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Record W2469355815 · doi:10.1021/acs.nanolett.6b01782

Profiling Photoinduced Carrier Generation in Semiconductor Microwire Arrays via Photoelectrochemical Metal Deposition

2016· article· en· W2469355815 on OpenAlexfundno aff
Mita Dasog, Azhar I. Carim, Sisir Yalamanchili, Harry A. Atwater, Nathan S. Lewis

Bibliographic record

VenueNano Letters · 2016
Typearticle
Languageen
FieldEngineering
TopicNanowire Synthesis and Applications
Canadian institutionsnot available
FundersBasic Energy SciencesNatural Sciences and Engineering Research Council of CanadaNational Science FoundationGovernment of CanadaDivision of ChemistryInnovative Research Group Project of the National Natural Science Foundation of ChinaU.S. Department of EnergyOffice of Science
KeywordsMaterials scienceSemiconductorOptoelectronicsCharge carrierDopingWavelengthDeposition (geology)MetalSubstrate (aquarium)

Abstract

fetched live from OpenAlex

Au was photoelectrochemically deposited onto cylindrical or tapered p-Si microwires on Si substrates to profile the photoinduced charge-carrier generation in individual wires in a photoactive semiconductor wire array. Similar experiments were repeated for otherwise identical Si microwires doped to be n-type. The metal plating profile was conformal for n-type wires, but for p-type wires was a function of distance from the substrate and was dependent on the illumination wavelength. Spatially resolved charge-carrier generation profiles were computed using full-wave electromagnetic simulations, and the localization of the deposition at the p-type wire surfaces observed experimentally correlated well with the regions of enhanced calculated carrier generation in the volumes of the microwires. This technique could potentially be extended to determine the spatially resolved carrier generation profiles in a variety of mesostructured, photoactive 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.

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 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 score0.011
Threshold uncertainty score0.520

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 head0.010
GPT teacher head0.201
Teacher spread0.191 · 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

Citations15
Published2016
Admission routes1
Has abstractyes

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