Scalable Polyol Synthesis of Doped Bi <sub>2</sub> Te <sub>3</sub> with Enhanced Thermoelectric Performance
Bibliographic record
Abstract
Bi 2 Te 3 -based compounds remain one of the most effective thermoelectric materials for low-temperature applications, and their properties can be further enhanced by nanostructuring and dopant incorporation. This work demonstrates significant enhancement of n -type Bi 2 Te 3 synthesized by scalable, solution-based methods through the incorporation of copper, sulfur, and selenium. A peak zT of 1.23 at 383 K and an average zT of 1.11 between 314 and 533 K were achieved. Multiple dopant incorporation strategies were evaluated to identify the most effective approach for achieving uniform dopant distribution, and anisotropy effects arising from preferred crystallite orientation were investigated, demonstrating its influence on transport properties. Overall, this study demonstrates a fast, cost-effective, and scalable synthesis route for Bi 2 Te 3 with enhanced thermoelectric performance, advancing the development of efficient materials for waste heat recovery and sustainable energy technologies.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".