Optimizing Thermoelectric Properties of PEDOT: PSS/Bi 2 Te 3 /reduced Graphene Oxide Ternary Composite Films for Energy Harvesting Applications
Bibliographic record
Abstract
Abstract We present a notable improvement in the TE efficiency of PEDOT: PSS through the fabrication of composite films incorporating Bi2Te3 and rGO. A set of five PEDOT: PSS/Bi2Te3 /rGO ternary composite films samples, namely, (a) PEDOT: PSS (b) PEDOT: PSS /0.4BT% Bi2Te3 (c) PEDOt :PSS/0.4% Bi2Te3 /0.1% rGO (d) PEDOT: PSS /0.4% Bi2Te3 /0.2% rGO, and (e) PEDOT: PSS /0.4% Bi2Te3 /0.3% rGO, were used for investigations, Using XRD, Raman, SEM, and XPS the Structural property and morphological characterstics of the composite films were thoroughly examined. At ambient temperature, the 0.1 rGO ternary composite film exhibited the highest electrical conductivity of 18.21 Scm-1, Seebeck coefficient of 15.5 ΜvK-1, and a power factor of 11.39 μWm-1 K-2. This value represents 5-6 times more than pristine PEDOT: PSS film. The observed notable enhancements can be ascribed to the highly structured arrangement of PEDOT chains on the surface of rGO. This alignment is a result of the strong interfacial interaction between PEDOT: PSS and rGO, as well as the separation of PEDOT and PSS phases. The findings of this study present an apparent and promising route for the utilization of PEDOT: PSS in the field of most promising and high-efficient TE conversion process.
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) | 0.001 | 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".