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Cited by 268

The DOI matches its Crossref record; 185 of the 185 references it cites were found in a registry or an index.

Magnetoresistive Sensor Development Roadmap (Non-Recording Applications)

Open access
Zheng, Chao, Zhu, Ke, Cardoso de Freitas, Susana, Chang, Jen-Yuan, Davies, Joseph E., Eames, Peter, Freitas, Paulo P., Kazakova, Olga, Kim, CheolGi, Leung, Chi-Wah, Liou, Sy-Hwang, Ognev, Alexey, Piramanayagam, S. N., Ripka, Pavel, Samardak, Alexander, Shin, Kwang-Ho, Tong, Shi-Yuan, Tung, Mean-Jue, Wang, Shan X., Xue, Songsheng, Yin, Xiaolu, Pong, Philip W. T.·2019·IEEE Transactions on Magnetics

Abstract

Magnetoresistive (MR) sensors have been identified as promising candidates for the development of high-performance magnetometers due to their high sensitivity, low cost, low power consumption, and small size. The rapid advance of MR sensor technology has opened up a variety of MR sensor applications. These applications are in different areas that require MR sensors with different properties. Future MR sensor development in each of these areas requires an overview and a strategic guide. An MR sensor roadmap (non-recording applications) was therefore developed and made public by the Technical Committee of the IEEE Magnetics Society with the aim to provide an research and development (R&D) guide for MR sensors intended to be used by industry, government, and academia. The roadmap was developed over a three-year period and coordinated by an international effort of 22 taskforce members from ten countries and 17 organizations, including universities, research institutes, and sensor companies. In this paper, the current status of MR sensors for non-recording applications was identified by analyzing the patent and publication statistics. As a result, timescales for MR sensor development were established and critical milestones for sensor parameters were extracted in order to gain insight into potential MR sensor applications (non-recording). Five application areas were identified, and five MR sensor roadmaps were established. These include biomedical applications, flexible electronics, position sensing and human–computer interactions, non-destructive evaluation and monitoring, and navigation and transportation. Each roadmap was analyzed using a logistic growth model, and new opportunities were predicted based on the extrapolated curve, forecast milestones, and professional judgment of the taskforce members. This paper provides a framework for MR sensor technology (non-recording applications) to be used for public and private R&D planning, in order to provide guidance into likely MR sensor applications, products, and services expected in the next 15 years and beyond.

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Metadata

Authors
Zheng, C., Zhu, K., Cardoso de Freitas, S., Chang, J.-Y., Davies, J. E., Eames, P., Freitas, P. P., Kazakova, O., Kim, C., Leung, C.-W., Liou, S.-H., Ognev, A., Piramanayagam, S. N., Ripka, P., Samardak, A., Shin, K.-H., Tong, S.-Y., Tung, M.-J., Wang, S. X., Xue, S., Yin, X., & Pong, P. W. T.
Venue
IEEE Transactions on Magnetics
Published
2019-04
Volume
55
Issue
4
Pages
1-30
ISSN
  • 0018-9464 (ISSN-L)
  • 1941-0069
OpenAlex
W2919859964
Cited by
268
References
185
FWCI
10.31
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Magnetoresistive Sensor Development Roadmap (Non-Recording Applications). https://app.cochat.ai/papers/10.1109/tmag.2019.2896036
The paper
Zheng, C., Zhu, K., Cardoso de Freitas, S., Chang, J.-Y., Davies, J. E., Eames, P., Freitas, P. P., Kazakova, O., Kim, C., Leung, C.-W., Liou, S.-H., Ognev, A., Piramanayagam, S. N., Ripka, P., Samardak, A., Shin, K.-H., Tong, S.-Y., Tung, M.-J., Wang, S. X., . . . Pong, P. W. T. (2019). Magnetoresistive Sensor Development Roadmap (Non-Recording Applications). IEEE Transactions on Magnetics. https://doi.org/10.1109/tmag.2019.2896036

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.