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Record W2955779970 · doi:10.3390/s19132966

Two-Dimensional Graphene Family Material: Assembly, Biocompatibility and Sensors Applications

2019· review· en· W2955779970 on OpenAlexaff
Xingying Zhang, Ying Wang, Gaoxing Luo, Malcolm Xing

Bibliographic record

VenueSensors · 2019
Typereview
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsGrapheneBiocompatibilityNanotechnologyMaterials scienceAptamerFabricationBiosensorCovalent bondChemistry

Abstract

fetched live from OpenAlex

Graphene and its chemically exfoliated derivatives-GO and rGO-are the key members of graphene family materials (GFM). The atomically thick crystal structure and the large continuous π conjugate of graphene imparts it with unique electrical, mechanical, optical, thermal, and chemical properties. Although those properties of GO and rGO are compromised, they have better scalability and chemical tunability. All GFMs can be subject to noncovalent modification due to the large basal plane. Besides, they have satisfying biocompatibility. Thus, GFMs are promising materials for biological, chemical and mechanical sensors. The present review summarizes how to incorporate GFMs into different sensing system including fluorescence aptamer-based sensors, field-effect transistors (FET), and electrochemical sensors, as well as, how to covalently and/or non-covalently modify GFMs to achieve various detection purpose. Sensing mechanisms and fabrication strategies that will influence the sensitivity of different sensing system are also reviewed.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.062
GPT teacher head0.359
Teacher spread0.297 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations50
Published2019
Admission routes1
Has abstractyes

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