive Dissolved Organic Matter in Mine Stream Sediments DOI
Zhaohui Guo, Jie Cao, Rui Xu

et al.

Environmental Science & Technology, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 11, 2024

The microbial reduction of arsenate (As(V)) significantly contributes to arsenic migration in mine stream sediment, primarily driven by heterotrophic microorganisms using dissolved organic matter (DOM) as a carbon source. This study reveals novel pathway sediments that photosensitive DOM generates photoelectrons stimulate diverse nonphototrophic reduce As(V). photoelectrophic As(V) (PEAsR) was investigated microcosm incubation, which showed the transfer from indigenous sediment microorganisms, thereby leading 50% higher rate abundance two marker genes for reduction,

Language: Английский

Citations

8

Exploring arsenic migration and transformation in anaerobic heterogeneous media through Column experiments DOI
Jigang Liu, Sanxi Peng, Huimei Shan

et al.

Journal of Hydrology, Journal Year: 2024, Volume and Issue: unknown, P. 132559 - 132559

Published: Dec. 1, 2024

Language: Английский

Citations

0

Machine-Learning-Aided Blasted Muckpile Analysis: Prospects for Reducing Ore and Profit Losses Through Developing Blast Techniques DOI
Zhi Yu, Xiuzhi Shi, Zong‐Xian Zhang

et al.

Mining Metallurgy & Exploration, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 18, 2024

Language: Английский

Citations

0