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Record W3004641960 · doi:10.1002/admt.201900939

Recent Progress in Transparent Conductors Based on Nanomaterials: Advancements and Challenges

2020· article· en· W3004641960 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

VenueAdvanced Materials Technologies · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsBerger (Canada)York University
FundersMitacsNational Research Foundation of Korea
KeywordsNanomaterialsElectrical conductorNanotechnologyMaterials scienceElectronicsFabricationNanocompositeTransparent conducting filmEngineeringElectrical engineeringComposite material

Abstract

fetched live from OpenAlex

Abstract Transparent conductors are essential to the fabrication of transparent electronics such as touch panels and displays, making them crucial elements in the current electronics industry. With the rapid surge of interest in stretchable electronics, transparent conductors now are also required to be stretchable. Therefore, new approaches to developing transparent and stretchable conductors (TSCs) are needed to replace conventional rigid transparent conductors. Constructing nanocomposites of various nanomaterials and substrates is one of the most promising approaches to developing TSCs due to the nanomaterials' geometrical, mechanical, electrical, and optical properties. Herein, the progress of carbon‐ and metal‐based nanomaterials and conductive polymers composites are investigated and categorization of TSCs based on types of nanomaterials and fabrication techniques are discussed. Lastly, a review of the demonstrated state‐of‐the‐art applications of TSCs and a perspective about the future of TSCs based on nanomaterials are provided.

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 categoriesMeta-epidemiology (narrow)
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 score0.161
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.060
GPT teacher head0.260
Teacher spread0.200 · 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