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Record W3160471814 · doi:10.3390/nano11051254

Effect of the Helium Background Gas Pressure on the Structural and Optoelectronic Properties of Pulsed-Laser-Deposited PbS Thin Films

2021· article· en· W3160471814 on OpenAlexaff
Ameni Rebhi, Anouar Hajjaji, Joël Leblanc-Lavoie, S. Aouida, Mounir Gaidi, B. Bessaı̈s, My Alı El Khakani

Bibliographic record

VenueNanomaterials · 2021
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsMaterials scienceTorrCrystallitePulsed laser depositionRaman spectroscopyThin filmBand gapPhononLattice constantDiffractionAnalytical Chemistry (journal)Condensed matter physicsOptoelectronicsNanotechnologyOpticsChemistry

Abstract

fetched live from OpenAlex

This work focuses on the dependence of the features of PbS films deposited by pulsed laser deposition (PLD) subsequent to the variation of the background pressure of helium (PHe). The morphology of the PLD-PbS films changes from a densely packed and almost featureless structure to a columnar and porous one as the He pressure increases. The average crystallite size related to the (111) preferred orientation increases up to 20 nm for PHe ≥ 300 mTorr. The (111) lattice parameter continuously decreases with increasing PHe values and stabilizes at PHe ≥ 300 mTorr. A downshift transition of the Raman peak of the main phonon (1LO) occurs from PHe = 300 mTorr. This transition would result from electron–LO–phonon interaction and from a lattice contraction. The optical bandgap of the films increases from 1.4 to 1.85 eV as PHe increases from 50 to 500 mTorr. The electrical resistivity of PLD-PbS is increased with PHe and reached its maximum value of 20 Ω·cm at PHe = 300 mTorr (400 times higher than 50 mTorr), which is probably due to the increasing porosity of the films. PHe = 300 mTorr is pointed out as a transitional pressure for the structural and optoelectronic properties of PLD-PbS films.

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)0.001
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 score0.004
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.015
GPT teacher head0.228
Teacher spread0.213 · 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

Citations11
Published2021
Admission routes1
Has abstractyes

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