MétaCan
Menu
Back to cohort
Record W2093658770 · doi:10.1021/am1002052

Room-Temperature Weak Ferromagnetism Induced by Point Defects in α-Fe<sub>2</sub>O<sub>3</sub>

2010· letter· en· W2093658770 on OpenAlexaff
Jiangtao Wu, S.-Y. Mao, Zuo‐Guang Ye, Zhaoxiong Xie, Lan‐Sun Zheng

Bibliographic record

VenueACS Applied Materials & Interfaces · 2010
Typeletter
Languageen
FieldEnergy
TopicIron oxide chemistry and applications
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsFerromagnetismMaterials scienceImpurityAntiferromagnetismAmorphous solidAnnealing (glass)Tartaric acidOxideRaw materialCondensed matter physicsChemical engineeringAnalytical Chemistry (journal)MetallurgyCrystallographyOrganic chemistryChemistryCitric acid

Abstract

fetched live from OpenAlex

Unusual room-temperature weak ferromagnetism alpha-Fe(2)O(3) was prepared by heating the mixture of commercial alpha-Fe(2)O(3) (as raw material) and tartaric acid at a mild temperature of 250 degrees C. This reaction involves a fast heating and cooling process resulting from the self-catalyzed oxidation of tartaric acid. Careful chemical analyses confirmed that no any ferromagnetic impurities, such as Fe, Fe(3)O(4), amorphous iron oxide and gamma-Fe(2)O(3,) were present in the treated sample. The unusual weak ferromagnetism was then attributed to the formation of a large amount of point defects in the treated sample during the peculiar synthetic process. Such a mechanism is supported by the result of annealing, which reduces the amount of point defects and thereby reestablishes the original antiferromagnetism in alpha-Fe(2)O(3).

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.008
GPT teacher head0.210
Teacher spread0.202 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations46
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueACS Applied Materials & InterfacesSame topicIron oxide chemistry and applicationsFrench-language works237,207