Machine learning for melting temperature predictions and design in polyhydroxyalkanoate-based biopolymers

KK Bejagam, J Lalonde, CN Iverson… - The Journal of …, 2022 - ACS Publications
Diminishing fossil fuel-based resources and ever-growing environmental concerns related
to plastic pollution demand for the development of sustainable and biodegradable polymeric …

Machine-learning-based predictive modeling of glass transition temperatures: a case of polyhydroxyalkanoate homopolymers and copolymers

G Pilania, CN Iverson, T Lookman… - Journal of Chemical …, 2019 - ACS Publications
Polyhydroxyalkanoate-based polymers—being ecofriendly, biosynthesizable, and
economically viable and possessing a broad range of tunable properties—are currently …

Multitask Neural Network for Mapping the Glass Transition and Melting Temperature Space of Homo- and Co-Polyhydroxyalkanoates Using σProfiles Molecular …

A Boublia, T Lemaoui, J AlYammahi… - ACS Sustainable …, 2022 - ACS Publications
Polyhydroxyalkanoates (PHAs) are an emerging type of bioplastic that have the potential to
replace petroleum-based plastics. They are biosynthetizable, biodegradable, and …

Molecular dynamics simulations for glass transition temperature predictions of polyhydroxyalkanoate biopolymers

KK Bejagam, CN Iverson, BL Marrone… - Physical Chemistry …, 2020 - pubs.rsc.org
Polyhydroxyalkanoates (PHAs) represent an emerging class of biosynthetic and
biodegradable polyesters that exhibit considerable potential to replace petroleum-based …

[HTML][HTML] A deep neural network for accurate and robust prediction of the glass transition temperature of polyhydroxyalkanoate homo-and copolymers

Z Jiang, J Hu, BL Marrone, G Pilania, X Yu - Materials, 2020 - mdpi.com
The purpose of this study was to develop a data-driven machine learning model to predict
the performance properties of polyhydroxyalkanoates (PHAs), a group of biosourced …

Composition and configuration dependence of glass-transition temperature in binary copolymers and blends of polyhydroxyalkanoate biopolymers

KK Bejagam, CN Iverson, BL Marrone… - Macromolecules, 2021 - ACS Publications
Polyhydroxyalkanoates (PHAs), a promising class of biomaterials, have gained
considerable attention to replace petroleum-based plastics owing to their excellent …

Polymer informatics beyond homopolymers

SS Shukla, C Kuenneth, R Ramprasad - MRS Bulletin, 2024 - Springer
Polymers are diverse and versatile materials that have met a wide range of material
application demands. They come in several flavors and architectures (eg, homopolymers …

[HTML][HTML] Bioplastic design using multitask deep neural networks

C Kuenneth, J Lalonde, BL Marrone… - Communications …, 2022 - nature.com
Non-degradable plastic waste jeopardizes our environment, yet our modern lifestyle and
current technologies are impossible to sustain without plastics. Bio-synthesized and …

[HTML][HTML] Predicting the mechanical response of polyhydroxyalkanoate biopolymers using molecular dynamics simulations

KK Bejagam, NS Gupta, KS Lee, CN Iverson… - Polymers, 2022 - mdpi.com
Polyhydroxyalkanoates (PHAs) have emerged as a promising class of biosynthesizable,
biocompatible, and biodegradable polymers to replace petroleum-based plastics for …

[PDF][PDF] Machine learning discovery of high-temperature polymers

L Tao, G Chen, Y Li - Patterns, 2021 - cell.com
To formulate a machine learning (ML) model to establish the polymer's structure-property
correlation for glass transition temperature T g, we collect a diverse set of nearly 13,000 real …