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Record W4413330233 · doi:10.1038/s41598-025-13210-0

Optical and temperature dependent electrical properties of Er-/Yb-doped ZnO schottky diodes and thin films

2025· article· en· W4413330233 on OpenAlexaff
Dechasa Tolera, Teshome Senbeta, Belayneh Mesfin

Bibliographic record

VenueScientific Reports · 2025
Typearticle
Languageen
FieldMaterials Science
TopicZnO doping and properties
Canadian institutionsBombardier (Canada)
FundersAdama Science and Technology University
KeywordsDopingMaterials scienceOptoelectronicsSchottky diodeThin filmDiodeNanotechnology

Abstract

fetched live from OpenAlex

The study reports the fabrication of undoped and Er-/Yb-doped ZnO thin films using the sol-gel spin coating technique. The structural and optical properties of the films were analyzed using X-ray diffraction (XRD) and photoluminescence (PL) spectroscopy. Electrical characteristics were studied through current-voltage (I-V) measurements using an HP 4140B pA meter/voltage source, capable of detecting currents as low as 10 −14 A . The XRD analysis confirmed that all films exhibited a hexagonal wurtzite structure, while the PL measurements at room temperature revealed a strong ultraviolet emission with a peak wavelength at 380 nm . The I-V measurements demonstrated good rectification behavior across all temperature ranges. Schottky diodes based on Er and Yb-doped ZnO thin films showed improved rectification, a lower ideality factor, and a higher barrier height. With increasing temperature, the ideality factor decreased while the barrier height increased, indicating enhanced diode performance. It is found that the lowest ideality factor is 1.6 in Er-doped ZnO at 300 K and the highest barrier height is 0.81 eV in Yb-doped samples. It is worth noting that while the ideality factor decreased and Schottky barrier height increased with temperature indicating more ideal thermionic transport, while the rectification ratio (1.4 × 10 4 ) was highest in Yb-doped samples at 50 K due to reduced reverse leakage current.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.007
Threshold uncertainty score0.648

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
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 head0.014
GPT teacher head0.233
Teacher spread0.219 · 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

Citations6
Published2025
Admission routes1
Has abstractyes

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