Towards high-performance electrochemical thermal energy harvester based on ferrofluids - Archive ouverte HAL Access content directly
Journal Articles Applied Materials Today Year : 2020

Towards high-performance electrochemical thermal energy harvester based on ferrofluids

(1) , (2) , (3) , (1) , (4) , (5) , (1)
1
2
3
4
5

Abstract

The ionic liquid-based thermo-electrochemical cells receive increasing attention as an inexpensive alternative to solid-state thermo-electrics for waste heat harvesting applications. Recently, it has been demonstrated that magnetic nanoparticles (MNPs) in liquid-based thermoelectric materials result in enhancement of the Seebeck effect opening new perspectives to the design of a thermoelectric device with relatively high efficiency and cost effectiveness. Here, the role of an interacting assembly of MNPs in the thermoelectric signal is studied for the first time. Based on a thermodynamic approach, an analytic expression has been derived for the Seebeck coefficient that includes the inter-particle magnetic interactions in the assembly and the nanoparticle’s magnetic characteristics (saturation magnetization, magnetic anisotropy). Mesoscopic scale modelling with the implementation of the Monte Carlo Metropolis algorithm is performed to calculate their contribution to the Seebeck coefficient, for diluted assemblies of γ-Fe2O3 and CoFe2O4 nanoparticles, materials commonly used in ferrofluids. The results demonstrate the increase of the size and temperature range of the Seebeck coefficient with the increase of nanoparticles’ magnetic anisotropy paving the way for the detailed study of the magneto-thermal effects in high-performance thermoelectric materials based on ferrofluids.

Dates and versions

cea-03747392 , version 1 (08-08-2022)

Identifiers

Cite

Marianna Vasilakaki, Ioulia Chikina, Valeri Shikin, Nikolaos Ntallis, Davide Peddis, et al.. Towards high-performance electrochemical thermal energy harvester based on ferrofluids. Applied Materials Today, 2020, 19, pp.100587. ⟨10.1016/j.apmt.2020.100587⟩. ⟨cea-03747392⟩
9 View
0 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More