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Record W4399971694 · doi:10.1002/adom.202401018

Tuning the Optical Anisotropy in Gradient Porous Germanium on Si Substrate

2024· article· en· W4399971694 on OpenAlex
Ying Zhu, Bowen Li, Jiacheng Hu, Guangrui Xia, Rui‐Tao Wen

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdvanced Optical Materials · 2024
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsUniversity of British Columbia
FundersDepartment of Education of Guangdong ProvinceScience, Technology and Innovation Commission of Shenzhen MunicipalityNational Natural Science Foundation of China
KeywordsMaterials scienceGermaniumAnisotropySubstrate (aquarium)Optical anisotropyOptoelectronicsPorositySiliconNanotechnologyOpticsComposite material

Abstract

fetched live from OpenAlex

Abstract Porous semiconductors have garnered significant attention owing to their distinctive physical and chemical properties. In this study, optical anisotropy is presented in porous germanium (PGe) on a Si (001) substrate. Both n ‐ and p ‐type PGe, achieved through bipolar electrochemical etching, exhibit optical anisotropy along the Ge <001> direction, as determined by spectroscopic ellipsometry. Birefringence and depolarization factors are controllable by adjusting the etching parameters and doping concentration of the epitaxial Ge layer. The gradient porosity and pore distribution in PGe can be well captured by the optical models. The findings of optical anisotropy in PGe‐on‐Si hold promise for applications in optical elements or sensors for gas or biomolecules.

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.

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 score0.126
Threshold uncertainty score0.740

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 head0.012
GPT teacher head0.261
Teacher spread0.249 · 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