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Record W2800048463 · doi:10.1021/acsami.8b03133

Charge Separation at Mixed-Dimensional Single and Multilayer MoS<sub>2</sub>/Silicon Nanowire Heterojunctions

2018· article· en· W2800048463 on OpenAlexfundno aff
Alex Henning, Vinod K. Sangwan, Hadallia Bergeron, Itamar Balla, Zhiyuan Sun, Mark C. Hersam, Lincoln J. Lauhon

Bibliographic record

VenueACS Applied Materials & Interfaces · 2018
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsnot available
FundersDivision of Emerging Frontiers in Research and InnovationNatural Sciences and Engineering Research Council of CanadaDivision of Graduate EducationDeutsche Forschungsgemeinschaft
KeywordsMaterials scienceHeterojunctionNanowireSiliconNanotechnologySilicon nanowiresOptoelectronicsCharge (physics)

Abstract

fetched live from OpenAlex

Layered two-dimensional (2-D) semiconductors can be combined with other low-dimensional semiconductors to form nonplanar mixed-dimensional van der Waals (vdW) heterojunctions whose charge transport behavior is influenced by the heterojunction geometry, providing a new degree of freedom to engineer device functions. Toward that end, we investigated the photoresponse of Si nanowire/MoS2 heterojunction diodes with scanning photocurrent microscopy and time-resolved photocurrent measurements. Comparison of n-Si/MoS2 isotype heterojunctions with p-Si/MoS2 heterojunction diodes under varying biases shows that the depletion region in the p–n heterojunction promotes exciton dissociation and carrier collection. We measure an instrument-limited response time of 1 μs, which is 10 times faster than the previously reported response times for planar Si/MoS2 devices, highlighting the advantages of the 1-D/2-D heterojunction. Finite element simulations of device models provide a detailed understanding of how the electrostatics affect charge transport in nanowire/vdW heterojunctions and inform the design of future vdW heterojunction photodetectors and transistors.

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), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.002
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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.003

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 head0.016
GPT teacher head0.250
Teacher spread0.234 · 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 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

Citations36
Published2018
Admission routes1
Has abstractyes

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