Ibarra-Pérez, D.; Faba, S.; Hernández-Muñoz, V.; Smith, C.; Galotto, M.J.; Garmulewicz, A.
Predicting the Composition and Mechanical Properties of Seaweed Bioplastics from the Scientific Literature: A Machine Learning Approach for Modeling Sparse Data. Appl. Sci. 2023, 13, 11841.
https://doi.org/10.3390/app132111841
AMA Style
Ibarra-Pérez D, Faba S, Hernández-Muñoz V, Smith C, Galotto MJ, Garmulewicz A.
Predicting the Composition and Mechanical Properties of Seaweed Bioplastics from the Scientific Literature: A Machine Learning Approach for Modeling Sparse Data. Applied Sciences. 2023; 13(21):11841.
https://doi.org/10.3390/app132111841
Chicago/Turabian Style
Ibarra-Pérez, Davor, Simón Faba, Valentina Hernández-Muñoz, Charlene Smith, MarÃa José Galotto, and Alysia Garmulewicz.
2023. "Predicting the Composition and Mechanical Properties of Seaweed Bioplastics from the Scientific Literature: A Machine Learning Approach for Modeling Sparse Data" Applied Sciences 13, no. 21: 11841.
https://doi.org/10.3390/app132111841
APA Style
Ibarra-Pérez, D., Faba, S., Hernández-Muñoz, V., Smith, C., Galotto, M. J., & Garmulewicz, A.
(2023). Predicting the Composition and Mechanical Properties of Seaweed Bioplastics from the Scientific Literature: A Machine Learning Approach for Modeling Sparse Data. Applied Sciences, 13(21), 11841.
https://doi.org/10.3390/app132111841
