A machine learning approach to predict C–H bond activation on dual-site doped graphene catalysts

Amrish Kumar, Iqra Ahangar, Shantanu Suryakant Sontakke, Manojkumar Ramteke, Tuhin S. Khan, M. Ali Haider

Open source

DOI: 10.1039/d6ra03770d
Published: 2026
Container: RSC Advances
Publisher: Royal Society of Chemistry (RSC)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1039/d6ra03770d,
  title = {A machine learning approach to predict C–H bond activation on dual-site doped graphene catalysts},
  author = {Amrish Kumar and Iqra Ahangar and Shantanu Suryakant Sontakke and Manojkumar Ramteke and Tuhin S. Khan and M. Ali Haider},
  year = {2026},
  journal = {RSC Advances},
  doi = {10.1039/d6ra03770d},
  url = {https://doi.org/10.1039/d6ra03770d}
}

RIS

TY  - JOUR
TI  - A machine learning approach to predict C–H bond activation on dual-site doped graphene catalysts
AU  - Amrish Kumar
AU  - Iqra Ahangar
AU  - Shantanu Suryakant Sontakke
AU  - Manojkumar Ramteke
AU  - Tuhin S. Khan
AU  - M. Ali Haider
PY  - 2026
JO  - RSC Advances
DO  - 10.1039/d6ra03770d
UR  - https://doi.org/10.1039/d6ra03770d
ER  -

APA

Kumar, A., Ahangar, I., Sontakke, S. S., Ramteke, M., Khan, T. S., & Haider, M. A. (2026). A machine learning approach to predict C–H bond activation on dual-site doped graphene catalysts. RSC Advances. https://doi.org/10.1039/d6ra03770d

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crossref · retrieved 2026-09-25T06:18:43.937Z