Skip to main content

Advertisement

Log in

Infrared imaging of modified chitosan hydrogel film morphology study of polyvinyl alcohol adsorption

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

The hydrogel film of chitosan with pore structure can be produced by using glutaraldehyde as reaction crosslinking agent to crosslink polyvinyl alcohol and chitosan, which has higher adsorption efficiency. The structure of film is characterized by infrared image, and its morphology is characterized by SEM. The adsorption of acid red 73 under different conditions is primarily studied. The results show that the hydrogel film has a three-dimensional porous microstructure, and the material kinetics is found to effectively absorb acid red 73, with a maximum adsorption amount of 6.5639 mg/g. It is proven as an ideal adsorption material. After studying the thermodynamics of adsorption of the material, △H < 0 was obtained, ∣△H∣ = −81.59861kJ/mol, which belongs to exothermic reaction, primarily reflected as chemical adsorption.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Abdulhay E, Alafeef M, Alzghoul L, Al Momani M, Al Abdi R, ArunKumar N, Munoz R, de Albuquerque VHC (2018) Computer-aided autism diagnosis via second-order difference plot area applied to EEG empirical mode decomposition. Neural Comput & Applic. https://doi.org/10.1007/s00521-018-3738-0. Accepted

  2. Mathews DT (2006) Characterisation of polyvinyl alcohol hydrogels modified with chitosan for cardiovascular applications. PhD thesis, Dublin City University

  3. Dongdong J, Arunkumar N, Wenyu Z, Beibei L, Xinlei Z, Guangjian Z (2019) Semantic clustering fuzzy c means spectral model based comparative analysis of cardiac color ultrasound and electrocardiogram in patients with left ventricular heart failure and cardiomyopathy. Futur Gener Comput Syst 92:324–328

    Article  Google Scholar 

  4. Guojie WU, Wei liang WU, Jin man LI et al (2006) The effects of the preparation conditions of polyvinyl alcohol-chitosan hydrogel on its swelling ration[J]. Journal of Guangdong University of Technology

  5. Guojie WU, Jinman LI, Cui Y et al (2006) Studies on the hardness of chitosan-polyvinyl alcohol hydrogel[J]. Materials Review 20(5):139–141

    Google Scholar 

  6. Haoyu L, Jianxing L, Arunkumar N, Hussein AF, Jaber MM (2018) An IoMT cloud-based real time sleep apnea detection scheme by using the SpO2 estimation supported by heart rate variability. Futur Gener Comput Syst. https://doi.org/10.1016/j.future.2018.12.001

  7. Khamparia A, Singh A, Anand D et al (2018) A novel deep learning-based multi-model ensemble method for the prediction of neuromuscular disorders. Neural Comput & Applic. https://doi.org/10.1007/s00521-018-3896-0

  8. Mahdavinia GR, Hosseini R, Darvishi F et al (2016) The release of cefazolin from chitosan/polyvinyl alcohol/sepiolite nanocomposite hydrogel films[J]. Iran Polym J 25(11):1–11

    Article  Google Scholar 

  9. Mathews DT, Birney YA, Cahill PA et al (2010) Vascular cell viability on polyvinyl alcohol hydrogels modified with water-soluble and -insoluble chitosan.[J]. J Biomed Mater Res B Appl Biomater 84B(2):531–540

    Article  Google Scholar 

  10. Mohammed MA, Abd Ghani MK, Arunkumar N, Hamed RI, Mostafa SA, Abdullah MK, Burhanuddin MA (2018) Decision support system for nasopharyngeal carcinoma discrimination from endoscopic images using artificial neural network. J Supercomput. https://doi.org/10.1007/s11227-018-2587-z

  11. Oh SL, Hagiwara Y, Raghavendra U, Yuvaraj R, Arunkumar N, Murugappan M, Acharya UR (2018) A deep learning approach for Parkinson’s disease diagnosis from EEG signals. Neural Comput & Applic:1–7. https://doi.org/10.1007/s00521-018-3689-5

