DFT-Machine Learning Approach for Accurate Prediction of p<i>K</i><sub>a</sub>
- DOI
- 10.1021/acs.jpca.1c05031
- Published
- 2021-09-23
- Container
- The Journal of Physical Chemistry A
- Publisher
- American Chemical Society (ACS)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1021/acs.jpca.1c05031,
title = {DFT-Machine Learning Approach for Accurate Prediction of p<i>K</i><sub>a</sub>},
author = {Robin Lawler and Yao-Hao Liu and Nessa Majaya and Omar Allam and Hyunchul Ju and Jin Young Kim and Seung Soon Jang},
year = {2021},
journal = {The Journal of Physical Chemistry A},
doi = {10.1021/acs.jpca.1c05031},
url = {https://doi.org/10.1021/acs.jpca.1c05031}
}RIS
TY - JOUR TI - DFT-Machine Learning Approach for Accurate Prediction of p<i>K</i><sub>a</sub> AU - Robin Lawler AU - Yao-Hao Liu AU - Nessa Majaya AU - Omar Allam AU - Hyunchul Ju AU - Jin Young Kim AU - Seung Soon Jang PY - 2021 JO - The Journal of Physical Chemistry A DO - 10.1021/acs.jpca.1c05031 UR - https://doi.org/10.1021/acs.jpca.1c05031 ER -
APA
Lawler, R., Liu, Y., Majaya, N., Allam, O., Ju, H., Kim, J. Y., & Jang, S. S. (2021). DFT-Machine Learning Approach for Accurate Prediction of p<i>K</i><sub>a</sub>. The Journal of Physical Chemistry A. https://doi.org/10.1021/acs.jpca.1c05031
Source records
- crossref · retrieved 2026-09-26T10:54:51.661Z