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Relevant bibliographies by topics / Double-network gel

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Academic literature on the topic 'Double-network gel'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 February 2022

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Journal articles on the topic "Double-network gel"

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Shigetomi, Shutaro, Haruna Takahashi, and Fujio Tsumori. "Magnetic Actuator Using Double Network Gel." Journal of Photopolymer Science and Technology 33, no. 2 (July 1, 2020): 193–97. http://dx.doi.org/10.2494/photopolymer.33.193.

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Wang, Xiao, and Wei Hong. "Pseudo-elasticity of a double network gel." Soft Matter 7, no. 18 (2011): 8576. http://dx.doi.org/10.1039/c1sm05787a.

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Chee, Pei Lin, Lakshmi Lakshmanan, Shan Jiang, Hongye Ye, Dan Kai, and Xian Jun Loh. "An Injectable Double-Network Hydrogel for Cell Encapsulation." Australian Journal of Chemistry 69, no. 4 (2016): 388. http://dx.doi.org/10.1071/ch15659.

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Further developing on the technique originally intended for the purpose of forming tough hydrogels, we showed in this study that the double-network system can also be used to synthesize an injectable gel. The gel was made up of poly(ethylene glycol) methyl ether methacrylate, sodium alginic acid, and calcium chloride, and two networks, consisting of ionic and covalent networks, were found to co-exist in the gel. Additionally, the rheology studies showed that the mechanical properties of the gel only deteriorated under high strain, demonstrating the robustness of the gel upon injection. The results of a cell cytotoxicity test and a preliminary cell encapsulation study were promising, showing good cell compatibility and thus suggesting that the hydrogels could potentially be used for cell delivery.

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Yao, Weiwei, Chengzhen Geng, Di Han, Feng Chen, and Qiang Fu. "Strong and conductive double-network graphene/PVA gel." RSC Adv. 4, no. 74 (August 15, 2014): 39588. http://dx.doi.org/10.1039/c4ra02674h.

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Wang, Hai-Wang, Tian-Bo Zhao, Guo-Zhong Lu, Shuai Zhang, Ce Miao, Xin-Fang Weia, and Feng-Yan Li. "Novel Micro/nanostructures from a Double Network Gel." Journal of the Chinese Chemical Society 58, no. 3 (June 2011): 282–85. http://dx.doi.org/10.1002/jccs.201190025.

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HASHIMOTO, Masaaki, Masashi UEDA, Isamu RIKU, and Koji MIMURA. "Study on High Strengthening of Double Network Gel." Proceedings of Conference of Kansai Branch 2017.92 (2017): M822. http://dx.doi.org/10.1299/jsmekansai.2017.92.m822.

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Chen, Jian, Yinyong Ao, Tingrui Lin, Xin Yang, Jing Peng, Wei Huang, Jiuqiang Li, and Maolin Zhai. "High-toughness polyacrylamide gel containing hydrophobic crosslinking and its double network gel." Polymer 87 (March 2016): 73–80. http://dx.doi.org/10.1016/j.polymer.2016.01.069.

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Arafune, Hiroyuki, Fumiya Muto, Toshio Kamijo, Saika Honma, Takashi Morinaga, and Takaya Sato. "Tribological Properties of Double-Network Gels Substituted by Ionic Liquids." Lubricants 6, no. 4 (October 8, 2018): 89. http://dx.doi.org/10.3390/lubricants6040089.

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Since human body joints have a gel-like structure with low friction that persists for several decades, hydrogels have attracted much interest for developing low-friction materials. However, such advantages can hardly be realized in industrial usage because water in the gel evaporates easily and the gel deswells. The substitution of water with an ionic liquid (IL) is one of the effective ways to overcome this problem. In this study, we substituted water in a double network (DN) hydrogel with 3-ethyl-1-methyl-imidazolium ethylsulfate (EMI-EtSulf), a hydrophilic IL, via a simple solvent exchange method to obtain a DN ion gel. A compressive test and thermogravimetric analysis showed that the DN ion gel has a high compression fracture stress and improved thermal properties, with the difference in 10% loss of temperature being ΔT10 = 234 °C. A friction test conducted using a reciprocating tribometer showed that the friction of a glass ball/DN ion gel was relatively higher than that of a glass ball/DN hydrogel. Because the minimum coefficient of friction (COF) value increased after substitution, the increase in polymer adhesion caused by the electrostatic shielding of the surface moieties of glass and poly 2-acrylamidomethylpropanesulfonic acid (PAMPS) was considered the main contributor to the high friction. As the COF value decreased with increasing temperature, the DN ion gel can achieve low friction via the restriction of polymer adhesion at high temperatures, which is difficult in the DN hydrogel owing to drying.

