Combined Machine Learning and Experimental Study for the Zintl Phase Thermoelectric Ba <sub> 1− <i>x</i> </sub> Sr <sub> <i>x</i> </sub> Zn <sub> 2− <i>y</i> </sub> Cd <sub> <i>y</i> </sub> Sb <sub>2</sub> System
Bibliographic record
Abstract
Two new Sr and Cd cosubstituted zintl phases of Ba 0.92(2) Sr 0.08 Zn 1.30(3) Cd 0.70 Sb 2 and Ba 0.60(2) Sr 0.40 Zn 0.32(4) Cd 1.68 Sb 2 are successfully synthesized, and these compounds are crystallized in the orthorhombic BaCu 2 S 2 ‐type and the trigonal CaAl 2 Si 2 ‐type phases, respectively. Overall, crystal structures are constructed by the assembly of 1) the structural backbone of the infinite chain and 2) the Ba/Sr mixed site, filling the space within or in‐between anionic frameworks. The structural selectivity between these two title phases can be explained by the radius ratio criterion of cationic‐to‐anionic elements ( r + / r – ). Furthermore, the r + / r – criterion determining the preferred structure is closely related to the Ba/SrSb bond distance and eventually affects the Sr substitution level in both phases. A series of DFT calculations suggest that the BaCu 2 S 2 ‐type phase exhibits a heavily doped semiconductor behavior, while the CaAl 2 Si 2 ‐type phase shows semiconducting behavior. The temperature‐dependent thermoelectric (TE) property measurements prove that Ba 0.60(2) Sr 0.40 Zn 0.32(4) Cd 1.68 Sb 2 exhibits a relatively higher ZT value than Ba 0.92(2) Sr 0.08 Zn 1.30(3) Cd 0.70 Sb 2 due to its higher electrical conductivities and Seebeck coefficients. Machine learning (ML)‐based predictions successfully capture general TE trends of the title phases and show higher ZT values for the BaCu 2 S 2 ‐type phase compared to the CaAl 2 Si 2 ‐type phase.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".