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Record W3120443573 · doi:10.1063/5.0036328

Polyamorphism in a solute-lean Al–Ce metallic glass

2021· article· en· W3120443573 on OpenAlexfundno aff
Ziliang Yin, Hongbo Lou, H. W. Sheng, Zhidan Zeng, Wendy L. Mao, Qiaoshi Zeng

Bibliographic record

VenueJournal of Applied Physics · 2021
Typearticle
Languageen
FieldEngineering
TopicMetallic Glasses and Amorphous Alloys
Canadian institutionsnot available
FundersArgonne National LaboratoryNational Natural Science Foundation of ChinaFundamental Research Funds for the Central UniversitiesOffice of ScienceCanadian Light SourceU.S. Department of Energy
KeywordsPolyamorphismDelocalized electronLanthanideChemical physicsMaterials scienceBulk modulusCrystallographyChemistryAmorphous solidCondensed matter physicsOrganic chemistry

Abstract

fetched live from OpenAlex

Polyamorphism discovered in lanthanide-rich metallic glasses (MGs) has been attributed to the electronic transition of the lanthanide element as a solvent element. In this work, we report that pressure-induced polyamorphism still exists in a Ce-poor Al93Ce7 binary MG where the 4f electron element serves as a solute and solute–solute avoidance is expected. The polyamorphic transition, observed by in situ high-pressure synchrotron x-ray diffraction, is accompanied by a volume collapse of ∼0.78% and occurs over a narrow pressure range from ∼0.8 to ∼1.8 GPa. Further synchrotron Ce L3-edge x-ray absorption spectroscopy measurements reveal that pressure-induced 4f electron delocalization underlies the polyamorphic transition. Molecular dynamics simulations confirm that the Ce atoms in the MG are completely isolated by the solvent Al atoms. This result demonstrates that 4f element-bearing alloys with extremely dilute concentrations can also exhibit polyamorphic states originating from electronic transitions, extending the compositional space of polyamorphism of MGs into very dilute regions. Our work suggests that tunable properties under compressive stress could be achieved in MGs by even minor doping of elements prone to electronic transitions.

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 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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.430
Threshold uncertainty score0.721

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 head0.013
GPT teacher head0.212
Teacher spread0.199 · 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 teacher head, 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

Citations5
Published2021
Admission routes1
Has abstractyes

Explore more

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