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Arafune, Hiroyuki, Saika Honma, Takashi Morinaga, Toshio Kamijo, Miki Miura, Hidemitsu Furukawa, and Takaya Sato. "Highly Robust and Low Frictional Double-Network Ion Gel." Advanced Materials Interfaces 4, no. 9 (March 21, 2017): 1700074. http://dx.doi.org/10.1002/admi.201700074.

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Li, Jie, Xiuchen Li, Zhaohui Zheng, and Xiaobin Ding. "A dynamic self-regulation actuator combined double network gel with gradient structure driven by chemical oscillating reaction." RSC Advances 9, no. 23 (2019): 13168–72. http://dx.doi.org/10.1039/c9ra02340b.

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Dissertations / Theses on the topic "Double-network gel"

1

Chen, Yan. "Investigation of Single and Double Network Gels by Maximum Bubble Pressure Rheology." University of Akron / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=akron1418329369.

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Singh, Nishant. "Functional gels as microreactors." Doctoral thesis, Universitat Jaume I, 2016. http://hdl.handle.net/10803/397698.

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Functionalized Hydrogels upon self-assembly demonslrate enzyme like catalysis owing to the formatin of hydrophobic pockets, increased local concentration of the catalytic sites, pKa change, pH shift etc. Here we present such hydrogelators being able to demonstrate enhanced catalysis for a range of reactions such as aldol, mannich, ester hydrolysis, deacetalisation etc.
Hidrogelantes funcionalizados sobre autoensamblaje pueden demostrar como la catálisis enzimática mejorada basada en varios factores tales como bolsillos hidrofóbicos, cambio en pH, cambio en pKa, aumento en la concentración local de los sitios activos etc. Aquí presentamos tales tipos de hidrogelantes que son capaces de demostrar varios tipos de reacciones importantes como aldolica, Mannicli, hidrolisis, deactetalisation, etc.

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Book chapters on the topic "Double-network gel"

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Wang, Chuang, Dongming Bian, Xingchen Xu, Jian Cheng, and Feilong Li. "Design of GEO/LEO Double-Layered Satellite Network Based on Rateless Code for Global Information Distribution." In Wireless and Satellite Systems, 13–24. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-19153-5_2.

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Conference papers on the topic "Double-network gel"

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Ahmed, Kumkum, Tomoya Higashihara, Hiroyuki Arafune, Toshio Kamijo, Takashi Morinaga, Takaya Sato, and Hidemitsu Furukawa. "Ionic liquid based multifunctional double network gel." In SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, edited by Nakhiah C. Goulbourne. SPIE, 2015. http://dx.doi.org/10.1117/12.2084160.

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Wang, Jilong, and Jenny Qiu. "Graphene Oxide Reinforced Double Network Hydrogel." In ASME 2016 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/imece2016-67729.

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In this paper, to improve the mechanical properties of calcium alginate/polyacrylamide double network hydrogel, the graphene oxide is introduced as a nano-reinfrocer in the naocomposite gel. In addition, the swelling property of gels is suppressed with GO.

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Morovati, Vahid, Mohammad Ali Saadat, and Roozbeh Dargazany. "Modelling Stress Softening and Necking Phenomena in Double Network Hydrogels." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-12253.

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Abstract Double network (DN) gels are three-dimensional polymer matrices formed by interpenetrating networks. In contrast to the conventional single-network gels, DN gels have significant toughness, which makes them a promising material for different biomedical and biological applications. However, DN gels show complicated inelastic behavior including the Mullins effect and necking instability. Despite extensive efforts on modelling different aspects of the damage process in gels, the micro-mechanical modelling of the mechanisms that lead to necking in DN gels remains to be a challenging task. Here, a constitutive model is proposed to understand and describe the mechanical behavior of DN gels based on statistical micro-mechanics of interpenetrating polymer networks. DN gels behavior is divided into three parts including pre-necking, necking, and hardening. The first network is dominant in the response of the gel in the pre-necking stage. The breakage of the first network to smaller network fractions (clusters) induces the stress softening observed in this stage. The interaction of both networks and the second network are also considered as main contributors to the response of gel in necking and hardening stages, respectively. The contribution of clusters decreases during the necking as the second network starts hardening. The numerical results of the proposed model are validated and compared by uni-axial cyclic tensile experimental data of DN gels.

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Abe, Mei, Masanori Arai, Azusa Saito, Kazuyuki Sakai, Masaru Kawakami, and Hidemitsu Furukawa. "Internal structure analysis of particle-double network gels used in a gel organ replica." In SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, edited by Vijay K. Varadan. SPIE, 2016. http://dx.doi.org/10.1117/12.2218235.

