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Record W4406385254 · doi:10.1007/s10570-025-06380-7

Optical assessment of lignin-containing nanocellulose films under extended sunlight exposure

2025· article· en· W4406385254 on OpenAlexaff
Rustem Nizamov, Joice Jaqueline Kaschuk, Yazan Al Haj, Mikael Nyberg, Monireh Imani, Eva Pasquier, Orlando J. Rojas, Tíffany Abitbol, Jaana Vapaavuori, Kati Miettunen

Bibliographic record

VenueCellulose · 2025
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of British Columbia
FundersTurun YliopistoSuomen KulttuurirahastoDivision of Materials ResearchSvenska Forskningsrådet FormasEuropean Commission
KeywordsNanocelluloseLigninCelluloseMaterials scienceTransmittanceUltimate tensile strengthBacterial celluloseChemical engineeringComposite materialChemistryOrganic chemistryOptoelectronics

Abstract

fetched live from OpenAlex

This study investigates the stability and UV-blocking properties of cellulose nanofibril (CNF) and TEMPO-oxidized cellulose nanofibril (TOCNF) films, with and without lignin, under 1000 h of artificial sunlight. The literature to date provides no quantitative analysis of such films' stability, however such insight is critical for optoelectronic applications for instance solar cells. This contribution examines the films from practical perspectives, considering aging with respect to their optical performance and retention of UV protective qualities. Films containing residual lignin (LignoCNF and LignoTOCNF), and lignin nanoparticles (CNF-LNP and TOCNF-LNP) demonstrated remarkable UV-blocking stability; even after the aging transmittance of LignoCNF and CNF-LNP films remained lower than 1% below 390 nm. Most lignin-containing films exhibited increased transmittance between 400 and 600 nm after aging, except for LignoTOCNF, which showed a decrease in transmittance that was comparable to that displayed by non-lignin films. Nevertheless, long-term light exposure induced a decrease in their mechanical properties. Tensile tests revealed increased brittleness in CNF and LignoCNF, while LNP-containing films showed reduced strain at the break. The observed changes were linked to the potential oxidation of COO- groups and structural modifications in both cellulose and lignin. Overall, the incorporation of lignin into nanocellulose films enhances their durability, UV protection, and mechanical stability, making them promising candidates for sustainable optoelectronic applications. Supplementary Information: The online version contains supplementary material available at 10.1007/s10570-025-06380-7.

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 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)0.001
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 score0.082
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.324
Teacher spread0.306 · 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 teacher head, not a consensus.

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

Citations11
Published2025
Admission routes1
Has abstractyes

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