MétaCan
Menu
Back to cohort
Record W2967841718 · doi:10.1039/c9nr04193a

Stretchable/flexible silver nanowire electrodes for energy device applications

2019· article· en· W2967841718 on OpenAlexaff
Jinwook Jung, Hyunmin Cho, Recep Yüksel, Dongkwan Kim, Habeom Lee, Jinhyeong Kwon, Phillip Lee, Junyeob Yeo, Sukjoon Hong, Hüsnü Emrah Ünalan, Seungyong Han, Seung Hwan Ko

Bibliographic record

VenueNanoscale · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsNovelis (Canada)
FundersNational Research Foundation of KoreaMinistry of Science, ICT and Future Planning
KeywordsNanowireMaterials scienceNanotechnologyElectrodeChemistry

Abstract

fetched live from OpenAlex

Research on sustainable and high-efficiency energy devices has recently emerged as an important global issue. These devices are now moving beyond the form of a bulk, rigid platform to a portable, flexible/stretchable format that is easily available in our daily lives. Similar to the development of an active layer for the production of next-generation energy devices, the fabrication of flexible/stretchable electrodes for the easy flow of electrons is also very important. Silver nanowire electrodes have high electronic conductivity even in a flexible/stretchable state due to their high aspect ratio and percolation network structures compared to conventional electrodes. Herein, we summarize the research in the field of flexible/stretchable electronics on energy devices fabricated using silver nanowires as the electrodes. Additionally, for a systematic presentation of the current research trends, this review classifies the surveyed research efforts into the categories of energy production, storage, and consumption.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.009
GPT teacher head0.225
Teacher spread0.216 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations123
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueNanoscaleSame topicAdvanced Sensor and Energy Harvesting MaterialsFrench-language works237,207