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Record W4388726580 · doi:10.1126/science.adk1633

Bimolecularly passivated interface enables efficient and stable inverted perovskite solar cells

2023· article· en· W4388726580 on OpenAlexaff
Cheng Liu, Yi Yang, Hao Chen, Jian Xu, Ao Liu, Abdulaziz S. R. Bati, Huihui Zhu, Luke Grater, Shreyash Hadke, Chuying Huang, Vinod K. Sangwan, Tong Cai, Donghoon Shin, Lin X. Chen, Mark C. Hersam, Chad A. Mirkin, Bin Chen, Mercouri G. Kanatzidis, Edward H. Sargent

Bibliographic record

VenueScience · 2023
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsUniversity of Toronto
FundersArmy Research OfficeDivision of Materials ResearchNorthwestern UniversityOffice of Naval ResearchMaterials Research Science and Engineering Center, Harvard UniversitySherman Fairchild FoundationNational Science Foundation
KeywordsPassivationPerovskite (structure)Materials sciencePhotovoltaic systemOptoelectronicsEnergy conversion efficiencyPhotoluminescenceCarrier lifetimeRecombinationTandemNanotechnologyChemistrySiliconCrystallographyComposite material

Abstract

fetched live from OpenAlex

Compared with the n-i-p structure, inverted (p-i-n) perovskite solar cells (PSCs) promise increased operating stability, but these photovoltaic cells often exhibit lower power conversion efficiencies (PCEs) because of nonradiative recombination losses, particularly at the perovskite/C 60 interface. We passivated surface defects and enabled reflection of minority carriers from the interface into the bulk using two types of functional molecules. We used sulfur-modified methylthio molecules to passivate surface defects and suppress recombination through strong coordination and hydrogen bonding, along with diammonium molecules to repel minority carriers and reduce contact-induced interface recombination achieved through field-effect passivation. This approach led to a fivefold longer carrier lifetime and one-third the photoluminescence quantum yield loss and enabled a certified quasi-steady-state PCE of 25.1% for inverted PSCs with stable operation at 65°C for >2000 hours in ambient air. We also fabricated monolithic all-perovskite tandem solar cells with 28.1% PCE.

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 head0.008
GPT teacher head0.211
Teacher spread0.203 · 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

Citations680
Published2023
Admission routes1
Has abstractyes

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