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Record W4407834059 · doi:10.1016/j.mtcomm.2025.111964

Eco-friendly nanostructured bio-polybenzoxazine films/coatings: One-pot green synthesis using Cardanol and Furfurylamine

2025· article· en· W4407834059 on OpenAlexaff
Shabnam Khan, Fahmina Zafar, Shaily, Mudsser Azam, Anujit Ghosal, Adnan Shahzaib, Manawwer Alam, M. Shahid, Qazi Mohd Rizwanul Haq, Nahid Nishat

Bibliographic record

VenueMaterials Today Communications · 2025
Typearticle
Languageen
FieldEngineering
TopicEpoxy Resin Curing Processes
Canadian institutionsUniversity of Manitoba
FundersAll-India Institute of Medical SciencesKing Saud UniversityDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsCardanolMaterials scienceEnvironmentally friendlyChemical engineeringComposite material

Abstract

fetched live from OpenAlex

This work highlights the in-situ green synthesis of thermally viable (250–300 °C) and antibacterial hydrophobic metal coordinated Cardanol formaldehyde aromatic polybenzoxazine [M(II)-CF-ArBz, whereas M(II)=Mn +2 , Zn +2 , Co +2 , and Ni +2 ] films using Cardanol (Col) and Furfurylamine (FAM). The effect of different transition metal ions and FAM on the overall performance of the developed films and coatings was investigated. The structure was elucidated with Fourier transform infrared spectroscopy (FTIR), Nuclear magnetic resonance NMR ( 1 H and 13 C), and X-ray photoelectron spectroscopy (XPS). The Powder X-ray diffraction (PXRD), scanning electron microscope (SEM), and transmission electron microscopy (TEM), revealed semi-crystalline behavior, nanostructures , and variation in morphology w.r.t. the metallic ions used. The different metal influences the nucleation and growth rate leading to different composite morphologies like ribbon (diameter 59 nm) in Co(II)-CF-ArBz, ultrafine spherical nanoparticles clusters of nano-dots (size 3 ± 1 nm) in Mn(II)-CF-ArBz, nanodisc (79 nm - 84 nm) in Zn(II)-CF-ArBz, and hollow tubular structure in case of Ni(II)-CF-ArBz. The improved antibacterial activity of developed M(II)-CF-ArBz films against various bacteria { Escherichia coli (MTCC 443), Pseudomonas aeruginosa (MTCC 2453) gram-negative, and Staphylococcus aureus (MTCC 902) and Bacillus subtilis (MTCC 736) gram-positive bacteria} were established via., growth inhibition and cell viability test. The physico-mechanical and surface wettability performance of M(II)-CF-ArBz coatings reveal mechanically more stable and hydrophobic than the respective virgin polybenzoxazine (CF-ArBz) coating. The relevance of the work is in the aspect of augmentation usage of renewable waste materials viz. Col and FAM, implementation of simple and in-situ route avoiding toxic residues, adoption of “Green Chemistry” principles, and highlighting the potential use of these sustainable films and coatings.

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 score0.002

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 communication0.0000.000
Open science0.0000.000
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 head0.019
GPT teacher head0.257
Teacher spread0.238 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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