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Record W3024481125 · doi:10.1149/ma2020-01352425mtgabs

Bio-Sourced, Potentially Biodegradable Materials for Fast Response Moisture Sensors

2020· article· en· W3024481125 on OpenAlexaff
Abdelaziz Gouda, Manuel Reali, Clara Santato

Bibliographic record

VenueECS Meeting Abstracts · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicmelanin and skin pigmentation
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsMelaninPolymerizationMoistureHumidityNanotechnologyMaterials scienceChemistryChemical engineeringPolymerComposite materialBiochemistryPhysics

Abstract

fetched live from OpenAlex

Humidity is a very important physical parameter that plays an imperative role in technology and human activity. Researchers are paying more attention to develop moisture-responsive materials with outstanding characteristics such as high sensitivity, wide humidity detection range, fast response and short recovery times to keep pace with the on-going development in technology. Abundant, bio-sourced and biodegradable organic materials, such as melanin, are needed to enable the development of eco-designed technologies that alleviate the environmental footprint of the electronics sector. Melanin is a ubiquitous biomacromolecule with diverse functions including hydration dependent electrical response [1], photoresponse [2], antioxidant [3] , metal chelation [4], and free radical scavenging [5]. Melanin originates from the oxidative polymerization of (5,6)-dihydroxindole (DHI) and (5,6)-dihydroxindole 2-carboxyl acid (DHICA) building blocks [6]. Natural melanin is expected to contain up to 70% of DHI in molecular ratio [7]. Due to the absence of the carboxyl group in the molecular structure, DHI-melanin features a ordered, conjugated structure thus expected to show better electrical conductivity with respect to DHICA-melanin [5]. Herein, we investigate DHI-melanin and DHI-DHICA melanin thin films (7:3 weight ratio), spin coated and polymerized on technologically relevant and potentially biodegradable substrates, as active layers for fast response moisture sensors. References [1] Wünsche J, Deng Y, Kumar P, Di Mauro E, Josberger E, Sayago J, Pezzella A, Soavi F, Cicoira F and Rolandi M 2015 Protonic and electronic transport in hydrated thin films of the pigment eumelanin Chem. Mater. 27 436-42 [2] Mostert A B, Rienecker S B, Noble C, Hanson G R and Meredith P 2018 The photoreactive free radical in eumelanin Science advances 4 eaaq1293 [3] Tu Y-g, Sun Y-z, Tian Y-g, Xie M-y and Chen J 2009 Physicochemical characterisation and antioxidant activity of melanin from the muscles of Taihe Black-bone silky fowl (Gallus gallus domesticus Brisson) Food Chem. 114 1345-50 [4] Hong L and Simon J D 2007 Current understanding of the binding sites, capacity, affinity, and biological significance of metals in melanin. ACS Publications) [5] Panzella L, Gentile G, D'Errico G, Della Vecchia N F, Errico M E, Napolitano A, Carfagna C and d'Ischia M 2013 Atypical structural and π‐electron features of a melanin polymer that lead to superior free‐radical‐scavenging properties Angew. Chem. Int. Ed. 52 12684-7 [6] Meredith P and Sarna T 2006 The physical and chemical properties of eumelanin Pigment cell research 19 572-94 [7] Pezzella A, d'Ischia M, Napolitano A, Palumbo A and Prota G 1997 An integrated approach to the structure of Sepia melanin. Evidence for a high proportion of degraded 5, 6-dihydroxyindole-2-carboxylic acid units in the pigment backbone Tetrahedron 53 8281-6

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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.015
GPT teacher head0.247
Teacher spread0.232 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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