  12. Pereira RF, da Silva Filho VER, Moura LB, Kumar NA, de Alexandria AR, de Albuquerque VHC (2018) Automatic quantification of spheroidal graphite nodules using computer vision techniques. J Supercomput. https://doi.org/10.1007/s11227-018-2579-z

  13. Rajendra Achary U, YukiHagiwara SND, Suren S, Koh JEW, Shu Lih O, Arunkumar N, Ciaccio EJ, Lim CM (2019) Characterization of focal EEG signals: a review. Futur Gener Comput Syst 91:290–299

    Article  Google Scholar 

  14. Santamaria-Granados L, Munoz-Organero M, Ramirez-Gonzalez G, Abdulhay E, Arunkumar N (2018) Using deep convolutional neural network for emotion detection on a physiological signals dataset (AMIGOS). IEEE Access. https://doi.org/10.1109/ACCESS.2018.2883213

  15. Sathishkumar BR, Sundaravadivazhagan B, Martin B, Sasi G, Chandrasekar M, Kumar SR, … Arunkumar N Revisiting computer networking protocols by wireless sniffing on brain signal/image portals. Neural Comput & Applic:1–13. https://doi.org/10.1007/s00521-018-3919-x

  16. Srinivasa PC, Ramesh MN, Kumar KR et al (2003) Properties and sorption studies of chitosan–polyvinyl alcohol blend films[J]. Carbohydr Polym 53(4):431–438

    Article  Google Scholar 

  17. Venkatraman V, Arunkumar N, Chantre-Astaiza A, Muñoz-Mazón AI, Fuentes-Moraleda L, Khan MS (2018) Mapping the structure and evolution of heavy vehicle research: a scientometric analysis and visualisation. Int J Heavy Vehicle Systems 25(3/4):344–368

    Article  Google Scholar 

  18. Wen YM, Si-Dong LI, Zhong JP et al (2007) Effect of preparation conditions on capability of polyvinyl alcohol-chitosan hydrogel[J]. Journal of Guangdong Ocean University

  19. Wu Z, Wang H, Arunkumar N (2019) Bayesian analysis model for the use of anesthetic analgesic drugs in cancer patients based on geometry reconstruction. Futur Gener Comput Syst 93:170–175

    Article  Google Scholar 

  20. Xiao G, Lan K, Su H et al (2014) Preparation of a modified chitosan-mycelium adsorbent with polyvinyl alcohol[J]. Sep Sci Technol 49(8):1279–1288

    Article  Google Scholar 

  21. Zhou D, Nguyen T, Breaz E, Zhao D, Clénet S, Gao F (2018) Global parameters sensitivity analysis and development of a two-dimensional real-time model of proton-exchange-membrane fuel cells. Energy Convers Manag 162:276–292. https://doi.org/10.1016/j.enconman.2018.02.036

    Article  Google Scholar 

  22. Zhou D, Al-Durra A, Zhang K, Ravey A, Gao F (2018) Online remaining useful life prediction of proton exchange membrane fuel cells using a novel robust methodology. J Power Sources 399(30):314–328

    Article  Google Scholar 

  23. Zu Y, Zhang Y, Zhao X et al (2012) Preparation and characterization of chitosan-polyvinyl alcohol blend hydrogels for the controlled release of nano-insulin[J]. Int J Biol Macromol 50(1):82–87

    Article  Google Scholar 

Download references

Acknowledgements

1. Sheng Tong Sheng technology innovation fund, Gansu Agricultural University (No. GSAU-STS-1721); 2. open school of science, Gansu Agricultural University (No. GAU-XKJS-2018-16); 3. introduction of talents from Gansu Agricultural University (No. GSAU-RCZX201714).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Wei Jia.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jia, W., Wenjun, G., Zhifang, Z. et al. Infrared imaging of modified chitosan hydrogel film morphology study of polyvinyl alcohol adsorption. Multimed Tools Appl 79, 17027–17043 (2020). https://doi.org/10.1007/s11042-019-7555-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-019-7555-y

Keywords

Navigation