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Record W4400138535 · doi:10.1002/cjce.25369

<scp>2D</scp>‐<scp>MXene</scp> composite systems for effective photocatalytic degradation of pharmaceutical compounds

2024· article· en· W4400138535 on OpenAlexvenueno aff
Vishwanath Gholap, Alsha Subash, Tharikha Joseph, Balasubramanian Kandasubramanian

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2024
Typearticle
Languageen
FieldMaterials Science
TopicMXene and MAX Phase Materials
Canadian institutionsnot available
Fundersnot available
KeywordsMXenesPhotocatalysisComposite numberDegradation (telecommunications)HeterojunctionMaterials scienceAdsorptionAntibioticsNanotechnologyBiochemical engineeringChemistryComposite materialComputer scienceMicrobiologyBiologyCatalysisEngineeringOrganic chemistryTelecommunications

Abstract

fetched live from OpenAlex

Abstract The escalating incidence of chronic diseases and infections has driven an increase in the use of antibiotics, raising concerns regarding their disposal and presence in water sources. Antibiotic‐resistant genes (ARGs) can arise in bacteria and other microorganisms when antibiotics are present in the water. Human, plant, and animal physiological processes may be negatively impacted by extended exposure to these substances. Since MXenes are effective photocatalysts and adsorption agents, they have garnered a lot of attention in the wastewater treatment industry. While employing MXene alone typically yields inadequate results, it is advantageous to combine MXene with other materials to generate derivatives or composites. This comprehensive review meticulously examines MXene composites with various materials to enhance their photocatalytic prowess, unveiling composite systems capable of achieving an exceptional degradation efficiency of up to 99%, as exemplified by the UiO‐66/MXene composite and g‐C 3 N 4 /Ti 3 C 2 MXene/black phosphorus heterojunction. Additionally, this paper provides critical insights into the intrinsic characteristics, synthesis methodologies, and performance efficiencies for these composites, thereby serving as an invaluable resource for researchers and practitioners in the field.

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)0.001
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 score0.030
Threshold uncertainty score0.624

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.017
GPT teacher head0.253
Teacher spread0.236 · 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.

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

Citations8
Published2024
Admission routes1
Has abstractyes

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