Novitskiy, Ivan M., and Kutateladze, Andrei G. DU8ML: Machine Learning-Augmented Density Functional Theory Nuclear Magnetic Resonance Computations for High-Throughput In Silico Solution Structure Validation and Revision of Complex Alkaloids. Retrieved from https://par.nsf.gov/biblio/10337208. The Journal of Organic Chemistry 87.7 Web. doi:10.1021/acs.joc.2c00169.

Novitskiy, Ivan M., & Kutateladze, Andrei G. DU8ML: Machine Learning-Augmented Density Functional Theory Nuclear Magnetic Resonance Computations for High-Throughput In Silico Solution Structure Validation and Revision of Complex Alkaloids. The Journal of Organic Chemistry, 87 (7). Retrieved from https://par.nsf.gov/biblio/10337208. https://doi.org/10.1021/acs.joc.2c00169

Novitskiy, Ivan M., and Kutateladze, Andrei G. "DU8ML: Machine Learning-Augmented Density Functional Theory Nuclear Magnetic Resonance Computations for High-Throughput In Silico Solution Structure Validation and Revision of Complex Alkaloids". The Journal of Organic Chemistry 87 (7). Country unknown/Code not available. https://doi.org/10.1021/acs.joc.2c00169. https://par.nsf.gov/biblio/10337208.

@article{osti_10337208,
place = {Country unknown/Code not available}, title = {DU8ML: Machine Learning-Augmented Density Functional Theory Nuclear Magnetic Resonance Computations for High-Throughput In Silico Solution Structure Validation and Revision of Complex Alkaloids}, url = {https://par.nsf.gov/biblio/10337208}, DOI = {10.1021/acs.joc.2c00169}, abstractNote = {}, journal = {The Journal of Organic Chemistry}, volume = {87}, number = {7}, author = {Novitskiy, Ivan M. and Kutateladze, Andrei G.}, }