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Structural transitions in RNi<sub>10</sub>Si<sub>2</sub>intermetallics

2009· article· en· W1633884075 on OpenAlexaff
O. Može, W. Kockelmann, M. Hofmann, J. M. Cadogan, D. H. Ryan, K.H.J. Buschow

Bibliographic record

VenueJournal of Physics Condensed Matter · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRare-earth and actinide compounds
Canadian institutionsMcGill UniversityUniversity of Manitoba
FundersBundesministerium für Bildung und Forschung
KeywordsIntermetallicNeutron diffractionThermal expansionMaterials scienceLattice constantCondensed matter physicsPhase transitionIsing modelLattice (music)Critical exponentTransition temperatureDiffractionExponentCrystallographyCrystal structureChemistrySuperconductivityPhysicsMetallurgy

Abstract

fetched live from OpenAlex

Intermetallic compounds of the type RFe(10)Si(2) and RCo(10)Si(2) crystallize in the ThMn(12) structure (space group I4/mmm) whilst the heavy rare earth series RNi(10)Si(2) crystallize in a maximal subgroup of I4/mmm, P4/nmm. Reported here are neutron powder diffraction investigations for TbNi(10)Si(2) and ErNi(10)Si(2) which show that the P4/nmm structure undergoes a high temperature order-disorder phase transition at approximately 930 °C above which the ordered Ni and Si fractions revert to a random distribution on 4d and 4e sites. The volume expansion has been tracked in detail via the temperature dependence of the lattice parameters, whilst the temperature dependence of the thermal expansion coefficients α(11), α(33) and α(volume) has been determined from the lattice parameters. Associated with the order-disorder transition is a transition associated with a displacement of the R ion along the c-axis. Both transitions are of second order and the critical exponent associated with the order-disorder and displacive transitions, β = 0.31, is in excellent agreement with the exponent determined for the three-dimensional Ising model.

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 categoriesMeta-epidemiology (narrow)
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 score0.097
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.230
Teacher spread0.221 · 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.

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

Citations2
Published2009
Admission routes1
Has abstractyes

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