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Gels
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Functional Gel Materials: Chemistry, Processing, Mechanical Performance, and Applications
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Functional Gel Materials: Chemistry, Processing, Mechanical Performance, and Applications

A special issue of Gels (ISSN 2310-2861). This special issue belongs to the section "Gel Applications".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 3595

Special Issue Editors

Dr. Zhaohan Yu

E-Mail Website
Guest Editor
Department of Mechanical Engineering, Michigan State University, East Lansing, MI 48824, USA
Interests: hydrogels; 3d printing; elastocaloric polymers; energy conversion
Special Issues, Collections and Topics in MDPI journals
Dr. Xiaolin Qiu

E-Mail Website
Guest Editor
School of Mechanical Engineering, Jiangnan University, Wuxi 214122, China
Interests: smart hydrogels; functional packaging materials; active packaging system; thermal storage and heat transfer; energy-efficient equipment

Special Issue Information

Dear Colleagues,

The Special Issue, entitled “Functional Gel Materials: Chemistry, Processing, Mechanical Performance, and Applications” focuses on the development of functional gel materials with unique chemical or mechanical properties, offering significant potential for applications in tissue engineering, soft robots, drug delivery, energy-saving buildings, and so forth. The Special Issue aims to explore the latest advancements in the synthesis, characterization, mechanical performance, and innovative applications of functional gel materials for various applications. By emphasizing on molecular composition design, microstructural optimization, fabrication strategies, and functional customization, this Special Issue provides a comprehensive overview of how functional gels can revolutionize biomedical applications and sustainable construction. Contributions will explore the challenges, opportunities, and future possibilities for functional gel materials, highlighting their potential to make a real difference in a wide range of applications.

Overall, this Special Issue aims to provide an in-depth understanding of the recent advancements in and applications of gel materials. We hope that the research articles we publish contribute to the growing body of knowledge on gel materials and inspire further exploration and innovation in this exciting field.

Dr. Zhaohan Yu
Dr. Xiaolin Qiu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Gels is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2100 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • functional gel materials
  • gel synthesis
  • tough hydrogel
  • biomedical
  • energy harvesting
  • elastocaloric polymer
  • self-healing
  • flexible electronics

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

15 pages, 5319 KiB  
Article
Synthesis and Application of SAPO-11 Molecular Sieves Prepared from Reaction Gels with Various Templates in the Hydroisomerization of Hexadecane
by Dmitry V. Serebrennikov, Arthur R. Zabirov, Alexey N. Saliev, Roman E. Yakovenko, Tatyana R. Prosochkina, Zulfiya R. Fayzullina, Vladimir Yu. Guskov, Boris I. Kutepov and Marat R. Agliullin
Gels 2024, 10(12), 792; https://doi.org/10.3390/gels10120792 - 4 Dec 2024
Cited by 1 | Viewed by 1263
Abstract
Among the most selective catalytic systems for the hydroisomerization of C16+ n-paraffins, catalytic systems based on SAPO-11 are quite promising. In order to increase the activity and selectivity of these bifunctional catalysts, it is necessary to reduce the diffusion restrictions [...] Read more.
Among the most selective catalytic systems for the hydroisomerization of C16+ n-paraffins, catalytic systems based on SAPO-11 are quite promising. In order to increase the activity and selectivity of these bifunctional catalysts, it is necessary to reduce the diffusion restrictions for the reacting molecules and their products in the microporous structure of SAPO-11 by reducing the crystal size. To solve this problem, we have studied the influence of different templates (diethylamine, dipropylamine, diisopropylamine, and dibutylamine) on the physicochemical properties of reaction gels and SAPO-11 silicoaluminophosphates during their crystallization. Using XRD, SEM, and NMR techniques, we found that regardless of the template used, the reaction gel after the aging process at 90 °C is an AlPO4·2H2O hydroaluminophosphate. At the same time, the nature of the template affects the morphology and crystal sizes of the intermediate alumophosphate, AlPO4·2H2O, and the molecular sieves, SAPO-11. The acidic properties and the porous structure characteristics of SAPO-11 are also affected by the template. A template was proposed to enable the synthesis of nanoscale SAPO-11 crystals. The influence of the morphology and crystal size of SAPO-11 on the catalytic properties of a bifunctional catalyst based on SAPO-11 in the hydroisomerization of hexadecane was investigated. Full article
(This article belongs to the Special Issue Functional Gel Materials: Chemistry, Processing, Mechanical Performance, and Applications)
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13 pages, 2636 KiB  
Article
Leveraging Deep Learning and Generative AI for Predicting Rheological Properties and Material Compositions of 3D Printed Polyacrylamide Hydrogels
by Sakib Mohammad, Rafee Akand, Kaden M. Cook, Sabrina Nilufar and Farhan Chowdhury
Gels 2024, 10(10), 660; https://doi.org/10.3390/gels10100660 - 15 Oct 2024
Cited by 3 | Viewed by 1985
Abstract
Artificial intelligence (AI) has the ability to predict rheological properties and constituent composition of 3D-printed materials with appropriately trained models. However, these models are not currently available for use. In this work, we trained deep learning (DL) models to (1) predict the rheological [...] Read more.
Artificial intelligence (AI) has the ability to predict rheological properties and constituent composition of 3D-printed materials with appropriately trained models. However, these models are not currently available for use. In this work, we trained deep learning (DL) models to (1) predict the rheological properties, such as the storage (G’) and loss (G”) moduli, of 3D-printed polyacrylamide (PAA) substrates, and (2) predict the composition of materials and associated 3D printing parameters for a desired pair of G’ and G”. We employed a multilayer perceptron (MLP) and successfully predicted G’ and G” from seven gel constituent parameters in a multivariate regression process. We used a grid-search algorithm along with 10-fold cross validation to tune the hyperparameters of the MLP, and found the R2 value to be 0.89. Next, we adopted two generative DL models named variational autoencoder (VAE) and conditional variational autoencoder (CVAE) to learn data patterns and generate constituent compositions. With these generative models, we produced synthetic data with the same statistical distribution as the real data of actual hydrogel fabrication, which was then validated using Student’s t-test and an autoencoder (AE) anomaly detector. We found that none of the seven generated gel constituents were significantly different from the real data. Our trained DL models were successful in mapping the input–output relationship for the 3D-printed hydrogel substrates, which can predict multiple variables from a handful of input variables and vice versa. Full article
(This article belongs to the Special Issue Functional Gel Materials: Chemistry, Processing, Mechanical Performance, and Applications)
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