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Record W2827319092 · doi:10.1039/c8cp01535j

Short-range ion dynamics in methylammonium lead iodide by multinuclear solid state NMR and<sup>127</sup>I NQR

2018· article· en· W2827319092 on OpenAlexfundno aff
Alessandro Senocrate, Igor Moudrakovski, Joachim Maier

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2018
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsnot available
FundersMax-Planck-GesellschaftUniversity of Ottawa
KeywordsChemistryIodideHalideRelaxation (psychology)IonRotation around a fixed axisChemical physicsSolid-state nuclear magnetic resonancePerovskite (structure)Spin–lattice relaxationMolecular dynamicsNuclear magnetic resonancePhysical chemistryCrystallographyComputational chemistryInorganic chemistryNuclear quadrupole resonancePhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

We explore the short-range ion dynamics in methylammonium lead iodide (MAPbI3, the archetypal halide perovskite) by means of solid-state NMR (1H, 13C, 14N, 15N and 207Pb) and Nuclear Quadrupolar Resonance (127I NQR), in combination with molecular dynamics simulations. We focus on the rotational motion of the methylammonium (MA) cation, and on the interaction between MA and the inorganic lattice, since these processes are linked to electronic carrier lifetimes, optical and electronic properties and even structural stability of this promising solar cell material. We show that the motion of the MA cation can be described by a bi-axial rotation, with similar interactions of CH3 and NH3+ groups with the inorganic framework. This motion becomes nearly isotropic above the cubic phase transition, dominating the spin-lattice relaxation of 1H, 13C and 15N through spin-rotational interactions. In addition, we observe strong cross-relaxation between 207Pb and 127I, which fully controls spin-spin and spin-lattice relaxation in 207Pb.

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 categoriesMeta-epidemiology (narrow)
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 score0.292
Threshold uncertainty score1.000

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 head0.008
GPT teacher head0.233
Teacher spread0.225 · 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.

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

Citations58
Published2018
Admission routes1
Has abstractyes

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