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Record W3188287295 · doi:10.1002/adma.202100288

Surface‐Anisotropic Janus Silicon Quantum Dots via Masking on 2D Silicon Nanosheets

2021· article· en· W3188287295 on OpenAlexafffund
Marc Julian Kloberg, Haoyang Yu, Felix Eckmann, Tassilo M. F. Restle, Thomas F. Fässler, Jonathan G. C. Veinot, Bernhard Rieger

Bibliographic record

VenueAdvanced Materials · 2021
Typearticle
Languageen
FieldMaterials Science
TopicPickering emulsions and particle stabilization
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaInternational Graduate School of Science and EngineeringCanada First Research Excellence FundTechnische Universität MünchenDeutsche Forschungsgemeinschaft
KeywordsMaterials scienceJanusMasking (illustration)SiliconNanotechnologyQuantum dotOptoelectronicsAnisotropySurface (topology)Optics

Abstract

fetched live from OpenAlex

Surface-anisotropic nanoparticles represent a new class of materials that shows potential in a variety of applications, including self-assembly, microelectronics, and biology. Here, the first synthesis of surface-anisotropic silicon quantum dots (SiQDs), obtained through masking on 2D silicon nanosheets, is presented. SiQDs are deposited on the 2D substrate, thereby exposing only one side of the QDs, which is functionalized through well-established hydrosilylation procedures. The UV-sensitive masking substrate is removed through UV-irradiation, which simultaneously initiates the hydrosilylation of a second substrate, thereby introducing a second functional group to the other side of the now free-standing SiQDs. This renders surface-anisotropic SiQDs that have two different functional groups on either side of the particle. This method can be used to introduce a variety of functional groups including hydrophilic and hydrophobic substrates, while the unique optoelectronic properties of the SiQDs remain unaffected. The anisotropic morphology of the QDs is confirmed through the aggregation behavior of amphiphilic Janus SiQDs at the interface of water and hexane. Additionally, anisotropic SiQDs are used to produce the first controlled (sub)monolayer of SiQDs on a gold wafer.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score1.000

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)0.0020.001

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 head0.019
GPT teacher head0.271
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

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

Citations19
Published2021
Admission routes2
Has abstractyes

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