Adiabatic demagnetization cooling well below the magnetic ordering temperature in the triangular antiferromagnet <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mrow><mml:mi>KBaGd</mml:mi><mml:mo>(</mml:mo><mml:msub><mml:mi>BO</mml:mi><mml:mn>3</mml:mn></mml:msub><mml:mo>)</mml:mo></mml:mrow><mml:mn>2</mml:mn></mml:msub></mml:mrow></mml:math>
Bibliographic record
Abstract
Crystal structure, thermodynamic properties, and adiabatic demagnetization refrigeration (ADR) effect in the spin-$\frac{7}{2}$ triangular antiferromagnet $\mathrm{KBaGd}{({\mathrm{BO}}_{3})}_{2}$ are reported. With the average nearest-neighbor exchange coupling of 44 mK, this compound shows magnetic order below ${T}_{N}=263$ mK in zero field. The ADR tests reach the temperature of ${T}_{min}=122\phantom{\rule{0.16em}{0ex}}\mathrm{mK}$, more than twice lower than ${T}_{N}$, along with the entropy storage capacity of 192 mJ ${\mathrm{K}}^{\ensuremath{-}1}$ ${\mathrm{cm}}^{\ensuremath{-}3}$ and the hold time of more than 8 h in the PPMS setup, both significantly improved compared to the spin-$\frac{1}{2}\phantom{\rule{4pt}{0ex}}{\mathrm{Yb}}^{3+}$ analog. We argue that $\mathrm{KBaGd}{({\mathrm{BO}}_{3})}_{2}$ shows a balanced interplay of exchange and dipolar couplings that together with structural randomness and geometrical frustration shift ${T}_{min}$ to well below the ordering temperature ${T}_{N}$, therefore facilitating the cooling.
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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) | 0.004 | 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".