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Record W3138375557 · doi:10.1002/adfm.202010623

Ambient Stable and Efficient Monolithic Tandem Perovskite/PbS Quantum Dots Solar Cells via Surface Passivation and Light Management Strategies

2021· article· en· W3138375557 on OpenAlexfundno aff
Mohammad Mahdi Tavakoli, Hadi Tavakoli Dastjerdi, Pankaj Yadav, Daniel Prochowicz, Huayan Si, Rouhollah Tavakoli

Bibliographic record

VenueAdvanced Functional Materials · 2021
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPassivationMaterials scienceTandemQuantum dotOptoelectronicsPerovskite (structure)Energy conversion efficiencyBand gapSolar cellPerovskite solar cellNanowireNanotechnologyLayer (electronics)Chemical engineeringComposite material

Abstract

fetched live from OpenAlex

Abstract Here, highly efficient and stable monolithic (2‐terminal (2T)) perovskite/PbS quantum dots (QDs) tandem solar cells are reported, where the perovskite solar cell (PSC) acts as the front cell and the PbS QDs device with a narrow bandgap acts as the back cell. Specifically, ZnO nanowires (NWs) passivated by SnO 2 are employed as an electron transporting layer for PSC front cell, leading to a single cell PSC with maximum power conversion efficiency (PCE) of 22.15%, which is the most efficient NWs‐based PSCs in the literature. By surface passivation of PbS QDs by CdCl 2 , QD devices with an improved open‐circuit voltage and a PCE of 8.46% (bandgap of QDs: 0.92 eV) are achieved. After proper optimization, 2T and 4T tandem devices with stabilized PCEs of 17.1% and 21.1% are achieved, respectively, where the 2T tandem device shows the highest efficiency reported in the literature for this design. Interestingly, the 2T tandem cell shows excellent operational stability over 500 h under continuous illumination with only 6% PCE loss. More importantly, this device without any packaging depicts impressive ambient stability (almost no change) after 70 days in an environment with controlled 65% relative humidity, thanks to the superior air stability of the PbS QDs.

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 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 categoriesnone
Consensus categoriesnone
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 score0.053
Threshold uncertainty score0.886

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.190
Teacher spread0.184 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations74
Published2021
Admission routes1
Has abstractyes

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