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Morphology features of β-Ga2O3 bulk crystals by EFG and CZ methods: A review

2024· review· en· W4405663312 on OpenAlex
Man Xu, Zining Wang, Rui Wang, Zhihong Yu, Bo Fu, Yujun Shi

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

VenueProgress in Crystal Growth and Characterization of Materials · 2024
Typereview
Languageen
FieldMaterials Science
TopicGa2O3 and related materials
Canadian institutionsUniversity of Calgary
FundersNatural Science Foundation of Shandong ProvinceState Key Laboratory of RoboticsNational Natural Science Foundation of ChinaState Key Laboratory of Crystal Materials
KeywordsMorphology (biology)Materials scienceCrystallographyMineralogyChemistryGeology

Abstract

fetched live from OpenAlex

High-quality crystals commonly exhibit regular morphology features and symmetries related to their crystal structures. The recognition of morphology features, especially on the shoulder morphology, will provide crucial guidance for the crystal growth and quality control. Here, the morphology features of β -Ga 2 O 3 bulk crystals were discussed from three aspects of growth technology, orientation of seed crystal as well as pulling and rotation rates. Combined with the theoretical morphology of β -Ga 2 O 3 crystal, the morphology features of β -Ga 2 O 3 bulk crystals under different growth conditions were illuminated and summarized. The hexagonal seed crystal was also demonstrated, and more suitable for the growth of β -Ga 2 O 3 bulk crystals with different principle surfaces by EFG method. The first review in the morphology features will become an important reference for future research on the growth of β -Ga 2 O 3 bulk crystals.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.204
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.022
GPT teacher head0.339
Teacher spread0.316 · 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