Beijing General Research Institute of Mining and Metallurgy

本机构学者在这里署名、按本站篇数

合作机构同一篇文章里的其他机构

1. Zhejiang University中国2
2. Northeastern University中国1
3. Central South University中国1
4. Xinjiang University中国1
5. University of Vienna奥地利1
6. Hainan University中国1
7. Anhui University of Science and Technology中国1
8. Chinese Academy of Sciences中国1

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逐年被引

最新文献

1. 1
   Characterization of spatial heterogeneity in an open-pit mine slope based on boreholes and UAV photogrammetry, with stability assessment and application to monitoring layout: a case studyGeomatics, Natural Hazards and Risk20260
2. 2
   Interpretable spatiotemporal machine learning reveals hydrogeological and climatic controls on groundwater heavy metal transport in acid mine drainageJournal of Hazardous Materials20263
3. 3
   Dramatic decoupling of nematode community responses to heavy metal pollution in high geological background soilsJournal of Hazardous Materials20265
4. 4
   Spatial delineation of AMD sources in a pyrite-rich waste rock site with spectral induced polarization methodJournal of Hazardous Materials20255
5. 5
   A hydrophilic/hydrophobic switch on polymer surface triggered by calcite towards separation of hazardous PVC from plastic mixturesJournal of Hazardous Materials202415
6. 6
   Machinery health prognostic with uncertainty for mineral processing using TSC-TimeGANReliability Engineering & System Safety20248

高被引文献

1. 1
   A hydrophilic/hydrophobic switch on polymer surface triggered by calcite towards separation of hazardous PVC from plastic mixturesJournal of Hazardous Materials202415
2. 2
   Machinery health prognostic with uncertainty for mineral processing using TSC-TimeGANReliability Engineering & System Safety20248
3. 3
   Dramatic decoupling of nematode community responses to heavy metal pollution in high geological background soilsJournal of Hazardous Materials20265
4. 4
   Spatial delineation of AMD sources in a pyrite-rich waste rock site with spectral induced polarization methodJournal of Hazardous Materials20255
5. 5
   Interpretable spatiotemporal machine learning reveals hydrogeological and climatic controls on groundwater heavy metal transport in acid mine drainageJournal of Hazardous Materials20263

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