Non-stationarynon-stationarynon-stationary mass transfer in gel systems with graphene oxide as applied to 3d-bioprinting technologies

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The pattern of diffusion front propagation in pure agarose hydrogels as well as with the addition of graphene oxide was compared by the methods of moving boundaries and optical sensing, and the mass-transfer properties of the gel systems were measured. It was found that graphene oxide has high surface activity, becomes part of the mesh structure of the gel, increasing its porosity and thus affecting the diffusion rate and efficiency. In addition, graphene oxide contributes to the ordering of the gel structure or reduces light scattering within the gel. The combination of hydrogels with graphene oxide enables the creation of systems with controllable optical properties, which in turn opens up new opportunities for improving 3D-bioprinting technologies. Based on the random walk method, a numerical model is proposed that is well suited to describe the structures of hydrogels with graphene oxide. This model will help to determine the quality of materials in 3D-bioprinting technologies in terms of nutrient delivery efficiency for living microorganisms located inside the gel. The comparison of experimental data and numerical modeling demonstrated a good agreement between them.

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Sobre autores

D. Khramtsov

MIREA – Russian Technological University

Email: a.moshin97@mail.ru
Rússia, Moscow

A. Moshin

Moscow Polytechnic University; MIREA – Russian Technological University

Autor responsável pela correspondência
Email: a.moshin97@mail.ru
Rússia, Moscow; Moscow

