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Mapping electrostatic potentials across the p‐n junction in <scp>GaAs</scp> nanowires by off‐axis electron holography

2016· other· en· W4239970225 on OpenAlexaff
Elisabetta Maria Fiordaliso, Zoltan Imre Balogh, Takeshi Kasama, Ray LaPierre, Martin Aagesen

Bibliographic record

VenueEuropean Microscopy Congress 2016: Proceedings · 2016
Typeother
Languageen
FieldEngineering
TopicNanowire Synthesis and Applications
Canadian institutionsMcMaster University
Fundersnot available
KeywordsElectron holographyNanowireMaterials scienceSemiconductorPassivationOptoelectronicsTransmission electron microscopyDopantSubstrate (aquarium)NanotechnologyDopingLayer (electronics)

Abstract

fetched live from OpenAlex

The development of III−V materials on Si platforms, with the aim of reducing production costs while achieving high conversion efficiency, has been a continuing area of photovoltaic research in the last decades [1,2]. This process is challenging due to large lattice mismatches, the polar non‐polar interfaces and the differences in thermal expansion coefficients. The use of III–V nanowires (NWs) provides a novel method of integrating III‐V materials with Si, which avoids dislocations [3]. However the control of other parameters, such as vertical yield in a patterned array, crystal phase, dopant concentrations and electrostatic potential distribution, become challenging. The electrical performance of a semiconductor device relies strongly on how precisely the electrostatic potentials are distributed across the active region. An accurate measurement of this potential distribution is of vital interest to the semiconductor industry. The technique of off‐axis electron holography in the transmission electron microscope (TEM) is a powerful tool for fulfilling the required accuracy in mapping electrostatic potentials [4]. Here, we present electron holography measurements from single GaAs core‐shell nanowires with a p‐n junction, grown on a Si (1 1 1) substrate. The Ga‐assisted vapor–liquid–solid (VLS) growth mechanism on a silicon substrate was used for the formation of a patterned array of radial p‐i‐n GaAs NWs encapsulated in AlInP passivation. A cross‐sectional specimen for off‐axis electron holography was prepared perpendicular to the growth direction of the NW using focused ion beam milling (FIB) and the in‐situ lift‐out technique in an FEI Helios Dualbeam FIB/SEM, equipped with a micromanipulator. Holograms were acquired at 120 kV using an FEI Titan 80‐300ST TEM, equipped with a rotatable Möllenstedt biprism. The thickness of the specimen was measured to be around 280 nm by convergent beam electron diffraction (CBED). Fig. 1 shows the reconstructed phase and amplitude from the hologram of the cross‐sectional specimen. A core‐shell structure is observed, with the core being p‐type and the shell being n‐type. The phase shift across the p‐n junction is close to 1 radian, corresponding to a built‐in potential of 0.4 V, as shown in Fig.2. The potential variation measured by holography is used to quantify the actual doping densities in the n‐type layer and p‐type layer of the NW. This holography measurement indicates that the active dopant concentrations are lower than nominal values, causing a low built‐in potential. A greater control on the dopant concentration and distribution is required in order to achieve a higher efficiency of the NW solar cells.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.277
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.005
GPT teacher head0.229
Teacher spread0.225 · 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 designNot applicable
Domainnot available
GenreOther

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".

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Citations2
Published2016
Admission routes1
Has abstractyes

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