Thermal Spintronics in Magnetic Tunnel Junctions

Summary

Thermal spintronics in magnetic tunnel junctions explores the generation and manipulation of spin currents by temperature gradients across nanometre-scale ferromagnetic–insulator–ferromagnetic stacks. In these devices, ferromagnetic electrodes are separated by an ultrathin dielectric barrier, allowing spin-dependent quantum tunnelling of electrons. When a thermal bias is applied, unequal occupation of spin channels on either side of the barrier gives rise to a spin-polarised thermoelectric voltage, commonly known as the tunnel magneto-Seebeck effect. Concurrently, temperature gradients can induce transverse voltages via the anomalous Nernst effect, offering additional read-out modalities. The interplay of heat, charge and spin currents in such junctions opens routes to energy-efficient memory elements, thermal logic and waste-heat harvesting in microelectronics. Key challenges include maximising thermoelectric conversion while preserving magnetic contrast, engineering interfacial thermal conductance and integrating these structures within existing device architectures.

Research from Nature Portfolio

Recent studies have demonstrated that selective choice of electrode materials can dramatically amplify spin-dependent thermoelectric signals. One work identified half-metallic Heusler compounds as ideal electrodes for enhancing the tunnel magneto-Seebeck effect. By exploiting the sharp asymmetry of the spin-split density of states near the Fermi level in Co2FeAl and Co2FeSi, devices exhibited substantially larger Seebeck voltages and magneto-Seebeck ratios than conventional Co-Fe-B junctions. This finding underpins the importance of electronic band engineering for high-performance thermal spintronic elements.

Another investigation revealed that laser-induced three-dimensional temperature gradients within junctions give rise not only to longitudinal Seebeck voltages but also to an anomalous Nernst response. By mapping in-plane and out-of-plane thermal profiles and correlating them with magnetisation orientation, researchers extracted a nanoscale anomalous Nernst coefficient for CoFeB electrodes. This approach extends the functionality of tunnel junctions towards direction-sensitive thermal sensing and suggests strategies for co-designing magnetic anisotropy and thermal landscape to tune thermomagnetic voltages.

Thermal Spintronics in Magnetic Tunnel Junctions publication trend

The graph below shows the total number of articles in thermal spintronics in magnetic tunnel junctions across all publications each year (not limited to Nature Index journals).

Technical terms

Magnetic tunnel junction (MTJ): A nanoscale device comprising two ferromagnetic electrodes separated by a thin insulating barrier, enabling spin-dependent quantum tunnelling.

Tunnel magneto-Seebeck effect: Generation of a spin-polarised voltage across an MTJ when a temperature gradient is applied, dependent on the relative orientation of the electrode magnetisations.

Anomalous Nernst effect: Transverse voltage produced in a magnetic material when subjected to a temperature gradient and magnetisation, orthogonal to both vectors.

Spin caloritronics: The study of interactions between spin currents, charge currents and heat flow in magnetic nanostructures.

Heusler compound: A class of intermetallic materials with tunable electronic structure, often exhibiting half-metallicity and high spin polarisation at the Fermi level.

References

  1. Large magneto-Seebeck effect in magnetic tunnel junctions with half-metallic Heusler electrodes. Nature Communications (2017).
  2. Anomalous Nernst effect and three-dimensional temperature gradients in magnetic tunnel junctions. Communications Physics (2018).
  3. Combined anomalous Nernst effect and thermography studies of ultrathin CoFeB/Pt nanowires. AIP Advances (2016).
  4. Seeking large thermoelectric effects in MgO-based tunnel junctions. New Journal of Physics (2016).
  5. Temperature increase in STT-MRAM at writing: A fully three-dimensional finite element approach. Solid-State Electronics (2022).

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