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Record W3048862536 · doi:10.1002/adfm.202004563

Multiphoton Absorption Stimulated Metal Chalcogenide Quantum Dot Solar Cells under Ambient and Concentrated Irradiance

2020· article· en· W3048862536 on OpenAlexaff
Bo Hou, Byung‐Sung Kim, Harrison Ka Hin Lee, Yuljae Cho, Paul Giraud, Mengxia Liu, Jingchao Zhang, Matthew L. Davies, James R. Durrant, Wing Chung Tsoi, Zhe Li, Stoichko D. Dimitrov, Jung Inn Sohn, SeungNam Cha, Jong Min Kim

Bibliographic record

VenueAdvanced Functional Materials · 2020
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsUniversity of Toronto
FundersEngineering and Physical Sciences Research CouncilEuropean Regional Development FundNational Research FoundationHorizon 2020 Framework ProgrammeNational Research Foundation of KoreaCardiff UniversityEuropean Commission
KeywordsMaterials scienceQuantum dotOptoelectronicsMultiple exciton generationChalcogenideAbsorption (acoustics)PhotovoltaicsAuger effectBand gapPhotonSolar cellQuantum efficiencyPhotovoltaic systemOpticsAugerPhysics

Abstract

fetched live from OpenAlex

Abstract Colloidal metal chalcogenide quantum dots (QDs) have excellent quantum efficiency in light–matter interactions and good device stability. However, QDs have been brought to the forefront as viable building blocks in bottom‐up assembling semiconductor devices, the development of QD solar cell (QDSC) is still confronting considerable challenges compared to other QD technologies due to their low performance under natural sunlight, as a consequence of untapped potential from their quantized density‐of‐state and inorganic natures. This report is designed to address this long‐standing challenge by accessing the feasibility of using QDSC for indoor and concentration PV (CPV) applications. This work finds that above bandgap photon energy irradiation of QD solids can generate high densities of excitons via multi‐photon absorption (MPA), and these excitons are not limited to diffuse by Auger recombination up to 1.5 × 10 19 cm −3 densities. Based on these findings, a 19.5% (2000 lux indoor light) and an 11.6% efficiency (1.5 Suns) have been facilely realized from ordinary QDSCs (9.55% under 1 Sun). To further illustrate the potential of the MPA in QDSCs, 21.29% efficiency polymer lens CPVs (4.08 Suns) and viable sensor networks powered by indoor QDSCs matrix have been demonstrated.

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 categoriesMeta-epidemiology (narrow), Insufficient 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 score0.003
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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.035
GPT teacher head0.227
Teacher spread0.192 · 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; both teacher heads agree on what is shown here.

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

Citations55
Published2020
Admission routes1
Has abstractyes

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