MétaCan
Menu
Back to cohort
Record W2151776902 · doi:10.1021/nn800093v

Efficient, Stable Infrared Photovoltaics Based on Solution-Cast Colloidal Quantum Dots

2008· article· en· W2151776902 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueACS Nano · 2008
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPhotovoltaicsQuantum dotMaterials scienceOptoelectronicsInfraredPhotovoltaic systemNanotechnologyEnergy conversion efficiencyAbsorption (acoustics)PhysicsOptics

Abstract

fetched live from OpenAlex

Half of the sun's power lies in the infrared. As a result, the optimal bandgaps for solar cells in both the single-junction and even the tandem architectures lie beyond 850 nm. However, progress in low-cost, large-area, physically flexible solar cells has instead been made in organic and polymer materials possessing absorption onsets in the visible. Recent advances have been achieved in solution-cast infrared photovoltaics through the use of colloidal quantum dots. Here we report stable solution-processed photovoltaic devices having 3.6% power conversion efficiency in the infrared. The use of a strongly bound bidentate linker, benzenedithiol, ensures device stability over weeks. The devices reach external quantum efficiencies of 46% in the infrared and 70% across the visible. We investigate in detail the physical mechanisms underlying the operation of this class of device. In contrast with drift-dominated behavior in recent reports of PbS quantum dot photovoltaics, we find that diffusion of electrons and holes over hundreds of nanometers through our PbSe colloidal quantum dot solid is chiefly responsible for the high external quantum efficiencies obtained in this new class of devices.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.030
GPT teacher head0.227
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it