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Record W2532348613 · doi:10.1021/acs.inorgchem.6b01307

Decomposition and Cell Failure Mechanisms in Lead Halide Perovskite Solar Cells

2016· article· en· W2532348613 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInorganic Chemistry · 2016
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsPerovskite (structure)HalideChemistryPhotovoltaic systemCadmium telluride photovoltaicsSolar cellDecompositionLead (geology)Thin filmEnergy conversion efficiencySiliconNanotechnologyEngineering physicsOptoelectronicsInorganic chemistryMaterials scienceElectrical engineeringOrganic chemistryPhysicsGeology

Abstract

fetched live from OpenAlex

Perovskite solar cells have experienced a remarkably rapid rise in power conversion efficiencies, with state-of-the-art devices now competing with multicrystalline silicon and thin-film cadmium telluride in terms of efficiency. Unfortunately, the lead halide perovskite absorbers suffer from a lack of chemical stability and decompose in response to a variety of environmental stimuli. In this Forum Article, we provide a brief overview of the decomposition mechanisms in lead halide perovskite thin films, as well as the processes contributing to cell failure in finished devices. We finish by briefly surveying recent efforts to extend the device lifetime. Ultimately, if perovskite solar cells can be made stable, they will be an exciting, highly complementary addition to existing photovoltaic technologies.

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.

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 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 score0.005
Threshold uncertainty score0.444

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.003
GPT teacher head0.176
Teacher spread0.174 · 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