MétaCan
Menu
Back to cohort
Record W2984301884 · doi:10.1021/acsphotonics.9b00951

Spectral Responsivity and Photoconductive Gain in Thin Film Black Phosphorus Photodetectors

2019· article· en· W2984301884 on OpenAlexafffund
Junjia Wang, Adrien Rousseau, Elad Eizner, Anne-Laurence Phaneuf-L’Heureux, Léonard Schué, S. Francoeur, Stéphane Kéna‐Cohen

Bibliographic record

VenueACS Photonics · 2019
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsResponsivityMaterials sciencePhotodetectorOptoelectronicsPhotoconductivityInfraredOpticsBand gapThin filmPhysicsNanotechnology

Abstract

fetched live from OpenAlex

We have fabricated black phosphorus photodetectors and characterized their full spectral responsivity. These devices, which are effectively in the bulk thin film limit, show broadband responsivity ranging from <400 nm to the ∼3.8 μm bandgap. In the visible, an intrinsic responsivity >6 A/W can be obtained due to internal gain mechanisms. By examining the full spectral response, we identify a sharp contrast between the visible and the infrared behavior. In particular, the visible responsivity shows a large photoconductive gain and gate-voltage dependence, while the infrared responsivity is nearly independent of gate voltage and incident light intensity under most conditions. This is attributed to a contribution from the surface oxide. In addition, we find that the polarization anisotropy in responsivity along armchair and zigzag directions can be as large as 103 and extends from the band edge to 500 nm. The devices were fabricated in an inert atmosphere and encapsulated by Al2O3, providing stable operation for more than 6 months.

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 categoriesInsufficient payload (model declined to judge)
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 score0.010
Threshold uncertainty score1.000

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)0.0010.001

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 head0.012
GPT teacher head0.252
Teacher spread0.240 · 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

Citations30
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueACS PhotonicsSame topic2D Materials and ApplicationsFrench-language works237,207