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Record W3014589278 · doi:10.1007/s40820-020-00418-0

Low-Temperature Aging Provides 22% Efficient Bromine-Free and Passivation Layer-Free Planar Perovskite Solar Cells

2020· article· en· W3014589278 on OpenAlexaff
Xin Wang, Luyao Wang, Tong Shan, Shibing Leng, Hongliang Zhong, Qinye Bao, Zheng‐Hong Lu, Lin‐Long Deng, Chun‐Chao Chen

Bibliographic record

VenueNano-Micro Letters · 2020
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsUniversity of Toronto
FundersNational Natural Science Foundation of China
KeywordsPassivationFormamidiniumPerovskite (structure)BromineHalideMaterials scienceNucleationChemical engineeringLayer (electronics)Phase (matter)Inorganic chemistryNanotechnologyChemistryMetallurgyOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Previous reports of formamidinium/methylamine (FAMA)-mixed halide perovskite solar cells have focused mainly on controlling the morphology of the perovskite film and its interface—for example, through the inclusion of bromine and surface passivation. In this paper, we describe a new processing pathway for the growth of a high-quality bromine-free FAMAPbI3 halide perovskites via the control of intermediate phase. Through low-temperature aging growth (LTAG) of a freshly deposited perovskite film, α-phase perovskites can be seeded in the intermediate phase and, at the same time, prevent beta-phase perovskite to nucleate. After postannealing, large grain-size perovskites with significantly reduced PbI2 presence on the surface can be obtained, thereby eliminating the need of additional surface passivation step. Our pristine LTAG-treated solar cells could provide PCEs of greater than 22% without elaborate use of bromine or an additional passivation layer. More importantly, when using this LTAG process, the growth of the pure alpha-phase FAMAPbI3 was highly reproducible.

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 score0.004

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)0.0010.001

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 head0.006
GPT teacher head0.177
Teacher spread0.171 · 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

Citations45
Published2020
Admission routes1
Has abstractyes

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