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Record W2605627140 · doi:10.1002/anie.201701321

Size‐Tunable Photothermal Germanium Nanocrystals

2017· article· en· W2605627140 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAngewandte Chemie International Edition · 2017
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaConnaught Fund
KeywordsPhotothermal therapyMaterials scienceGermaniumNanocrystalNanomaterialsNanotechnologyGermanateRaman spectroscopyOxideDisproportionationSiliconOptoelectronicsDopingChemical engineeringCatalysisChemistryOpticsMetallurgy

Abstract

fetched live from OpenAlex

Abstract Germanium nanocrystals (ncGe) have not received as much attention as silicon nanocrystals (ncSi). However, Ge has demonstrated superiority over Si nanomaterials in some applications. Examples include, high charge–discharge rate lithium‐ion batteries, [1] small band‐gap opto‐electronic devices, [2] and photo‐therapeutics. [3] When stabilized in an oxide matrix (ncGe/GeO x ), its high charge‐retention has enabled non‐volatile memories. [4] It has also found utility as a high‐capacity anode material for Li‐ion batteries with impressive stability. [5] Herein, we report an organic‐free synthesis of size‐controlled ncGe in a GeO x matrix as well as freestanding ncGe, via the thermal disproportionation of GeO prepared from thermally induced dehydration of Ge(OH) 2 . The photothermal effect of ncGe, quantified by Raman spectroscopy, is found to be size dependent and superior to ncSi. This advance suggests applications of ncGe in photothermal therapy, desalination, and catalysis.

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 categoriesInsufficient payload (model declined to judge)
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 score0.038
Threshold uncertainty score0.993

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.013
GPT teacher head0.266
Teacher spread0.252 · 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