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Record W4414437180 · doi:10.1080/23746149.2025.2557918

Spintronics and magnetic memory devices

2025· article· en· W4414437180 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdvances in Physics X · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic properties of thin films
Canadian institutionsKootenay Association for Science & Technology
FundersNational Research Council of Science and TechnologyNational Research Foundation of Korea
KeywordsSpintronicsMagnetoresistive random-access memoryMagnetoresistanceMagnetic storageGiant magnetoresistanceNon-volatile memoryRandom access memoryKey (lock)

Abstract

fetched live from OpenAlex

Spintronics technology enables electrical reading and writing of magnetization orders, thus have led to development of magnetic random access memory (MRAM). Owing to its superior properties of size, speed, and endurance, MRAM is promising for applications in internet-of-things, automotive microcontrollers, and data centers. Here, we review key spintronic technologies of magnetoresistance and spin-transfer torque, which are the operating mechanism for MRAM, and properties and status of MRAM commercialization. We also review recent achievements and future challenges in emerging topics of spin-orbit torque, voltage gating, orbitronics, and antiferromagnetic spintronics, and new applications of spin-torque oscillators, probabilistic computing, and skyrmion-based applications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.859
Threshold uncertainty score0.495

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.239
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it