MétaCan
Menu
Back to cohort
Record W4284975842 · doi:10.1002/smll.202203768

Enhancing the Microstructure of Perovskite‐Inspired Cu‐Ag‐Bi‐I Absorber for Efficient Indoor Photovoltaics

2022· article· en· W4284975842 on OpenAlexaff
G. Krishnamurthy Grandhi, Basheer Al‐Anesi, Hannu P. Pasanen, Harri Ali‐Löytty, Kimmo Lahtonen, Sari Granroth, Nino Christian, Anastasia Matuhina, Maning Liu, Alex Berdin, Vincenzo Pecunia, Paola Vivo

Bibliographic record

VenueSmall · 2022
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsSimon Fraser University
FundersJane ja Aatos Erkon SäätiöSuomen KulttuurirahastoAcademy of Finland
KeywordsMaterials sciencePhotovoltaicsPhotovoltaic systemPassivationPerovskite (structure)Energy conversion efficiencyOptoelectronicsNanotechnologyChemical engineeringLayer (electronics)Electrical engineering

Abstract

fetched live from OpenAlex

Abstract Lead‐free perovskite‐inspired materials (PIMs) are gaining attention in optoelectronics due to their low toxicity and inherent air stability. Their wide bandgaps (≈2 eV) make them ideal for indoor light harvesting. However, the investigation of PIMs for indoor photovoltaics (IPVs) is still in its infancy. Herein, the IPV potential of a quaternary PIM, Cu 2 AgBiI 6 (CABI), is demonstrated upon controlling the film crystallization dynamics via additive engineering. The addition of 1.5 vol% hydroiodic acid (HI) leads to films with improved surface coverage and large crystalline domains. The morphologically‐enhanced CABI+HI absorber leads to photovoltaic cells with a power conversion efficiency of 1.3% under 1 sun illumination—the highest efficiency ever reported for CABI cells and of 4.7% under indoor white light‐emitting diode lighting—that is, within the same range of commercial IPVs. This work highlights the great potential of CABI for IPVs and paves the way for future performance improvements through effective passivation strategies.

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)0.0010.000

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 head0.010
GPT teacher head0.206
Teacher spread0.196 · 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

Citations57
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueSmallSame topicPerovskite Materials and ApplicationsFrench-language works237,207