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Record W2583312648 · doi:10.1088/1361-6641/aa5cfb

Piezoelectricity of 2D nanomaterials: characterization, properties, and applications

2017· article· en· W2583312648 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

VenueSemiconductor Science and Technology · 2017
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsPiezoelectricityNanotechnologyCharacterization (materials science)NanomaterialsNanoelectronicsMaterials science

Abstract

fetched live from OpenAlex

Abstract The discovery of piezoelectricity in 2D nanomaterials represents a milestone towards embedding low-dimensional materials into future technologies. This article reviews recent progress in the characterization, properties evaluation, and applications of piezoelectricity of 2D piezoelectric nanomaterials (PNs). To begin, an introduction to the existing 2D PNs, which exhibit a wide range of atomic structures and configurations, is presented. The nanoscale measurements and associated experimental techniques as well as the atomic simulations of the piezoelectric properties of 2D PNs are then summarized. Some of the pertinent parameters, which govern the piezoelectric properties of 2D PNs, are discussed. Furthermore, our article concludes with some potential applications including piezotronics, piezophototronics, and energy harvesting of 2D PNs, which can open the doors to the innovative design of next-generation nanoelectronics and nanodevices. Finally, we highlight perspectives and challenges for the future development of 2D PNs.

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 score0.021
Threshold uncertainty score0.937

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 studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.025
GPT teacher head0.249
Teacher spread0.224 · 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