Near‐Zero Thermal Expansion in <scp> <scp>In</scp> </scp> ( <scp> <scp>HfMg</scp> </scp> ) <sub>0.5</sub> <scp> <scp>Mo</scp> </scp> <sub>3</sub> <scp> <scp>O</scp> </scp> <sub>12</sub>
Bibliographic record
Abstract
In ( HfMg ) 0.5 Mo 3 O 12 , which can be considered as a 1:1 mole ratio solid solution of the low‐positive thermal expansion material HfMgMo 3 O 12 and the low‐negative thermal expansion (NTE) material In 2 Mo 3 O 12 was prepared. From DSC and XRPD results, we show that In ( HfMg ) 0.5 Mo 3 O 12 exists in a monoclinic ( P 2 1 / a ) structure at low temperature and undergoes a phase transition at ~425 K to an orthorhombic phase ( Pnma ), with an associated enthalpy change of 0.89 kJ mol −1 . Thermal expansion is large and positive in the low‐temperature monoclinic phase (average α ℓ = 16 × 10 −6 K −1 and 20 × 10 −6 K −1 , from dilatometry and XRPD , respectively). Remarkably, this material has a near‐zero thermal expansion (ZTE) coefficient over the temperature range ~500 to ~900 K in the high‐temperature orthorhombic phase, both intrinsically and for the bulk sample. The average linear intrinsic ( XRPD ) value is α ℓ = −0.4 × 10 −6 K −1 , and the average bulk (dilatometric) value is α ℓ = 0.4 × 10 −6 K −1 with an uncertainty of ± 0.2 × 10 −6 K −1 . The slight difference between intrinsic and bulk thermal expansion is attributed to microstructural effects. XRPD results show that the thermal expansion is more isotropic than for the parent compounds HfMgMo 3 O 12 and In 2 Mo 3 O 12 .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".