Predicting effect of fibers on thermal gelation of methylcellulose using Bayesian optimization

Isaac Yair Miranda-Valdez; Leevi Viitanen; Jonatan Mac Intyre; Antti Puisto; Juha Koivisto; Mikko Alava

doi:10.1016/j.carbpol.2022.119921

Predicting effect of fibers on thermal gelation of methylcellulose using Bayesian optimization

Isaac Yair Miranda-Valdez, Leevi Viitanen (Corresponding Author), Jonatan Mac Intyre, Antti Puisto, Juha Koivisto, Mikko Alava

BA5510 ProperTune Soft Condensed Materials

Research output: Contribution to journal › Article › Scientific › peer-review

Abstract

Understanding of the viscoelastic behavior of a polymer is a prerequisite for its thermomechanical processing beyond laboratory scale. Utilizing rheological characterization is a powerful tool to comprehend the complex nature and time-dependent properties of macromolecular materials. Nevertheless, it consumes time as rheometry involves iterating experiments under several conditions to visualize the non-linear behavior of materials under varying conditions. The work hereunder examines the rheology of cellulosic aqueous suspensions prepared using cellulose fibers as the dispersed phase (Refcell and Storacell) and methylcellulose (MC) as the polymeric matrix. Interfacial phenomena between MC and cellulose fibers arise in particle laden systems with supramolecular structures formed by non-covalent interactions. Therefore, this study elucidates the rheological evolution of these interactions as a function of temperature and fiber concentration. This study displays how researchers may reduce the number of rheological experiments and save time utilizing a novel method based on a Bayesian optimization with Gaussian processes.

Original language	English
Article number	119921
Journal	Carbohydrate Polymers
Volume	298
DOIs	https://doi.org/10.1016/j.carbpol.2022.119921
Publication status	Published - 15 Dec 2022
MoE publication type	A1 Journal article-refereed

Keywords

Bayesian optimization
Fibers
Methylcellulose
Rheology

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10.1016/j.carbpol.2022.119921

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@article{d0ade20840a7401080524786ac239846,

title = "Predicting effect of fibers on thermal gelation of methylcellulose using Bayesian optimization",

abstract = "Understanding of the viscoelastic behavior of a polymer is a prerequisite for its thermomechanical processing beyond laboratory scale. Utilizing rheological characterization is a powerful tool to comprehend the complex nature and time-dependent properties of macromolecular materials. Nevertheless, it consumes time as rheometry involves iterating experiments under several conditions to visualize the non-linear behavior of materials under varying conditions. The work hereunder examines the rheology of cellulosic aqueous suspensions prepared using cellulose fibers as the dispersed phase (Refcell and Storacell) and methylcellulose (MC) as the polymeric matrix. Interfacial phenomena between MC and cellulose fibers arise in particle laden systems with supramolecular structures formed by non-covalent interactions. Therefore, this study elucidates the rheological evolution of these interactions as a function of temperature and fiber concentration. This study displays how researchers may reduce the number of rheological experiments and save time utilizing a novel method based on a Bayesian optimization with Gaussian processes.",

keywords = "Bayesian optimization, Fibers, Methylcellulose, Rheology",

author = "Miranda-Valdez, {Isaac Yair} and Leevi Viitanen and {Mac Intyre}, Jonatan and Antti Puisto and Juha Koivisto and Mikko Alava",

note = "Funding Information: J. K. acknowledges funding from Academy of Finland (308235). M. J. A. A. P. and J. K. acknowledge support from FinnCERES flagship (151830423), Business Finland (211835) and Future Makers programs. L. V. acknowledges funding from the Vilho, Yrj{\"o}, and Kalle V{\"a}is{\"a}l{\"a} Foundation via personal grants. Authors acknowledge Aalto Science IT project for computational resources. Funding Information: J. K. acknowledges funding from Academy of Finland ( 308235 ). M. J. A., A. P. and J. K. acknowledge support from FinnCERES flagship ( 151830423 ), Business Finland ( 211835 ) and Future Makers programs. L. V. acknowledges funding from the Vilho, Yrj{\"o}, and Kalle V{\"a}is{\"a}l{\"a} Foundation via personal grants. Authors acknowledge Aalto Science IT project for computational resources. Publisher Copyright: {\textcopyright} 2022",

year = "2022",

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doi = "10.1016/j.carbpol.2022.119921",

language = "English",

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journal = "Carbohydrate Polymers",

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T1 - Predicting effect of fibers on thermal gelation of methylcellulose using Bayesian optimization

AU - Miranda-Valdez, Isaac Yair

AU - Viitanen, Leevi

AU - Mac Intyre, Jonatan

AU - Puisto, Antti

AU - Koivisto, Juha

AU - Alava, Mikko

N1 - Funding Information: J. K. acknowledges funding from Academy of Finland (308235). M. J. A. A. P. and J. K. acknowledge support from FinnCERES flagship (151830423), Business Finland (211835) and Future Makers programs. L. V. acknowledges funding from the Vilho, Yrjö, and Kalle Väisälä Foundation via personal grants. Authors acknowledge Aalto Science IT project for computational resources. Funding Information: J. K. acknowledges funding from Academy of Finland ( 308235 ). M. J. A., A. P. and J. K. acknowledge support from FinnCERES flagship ( 151830423 ), Business Finland ( 211835 ) and Future Makers programs. L. V. acknowledges funding from the Vilho, Yrjö, and Kalle Väisälä Foundation via personal grants. Authors acknowledge Aalto Science IT project for computational resources. Publisher Copyright: © 2022

PY - 2022/12/15

Y1 - 2022/12/15

N2 - Understanding of the viscoelastic behavior of a polymer is a prerequisite for its thermomechanical processing beyond laboratory scale. Utilizing rheological characterization is a powerful tool to comprehend the complex nature and time-dependent properties of macromolecular materials. Nevertheless, it consumes time as rheometry involves iterating experiments under several conditions to visualize the non-linear behavior of materials under varying conditions. The work hereunder examines the rheology of cellulosic aqueous suspensions prepared using cellulose fibers as the dispersed phase (Refcell and Storacell) and methylcellulose (MC) as the polymeric matrix. Interfacial phenomena between MC and cellulose fibers arise in particle laden systems with supramolecular structures formed by non-covalent interactions. Therefore, this study elucidates the rheological evolution of these interactions as a function of temperature and fiber concentration. This study displays how researchers may reduce the number of rheological experiments and save time utilizing a novel method based on a Bayesian optimization with Gaussian processes.

AB - Understanding of the viscoelastic behavior of a polymer is a prerequisite for its thermomechanical processing beyond laboratory scale. Utilizing rheological characterization is a powerful tool to comprehend the complex nature and time-dependent properties of macromolecular materials. Nevertheless, it consumes time as rheometry involves iterating experiments under several conditions to visualize the non-linear behavior of materials under varying conditions. The work hereunder examines the rheology of cellulosic aqueous suspensions prepared using cellulose fibers as the dispersed phase (Refcell and Storacell) and methylcellulose (MC) as the polymeric matrix. Interfacial phenomena between MC and cellulose fibers arise in particle laden systems with supramolecular structures formed by non-covalent interactions. Therefore, this study elucidates the rheological evolution of these interactions as a function of temperature and fiber concentration. This study displays how researchers may reduce the number of rheological experiments and save time utilizing a novel method based on a Bayesian optimization with Gaussian processes.

KW - Bayesian optimization

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KW - Methylcellulose

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Predicting effect of fibers on thermal gelation of methylcellulose using Bayesian optimization

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Keywords

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