XGBoost, mordred and RDKit for the prediction of glass transition temperature of polymers
Glass transition temperature (Tg) is the temperature at which a polymer changes from crystalline state to rubbery state. This change in the property below and above Tg is very important in food science and pharmaceutical industries. In recent decades, there has been a growth in using machine learni...
Saved in:
Main Author: | Goh, Kai Leong |
---|---|
Other Authors: | Lu Yunpeng |
Format: | Student Research Paper |
Language: | English |
Published: |
Nanyang Technological University
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/155298 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Comparing the performances of glass transition temperatures prediction : SMILES vs. Molfile
by: Goh, Kai Leong
Published: (2022) -
Xgboost-based framework for smoking-induced noncommunicable disease prediction
by: Khishigsuren Davagdorj, et al.
Published: (2020) -
A stacked generalisation with gradient boosting for highly accurate predictions of polymer bandgap
by: Goh, Kai Leong
Published: (2022) -
Relationship of gelatinization and recrystallization of cross-linked rice to glass transition temperature
by: Pathama Chatakanonda, et al.
Published: (2018) -
Glass transition temperature influence on crosslinked and entangled polymer interfaces
by: Deng, M., et al.
Published: (2014)