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Record W2956062247 · doi:10.71781/17549

Calculs numériques du spectre Raman double-résonant du phosphorène

2018· dissertation· fr· W2956062247 on OpenAlexfundaboutno aff
Félix Antoine Goudreault

Bibliographic record

VenueOpen MIND · 2018
Typedissertation
Languagefr
FieldPhysics and Astronomy
TopicQuantum optics and atomic interactions
Canadian institutionsnot available
FundersFonds de recherche du Québec – Nature et technologiesUniversité de MontréalNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsMinistère de l'Économie, de la Science et de l'Innovation - QuébecCompute Canada
KeywordsPhosphorPhysicsChemistryMaterials scienceOptoelectronics

Abstract

fetched live from OpenAlex

Ce mémoire présente une étude du spectre Raman de second-ordre du phosphorène. Quatre nouveaux modes Raman induits par des défauts ont étés identifiés dans les régions de A1g et A2g pour des couches minces de phosphore noir. Dans le but de comprendre leur origine, nous avons effectué le calcul du spectre Raman double-résonant du phosphorène à partir de données ab initio calculées en DFT. L’étude effectuée corrobore l’identification de ces modes médiés par un phonon de momentum non nul et par un défaut. De plus, on conclut que les pics correspondants sont le résultat de l’accumulation des électrons et des trous dans une certaine région de la première vallée de la structure électronique. Des prédictions sur la dispersion de ces pics en fonction de l’énergie incidente sont ensuite établies. Cette étude pose les fondations d’une compréhension du spectre Raman de minces couches de phosphore noir en présence de défauts. Elle ouvre la voie à une possible caractérisation de ce matériau à partir de son spectre. Ce projet est le fruit d’une collaboration entre le groupe de recherche de Michel Côté du département de physique et celui de Richard Martel du département de chimie de l’Université de Montréal.

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), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.732
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0390.012

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 head0.020
GPT teacher head0.310
Teacher spread0.291 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueOpen MINDSame topicQuantum optics and atomic interactionsFrench-language works237,207