The effect of photon recycling on thermophotovoltaic systems
Bibliographic record
Abstract
Thermophotovoltaic (TPV) systems are optical heat engines that directly convert radiant heat from an emitter into electricity using a photovoltaic (PV) cell. TPV is a versatile technology that can convert heat from any high temperature source (>1000 K) into electricity. Recently, TPV systems have achieved greater than ~40 % conversion efficiencies and are emerging as a promising method for grid energy storage and combined heat and power for the industrial and residential sectors in decarbonized energy systems. However, the efficiency of TPV systems is still low compared to their maximum theoretical efficiency and is often limited by the operating temperature of their emitter. For example, according to Planck’s law, for a TPV system with a blackbody (BB) emitter and GaSb PV cell (Eg = 1.72 ?m), increasing the temperature of the emitter from 1500 K to 1650 K (10% increase) results in a 94% increase in the number of photons with energy above the bandgap energy of the PV cell which can be converted into electricity.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".