ML-RKIM: Physics-Informed Machine Learning for Reaction Kinetics Identification and Modeling

Paulina Portales Picazo, Navid Zobeiry

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DOI: 10.1021/acs.jcim.6c01936
Published: 2026-09-22
Container: Journal of Chemical Information and Modeling
Publisher: American Chemical Society (ACS)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1021/acs.jcim.6c01936,
  title = {ML-RKIM: Physics-Informed
Machine Learning for Reaction
Kinetics Identification and Modeling},
  author = {Paulina Portales Picazo and Navid Zobeiry},
  year = {2026},
  journal = {Journal of Chemical Information
and Modeling},
  doi = {10.1021/acs.jcim.6c01936},
  url = {https://doi.org/10.1021/acs.jcim.6c01936}
}

RIS

TY  - JOUR
TI  - ML-RKIM: Physics-Informed
Machine Learning for Reaction
Kinetics Identification and Modeling
AU  - Paulina Portales Picazo
AU  - Navid Zobeiry
PY  - 2026
JO  - Journal of Chemical Information
and Modeling
DO  - 10.1021/acs.jcim.6c01936
UR  - https://doi.org/10.1021/acs.jcim.6c01936
ER  -

APA

Picazo, P. P., & Zobeiry, N. (2026). ML-RKIM: Physics-Informed Machine Learning for Reaction Kinetics Identification and Modeling. Journal of Chemical Information and Modeling. https://doi.org/10.1021/acs.jcim.6c01936

Source records

crossref · retrieved 2026-11-05T23:28:09.641Z