Comparison of Machine Learning Methods towards Developing Interpretable Polyamide Property Prediction
Polyamides are often used for their superior thermal, mechanical, and chemical properties. They form a diverse set of materials that have a large variation in properties between linear to aromatic compounds, which renders the traditional quantitative structure–property relationship (QSPR) challengin...
Guardado en:
Autores principales: | Franklin Langlang Lee, Jaehong Park, Sushmit Goyal, Yousef Qaroush, Shihu Wang, Hong Yoon, Aravind Rammohan, Youngseon Shim |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
MDPI AG
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/ee58647ad139413381d2a2c9efa14436 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Manufacturing and Analysis of Overmolded Hybrid Fiber Polyamide 6 Composite
por: Heru S. B. Rochardjo, et al.
Publicado: (2021) -
Effect of humidity on diameter of polyamide 6 nanofiber in electrospinning process
por: Kazuto TANAKA, et al.
Publicado: (2016) -
Aromatic polyamide nonporous membranes for gas separation application
por: Bera Debaditya, et al.
Publicado: (2021) -
APPLICATION OF MULTIVARIATE IMAGE ANALYSIS IN QSPR STUDY OF pKa OF VARIOUS ACIDS BY PRINCIPAL COMPONENTS-LEAST SQUARES SUPPORT VECTOR MACHINE
por: VEYSEH,SOMAYEH, et al.
Publicado: (2015) -
Polydopamine-induced hydroxyapatite coating facilitates hydroxyapatite/polyamide 66 implant osteogenesis: an in vitro and in vivo evaluation
por: Xu Y, et al.
Publicado: (2018)