Machine learning approach for prediction of the grafting yield in radiation-induced graft polymerization

Ueki, Yuji; Seko, Noriaki; Maekawa, Yasunari

doi:10.1016/j.apmt.2021.101158

Cited by 16 publications

(18 citation statements)

References 37 publications

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“…All graft polymerization data were already published in a paper and used in this study as reported. 25 Scheme 3 provides an overview of the RIGP process to guide the selection of the explanatory variables. As depicted in Scheme 3, the RIGP process should involve the following three important steps, even though the individual contribution cannot be accounted for.…”

Section: Selection Of the Explanatory Variablesmentioning

confidence: 99%

“…As such, some of the authors reported a ground-breaking study on the machine learning model building aiming at RIGP reactivity prediction. 25 A machine learning model was constructed using the experimental reactivity of graft polymerization as a predictor variable. Furthermore, various calculated values that can be derived from quantum chemical calculations of the vinyl 4 monomers were employed as explanatory variables.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Building Machine Learning Models for Reactivity Prediction in Radiation-Induced Graft Polymerization Using Interpretable Parameters

Matsubara

Takahashi

Matsuda

et al. 2023

Preprint

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Machine learning prediction models for radiation-induced graft polymerization reactivity of methacrylate monomers were feasibly built with chemically interpretable parameters. The reactivity can be predicted based on the decision-tree-based machine learning algorithms. Among these algorithms, the XGBoost algorithm exhibited a good performance using five interpretable parameters: the solvation free energy of the methacrylate monomer in water, solvation free energy of the methacrylate monomer in hexane, methacrylate monomer radius, conformational entropy of the methacrylate monomers, and the dipole moments of the methacrylate monomers. The machine learning model building resulted in effective reactivity predictions and unveiled important factors for the radiation-induced graft polymerization in a chemically interpretable fashion.

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Section: Selection Of the Explanatory Variablesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Building Machine Learning Models for Reactivity Prediction in Radiation-Induced Graft Polymerization Using Interpretable Parameters

Matsubara

Takahashi

Matsuda

et al. 2023

Preprint

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show abstract

“…Besides, ML can be utilized to predict the grafting yield in radiation-induced graft polymerization reactions. It can also help to determine the accuracy of grafting yield prediction and the relevance of parameters of monomers [168].…”

Section: Challenges and Future Directionmentioning

confidence: 99%

Surface Design of Liquid Separation Membrane through Graft Polymerization: A State of the Art Review

et al. 2021

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Surface modification of membranes is an effective approach for imparting unique characteristics and additional functionalities to the membranes. Chemical grafting is a commonly used membrane modification technique due to its versatility in tailoring and optimizing the membrane surface with desired functionalities. Various types of polymers can be precisely grafted onto the membrane surface and the operating conditions of grafting can be tailored to further fine-tune the membrane surface properties. This review focuses on the recent strategies in improving the surface design of liquid separation membranes through grafting-from technique, also known as graft polymerization, to improve membrane performance in wastewater treatment and desalination applications. An overview on membrane technology processes such as pressure-driven and osmotically driven membrane processes are first briefly presented. Grafting-from surface chemical modification approaches including chemical initiated, plasma initiated and UV initiated approaches are discussed in terms of their features, advantages and limitations. The innovations in membrane surface modification techniques based on grafting-from techniques are comprehensively reviewed followed by some highlights on the current challenges in this field. It is concluded that grafting-from is a versatile and effective technique to introduce various functional groups to enhance the surface properties and separation performances of liquid separation membranes.

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“…Based on their design structure, the changed materials can be applied in a wide variety of applications. RIG polymerization is a method of designing and developing additional functionality for polymer materials while maintaining the shape and physical qualities of the trunk polymer [2] [3]. Apart from that, while utilizing RIG polymerization to transfer functional groups to polymers, there is no unnecessary use of chemicals or catalysts.…”

Section: Introductionmentioning

confidence: 99%

“…Because it demonstrates the presence of a significant number of monomer functions in the trunk polymer, a higher grafting yield suggested the superiority of the functional materials. Apart from being associated with its application, the grafted polymer with a high grafting yield is the most desired while producing the polymer [2].…”

Section: Introductionmentioning

confidence: 99%

Modified Surface Polymer Prepared by using Radiation-Induced Grafting Co-polymerization Method and Its Application: A Mini Review

Seman

Tarmizi

Ali

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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The use of radiation-induced grafting (RIG) polymerization techniques is an appealing way to create and develop polymerization of polymer. The method of copolymerization preparation was evaluated in this paper based on the types of radiation-induced grafting polymerization and their prospective applications. Based on the method of preparation, the optimum grafting yield of the monomer in the polymer backbone is described. The approach used to summarise this review was to go through polymer-related papers from the science direct online database from 2010 to 2021. Then, from those selected journals, the technique of preparation, the grafting yield, and the application were reviewed. Furthermore, the majority of researchers from reviewed journals employed gamma irradiation to prepare the modified polymer, followed by electron beam irradiation, plasma irradiation and UV irradiation. Gamma irradiation is popular because it has a better penetration rate and generates a purer result. As a result of this review paper, the radiation-induced graft polymer from the conducted study is ideal for use in biomedical applications, as a material for wastewater treatment fibre membranes, as an absorbent, and as a gas remover.

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Machine learning approach for prediction of the grafting yield in radiation-induced graft polymerization

Cited by 16 publications

References 37 publications

Building Machine Learning Models for Reactivity Prediction in Radiation-Induced Graft Polymerization Using Interpretable Parameters

Building Machine Learning Models for Reactivity Prediction in Radiation-Induced Graft Polymerization Using Interpretable Parameters

Surface Design of Liquid Separation Membrane through Graft Polymerization: A State of the Art Review

Modified Surface Polymer Prepared by using Radiation-Induced Grafting Co-polymerization Method and Its Application: A Mini Review

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