Unzueta, Pablo A., Greenwell, Chandler S., and Beran, Gregory J. Predicting Density Functional Theory-Quality Nuclear Magnetic Resonance Chemical Shifts via Δ-Machine Learning. Retrieved from https://par.nsf.gov/biblio/10295841. Journal of Chemical Theory and Computation 17.2 Web. doi:10.1021/acs.jctc.0c00979.

Unzueta, Pablo A., Greenwell, Chandler S., & Beran, Gregory J. Predicting Density Functional Theory-Quality Nuclear Magnetic Resonance Chemical Shifts via Δ-Machine Learning. Journal of Chemical Theory and Computation, 17 (2). Retrieved from https://par.nsf.gov/biblio/10295841. https://doi.org/10.1021/acs.jctc.0c00979

Unzueta, Pablo A., Greenwell, Chandler S., and Beran, Gregory J. "Predicting Density Functional Theory-Quality Nuclear Magnetic Resonance Chemical Shifts via Δ-Machine Learning". Journal of Chemical Theory and Computation 17 (2). Country unknown/Code not available. https://doi.org/10.1021/acs.jctc.0c00979. https://par.nsf.gov/biblio/10295841.

@article{osti_10295841,
place = {Country unknown/Code not available}, title = {Predicting Density Functional Theory-Quality Nuclear Magnetic Resonance Chemical Shifts via Δ-Machine Learning}, url = {https://par.nsf.gov/biblio/10295841}, DOI = {10.1021/acs.jctc.0c00979}, abstractNote = {}, journal = {Journal of Chemical Theory and Computation}, volume = {17}, number = {2}, author = {Unzueta, Pablo A. and Greenwell, Chandler S. and Beran, Gregory J.}, editor = {null} }