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Record W4403778225 · doi:10.1002/smll.202407277

Electrical Doping in Sc‐III‐Nitrides: Toward Multifunctional Devices at the Single Device Level

2024· article· en· W4403778225 on OpenAlexafffund
Milad Fathabadi, Mohammad Fazel Vafadar, Jean‐Christophe Lamanque, Songrui Zhao

Bibliographic record

VenueSmall · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsMcGill University
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceDopingScandiumDopantNitrideOptoelectronicsNanotechnologyLayer (electronics)Metallurgy

Abstract

fetched live from OpenAlex

A homogeneous integration of various types of devices using a single material platform is an ideal route toward multifunctional devices at the single-device level for miniaturized, fast, and energy-efficient systems. However, such a single material platform is still missing. Scandium-containing III-nitrides (Sc-III-nitrides) are promising, but their electrical doping properties remain unknown. In this work, the electrical doping in Sc-III-nitrides is investigated and optoelectronic devices using Sc-III-nitrides on silicon (Si) are further demonstrated. The material format of the nanowire is used, with magnesium (Mg) serving as the impurity dopant to control the electrical doping. It is discovered that, by adjusting the Mg doping concentrations, the Sc-III-nitrides can be tuned from n-type to p-type. Device application in light-emitting is further demonstrated using the p-type Sc-III-nitrides as the hole injection layer. The performance comparison between devices using the regrown Sc-containing p-type contact layers and non-Sc-containing p-type contact layers indicates the advantage of Sc incorporation in improving the quality of the regrown p-type layer in a device structure. The electrical doping in Sc-III-nitrides demonstrated in this study represents an important step toward a homogeneous integration of different types of devices using a single material platform.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.489
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 studies0.0000.000
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 head0.072
GPT teacher head0.276
Teacher spread0.204 · 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

Citations6
Published2024
Admission routes2
Has abstractyes

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