Gradient-Doped Colloidal Quantum Dot Solids Enable Thermophotovoltaic Harvesting of Waste Heat
Bibliographic record
Abstract
Electromagnetic radiation emitted from hot objects represents a sizable source of energy, one that in most applications is not harvested efficiently. Even for a blackbody at 800 °C, the radiation intensity peaks near 2.7 μm wavelength, and this requires a semiconductor absorber having a band gap in the short-wavelength infrared and beyond to enable thermophotovoltaic (TPV) heat recovery. Here we report the first solution-processed TPV device to harvest efficiently 800 °C heat. The active layer consists of colloidal quantum dots (CQDs), infrared-absorbing nanoparticles synthesized using a scalable solution-based method, having 0.75 eV band gap. We construct rectifying junction devices based on controllably p- and n-doped CQD solids that benefit from a gradient in electron affinity that extends over the devices’ thickness. The gradient-doped architecture relies on engineered charge carrier drift and overcomes the existing limitations of small band gap CQD solids. The devices provide 2.7% efficiency in the conversion of optical power from above-band gap photons from a blackbody source at 800 ± 20 °C into electrical power. The cells were thermally stable up to 140 °C, increasing the promise of CQD solids for TPV applications.
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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) | 0.000 | 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 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".