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Record W4406661373 · doi:10.1016/j.susmat.2025.e01267

FeNi bimetallic functionalized lignin catalyst for sustainable oxidation processes

2025· article· en· W4406661373 on OpenAlex

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.

Bibliographic record

VenueSustainable materials and technologies · 2025
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsUniversité Laval
FundersUniversité Mohammed VI Polytechnique
KeywordsBimetallic stripCatalysisLigninChemistryChemical engineeringMaterials scienceOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

The advancement of sustainable and efficient catalytic procedures is crucial in tackling the continuous environmental and industrial challenges, with research being inherently focused on sustainable chemical science to exploit the possibilities of cost-effective bio-based materials for practical applications. Considerably, this investigation delves into the synthesis, characterization, and use of Fe Ni bimetallic functionalized lignin (FeNi@Lig) catalysts using lignin extracted from spent coffee grounds, an underutilized agro-industrial waste. This eco-friendly approach emphasizes the valorization of non-traditional biomass while reducing waste streams. FeNi@Lig was used for oxidation processes, concentrating on the oxidation of bromothymol blue and cellulose for environmental remediation and the production of valuable chemicals. By capitalizing on the multifaceted attributes of lignin, FeNi@Lig catalysts were produced and examined using several techniques, uncovering an effective dispersion of Fe and Ni nanoparticles on the lignin support. The catalysts displayed remarkable efficiency and selectivity in oxidative processes, notably boosting reaction speeds and diminishing the creation of unwanted side products. The oxidation of bromothymol blue (BB) was carried out with a 2 % catalyst, yielding a conversion efficiency of 99.35 % in just 180 s. Likewise, the optimal cellulose oxidation exhibited an oxidation degree of 91.11 % with a 5 % catalyst. The outcomes emphasize the promise of catalysts derived from biomass in industrial settings, advocating for sustainable methodologies and propelling the realm of eco-friendly chemistry. • Fe Ni bimetallic lignin catalyst achieves 99.35 % dye oxidation in 3 min. • Efficient cellulose oxidation reaches 91.11 % using 5 % in 60 min at 60 °C. • High recyclability demonstrated, maintaining superior efficiency over multiple cycles. • Functionalized catalyst combines lignin biopolymer with metal nanoparticle synergy. • Sustainable solution for environmental cleanup and chemical transformations.

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 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 score0.168
Threshold uncertainty score0.711

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 head0.004
GPT teacher head0.205
Teacher spread0.200 · 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