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Record W4406570396 · doi:10.1016/j.cej.2025.159298

Ultraviolet-laser-induced graphene with heterogeneous CuO, Fe3O4, TiO2 ternary metal oxide nanoparticles for enhanced environmental applications

2025· article· en· W4406570396 on OpenAlex
Jun Uk Lee, So Yoon Park, Anthony V. Tuccitto, Nello D. Sansone, Rafaela Aguiar, Ho Hyun Chun, Bo Sung Shin, Patrick Lee

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemical Engineering Journal · 2025
Typearticle
Languageen
FieldEngineering
TopicLaser-Ablation Synthesis of Nanoparticles
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaWorld Institute of KimchiMinistry of Trade, Industry and Energy
KeywordsTernary operationGrapheneOxideNanoparticleUltravioletMaterials scienceMetalLaserNanotechnologyChemical engineeringOptoelectronicsMetallurgyOpticsComputer science

Abstract

fetched live from OpenAlex

• Created a cost-effective method for hetero-conjugated ternary MONPs/UV-LIG production. • MB adsorption kinetics fit a pseudo-second-order model; max capacity: 402.9 mg/g (Langmuir isotherm). • Demonstrated MB photodegradation with strong reusability, suitable for water purification. • Achieved 99.999% (5-log) reduction in pathogens in 60 s, proving self-sterilization properties. Pressing concerns regarding increasing industrial emissions and the spread of environmental pathogens have catalyzed substantial research into developing absorbents and antibacterial surfaces. Graphene-based composites incorporating metal oxide nanoparticles (MONPs) have recently gained significant attention for large-scale implementation, offering excellent absorbent behavior, photocatalytic performance, antibacterial properties, and straightforward fabrication pathways. However, the integration of heterogeneous ternary MONPs on highly porous graphene structures remains challenging. Laser-induced graphene (LIG) offers a promising avenue for customizing graphene-based composite materials, potentially transforming various industries through the rapid and cost-effective production of three-dimensional, multifunctional porous structures. This study pioneers the fabrication of nanocomposites composed of hetero-conjugated CuO, Fe 3 O 4 , and TiO 2 ternary MONPs embedded in high-surface-area bilayer ultraviolet (UV)-LIG, targeting absorption, photocatalysis, and self-sterilization against foodborne pathogens. This hybrid nanocomposite demonstrates consistent absorption and photodegradation performance, making it a strong candidate for industrial waste absorption, photodegradation of volatile organic compounds, and antibacterial surfaces for food packaging. For industrial waste adsorption, the adsorption kinetics of methylene blue (MB) was examined and followed a pseudo-second-order model with a maximum adsorption capacity of 402.9 mg/g according to the Langmuir isotherm. The ternary MONPs/UV-LIG photocatalyst exhibits outstanding performance, achieving approximately 95 % degradation efficiency of MB under visible light irradiation. The ternary MONPs/UV-LIG also demonstrated remarkable self-sterilization, achieving a 5-log cycle (99.999 %) reduction in foodborne pathogens in 60 s, making it ideal for applications necessitating antimicrobial surfaces. Ternary MONPs/UV-LIG composites exhibit exceptional adsorptive and photocatalytic efficiency under visible light, enabling sustainable degradation of organic pollutants and pathogens without external stimulation, making them ideal for environmental remediation and antimicrobial applications.

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.

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)0.000
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 score0.091
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.006
GPT teacher head0.194
Teacher spread0.188 · 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