APA (7th ed.) Citation

Acosta-Angulo, B., Lara-Ramos, J., Niño-Vargas, A., Diaz-Angulo, J., Benavides-Guerrero, J., Bhattacharya, A., . . . Machuca-Martínez, F. (2024). Unveiling the potential of machine learning in cost-effective degradation of pharmaceutically active compounds: A stirred photo-reactor study. Chemosphere, 358, N.PAG. https://doi.org/10.1016/j.chemosphere.2024.142222

Chicago Style (17th ed.) Citation

Acosta-Angulo, B., J. Lara-Ramos, A. Niño-Vargas, J. Diaz-Angulo, J. Benavides-Guerrero, A. Bhattacharya, S. Cloutier, and F. Machuca-Martínez. "Unveiling the Potential of Machine Learning in Cost-effective Degradation of Pharmaceutically Active Compounds: A Stirred Photo-reactor Study." Chemosphere 358 (2024): N.PAG. https://doi.org/10.1016/j.chemosphere.2024.142222.

MLA (9th ed.) Citation

Acosta-Angulo, B., et al. "Unveiling the Potential of Machine Learning in Cost-effective Degradation of Pharmaceutically Active Compounds: A Stirred Photo-reactor Study." Chemosphere, vol. 358, 2024, p. N.PAG, https://doi.org/10.1016/j.chemosphere.2024.142222.