Some thermodynamic properties of larnite (β-Ca <sub>2</sub> SiO <sub>4</sub> ) constrained by high <i>T</i> / <i>P</i> experiment and/or theoretical simulation
Bibliographic record
Abstract
Pure larnite (β-Ca 2 SiO 4 ; Lrn) was synthesized at 6 GPa and 1473 K for 6 h by using a cubic press, its thermal expansivity was investigated up to 923 K by using an X-ray powder diffraction technique (ambient P ), and its compressibility was investigated up to ∼16 GPa by using a diamond-anvil cell coupled with synchrotron X-ray radiation (ambient T ). Its volumetric thermal expansion coefficient (α V ) and isothermal bulk modulus ( K T ) were constrained as α V = 4.24(4) × 10 −5 K −1 and K T = 103(2) GPa [the first pressure derivative KT′$K_{\rm{T}}^\prime $ obtained as 5.4(4)], respectively. Its compressibility was further studied with the CASTEP code using density functional theory and planewave pseudopotential technique. We obtained the K T values as 123(3) GPa (LDA; high boundary) and 92(2) GPa (GGA; low boundary), with the values of the KT′$K_{\rm{T}}^\prime $ as 4.4(9) and 4.9(5), respectively. The phonon dispersions and vibrational density of states (VDoS) of Lrn were simulated using density functional perturbation theory, and the VDoS was combined with a quasi-harmonic approximation to compute the isobaric heat capacity ( C P ) and standard vibrational entropy (S2980)$\left( {S_{298}^0} \right)$, yielding C P = 212.1(1) − 9.69(5) × 10 2 T −0.5 − 4.1(3) × 10 6 T −2 + 5.20(7) × 10 8 T −3 J/(mol.K) for the T range of ∼298–1000 K and (S2980) = 129.8(13)$\left( {S_{298}^0} \right)\, = \,129.8\left( {13} \right)$ J/(mol.K). The microscopic and macroscopic thermal Grüneisen parameters of Lrn at 298 K were calculated to be 0.75(6) and 1.80(4), respectively.
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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) | 0.002 | 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".