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Record W2468505094 · doi:10.1038/srep29610

Strong and Anomalous Thermal Expansion Precedes the Thermosalient Effect in Dynamic Molecular Crystals

2016· article· en· W2468505094 on OpenAlexfundno aff
Manas K. Panda, Roberto Centore, Mauro Causà, Angela Tuzi, Fabio Borbone, Pancě Naumov

Bibliographic record

VenueScientific Reports · 2016
Typearticle
Languageen
FieldMaterials Science
TopicThermal Expansion and Ionic Conductivity
Canadian institutionsnot available
FundersYork UniversityNew York University Abu Dhabi
KeywordsNegative thermal expansionThermal expansionAnisotropyCrystal (programming language)Phase transitionThermalStrain (injury)Materials scienceChemical physicsPhase (matter)Molecular dynamicsWork (physics)ChemistryCrystallographyCondensed matter physicsThermodynamicsPhysicsComputational chemistryBiologyComposite materialOrganic chemistryComputer science

Abstract

fetched live from OpenAlex

The ability of thermosalient solids, organic analogues of inorganic martensites, to move by rapid mechanical reconfiguration or ballistic event remains visually appealing and potentially useful, yet mechanistically elusive phenomenon. Here, with a material that undergoes both thermosalient and non-thermosalient phase transitions, we demonstrate that the thermosalient effect is preceded by anomalous thermal expansion of the unit cell. The crystal explosion occurs as sudden release of the latent strain accumulated during the anisotropic, exceedingly strong expansion of the unit cell with αa = 225.9 × 10(-6) K(-1), αb = 238.8 × 10(-6) K(-1) and αc = -290.0 × 10(-6) K(-1), the latter being the largest negative thermal expansivity observed for an organic compound thus far. The results point out to the occurence of the thermosalient effect in phase transitions as means to identify new molecular materials with strong positive and/or negative thermal expansion which prior to this work could only be discovered serendipitously.

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 score0.005

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 head0.007
GPT teacher head0.240
Teacher spread0.233 · 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

Citations122
Published2016
Admission routes1
Has abstractyes

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