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Yahagi, Hikaru, Masato Wada, Kazunari Yoshida, Ajit Khosla, Masaru Kawakami, and Hidemitsu Furukawa. "Development of double network gel ring and evaluation of friction properties." In Nano-, Bio-, Info-Tech Sensors and 3D Systems, edited by Vijay K. Varadan. SPIE, 2018. http://dx.doi.org/10.1117/12.2296454.

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Morovati, Vahid, and Roozbeh Dargazany. "Micro-Mechanical Modeling of the Stress Softening in Double-Network Hydrogels." In ASME 2018 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/imece2018-88252.

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While single network hydrogels show limited extensibility and low strength, double-network hydrogels benefit from significantly high stretchability and toughness due to their reinforcing mechanism of combining two soft and rigid networks. Here, a micro-mechanical model is developed to characterize the constitutive behavior of DN hydrogels in quasi-static large deformation. In particular, we focused on describing the permanent damage in DN gels under large deformations. Irreversible chain detachment and decomposition of the first network are explored as the underlying reasons for the nonlinear inelastic phenomenon. The proposed model enables us to describe the damage and the way it influences the micro-structure of the gel. The model is validated with uni-axial loading and unloading experiments of DN gels. The proposed model contains a few numbers of material constants and shows a good agreement with cyclic uni-axial test data.

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FUKUNAGA, M., M. TAKESADA, A. ONODERA, R. KUWADARA, J. P. GONG, Y. OSADA, and T. YAGI. "LIGHT SCATTERING STUDY IN DOUBLE NETWORK GELS." In Proceedings of the International Symposium. WORLD SCIENTIFIC, 2007. http://dx.doi.org/10.1142/9789812708687_0013.

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8

Wada, Masato, Jin Gong, Masato Makino, Muhamado H. Kabir, and Hidemitsu Furukawa. "Surface Friction of Double Network Gels and Shape Memory Gels." In Proceedings of the 12th Asia Pacific Physics Conference (APPC12). Journal of the Physical Society of Japan, 2014. http://dx.doi.org/10.7566/jpscp.1.012042.

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9

Morovati, Vahid, and Roozbeh Dargazany. "Modelling Damage Accumulation During Cyclic Loading in Elastomeric Gels With Interpenetrating Networks." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-11931.

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Abstract Double network (DN) elastomers are a class of reinforced gels that benefit from a significantly high stretch-ability and toughness. However, DN gels lose their toughness due to the accumulation of damage under cyclic loading during their lifetime. While recent advances in the process and characterization of the DN gels have led to significant improvements in their properties, our understandings of the accumulated damage mechanisms within the material remain sparse and inconclusive. Here, a physically motivated constitutive model is presented for DN gels subjected to a high number of cyclic deformations, which will eventually approach a steady-state after thousands of cycles. The model can be particularly used to elucidate the inelastic features, such as permanent damage during deformation of each cycle. The observed damage may be induced from the chain scission, chain slippage, or polymer relaxation. Therefore, irreversible chain detachment and decomposition of the first network due to its highly cross-linked structure are explored as the underlying reasons for the nonlinear stress softening phenomenon. The model is validated against the experimental tests. The model contains a few numbers of material constants and shows good agreement with cyclic uni-axial tensile test data.

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Yoon, Jae Eun, Jong Joon Lee, Tong Seop Kim, and Jeong Lak Sohn. "Simulation of Performance Deterioration of a Microturbine and Application of Neural Network to Its Performance Diagnosis." In ASME Turbo Expo 2008: Power for Land, Sea, and Air. ASMEDC, 2008. http://dx.doi.org/10.1115/gt2008-51494.

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This study aims to simulate performance deterioration of a microturbine and apply artificial neural network to its performance diagnosis. As it is hard to obtain test data with degraded component performance, the degraded engine data have been acquired through simulation. Artificial neural network is adopted as the diagnosis tool. First, the microturbine has been tested to get reference operation data, assumed to be degradation free. Then, a simulation program was set up to regenerate the performance test data. Deterioration of each component (compressor, turbine and recuperator) was modeled by changes in the component characteristic parameters such as compressor and turbine efficiency, their flow capacities and recuperator effectiveness and pressure drop. Single and double faults (deterioration of single and two components) were simulated to generate fault data. The neural network was trained with majority of the data sets. Then, the remaining data sets were used to check the predictability of the neural network. Given measurable performance parameters (power, temperatures, pressures) as inputs to the neural network, characteristic parameters of each component were predicted as outputs and compared with original data. The neural network produced sufficiently accurate prediction. Reducing the number of input data decreased prediction accuracy. However, excluding up to a couple of input data still produced acceptable accuracy.

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