journal article·2022

Structure and magnetization of a magnetoactive ferrocomposite

Dmitriy I. Radushnov, Anna Yu. Solovyova, Ekaterina A. Elfimova

Nanoscale· Volume 14· Issue 29
Publisher page

Abstract

This work is devoted to the theoretical study of the structural and magnetic properties of an ensemble of single-domain interacting magnetic nanoparticles immobilized in a non-magnetic medium. This model is typical for describing magnetically active soft materials, "smart" polymer ferrocomposites, which have been applied in science-intensive industrial and biomedical technologies. It is assumed that the ferrocomposite is obtained by solidification of the carrier medium in a ferrofluid under an external magnetic field, the intensity of which is determined by the Langevin parameter αp; after the solidification of the carrier liquid, the nanoparticles retain the spatial distribution and orientation of their easy magnetization axes. The features of the orientational texture formed in the sample are analyzed depending on the intensity of the magnetic field αp and interparticle dipole-dipole interactions. The magnetization of a textured ferrocomposite in the magnetic field α is also investigated. Our results show that in the case of a co-directional arrangement of the considered fields and if α < αp, the ferrocomposites are magnetized much more efficiently than ferrofluids due to their texture. In the fields α > αp, the ferrocomposite is magnetized less efficiently than the ferrofluid due to the internal magnetic anisotropy of the nanoparticles. The analytical expressions presented here make it possible to predict the magnetization of a ferrocomposite depending on its internal structure and synthesis conditions, which is the theoretical basis for the synthesis of ferrocomposites with a predetermined magnetic response in a given magnetic field.
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Research context

OpenAlex topics: Characterization and Applications of Magnetic Nanoparticles · Geomagnetism and Paleomagnetism Studies · Magnetic and Electromagnetic Effects

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Ural Federal University, 51 Lenin Avenue, 620000 Ekaterinburg, Russian Federation

Funding

Russian Foundation for Basic Research

References (43)

Show source-provided references
1. Rodriguez-Arco · Nanoscale · 2016 · 8 · 813810.1039/C6NR00224B ↗
2. Kazantseva · Nanomaterials · 2021 · 11 · 340210.3390/nano11123402 ↗
3. Choi · Smart Mater. Struct. · 2016 · 25 · 04300110.1088/0964-1726/25/4/043001 ↗
4. Sharma · J. Environ. Manage. · 2022 · 306 · 11448310.1016/j.jenvman.2022.114483 ↗
5. Becker · Smart Mater. Struct. · 2017 · 26 · 09503510.1088/1361-665X/aa75ec ↗
6. Lavorato · Nanoscale Adv. · 2021 · 3 · 86710.1039/D0NA00828A ↗
7. Makarova · Smart Mater. Struct. · 2017 · 26 · 09505410.1088/1361-665X/aa82e9 ↗
8. Campos · Mater. Sci. Eng., C · 2021 · 118 · 11147610.1016/j.msec.2020.111476 ↗
9. Kolhatkar · Int. J. Mol. Sci. · 2013 · 14 · 1597710.3390/ijms140815977 ↗
10. Rui · Adv. Mater. · 2010 · 22 · 272910.1002/adma.201000260 ↗
11. Guo · Adv. Compos. Hybrid Mater. · 2021 · 4 · 53410.1007/s42114-021-00242-z ↗
12. Behrens · Nanoscale · 2011 · 3 · 87710.1039/C0NR00634C ↗
13. Dobroserdova · Soft Matter · 2022 · 18 · 49610.1039/D1SM01349A ↗
14. Elder · Adv. Mater. · 2020 · 32 · 190714210.1002/adma.201907142 ↗
15. Stepanov · Phys. Sci. Rev. · 202010.1515/psr-2020-0008 ↗
16. Baron · Polymers · 2021 · 13 · 169310.3390/polym13111693 ↗
17. Krasia-Christoforou · Nanomaterials · 2020 · 10 · 110.3390/nano10112178 ↗
18. Filipcsei · Adv. Polym. Sci. · 2007 · 206 · 13710.1007/12_2006_104 ↗
19. Abramchuk · Polym. Adv. Technol. · 2007 · 18 · 88310.1002/pat.924 ↗
20. Deuflhard · Phys. Chem. Chem. Phys. · 2019 · 21 · 1465410.1039/C9CP02910A ↗
21. Ikhaddalene · Period. Polytech., Chem. Eng. · 2021 · 65 · 37810.3311/PPch.17148 ↗
22. R. E.Rosensweig , Ferrohydrodynamics , Courier Corporation , 2013
23. Elrefai · IEEE Trans. Magn. · 2021 · 57 · 920102110.1109/TMAG.2020.3024864 ↗
24. Borin · Eur. Phys. J.: Spec. Top. · 2022 · 231 · 1165
25. Borin · Philos. Trans. R. Soc., A · 2020 · 378 · 025610.1098/rsta.2019.0256 ↗
26. Raikher · J. Magn. Magn. Mater. · 1983 · 39 · 1110.1016/0304-8853(83)90385-2 ↗
27. Zubarev · Phys. Rev. E · 2018 · 98 · 03261010.1103/PhysRevE.98.032610 ↗
28. Dieckhoff · J. Appl. Phys. · 2016 · 119 · 04390310.1063/1.4940724 ↗
29. Elfimova · Phys. Rev. E · 2021 · 104 · 05461610.1103/PhysRevE.104.054616 ↗
30. Elfimova · Nanoscale · 2019 · 11 · 2183410.1039/C9NR07425B ↗
31. Enpuku · AIP Adv. · 2021 · 11 · 12512310.1063/5.0076534 ↗
32. Draack · J. Magn. Magn. Mater. · 2019 · 474 · 57010.1016/j.jmmm.2018.11.023 ↗
33. Déjardin · J. Appl. Phys. · 2011 · 110 · 11392110.1063/1.3665886 ↗
34. Ambarov · J. Magn. Magn. Mater. · 2020 · 497 · 16601010.1016/j.jmmm.2019.166010 ↗
35. Ambarov · Modell. Simul. Mater. Sci. Eng. · 2020 · 28 · 08500910.1088/1361-651X/abbfbb ↗
36. Elrefai · J. Appl. Phys. · 2021 · 129 · 09390510.1063/5.0041215 ↗
37. Solovyova · Phys. Rev. E · 2021 · 104 · 06461610.1103/PhysRevE.104.064616 ↗
38. M.Allen and D.Tildesley , Computer Simulation of Liquids , Clarendon Press , 1989
39. D.Frenkel and B.Smit , Understanding Molecular Simulation: From Algorithms to Applications , Academic Press , 2001
40. Pshenichnikov · J. Magn. Magn. Mater. · 1996 · 161 · 9410.1016/S0304-8853(96)00067-4 ↗
41. Enpuku · AIP Adv. · 2022 · 12 · 05521110.1063/5.0090915 ↗
42. Enpuku · J. Appl. Phys. · 2021 · 130 · 11390310.1063/5.0056481 ↗
43. Yoshida · J. Magn. Magn. Mater. · 2017 · 427 · 16210.1016/j.jmmm.2016.10.040 ↗