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Record W2222143222 · doi:10.1021/acs.jpclett.5b02681

Heterovalent Dopant Incorporation for Bandgap and Type Engineering of Perovskite Crystals

2016· article· en· W2222143222 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.

Bibliographic record

VenueThe Journal of Physical Chemistry Letters · 2016
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsUniversity of Toronto
FundersDivision of Materials ResearchKing Abdullah University of Science and Technology
KeywordsDopantPerovskite (structure)Materials scienceBand gapDopingOptoelectronicsEngineering physicsCrystallographyChemistryPhysics

Abstract

fetched live from OpenAlex

Controllable doping of semiconductors is a fundamental technological requirement for electronic and optoelectronic devices. As intrinsic semiconductors, hybrid perovskites have so far been a phenomenal success in photovoltaics. The inability to dope these materials heterovalently (or aliovalently) has greatly limited their wider utilizations in electronics. Here we show an efficient in situ chemical route that achieves the controlled incorporation of trivalent cations (Bi(3+), Au(3+), or In(3+)) by exploiting the retrograde solubility behavior of perovskites. We term the new method dopant incorporation in the retrograde regime. We achieve Bi(3+) incorporation that leads to bandgap tuning (∼300 meV), 10(4) fold enhancement in electrical conductivity, and a change in the sign of majority charge carriers from positive to negative. This work demonstrates the successful incorporation of dopants into perovskite crystals while preserving the host lattice structure, opening new avenues to tailor the electronic and optoelectronic properties of this rapidly emerging class of solution-processed semiconductors.

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 score0.009
Threshold uncertainty score0.168

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 head0.007
GPT teacher head0.197
Teacher spread0.190 · 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