Maier, Sarah, Collins, Eric M., and Raghavachari, Krishnan. Quantitative Prediction of Vertical Ionization Potentials from DFT via a Graph-Network-Based Delta Machine Learning Model Incorporating Electronic Descriptors. Retrieved from https://par.nsf.gov/biblio/10414641. The Journal of Physical Chemistry A 127.15 Web. doi:10.1021/acs.jpca.2c08821.

Maier, Sarah, Collins, Eric M., & Raghavachari, Krishnan. Quantitative Prediction of Vertical Ionization Potentials from DFT via a Graph-Network-Based Delta Machine Learning Model Incorporating Electronic Descriptors. The Journal of Physical Chemistry A, 127 (15). Retrieved from https://par.nsf.gov/biblio/10414641. https://doi.org/10.1021/acs.jpca.2c08821

Maier, Sarah, Collins, Eric M., and Raghavachari, Krishnan. "Quantitative Prediction of Vertical Ionization Potentials from DFT via a Graph-Network-Based Delta Machine Learning Model Incorporating Electronic Descriptors". The Journal of Physical Chemistry A 127 (15). Country unknown/Code not available. https://doi.org/10.1021/acs.jpca.2c08821. https://par.nsf.gov/biblio/10414641.

@article{osti_10414641,
place = {Country unknown/Code not available}, title = {Quantitative Prediction of Vertical Ionization Potentials from DFT via a Graph-Network-Based Delta Machine Learning Model Incorporating Electronic Descriptors}, url = {https://par.nsf.gov/biblio/10414641}, DOI = {10.1021/acs.jpca.2c08821}, abstractNote = {}, journal = {The Journal of Physical Chemistry A}, volume = {127}, number = {15}, author = {Maier, Sarah and Collins, Eric M. and Raghavachari, Krishnan}, }