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Record W3156395660 · doi:10.1016/j.isci.2021.102421

Biomass waste-derived porous carbon efficient for simultaneous removal of chlortetracycline and hexavalent chromium

2021· article· en· W3156395660 on OpenAlexaff
Kai Yan, Ruiqi Li, Zhiyu Yang, Xin Li, Yuchen Wang, Guosheng Wu

Bibliographic record

VenueiScience · 2021
Typearticle
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsLakehead University
FundersNational Natural Science Foundation of China
KeywordsHexavalent chromiumChemistryBifunctionalChromiumWastewaterPhotocatalysisNuclear chemistryDegradation (telecommunications)Biomass (ecology)Mass spectrometryCarbon fibersCatalysisChromatographyOrganic chemistryWaste managementMaterials science

Abstract

fetched live from OpenAlex

The simultaneous removal of mixed containments of antibiotics and heavy metals is still a big challenge in wastewater treatment. Herein, we report the successful synthesis of N-doped porous carbon (abbreviated as NC) from straw waste through the Maillard reaction to activate sp 3 -sp 2 conversion efficient for the simultaneous removal of chlortetracycline (CTC) and hexavalent chromium (Cr(VI)). In 200 min, 96.9% of Cr(VI) was reduced into Cr(III) and 93.1% of CTC was oxidatively degraded. Reactive substances (e.g., h + , e −1 , ⋅OH, and ⋅O 2 - ) were verified for the photocatalytic reactions. Besides, the possible degradation intermediates of CTC were analyzed with ultra performance liquid chromatography-mass spectrometry (UPLC-MS/MS), and the mechanism of photocatalytic degradation of CTC was then proposed. The synthesized bifunctional NC materials could also be applied for the similar system; this will open the door for promising practical 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.

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 score0.002
Threshold uncertainty score0.004

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 head0.013
GPT teacher head0.272
Teacher spread0.259 · 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

Citations39
Published2021
Admission routes1
Has abstractyes

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