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Record W4414908054 · doi:10.1021/acsaelm.5c01298

From Tradition to Innovation: Shellac as a Sustainable Solution to Challenges in Flexible and Printed Electronics

2025· article· en· W4414908054 on OpenAlexafffund
Rahaf Nafez Hussein, Tricia Breen Carmichael

Bibliographic record

VenueACS Applied Electronic Materials · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsShellacThe RenaissanceElectronicsComponent (thermodynamics)SustainabilityPrinted electronics

Abstract

fetched live from OpenAlex

Shellac, a natural resin with centuries of historical use in coatings, adhesives, and varnishes, is emerging as a promising material for addressing key challenges in modern flexible and printed electronics. As the field seeks environmentally friendly, biocompatible, and processable alternatives to petroleum-based polymers, shellac offers a unique combination of favorable properties, including film-forming ability, dielectric behavior, gas barrier performance, and biodegradability. This review traces the path from traditional applications to the current renaissance of shellac in electronic technologies. We examine the chemical composition and structure–property relationships, fabrication methods compatible with printed electronics, and the use of shellac as a substrate, a dielectric layer, a binder in functional printing inks, and a gas barrier coating. With responsible sourcing and a commitment to sustainability throughout the life cycle, shellac has great potential as a foundational component of the next generation of printed, flexible, and environmentally conscious electronics.

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)0.003
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.007
Scholarly communication0.0040.007
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.013
GPT teacher head0.238
Teacher spread0.226 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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