Anti-irradiation reinforcement in NiFe/oxide composite structure by electronic reconstruction and structural stabilization for efficient magnetoresistive sensor in aerospace/radiotherapy applications

The construction of irradiation-tolerant anisotropic magnetoresistance (AMR) sensors is crucial for weak-field detection in scenarios of aerospace and radiotherapy. Presently, the utilization of the NiFe/oxide composite structure was considered to be an effective scheme to optimize the spin-dependent transport property; however, it exhibited poor anti-irradiation ability due to the crystal instability of oxide. Here, a strategy was proposed to break through the limitation based on the electronic reconstruction and structural stabilization. By introducing an oxygen-affinitive Hf intercalation into the Ta/MgO/NiFe/MgO/Ta multilayer, the electron coordination was modified to tune the 3d orbital occupancy of Fe, apparently boosting the s-d electron scattering and spin-related transport property. Meanwhile, the irradiation stability of electronic and crystal structures was effectively improved due to the emergence of the Hf–O–Mg bond with high dissociation energy. Therefore, we constructed a highly reliable AMR sensor with both the ultrahigh sensitivity of 3.1 mV/V/Oe and excellent irradiation-tolerant ability capable of resisting the γ-ray irradiation of 1000 Gy. These results not only build an important basis for the sensor application in the irradiation environment but also provide a possible idea for the anti-irradiation design in spintronic devices.

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Publication Details

Journal
Applied Physics Letters
Published
2025-02-10
DOI
https://doi.org/10.1063/5.0251492
Citations
1
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.73

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article

Anti-irradiation reinforcement in NiFe/oxide composite structure by electronic reconstruction and structural stabilization for efficient magnetoresistive sensor in aerospace/radiotherapy applications

Lei Ding, Chun Feng, Xutong Meng, Baohe Li et al.
1 citations
Applied Physics Letters
Advanced Memory and Neural Computing
0.73
article

Anti-irradiation reinforcement in NiFe/oxide composite structure by electronic reconstruction and structural stabilization for efficient magnetoresistive sensor in aerospace/radiotherapy applications

Lei Ding, Chun Feng, Xutong Meng, Baohe Li, Tong Guo, Boyi Wang, Fei Meng, Ronggui Zhu, Guanghua Yu, Yu Qi
article en
1 citations

Abstract

The construction of irradiation-tolerant anisotropic magnetoresistance (AMR) sensors is crucial for weak-field detection in scenarios of aerospace and radiotherapy. Presently, the utilization of the NiFe/oxide composite structure was considered to be an effective scheme to optimize the spin-dependent transport property; however, it exhibited poor anti-irradiation ability due to the crystal instability of oxide. Here, a strategy was proposed to break through the limitation based on the electronic reconstruction and structural stabilization. By introducing an oxygen-affinitive Hf intercalation into the Ta/MgO/NiFe/MgO/Ta multilayer, the electron coordination was modified to tune the 3d orbital occupancy of Fe, apparently boosting the s-d electron scattering and spin-related transport property. Meanwhile, the irradiation stability of electronic and crystal structures was effectively improved due to the emergence of the Hf–O–Mg bond with high dissociation energy. Therefore, we constructed a highly reliable AMR sensor with both the ultrahigh sensitivity of 3.1 mV/V/Oe and excellent irradiation-tolerant ability capable of resisting the γ-ray irradiation of 1000 Gy. These results not only build an important basis for the sensor application in the irradiation environment but also provide a possible idea for the anti-irradiation design in spintronic devices.

Applied Physics LettersVol. 126(6)
Beijing Technology and Business University (CN), Hainan University (CN), University of Science and Technology Beijing (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 31%
Advanced Memory and Neural Computing
0.73
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