Cite
Predicting the multiple parameters of organic acceptors through machine learning using RDkit descriptors: An easy and fast pipeline.
MLA
Katubi, Khadijah Mohammedsaleh, et al. “Predicting the Multiple Parameters of Organic Acceptors through Machine Learning Using RDkit Descriptors: An Easy and Fast Pipeline.” International Journal of Quantum Chemistry, vol. 123, no. 23, Dec. 2023, pp. 1–13. EBSCOhost, https://doi.org/10.1002/qua.27230.
APA
Katubi, K. M., Saqib, M., Mubashir, T., Tahir, M. H., Halawa, M. I., Akbar, A., Basha, B., Sulaman, M., Alrowaili, Z. A., & Al, B. M. S. (2023). Predicting the multiple parameters of organic acceptors through machine learning using RDkit descriptors: An easy and fast pipeline. International Journal of Quantum Chemistry, 123(23), 1–13. https://doi.org/10.1002/qua.27230
Chicago
Katubi, Khadijah Mohammedsaleh, Muhammad Saqib, Tayyaba Mubashir, Mudassir Hussain Tahir, Mohamed Ibrahim Halawa, Alveena Akbar, Beriham Basha, Muhammad Sulaman, Z. A. Alrowaili, and Buriahi, M. S. Al. 2023. “Predicting the Multiple Parameters of Organic Acceptors through Machine Learning Using RDkit Descriptors: An Easy and Fast Pipeline.” International Journal of Quantum Chemistry 123 (23): 1–13. doi:10.1002/qua.27230.