B. Pokusaev

Moscow Polytechnic University; MIREA – Russian Technological University

Email: a.moshin97@mail.ru
Rússia, Moscow; Moscow

D. Nekrasov

Moscow Polytechnic University; MIREA – Russian Technological University

Email: a.moshin97@mail.ru
Rússia, Moscow; Moscow

N. Zakharov

MIREA – Russian Technological University

Email: a.moshin97@mail.ru
Rússia, Moscow

Bibliografia

  1. Xu W., Jambhulkar S., Ravichandran D., Zhu Y., Kakarla M., Nian Q., Azeredo B., Chen X., Jin K., Vernon B. 3D printing– enabled nanoparticle alignment: A review of mechanisms and applications // Small. 2021. V. 17.
  2. Kumar V., Kaur H., Kumari A., Hooda G., Garg V., Dureja H. Drug delivery and testing via 3D printing // Bioprinting. 2023. V. 36.
  3. Banga H.K., Kalra P., Belokar R.M., Kumar R. Design and fabrication of prosthetic and orthotic product by 3D printing. In Prosthetics and Orthotics // IntechOpen. London, 2020.
  4. Pokusaev B.G., Vyazmin A.V., Zakharov N.S., Khramtsov D.P., Nekrasov D.A. Unsteady mass transfer of nutrients in gels with channels of different spatial structures // Theoretical Foundations of Chemical Engineering. 2020. V. 54. P. 277. [Покусаев Б.Г., Вязьмин А.В., Захаров Н.С., Храмцов Д.П., Некрасов Д.А. Нестационарный массоперенос питательных веществ в гелях с каналами различной пространственной структуры // Теоретические основы химической технологии. 2020. Т. 54. № 2. С. 163.]
  5. Itapu B.M., Jayatissa A.H. A review in graphene/polymer composites // Chem. Sci. Int. J. 2018. № 23. Р. 1.
  6. Palmieri, V., Spirito M.D., Papi M. Graphene-based scaffolds for tissue engineering and photothermal therapy // Nanomedicine. 2020. № 15. Р. 1411.
  7. Mantecón-Oria M., Tapia O., Lafarga M., Berciano M.T., Munuera J.M., Villar-Rodil S., Paredes J.I., Rivero M.J., Diban N., Urtiaga A. Influence of the properties of different graphene-based nanomaterials dispersed in polycaprolactone membranes on astrocytic differentiation // Sci. Rep. 2022. № 12. Р. 13408.
  8. Patil R., Alimperti S. Graphene in 3D Bioprinting // J. Funct. Biomater. 2024. № 15. Р. 82. https://doi.org/10.3390/jfb15040082.
  9. Hong N., Yang G. H., Lee J., Kim G. 3D Bioprinting and Its in vivo Applications // J. Biomed. Mater. Res. Part B. 2018. V. 106. № 1. P. 444.
  10. Holzl K., Lin S. M., Tytgat L., Van Vlierberghe S., Gu, L.X., Ovsianikov A. Bioink Properties Before, During and After 3D Bioprinting // Biofabrication. 2016. V. 8. № 3. P. 032002.
  11. Gillies A.R., Lieber R.L. Structure and Function of the Skeletal Muscle Extracellular Matrix // Muscle Nerve. 2011. V. 44. № 3. Р. 318.
  12. Derakhshanfar S., Mbeleck R., Xu K., Zhang X., Zhong W., Xing M. 3D Bioprinting for Biomedical Devices and Tissue Engineering: A Review of Recent Trends and Advances // Bioact. Mater. 2018. V. 3. № 2. Р. 144.
  13. Shi Y., Xing T.L., Zhang H.B., Yin R.X., Yang S.M., Wei J., Zhang W.J. Tyrosinase-doped Bioink for 3D Bioprinting of Living Skin Constructs // Biomed. Mater. 2018. V. 13. № 3. Р. 035008.
  14. Haring A.P., Thompson E.G., Tong Y., Laheri S., Cesewski E., Sontheimer H., Johnson B.N. Process– and Bio-inspired Hydrogels for 3D Bioprinting of Soft Free-standing Neural and Glial Tissues // Biofabrication. 2019. V. 11. № 2. Р. 025009.
  15. Birenboim. M., Nadiv. R., Alatawna. A., Buzaglo. M., Schahar. G., Lee. J., Kim. G., Peled A., Regev O. Reinforcement and workability aspects of graphene-oxide-reinforced cement nanocomposites // Compos. Part. B Eng. 2019. № 161. Р. 68.
  16. Yoo M.J., Park H.B. Effect of hydrogen peroxide on properties of graphene oxide in Hummers method // Carbon. 2019. № 141. Р. 515.
  17. Dmitriev A.S., Klimenko A.V. Prospects for the Use of Two-Dimensional Nanomaterials in Energy Technologies (Review) // Thermal Engineering. 2023. V. 70. № 8. Р. 551.
  18. Motiee E.S., Karbasi S., Bidram E., Sheikholeslam M. Investigation of physical, mechanical and biological properties of polyhydroxybutyrate-chitosan/graphene oxide nanocomposite scaffolds for bone tissue engineering applications // Int. J. Biol.Macromol. 2023. № 247. Р. 125593.
  19. Challa A.A., Saha N., Szewczyk P.K., Karbowniczek J.E., Stachewicz U., Ngwabebhoh F.A., Saha P. Graphene oxide produced from spent coffee grounds in electrospun cellulose acetate scaffolds for tissue engineering applications // Mater. Today Commun. 2023. № 35. Р. 105974.
  20. Wajahat M., Kim J.H., Ahn J., Lee S., Bae J., Pyo J., Seol S.K. 3D printing of Fe3O4 functionalized graphene-polymer (FGP) composite microarchitectures // Carbon. 2020. № 167. Р. 278.
  21. Palaganas J.O., Palaganas N.B., Ramos L.J.I., David C.P.C. 3D printing of covalent functionalized graphene oxide nanocomposite via stereolithography // ACS Appl. Mater. Interfaces. 2019. № 11. Р. 46034.
  22. Ibrahim A., Klopocinska A., Horvat K., Abdel Hamid, Z. Graphene-based nanocomposites: Synthesis, mechanical properties, and characterizations // Polymers. 2021. № 13. Р. 2869.
  23. Vatani M., Zare Y., Gharib N., Rhee K.Y., Park S.J. Simulating of effective conductivity for graphene–polymer nanocomposites // Sci. Rep. 2023. № 13. Р. 5907.
  24. Haney R., Tran P., Trigg E.B., Koerner H., Dickens T., Ramakrishnan S. Printability and performance of 3D conductive graphite structures // Addit. Manuf. 2021. № 37. Р. 101618.
  25. Borode A.O., Ahmed N.A., Olubambi P.A., Sharifpur M., Meyer J.P. Effect of various surfactants on the viscosity, thermal and electrical conductivity of graphene nanoplatelets Nanofluid // Int. J. Thermophys. 2021. № 42. Р. 158.
  26. Solìs Moré Y., Panella G., Fioravanti G., Perrozzi F., Passacantando M., Giansanti F., Ardini M., Ottaviano L., Cimini A., Peniche C. Biocompatibility of composites based on chitosan, apatite, and graphene oxide for tissue applications // J. Biomed. Mater. Res. Part A. 2018. № 106. Р. 1585.
  27. Patil R., Bahadur P., Tiwari S. Dispersed graphene materials of biomedical interest and their toxicological consequences. Adv. Colloid Interface Sci. 2020. № 275. Р. 102051.
  28. Khramtsov D.P., Sulyagina O.A., Pokusaev B.G., Vyazmin A.V., Nekrasov D.A., Moshin A.A. Nonstationary mass transfer of nutrient medium for microorganisms in mixed gels // Theoretical Foundations of Chemical Engineering. 2022. V. 56. P. 669. [Храмцов Д.П., Сулягина О.А., Покусаев Б.Г., Вязьмин А.В., Некрасов Д.А., Мошин А.А. Нестационарный массоперенос питательной среды для микроорганизмов в смесевых гелях // Теоретические основы химической технологии. 2022. Т. 56. № 5. С. 539.]
  29. Lin C.C., Metters A.T. Hydrogels in controlled release formulations: Network design and mathematical modeling // Advanced Drug Delivery Reviews. 2006. V. 58. P. 1379.
  30. Masuda N., Porter M.A., Lambiotte R. Random walks and diffusion on networks // Physics Reports. 2017. V. 716–717. P. 1.
  31. Geim A.K. Random walk to graphene // International journal of Modern Physics B. 2011. V. 25. № 30. P. 4055.
  32. Vamos, Calin, et al. Generalized Random Walk Algorithm for the Numerical Modeling of Complex Diffusion Processes // Journal of Computational Physics. 2023. V. 186. № 2. P. 527. doi: 10.1016/S0021-9991(03)00073-1.
  33. Ghoniem, Ahmed F., and Frederick S. Sherman. Grid-Free Simulation of Diffusion Using Random Walk Methods // Journal of Computational Physics. 1985. V. 61. № 1. 1985. P. 1. doi: 10.1016/0021-9991(85)90058-0.
  34. Zabet M., Mishra S., Kundu S. Effect of graphene on the self-assembly and rheological behavior of a triblock copolymer gel // RSC Advances. 2015. № 5. Р. 83936. doi: 10.1039/c5ra13672e.
  35. Siripongpreda T., Jiraborvornpongsa N., Composto R.J., Rodthongkum N. Titanium dioxide/nitrogen-doped graphene-biopolymer based nanocomposite films for pollutant photodegradation and laser desorption ionization mass spectrometry of biomarkers // Nano-Structures & Nano-Objects. 2024. V. 38. Р. 101203.

