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Record W2617165101 · doi:10.1002/anie.201701724

The Nature of Ion Conduction in Methylammonium Lead Iodide: A Multimethod Approach

2017· article· en· W2617165101 on OpenAlexfundno aff
Alessandro Senocrate, Igor Moudrakovski, Gee Yeong Kim, Tae‐Youl Yang, Giuliano Gregori, Michaël Grätzel, Joachim Maier

Bibliographic record

VenueAngewandte Chemie International Edition · 2017
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsnot available
FundersMax Planck-EPFL Center for Molecular Nanoscience and TechnologyMax-Planck-GesellschaftUniversity of Ottawa
KeywordsIonConductivityChemistryStoichiometryIodineIodideDiffusionDopingAnalytical Chemistry (journal)Chemical physicsInorganic chemistryPhysical chemistryCondensed matter physicsThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Abstract By applying a multitude of experimental techniques including 1 H, 14 N, 207 Pb NMR and 127 I NMR/NQR, tracer diffusion, reaction cell and doping experiments, as well as stoichiometric variation, conductivity, and polarization experiments, iodine ions are unambiguously shown to be the mobile species in CH 3 NH 3 PbI 3 , with iodine vacancies shown to represent the mechanistic centers under equilibrium conditions. Pb 2+ and CH 3 NH 3 + ions do not significantly contribute to the long range transport (upper limits for their contributions are given), whereby the latter exhibit substantial local motion. The decisive electronic contribution to the mixed conductivity in the experimental window stems from electron holes. As holes can be associated with iodine orbitals, local variations of the iodine stoichiometry may be fast and enable light effects on ion transport.

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 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 score0.108
Threshold uncertainty score0.294

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 head0.021
GPT teacher head0.291
Teacher spread0.270 · 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 teacher head, 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

Citations264
Published2017
Admission routes1
Has abstractyes

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