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Record W2979002590 · doi:10.1002/adma.201903559

Efficient and Stable Inverted Perovskite Solar Cells Incorporating Secondary Amines

2019· article· en· W2979002590 on OpenAlexaff
Hao Chen, Qi Wei, Makhsud I. Saidaminov, Fei Wang, Andrew Johnston, Yi Hou, Zijian Peng, Kaimin Xu, Wenjia Zhou, Zhenghao Liu, Lu Qiao, Xiao Wang, Siwen Xu, Jiangyu Li, Run Long, Youqi Ke, Edward H. Sargent, Zhijun Ning

Bibliographic record

VenueAdvanced Materials · 2019
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsUniversity of Toronto
FundersOffice of Naval ResearchShanghaiTech UniversityScience Fund for Creative Research Groups
KeywordsMaterials sciencePerovskite (structure)Energy conversion efficiencyPhotovoltaicsOptoelectronicsPerovskite solar cellDopantBand gapMethylamineDimethylamineSolar cellPhotovoltaic systemNanotechnologyChemical engineeringDopingChemistryOrganic chemistryElectrical engineering

Abstract

fetched live from OpenAlex

Abstract Large‐bandgap perovskites offer a route to improve the efficiency of energy capture in photovoltaics when employed in the front cell of perovskite–silicon tandems. Implementing perovskites as the front cell requires an inverted (p–i–n) architecture; this architecture is particularly effective at harnessing high‐energy photons and is compatible with ionic‐dopant‐free transport layers. Here, a power conversion efficiency of 21.6% is reported, the highest among inverted perovskite solar cells (PSCs). Only by introducing a secondary amine into the perovskite structure to form MA1−xDMAxPbI3 (MA is methylamine and DMA is dimethylamine) are defect density and carrier recombination suppressed to enable record performance. It is also found that the controlled inclusion of DMA increases the hydrophobicity and stability of films in ambient operating conditions: encapsulated devices maintain over 80% of their efficiency following 800 h of operation at the maximum power point, 30 times longer than reported in the best prior inverted PSCs. The unencapsulated devices show record operational stability in ambient air among PSCs.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.004
GPT teacher head0.185
Teacher spread0.181 · 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 source (direct Gemma or distilled Codex), 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

Citations188
Published2019
Admission routes1
Has abstractyes

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