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2. Fig. 1. Scanning electron microscopy photograph of a colloidal graphene oxide solution.

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3. Fig. 2. Schematic diagram of the experimental setup.

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4. Fig. 3. Schematic diagram of the setup.

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5. Fig. 4. The probability of the microchannel direction is determined by the weighting coefficients r1, r2, r3.

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6. Fig. 5. Formation of channels of random walk methods.

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7. Fig. 6. Graph of the dependence of the intensity of light transmission by a sample of agarose hydrogel 0.4 wt.% with graphene oxide 1 wt.% at different points in time from the beginning of the process, min: 1 – 0, 2 – 60, 3 – 90, 4 – 120, 5 – 150, 6 – 180.

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8. Fig. 7. Pattern of fuchsin front propagation: (A) agarose hydrogel 0.4 wt.%, (B) agarose hydrogel 0.4 wt. % with the addition of graphene oxide 1 wt. % at different time points from the beginning of the experiment, min: 1 – 0, 2 – 60, 3 – 90, 4 – 120, 5 – 150, 6 – 180.

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9. Fig. 8. Dependences of the time dynamics of the fuchsin front boundary growth in the volume of 0.4 wt. % agarose gel with the addition of graphene oxide. 1 – 0.4 wt. % agarose gel + 0.1 wt. % graphene oxide, 2 – 0.4 wt. % agarose gel + 0.5 wt. % graphene oxide, 3 – 0.4 wt. % agarose gel + 1 wt. % graphene oxide, 4 – pure 0.4 wt. % agarose gel.

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10. Fig. 9. Dependences of the temporal dynamics of the growth of the fuchsin front boundary in the volume of 0.6 wt. % agarose gel with the addition of graphene oxide. 1 - agarose gel 0.6 wt. % + graphene oxide 0.1 wt. %, 2 - agarose gel 0.6 wt. % + graphene oxide 0.5 wt. %, 3 - agarose gel 0.6 wt. % + graphene oxide 1 wt. %, 4 - pure agarose gel 0.6 wt. %.

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11. Fig. 10. Dependences of the temporal dynamics of the growth of the fuchsin front boundary in the volume of 0.8 wt. % agarose gel with the addition of graphene oxide. 1 - agarose gel 0.8 wt. % + graphene oxide 0.1 wt. %, 2 - agarose gel 0.8 wt. % + graphene oxide 0.5 wt. %, 3 – agarose gel 0.8 wt. % + graphene oxide 1 wt. %, 4 – pure agarose gel 0.8 wt. %.

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12. Fig. 11. Dependence of the optical density of agarose gels on the concentration of graphene oxide 0.1 wt. %, 0.5 wt. %, 1 wt. % at a wavelength of 450 nm. 1 – 0.4 wt. %, 2 – 0.6 wt. %, 3 – 0.8 wt. %.

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13. Fig. 12. Dependence of the temporal dynamics of fuchsin growth in agarose gel 0.4% with the addition of graphene oxide. 1 – agarose gel 0.4 wt. % + graphene oxide 0.5 wt. %; 2 – agarose gel 0.4 wt. % + graphene oxide 1.0 wt. %; 3 – pure agarose gel 0.4 wt. %; 4 – agarose gel 0.4 wt. % + graphene oxide 0.5 wt. % (model); 5 – agarose gel 0.4 wt. % + graphene oxide 1.0 wt. % (model); 6 – pure agarose gel 0.4 wt. % (model).

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