Thermoelectric properties of<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>p</mml:mi></mml:math>-type CuInSe<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msub><mml:mrow/><mml:mn>2</mml:mn></mml:msub></mml:math>chalcopyrites enhanced by introduction of manganese
Bibliographic record
Abstract
Thermoelectric properties, x-ray photoelectron spectroscopy, Raman spectroscopy, and electronic structures have been studied for Mn-substituted CuInSe${}_{2}$ chalcopyrites. Raman spectroscopy verifies the lattice disorder due to the introduction of Mn into the CuInSe${}_{2}$ matrix, leading to a slight suppression of thermal conductivity. On the other hand, the Mn substitution significantly increases the electrical conductivity and Seebeck coefficient. Therefore the thermoelectric figure of merit $ZT$ has been enhanced by over two orders of magnitude by the introduction of Mn into CuInSe${}_{2}$. These materials are $p$-type degenerate semiconductors, containing divalent Mn species as confirmed by x-ray photoelectron spectroscopy. The crystal structure of Mn-substituted CuInSe${}_{2}$, as well as related ternary and quaternary diamond-like semiconductors, can be viewed as a combination of an electrically conducting unit, the Cu-Se and Mn-Se networks, and an electrically insulating unit, the In-Se network. Therefore, diamond-like semiconductors can serve as a potential class of thermoelectric materials with relatively wide band gaps upon substitution with Mn or other transition metals.
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 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) | 0.003 | 0.001 |
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".